Efficient fidelity simulation of high-rate magic distillation circuits Authors Xiao Xiao, Dominik Hangleiter, J. Pablo Bonilla Ataides, Rohan Mehta, Varun Menon, Mikhail D. Lukin, Michael J. Gullans Published: 10.02.2026 Updated: 10.02.2026 Summary Non-Clifford gates are essential for avoiding classical simulability under the Gottesman-Knill theorem. An error-corrected circuit with non-Clifford gates will therefore be an important element for realizing useful fault-tolerant quantum algorithms. However, accurately understanding the fault-tolerant performance of such circuits faces challenges due to the classical hardness of simulating these circuits. We avoid simulating logical measurements and develop exact and efficient classical methods for benchmarking circuits composed of X, CNOT, and diagonal gates in the Clifford hierarchy, including state and gate teleportation gadgets with feedforward. For circuits with third-level diagonal gates, our benchmarking algorithm efficiently samples syndrome statistics and estimates the output logical fidelity and expectation values of certain Clifford observables, including all Pauli observables. The evaluation of syndrome expectation values also extends to circuits with fourth-level diagonal gates. Our algorithm scales polynomially in the number of physical qubits n and circuit depth T, independent of the number of logical qubits. The benchmarking applications include IQP sampling and magic state preparation/cultivation. We demonstrate the practical utility of our simulation algorithms by using them to optimize high-rate magic state distillation factories based on three copies of a [[27,3,3]] tricycle code. Source arXiv: 2610.03605v1
Efficient fidelity simulation of high-rate magic distillation circuits Authors Xiao Xiao, Dominik Hangleiter, J. Pablo Bonilla Ataides, Rohan Mehta, Varun Menon, Mikhail D. Lukin, Michael J. Gullans Published: 10.02.2026 Updated: 10.02.2026 Summary Non-Clifford gates are essential for avoiding classical simulability under the Gottesman-Knill theorem. An error-corrected circuit with non-Clifford gates will therefore be an important element for realizing useful fault-tolerant quantum algorithms. However, accurately understanding the fault-tolerant performance of such circuits faces challenges due to the classical hardness of simulating these circuits. We avoid simulating logical measurements and develop exact and efficient classical methods for benchmarking circuits composed of X, CNOT, and diagonal gates in the Clifford hierarchy, including state and gate teleportation gadgets with feedforward. For circuits with third-level diagonal gates, our benchmarking algorithm efficiently samples syndrome statistics and estimates the output logical fidelity and expectation values of certain Clifford observables, including all Pauli observables. The evaluation of syndrome expectation values also extends to circuits with fourth-level diagonal gates. Our algorithm scales polynomially in the number of physical qubits n and circuit depth T, independent of the number of logical qubits. The benchmarking applications include IQP sampling and magic state preparation/cultivation. We demonstrate the practical utility of our simulation algorithms by using them to optimize high-rate magic state distillation factories based on three copies of a [[27,3,3]] tricycle code. Source arXiv: 2610.03605v1
Optimal two-mode bosonic loss codes from finite group symmetry Authors Argyris Giannisis Manes, Mahadevan Subramanian, Liang Jiang Published: 09.30.2026 Updated: 09.30.2026 Summary Photon loss is a dominant noise process in bosonic quantum hardware, including superconducting cavities. Fixed-total-photon-number qubit encodings in two bosonic modes retain the loss-detection advantage of dual-rail qubits while supporting photon loss correction. Optimizing entanglement fidelity in this setting for $4leq nleq25$ over arbitrary encoders and decoders reveals finite-group structure in every best-found code: 11 correspond to two-dimensional irreducible representations and 11 to reducible ones. Motivated by this emergence, we derive the necessary-and-sufficient Knill-Laflamme conditions for arbitrary finite-group-invariant codes, reducing their construction to equations on representation multiplicity spaces. For every finite subgroup of $SU(2)$ and every tensor rank, we explicitly construct the minimum number of operators required to impose all corresponding loss-correction constraints. These results produce analytic counterparts to most numerical codes and predict constructions missed by the initial search. Exact MacWilliams-Farkas certificates show that our codes achieve the maximum possible loss distance in 21 of the 22 sectors, and we prove that the resulting distance bound is monotone in total photon number. Beyond the scan, we identify a binary-polyhedral sequence with photon number $n_d=lceil(3d^2+1)/4rceil$ and construct each corresponding code through distance $d=10$. To our knowledge, the constructed $(n,d)=(28,6),(49,8),(76,10)$ codes give the smallest reported $n$ for their respective distances; all members through $d=9$ attain the fixed-$n$ LP distance bound. Together, these constructions, certificates, and a symmetry-reduced constraint count provide evidence for an infinite code family conjectured to attain every distance at the minimum photon number. Source arXiv: 2610.00561v1
AIR-LLM: Broadcasting AI Weights over Radio for Memory-Free Edge LLM Inference via RF Computing Authors Zhihui Gao, Tingjun Chen, Dirk Englund Published: 09.30.2026 Updated: 09.30.2026 Summary Next-generation large language models (LLMs) are expanding from the cloud to ubiquitous edge devices. However, edge devices typically either lack the memory to store increasingly large LLM weights or, even with enough memory, spend unaffordable energy on loading the weights. This raises our question: can an edge device run an LLM without storing or loading its weights, but receive them over the air and consume them on the fly? Inspired by wireless broadcasting, we present AIR-LLM, an LLM inference architecture for edge devices, which is composed of: (i) a central radio (e.g., 5G base stations) that broadcasts the LLM weights into the air, and (ii) the edge user that receives the weights and completes the general matrix-vector multiplication (GEMV) of LLM inference directly in the radio frequency (RF) domain using RF mixers. To further shorten the airtime, AIR-LLM exploits MIMO spatial multiplexing and proposes an energy-efficient precoder-postcoder pair on the edge to calibrate its own wireless channel. Since the central radio stays user-unaware, AIR-LLM is user-scalable so that one broadcast serves unlimited users within its coverage. We implement AIR-LLM on the NVIDIA Sionna ray-traced channels of two real-world urban scenes and the profiling of a real RF mixer. With a WikiText-2 perplexity degradation of 4.0% on LLaMA-3.1-8B, AIR-LLM saves the energy by 157.7x/40.4x against the FP16 and weight-only quantization baselines; with 20 users, its airtime is 104.1x/26.0x shorter, respectively. Source arXiv: 2610.00465v1
Generalized Reimpell-Werner Iteration Authors Shihao Ru, Bikun Li, Weibo Gao, Liang Jiang Published: 09.30.2026 Updated: 09.30.2026 Summary Quantum measurements and channels determine how information is extracted, encoded, and transmitted in quantum protocols. Optimizing their performance often requires numerical methods that remain practical as Hilbert space dimensions increase. The Reimpell-Werner iteration offers a practical approach to these tasks through repeated matrix updates that respect the constraints. Here, we generalize this iteration to linear objectives with arbitrary Hermitian cost matrices. We prove that the iterates converge to a global optimum whenever the initialization satisfies suitable support overlap conditions. For each fixed problem, choice of iteration parameters, and admissible initialization, $mathcal{O}(1/varepsilon)$ iterations suffice asymptotically to bring the objective value within $varepsilon$ of the optimum. These results provide a rigorous foundation for the iteration and broaden the class of optimization problems to which its convergence guarantees apply. Source arXiv: 2609.40203v1
Distillation of N-Qubit Stabilizer States on a Star Network Topology Authors Theodore M. Mahaffey, Chaohan Cui, Saikat Guha, Murphy Yuezhen Niu Published: 09.30.2026 Updated: 09.30.2026 Summary We introduce an entanglement distillation protocol that utilizes an arbitrary $[[n,k,d]]$ stabilizer code to convert $n$ raw copies of an $N$-qubit Greenberger-Horne-Zeilinger (GHZ) state into $k$ logical copies in the presence of Pauli noise. Our explicit formulation of the scheme on a star network topology is efficiently scalable to arbitrary $N$, requires only local operations, and minimizes the impact of errors on idle physical qubits, enabling the distribution of high-fidelity entangled logical states between any number of quantum processors. We report the results of numerical experiments using the 5-qubit code, toric code, and $[[144,12,12]]$ bivariate bicyle code to protect against independent single-qubit depolarizing noise on all qubits. Our encoding scheme improves the final GHZ state fidelity relative to a single bare GHZ state sent over the same noisy channel for depolarizing rates up to or above $6 %$ for all codes tested. Additionally, we use the stabilizer formalism to prove that our protocol can be applied to any $N$-qubit Calderbank-Shor-Steane (CSS) stabilizer state, from which the GHZ state emerges as a special case. This result explicitly establishes the working principle of previous stabilizer-based Bell pair and GHZ state distillation schemes, and generalizes such protocols beyond the traditionally considered states. We also show that some stabilizer codes can distill any stabilizer state with our protocol. Source arXiv: 2609.39916v1
Doing More with Less Tokens: Hierarchical Reinforcement Learning for Efficient Coding Agents Authors Haobin Li, Liang Jiang, Zhenyu Huang, Mouxing Yang, Xi Peng Published: 09.30.2026 Updated: 09.30.2026 Summary Recently, coding agents have emerged as a dominant paradigm for real-world software engineering (SWE) scenarios, which solve complex tasks through multi-turn interactions with development environments. However, frequent interactions with environments would inevitably introduce substantial token overhead, leading to high usage costs and latency. Although recent studies have explored reducing token usage by context manipulation and interaction limits at inference time, these approaches focus on improving token efficiency while overlooking the risk of discarding task-relevant information, thus struggling to balance the trade-off between resolution rate and token efficiency. In this paper, we study a more general paradigm without suffering from the limitation, i.e., training token-efficient coding agents with promising resolution performance, which is a highly-practical yet less-explored problem. To this end, we reveal two core observations in SWE scenarios: i) Efficiency Variation: successful resolution could be achieved with fewer tokens; ii) Entropy Correlation: unproductive behaviors are associated with turn-level entropy. Motivated by observations, we propose a novel reinforcement learning framework, dubbed HERO. Specifically, HERO prioritizes task resolution over token efficiency during policy optimization and encourages efficient reasoning patterns at both trajectory and turn levels. Extensive experiments on SWE-bench Verified and SWE-bench Multilingual demonstrate that HERO achieves a favorable trade-off between resolution rate and token efficiency compared with state-of-the-art coding agents and reinforcement learning methods. Source arXiv: 2609.38885v1
Entangling Atomic Quantum Memories Using High-Order Modulated Coherent States Authors Chaohan Cui, Prajit Dhara, Saikat Guha Published: 09.30.2026 Updated: 09.30.2026 Summary High-order coherent-state modulation with reflective cavity-coupled atomic memories can distribute multiple heralded ebits per transmitted optical mode, but requires a collective midpoint POVM optimized for maximum distillable entanglement rather than minimum-error state discrimination. An SRM-inspired 16-QAM receiver reaches $1.75$ ebits per mode at $0.5$~dB end-to-end loss, $3.8$~dB below the half-link capacity benchmark. For 4-QAM, a variational POVM with more outcomes than constellation points improves the SRM rate by $4.0%$ yet remains below capacity, revealing measurement-design headroom. The advantage over single-qubit-per-mode midpoint protocols persists for per-interface loss $<0.2$~dB and calibrated phase error $<0.2π$. Source arXiv: 2609.38804v1
Entangling Atomic Quantum Memories Using High-Order Modulated Coherent States Authors Chaohan Cui, Prajit Dhara, Saikat Guha Published: 09.30.2026 Updated: 10.01.2026 Summary High-order coherent-state modulation and collective midpoint measurements enable multi-ebit entanglement distribution between cavity-coupled atomic memories. An SRM-inspired 16-QAM receiver achieves $1.75$ ebits per network mode use at $0.5$~dB end-to-end loss, exceeding single-qubit-per-mode benchmarks by $5.8$~dB and lying $3.8$~dB below the half-link capacity bound. The advantage persists for per-interface loss below $0.2$~dB and calibrated phase errors below $0.2π$. For 4-QAM, an optimized POVM with twice as many outcomes raises the achievable rate by $4.0%$, revealing measurement-design headroom. Source arXiv: 2609.38804v2
Acoustoelectrically enhanced acousto-optic modulation in an integrated silicon nitride and thin film lithium niobate platform Authors Matthew J. Storey, John H. Dallyn, Kiyan Hocek, Michael Miller, Peter T. Rakich, Scott A. Diddams, Nils T. Otterstrom, Matt Eichenfield Published: 09.29.2026 Updated: 09.29.2026 Summary Acoustoelectric interactions in piezoelectric-semiconductor heterostructures allow the propagation characteristics of microwave frequency phonons in piezoelectric media to be controlled and radically enhanced, providing electrically controllable phonon gain, large velocity tuning, isolation, and circulation, as well as extremely large electron-mediated phononic nonlinearities. Here, for the first time, we create such a piezoelectric-semiconductor heterostructure with lithium-niobate-on-insulator and InGaAs that also supports guided optical modes through the addition of a silicon nitride waveguide and modification of the acoustic materials to provide an optical lower cladding. We use this new architecture to demonstrate acoustoelectrically enhanced acousto-optic modulation, where 1 GHz phonons are piezoelectrically generated and acoustoelectrically amplified on-chip by up to 60 dB before impinging on the optical waveguide, providing pure phase modulation with a $V_πL$ figure-of-merit of 0.077 V-cm while only consuming 3.77 mW of DC electrical power to provide the amplification. We then consider future applications enabled by these functionalities and describe a novel tunable optical delay and an optoelectronic oscillator (OEO) analog—an acoustoelectrically enhanced opto-acoustic oscillator (AE-OAO). We show that using Brillouin optomechanical transduction and acoustoelectrically lossless acoustic time delay, the AE-OAO could replace kilometers of optical fiber delay used in OEOs but on a single, centimeter-scale chip. Source arXiv: 2609.36439v1
Mode-selective acousto-electric modulation of phonons in a silicon photonic platform Authors Ruoyu Yuan, Yishu Zhou, Matthew J. Storey, Ryan O. Behunin, Haotian Cheng, Betul Sen, Andrew L. Starbuck, Douglas C. Trotter, Andrew L. Leenheer, Matt Eichenfield, Nils T. Otterstrom, Peter T. Rakich Published: 09.28.2026 Updated: 09.28.2026 Summary Acousto-electric (AE) interactions enable electrical control of acoustic propagation through piezoelectric media. Bringing AE control onto integrated photonic platforms provides a powerful on-chip control mechanism to reconfigure both the acoustic propagation through piezoelectric media. Bringing AE control onto integrated photonic platforms provides a powerful on-chip control mechanism to reconfigure both the acoustic delay line response and the effective photon-phonon interaction by electrically tuning the phonon propagation. Here we report a mode-selective AE modulation effect in a scalable aluminum nitride on silicon-on-insulator (AlN-on-SOI) platform. An applied DC field is seen to modulate the phonon dissipation via changes in carrier concentration in a mode-selective fashion, producing up to 20 dB forward transmission suppression of non-fundamental modes within an acoustic delay line while maintaining the fundamental Rayleigh mode, a phenomenon not captured by conventional AE treatments. To probe these dynamics, we integrate an optical waveguide along the acoustic delay line, providing a broadband, non-destructive interface between the acoustic and optical domains. Leveraging both this optical interface and the underlying mode selectivity, we demonstrate proof-of-concept multi-domain transduction and Rayleigh-mode filtering on this hybrid platform, outlining a scalable path toward electrically reconfigurable mode engineering and microwave-photonic functionality. Source arXiv: 2609.36198v1
Learning sparse quantum states from single-qubit measurements Authors Su-un Lee, Liang Jiang, Kunal Sharma Published: 09.28.2026 Updated: 09.28.2026 Summary We study the problem of learning a sparse quantum state, an $n$-qubit quantum state whose density matrix has at most $s$ nonzero matrix entries in an unknown product basis. While such states admit compact classical descriptions, they can carry long-range entanglement that prevents reconstruction from local reduced density matrices alone. Therefore, previous learning approaches addressed such long-range-entangled states using many entangling gates to extract the necessary information. In this work, we show that sparse states can nevertheless be efficiently learned using only single-qubit measurements. Specifically, when the sparsity $s$ is constant, our algorithm can learn sparse states from single-qubit measurements with polynomial sample complexity and classical computational complexity. When $s$ grows polynomially with $n$, sparse states can still be learned from single-qubit measurements with polynomial sample complexity, although efficient classical computation is not guaranteed in general. In this regime, however, the classical computational complexity becomes quasipolynomial when the state is sparse in an unknown basis that is a product of a known fixed finite set of single-qubit bases (e.g., eigenbases of Pauli operators). These results establish efficient learning of sparse states with long-range entanglement without entangling gates, and the single-qubit measurement requirements make our algorithms compatible with current quantum devices. Source arXiv: 2609.35648v1
Sample-Efficient Tomography of a Class of Mixed States with Extensive Entanglement and Magic Authors Pengcheng Liao, Quntao Zhuang Published: 09.23.2026 Updated: 09.23.2026 Summary Full tomography of a generic many-qubit quantum state requires exponentially many copies, while suitable structural constraints can make reconstruction sample-efficient. Existing approaches exploit, for example, limited entanglement structure, low magic, or constrained state-preparation circuits. Here we consider a class of mixed states that can simultaneously exhibit extensive entanglement and extensive magic. Specifically, we introduce Clifford-encoded block-product (CEBP) states, obtained by applying an unknown global Clifford unitary to a tensor product of arbitrary mixed states supported on unknown blocks of bounded size. We show that, for a fixed block size, CEBP states can be reconstructed using polynomially many copies by exploiting Clifford-preserved Pauli correlations to recover the latent structure and reduce the remaining problem to local tomography. Our result demonstrates that sample-efficient tomography can arise from bounded complexity in a latent frame even when the physical state is highly entangled, highly magical, and mixed, and suggests complexity modulo structured transformations as a broader organizing principle for quantum-state learnability. Source arXiv: 2609.27177v1
Resonant multi-harmonic acousto-optics for programmable frequency control of visible light in a CMOS platform Authors Jacob M. Freedman, Matthew J. Storey, Daniel Dominguez, Andrew Leenheer, Nils T. Otterstrom, Matt Eichenfield Published: 09.22.2026 Updated: 09.22.2026 Summary Scaling quantum control for atoms, ions, and solid-state emitters requires gigahertz-frequency spectral control of high-power visible light in a volume-manufacturable platform. Silicon nitride photonics provides high power handling and CMOS-foundry compatibility but has no intrinsic mechanism for high-speed modulation. Integration with piezoelectric materials enables acousto-optic phase modulation, and mechanical resonant enhancement has made it efficient at gigahertz frequencies. However, a single resonance restricts the modulation waveform to a single tone, imposing Bessel-function sideband amplitudes and limiting frequency-shifting efficiency to 33.9%. Here we engineer a silicon nitride acousto-optic microstructure to support harmonically spaced resonances at 1.14 GHz and 2.28 GHz, each strongly optomechanically coupled to a 730 nm guided optical mode, so that tailored non-sinusoidal modulation waveforms can be resonantly synthesized. By piezoelectrically controlling the two mechanical amplitudes and their relative phase, we demonstrate 50% conversion to one sideband (1.5x the single-tone theoretical maximum), a flat seven-line comb, and a frequency shift with 60 dB carrier and 53 dB image suppression – to our knowledge the highest reported for an integrated modulator. The devices are fabricated in a 200 mm CMOS foundry, and we measure 91.7% yield without post-fabrication tuning across 36 devices from three wafers. We also show how the technique can be straightforwardly scaled to three or more harmonics. This result overcomes the trade-off between resonant enhancement and spectral programmability, with important consequences including improved single-qubit gate efficiency for hyperfine qubits. Source arXiv: 2609.25593v1
Scalable entanglement distribution using encoded hybrid repeater chains Authors Stav Haldar, Saikat Guha, Don Towsley, Filip Rozpędek Published: 09.17.2026 Updated: 09.17.2026 Summary Long-distance entanglement distribution requires error correction protocols to compensate for qubit decoherence in quantum memories and noise introduced during entanglement swapping. We argue that repeater chains with error-correction capabilities should exploit more than one physical platform, combining the complementary strengths of different quantum memory technologies into a single hybrid repeater architecture. An important constituent of such an architecture is a hybrid repeater which combines type-1 memories, characterized by fast entanglement generation rates and suitability for multiplexing, and type-2 memories that offer long coherence times and low two-qubit gate error rates. Taking the resource-intensive nature of hybrid nodes into account, we propose and analyze repeater chains in which only a subset of nodes need to be hybrid, while the remaining nodes are simpler first-generation repeaters with no error-correction capability. Through detailed Monte Carlo simulations of fault-tolerant encoded repeater chain protocols based on the three-qubit phase-flip repetition code, the $[[7,1,3]]$ Steane code, and the $[[9,1,3]]$ Shor code, we demonstrate that these hybrid architectures outperform pure architectures based on a single memory platform in terms of end-to-end entanglement distribution rate. In our study we develop a full circuit-level noise model of our architectures and examine the impact of an imperfect interface between the two platforms on our hybrid architecture. We also develop a modified version of the swap-as-soon-as-possible policy with multiplexing, more suited to our architecture where some nodes perform error-correction while others do not. This modified policy significantly reduces the information storage time in memory qubits relative to the previously considered swap policies in encoded repeater chains. Source arXiv: 2609.19783v1
Radio-Frequency Convolutional Neural Networks Authors Zhihui Gao, Shi-Yuan Ma, Yiran Chen, Dirk Englund, Tingjun Chen Published: 09.16.2026 Updated: 09.16.2026 Summary Running artificial intelligence (AI) models directly on edge devices such as smartphones, wearables, and drones offers low latency, pervasive scalability, and data privacy, but these devices rarely carry the computing capability that modern neural networks demand. Edge accelerators have been developed in response, yet each adds computing hardware to devices already constrained in size, weight, power, and cost (SWaP-C). An alternative lies in what these devices already carry: the frequency mixer in every wireless radio multiplies signals in time, natively performing convolution in the frequency domain. Here we introduce radio-frequency convolutional neural networks (RF-CNNs), which repurpose existing communication hardware for CNN inference. Multi-channel convolutions are mapped onto frequency tones for a passive mixer to execute in a single pass. We experimentally demonstrate that RF-CNN runs deep CNNs up to 26.4 million parameters and nine layers from classification of wireless signals and images to controllable image generation, close to full-precision performance. Because the weights arrive over the air and the analog hardware is shared with communication, the edge device spends energy only on data preparation and readout-down to 0.72 femtojoules per multiply-accumulate, two orders of magnitude less than it would cost on an added digital processor. These results suggest that deployed wireless infrastructure can bring efficient, state-of-the-art AI inference to the billions of devices it already connects. Source arXiv: 2609.19279v1
Hysteresis and trap emission in dc-biased integrated lithium niobate electro-optic modulators Authors Matthew Yeh, CJ Xin, Donald Witt, David R. Barton, Evelyn L. Hu, Marko Lončar Published: 09.15.2026 Updated: 09.15.2026 Summary The electro-optic effect is crucially important for low power and efficient tuning of integrated photonic circuits. However, in electro-optic materials such as lithium niobate, dc biasing for an extended duration of time results in the emergence of numerous nonidealities, including hysteresis — a persistent degradation of the magnitude and linearity of the dc electro-optic response. We show that electro-optic hysteresis can be reversed under both zero-bias and reverse-bias conditions, given sufficient time or reverse voltage and consistent with a defect model of the underlying physics. Specifically, we find that drift phenomena at short time scales can be explained by charge trapping dynamics near the contact junction, and thereby devise an active reset protocol that restores the magnitude of the response and partially restores the drift time scales. Source arXiv: 2609.17489v1
Pump-Free Microwave-Optical Bell Pair Generation for Teleportation-Based Quantum Transduction Authors Fangxin Li, Jaesung Heo, Zhaoyou Wang, Benjamin Pingault, Xingyu Gao, Tengyang Ruan, Anjun Chu, David D. Awschalom, Andrew N. Cleland, Andrew P. Higginbotham, Alexander A. High, Liang Jiang Published: 09.14.2026 Updated: 09.14.2026 Summary The coherent conversion between microwave and optical photons, known as quantum transduction, is critical for connecting superconducting processors to optical networks. Existing methods are limited by complications associated with optical pumping. We propose a pump-free microwave-optical Bell-pair source for teleportation-based transduction. Using a spin or atomic system resonantly coupled to optical and microwave cavities, the scheme generates loss-robust heralded Bell pairs. Across color centers, atomic ensembles, and phonon-mediated systems, this assembly achieves kilohertz-range heralding rates with high fidelity. Source arXiv: 2609.16364v1
Utility-Based Path Selection and Configuration in Quantum Networks via Layered Shortest Paths Authors Leonardo Bacciottini, Subhransu Maji, Don Towsley, Gayane Vardoyan Published: 09.14.2026 Updated: 09.14.2026 Summary A path in a quantum network is a chain of repeaters that distributes entanglement between two users. Selecting a path requires balancing the rate and quality (e.g., fidelity) of the delivered entanglement, but these quantities, unlike standard routing metrics, compose non-additively. The problem is compounded by link-level configuration choices (e.g., distillation rounds or emitter brightness tuning), each trading rate against fidelity, so that a path’s performance depends jointly on its route and its per-link settings. We cast this joint path selection and configuration problem as a shortest path computation on a layered graph whose layers track discretized end-to-end fidelity. A single run returns the full rate fidelity Pareto frontier, from which the path maximizing any nondecreasing utility function of rate and fidelity can be selected. We prove that for certain utility functions (including the secret key rate of BB84), the method is a fully polynomial time approximation scheme, returning a near-optimal path within a specified tolerance. We further characterize exactly when cheaper scalarization-based routing suffices: it is optimal for utility functions with convex fidelity profiles, but can be arbitrarily suboptimal otherwise (e.g., for step-like, sigmoidal utilities), whereas the layered method remains reliable in all cases. Source arXiv: 2609.16198v1
Towards Block-Level Fault-Tolerant Quantum Simulation on Small High-Rate Non-CSS Codes Authors Zhuangzhuang Chen, Narayanan Rengaswamy Published: 09.14.2026 Updated: 09.14.2026 Summary Small high-rate non-CSS stabilizer codes provide compact platforms for encoded quantum computation, but mixed-Pauli checks and limited native transversal logical gates complicate fault-tolerant dynamics. Block-level constructions offer an alternative by mapping an entire logical block to a physical circuit rather than compiling separately protected logical gates. We investigate this approach using the high-rate [[8,3,3]] non-CSS code and logical Trotter circuits as a testbed. We construct flagged syndrome-extraction circuits and establish a circuit-level memory pseudo-threshold near (1.5times10^{-3}). We then apply our symplectic-transvection construction, which maps a logical Trotter circuit to a physical circuit with the same block pattern for any stabilizer code. Although this mapping preserves the intended unitary algebraically, encoded Trotter circuits exhibit asymmetry between logical-(X) and logical-(Z) failure channels. Single-fault analysis identifies the mechanism: a fault on the shared parity ancilla can propagate through the uncomputation network into an undetectable logical operator, reducing the effective circuit distance in the affected sector. We evaluate flag-conditioned recovery, biased-noise decoding, CliNR resource verification, flag postselection, and asymmetric gate-noise models. These methods suppress propagated faults but do not simultaneously suppress both logical sectors in the realistic configurations studied. A diagnostic protected limit removing the identified malignant first-order locations restores pseudo-threshold behavior in both sectors, approaching memory performance. These results demonstrate the potential of block-level logical constructions for non-CSS codes without rich native transversal gate sets and the joint protection of the parity network, analog rotation, and recovery required to preserve fault-tolerant distance. Source arXiv: 2609.16159v1
Identifiability in Quantum State, Process, and Network Tomography Authors Athira Kalavampara Raghunadhan, Matheus Guedes De Andrade, Don Towsley, Indrakshi Dey, Daniel Kilper, Nicola Marchetti Published: 09.11.2026 Updated: 09.11.2026 Summary Quantum State Tomography (QST), Quantum Process Tomography (QPT), and Quantum Network Tomography (QNT) are related parameter-estimation problems that aim to reconstruct different physical quantities. QST estimates an unknown quantum state, represented by its density matrix, from the measurement outcomes. QPT characterises an unknown quantum channel using known input states and measurements of the corresponding outputs. QNT, in contrast, aims to infer parameters associated with individual links from end-to-end probe measurements collected at accessible monitor nodes. A key distinction among the three tomography problems lies in the conditions required to achieve identifiability, the ability to determine unknown parameters uniquely from the available measurement statistics. In QST and QPT, the experimenter can choose an Informationally Complete (IC) measurement set. QNT limits the reachable measurements to what topology and monitor placement allow, so the admissible probe paths fix the information available about the link parameters. This work studies all three tomography problems through a common Fisher Information Matrix (FIM). We factorise QNT FIM and show that its rank equals the rank of the path-link incidence matrix at every interior parameter value, so local and global identifiability coincide. We then show that QST and QPT attain full rank under IC settings, QNT loses rank when the probe paths leave link parameters indistinguishable, and increasing the number of copies scales the FIM eigenvalues while leaving its rank fixed. Source arXiv: 2609.13584v1
Optimal Hamiltonian Parameter Estimation in the Presence of Nuisance Parameters Authors Zhiyao Hu, Haidong Yuan, Liang Jiang, Zain H. Saleem Published: 09.11.2026 Updated: 09.11.2026 Summary In many sensing applications, the quantity of interest is not the only unknown, there are also additional unknown parameters, known as nuisance parameters, that affect the precision of estimation. While the ultimate local precision limit for a target parameter is well understood in the absence of nuisance parameters, the problem becomes significantly more challenging when they are present. In this work, we develop a framework for optimal Hamiltonian parameter estimation in the presence of nuisance parameters. We introduce an effective generator that captures the influence of nuisance parameters on the target precision, providing an explicit characterization of the ultimate precision limit for estimating the target parameter. Finally, we provide explicit optimal protocols, including probe state, control, and measurement that saturate this fundamental limit. Source arXiv: 2609.12857v1
Nonlinear dynamics and mechanical frequency combs with a Meissner-levitated micromagnet Authors Yiqi Wang, Trisha Madhavan, Vanessa Wachter, J. DaLi Schaefer, Addison NewRingeisen, Zhiyuan Wei, Frankie Fung, Benjamin A. Stickler, Mikhail D. Lukin Published: 09.10.2026 Updated: 09.10.2026 Summary Nonlinearities in multimode mechanical systems can give rise to rich dynamical phenomena with great potential for sensing applications and for future quantum experiments. We demonstrate that the coupled center-of-mass and rotational motion of a Meissner-levitated micromagnet offer a promising platform for nonlinear dynamics, combining low dissipation, magnetic tunability, strong intrinsic Duffing nonlinearities, and nonlinear intermodal couplings. We use this tunability to demonstrate the generation of a mechanical frequency comb in the micromagnet dynamics, realized by parametric excitation of two translational modes followed by cascaded nonlinear frequency mixing, which produces a phononic comb with tunable spacing. At large amplitudes, nonlinear coupling to a low-frequency librational mode of the magnet leads to parametric excitation and phase locking of that mode, generating a dense spectral fine structure at subharmonics of the drive. These results establish levitated micromagnets as a platform for nonlinear multimode mechanics, with potential applications in precision sensing and quantum-limited metrology. Source arXiv: 2609.11668v1
Nonlinear dynamics and mechanical frequency combs with a Meissner-levitated micromagnet Authors Yiqi Wang, Trisha Madhavan, Vanessa Wachter, J. DaLi Schaefer, Addison NewRingeisen, Zhiyuan Wei, Frankie Fung, Benjamin A. Stickler, Mikhail D. Lukin Published: 09.10.2026 Updated: 09.11.2026 Summary Nonlinearities in multimode mechanical systems can give rise to rich dynamical phenomena with great potential for sensing applications and for future quantum experiments. We demonstrate that the coupled center-of-mass and rotational motion of a Meissner-levitated micromagnet offer a promising platform for nonlinear dynamics, combining low dissipation, magnetic tunability, strong intrinsic Duffing nonlinearities, and nonlinear intermodal couplings. We use this tunability to demonstrate the generation of a mechanical frequency comb in the micromagnet dynamics, realized by parametric excitation of two translational modes followed by cascaded nonlinear frequency mixing, which produces a phononic comb with tunable spacing. At large amplitudes, nonlinear coupling to a low-frequency librational mode of the magnet leads to parametric excitation and phase locking of that mode, generating a dense spectral fine structure at subharmonics of the drive. These results establish levitated micromagnets as a platform for nonlinear multimode mechanics, with potential applications in precision sensing and quantum-limited metrology. Source arXiv: 2609.11668v2
Optically induced metallic state with persistent monoclinic symmetry in NdNiO$_3$ Authors Christian Tzschaschel, Felix Utsch, Qi Song, Spencer Doyle, Grace A. Pan, Charles M. Brooks, Julia A. Mundy, Clemens von Korff Schmising, Stefan Eisebitt Published: 09.10.2026 Updated: 09.10.2026 Summary Understanding whether electronic and structural order remain coupled under nonequilibrium conditions is a central challenge in correlated materials. Here, we simultaneously track metallicity and symmetry across the photoinduced insulator-to-metal transition in NdNiO$_3$ using time-resolved optical reflectivity and symmetry-sensitive second-harmonic generation. We find that metallic reflectivity emerges at significantly lower excitation fluence than restoration of the orthorhombic high-temperature symmetry. As a result, optical excitation stabilizes a metastable state that combines the reflectivity of the metallic phase with the monoclinic symmetry of the insulating phase, revealing an optically induced monoclinic metal. Only at substantially higher fluences does the symmetry fully recover to that of the high-temperature phase. These results demonstrate a nonequilibrium decoupling of metallicity and structural symmetry and establish simultaneous multiprobe spectroscopy as a powerful approach for identifying emergent phases in correlated materials. Source arXiv: 2609.11238v1
AxQM: A Textbook-Scale Benchmark for Formal Proof Synthesis in a Library of Finite-Dimensional Quantum Mechanics Authors Weichen Winston Yin, Jacob M. Taylor, Dirk R. Englund, Frank H. L. Koppens Published: 09.04.2026 Updated: 09.04.2026 Summary Formalizing mathematics in a proof assistant, where a machine checks every definition, statement and proof, has set a new standard of rigor. Large language models are now capable of formalizing autonomously, even at the scale of whole textbooks. We bring this standard of rigor to physics, where theoretical arguments carry idealizations that are rarely stated fully, and any logical gaps could have a cascading effect on interdependent results. Recognizing the need to evaluate autoformalization systems for physics, we release AxQM, 1,019 kernel-checkable proof-synthesis tasks over 479 items drawn from the textbook Quantum Computation and Quantum Information by Nielsen and Chuang. The tasks are stated in a custom Lean library of finite-dimensional quantum mechanics. By task count, it is the largest proof-synthesis benchmark in physics by a factor of four. AxQM is derived from a near-complete formalization of the formal portions of the textbook, so every task is guaranteed a solution, which we keep private. Grading of the benchmark is done deterministically by the Lean kernel, which checks that the proof compiles, that no sorry appears in it or in any declaration it depends on, and that it introduces no new axioms. Source arXiv: 2609.05157v1
Nanoscale magnetometry via collective many-body dynamics in diamond Authors Haoyang Gao, Piotr Put, Nathaniel T. Leitao, Nazlı U. Köylüoğlu, Andrew Maccabe, Mathew Mammen, Siddharth Dandavate, Lillian B. Hughes Wyatt, Leigh S. Martin, Ania C. Bleszynski Jayich, Hongkun Park, Mikhail D. Lukin Published: 09.02.2026 Updated: 09.02.2026 Summary Many-body dynamics constitutes a promising approach for creating correlations between quantum particles which can be used for applications in sensing and metrology. However, utilizing this potential for substantial gains in practical settings is a challenging task with only a very few applications realized to date. Here, we demonstrate an approach to nanoscale magnetic sensing enabled by strongly interacting electronic spins in a room temperature solid. By coherently controlling collective many-body dynamics of a dipolar ensemble of $sim 10^4$ nitrogen-vacancy (NV) centres in diamond with pulsed magnetic field gradients, we demonstrate practical metrological gain up to $7.9(2),mathrm{dB}$ for magnetic signal detection and $8.8(3),mathrm{dB}$ for magnetic noise sensing, fully accounting for experimental overheads. Finally, we combine these methods to demonstrate a momentum-space-resolved sensing modality that enables detection of spatially correlated magnetic noise at continuously tunable length scales down to 50 nanometers. These observations open the door toward practical applications of interaction-enhanced quantum sensors for nanoscale biological imaging and material characterization. Source arXiv: 2609.03039v1
Contribution-Aware Bandwidth Allocation for Multimodal Split Learning Authors Iason Ofeidis, Leandros Tassiulas Published: 09.01.2026 Updated: 09.01.2026 Summary Multimodal models are increasingly the default option for perception at the network edge, yet they are trained almost entirely in the datacenter, because a client holding several sensor streams cannot host an encoder per modality. Split Learning makes such training feasible by keeping only the first layers on the device, at the cost of an uplink that must carry smashed activations for every modality at every step. Existing compression schemes give each modality the same keep-ratio, so the shared budget is divided in proportion to smashed-activation dimension, a quantity unrelated to how much each modality contributes to the fused prediction. We make that division an explicit decision and call it inter-modality allocation: under a fixed uplink budget, every policy transmits the same expected payload and differs only in how that payload is split across modalities. Our allocator, ModalShare, sets each modality’s keep-ratio from a Shapley contribution score that the server computes over coalitions of activations it has already received. Measuring this score adds no uplink traffic and no client-side computation, and needs no prior knowledge of which stream is which. ModalShare improves accuracy over equal keep-ratios by 15.4 and 12.4 percentage points on CREMA-D and MVSA at matched payload in 5x compression, with strong performance across three compressors, three datasets, and four budgets. We show that existing compressors underperform in multimodal settings, with ModalShare recovering what gains are left behind. Source arXiv: 2609.01406v1
High-Rank Encoding Can Improve Approximate Quantum Error Correction Authors Bikun Li, Liang Jiang Published: 09.01.2026 Updated: 09.01.2026 Summary Conventional quantum-code constructions encode pure logical states as pure code states, but this restriction can sacrifice performance. We show that intrinsic encoding randomness can improve optimal entanglement fidelity. We bound the loss from imposing a rank-one encoder and prove it is at most quadratic near perfect recovery after joint optimization. The optimized advantage survives small noise perturbations. An explicit noise family requires higher-rank encoders arbitrarily close to perfect recovery, with every optimal encoder mapping pure inputs to mixed code states. Source arXiv: 2609.00778v1
Fast Fault-Tolerant Decoders for Hypergraph Product and Lifted-Product Codes Authors Asit Kumar Pradhan, Nithin Raveendran, David Declercq, Bane Vasić Published: 08.31.2026 Updated: 08.31.2026 Summary We design low-complexity, fault-tolerant decoders for quantum low-density parity-check (QLDPC) codes with the goal of reducing decoding latency. We target two major bottlenecks of decoding under the emph{circuit-level} noise model: (i) post-processing via order-statistics decoding (OSD), and (ii) the large number of auxiliary variable nodes commonly introduced to represent CNOT-induced correlations during syndrome extraction. Our key observation is that propagating CNOT faults (emph{hook errors}) create emph{stabilizer-induced} trapping sets (TSs) that are intrinsic to hypergraph-product (HGP) and lifted-product (LP) constructions. Therefore, instead of modeling each such fault with an explicit correlation node and relying on OSD to clean up the resulting failures, we design message-passing decoders that resolve the corresponding emph{stabilizer-induced} TSs directly. We obtain these decoders by deriving QLDPC decoders from decoders for the parent classical LDPC codes and using them collectively to correct broad families of emph{stabilizer-induced} TSs. For CNOT faults that manifest primarily as syndrome errors, we show that their effect is equivalent to a data error together with syndrome-bit measurement errors. Consequently, given repeated measurements and a decoding graph that already includes nodes representing syndrome-bit errors, no distinct variable node is needed for each CNOT fault. Using a emph{phenomenological} Tanner graph with nodes representing only data errors and syndrome-bit errors, simulations on the LP codes show a reduction in, or comparable, logical error rates relative to BP+OSD, at substantially lower decoding complexity. Source arXiv: 2608.31040v1
Multipair-resilient entanglement swapping with complementary linear-optical measurements Authors Siavash Mirzaei Ghormish, Ryan M. Camacho Published: 08.25.2026 Updated: 08.25.2026 Summary Multipair emission is a principal source of false heralds in entanglement swapping with spontaneous parametric down-conversion sources. A conventional Bell-state measurement (BSM) cannot distinguish the desired arrival of one photon from each neighboring source from a mixed-polarization double emission by one source accompanied by vacuum from the other. We show that a cascaded network can resolve this ambiguity by allowing its successive swapping stations to perform different measurements. A direct-basis BSM rejects same-polarization double emissions, whereas a balanced equatorial analyzer, implemented by a four-mode Green Machine (GM), uses two-photon interference to reject mixed-polarization double emissions. At the same time, it recovers same-polarization inter-source events rejected by the BSM as resolved $φ$-type Bell heralds. Their rejection sets jointly cover both single-source two-photon classes while retaining contributions from both useful inter-source classes. We classify the passive four-mode, number-resolving analyzers satisfying this condition and identify the BSM and GM as canonical balanced representatives. Using a Gaussian-state analysis exact to all orders of multipair emission, we evaluate three-source BSM–GM and four-source BSM–GM–BSM Pure Bell Pair sources under coupling, detector, and channel loss. The three-source network suppresses the leading infidelity, while the four-source network heralds an exact Bell state in the lossless limit, a property that holds for every alternating BSM–GM chain with four or more sources. The fidelity advantage over source-count-matched all-BSM networks persists at every loss level studied, a single-channel rate advantage appears without multiplexing, and spectral multiplexing raises the Bell-pair delivery probability toward the asymptotically deterministic limit. Source arXiv: 2608.25211v1
Robust Code RL via Faulty-Code-Driven Test case Synthesis and Dense Reward Shaping Authors Yiwen Zhang, Xiaodong Yan, Zhenyu Huang, Deng Zhao, Liang Jiang, Qing Cui, Zujie Wen, Zhiqiang Zhang, Jun Zhou Published: 08.25.2026 Updated: 08.25.2026 Summary Reinforcement learning from verifiable rewards (RLVR) has emerged as a pivotal technique for enhancing the code generation capabilities of Large Language Models (LLMs). However, the efficacy of RLVR in coding implementations is fundamentally limited by the comprehensiveness of test cases, because insufficient test coverage in code validation often causes false positives, further leading to reward hacking and policy degradation. To mitigate the reward bias stemming from the suboptimal quality of current automated generation methods, we propose the RobustTests framework, which introduces a faulty-code-driven test case synthesis strategy that leverages “near correct” faulty codes to guide the model in precisely capturing latent logical discrepancies and further integrates validator agents with behavioral feature clustering to facilitate the granular filtering of invalid and redundant test cases. To address false negatives caused by inherent hallucination noise in synthetic test cases, RobustTests also incorporates a stepwise dense reward function based on pass rates, bolstering training robustness through fine-grained feedback. By employing this pipeline, we construct a high-quality dataset that augmented the test cases in CodeContests, encompassing a broader spectrum of faulty code scenarios and significantly enhances diagnostic utility. Experimental results demonstrate that, by leveraging a moderately challenging subset of problems from CodeContests for training, RL fine-tuning of Qwen3-32B via RobustTests achieves an absolute 3% performance gain on the LiveCodeBench benchmark compared to baseline methods, confirming the effectiveness of the RobustTests framework in advancing the code generation proficiency of LLMs. Source arXiv: 2608.24135v1
Robust Code RL via Faulty-Code-Driven Test case Synthesis and Dense Reward Shaping Authors Yiwen Zhang, Xiaodong Yan, Zhenyu Huang, Deng Zhao, Liang Jiang, Qing Cui, Zujie Wen, Zhiqiang Zhang, Jun Zhou Published: 08.25.2026 Updated: 08.27.2026 Summary Reinforcement Learning from Verifiable Rewards (RLVR) is pivotal for enhancing LLM code generation, yet its efficacy is often hindered by insufficient test case coverage, leading to reward hacking and policy degradation. To address this, we propose RobustTests, a framework featuring a faulty-code-driven test case synthesis strategy. By leveraging “near-correct” faulty codes, RobustTests captures latent logical discrepancies and employs validator agents with behavioral feature clustering to filter invalid or redundant test cases. Additionally, a stepwise dense reward function based on pass rates is introduced to mitigate false negatives and enhance training robustness. Using this pipeline, we construct an augmented version of the CodeContests+ dataset with superior diagnostic utility. Experimental results show that RL fine-tuning of Qwen3-32B via RobustTests achieves a 3% absolute gain on LiveCodeBench, demonstrating its effectiveness in advancing LLM code generation proficiency. Codes and data are available at https://huggingface.co/datasets/sid6/RobustTests. Source arXiv: 2608.24135v2
Development and Feasibility Evaluation of an Edge AI as Medical Device System for Breast Cancer Multidisciplinary Team Meetings Authors Aarzoo Dhiman, Farzana Haque, Iqtedar Muazzam, Kartikae Grover, Lydia Brian Smith, William Stephen Jones Published: 08.22.2026 Updated: 09.14.2026 Summary Breast Cancer Multidisciplinary Team (MDT) meetings manage increasingly complex cases under considerable time pressure, and documentation requirements can reduce clinical efficiency and decision quality. Existing AI based MDT workflows rely on cloud-based processing, limiting their use because patient discussions contain identifiable information. We developed a fully on-device AI pipeline using open-source Automatic Speech Recognition (ASR) and Large Language Models (LLMs) that transcribes breast cancer MDT discussions, structures clinical information, and generates treatment recommendations using retrieval-augmented generation (RAG) grounded in National Institute for Health and Care Excellence (NICE) guidance. The pipeline runs on a single NVIDIA Jetson AGX Orin, ensuring that patient audio, transcripts, and outputs remain within institutional infrastructure. Evaluation included two recorded simulated MDT discussions, ten clinically validated synthetic discussions, and 1,270 acoustically augmented recordings. Optimisation of Whisper large-v3 reduced word error rate by 20.7% and 24.4% on the recorded discussions and achieved performance within 0.58% WER and 1.58% word information lost of a commercial clinical ASR benchmark on augmented audio. MedGemma-RAG identified 2.3 times more MDT-concordant interventions than a proprietary cloud comparator (p = 0.020), with no significant difference in overall accuracy. Stakeholders identified automated documentation, treatment recommendation support, and case triage as the most credible near-term applications while highlighting workflow integration, governance, and clinician trust as key implementation challenges. These findings demonstrate the feasibility of privacy-preserving, fully on-device AI for MDT documentation and guideline-informed decision support, providing a foundation for prospective clinical evaluation. Source arXiv: 2608.22108v2
Development and Feasibility Evaluation of an Edge AI as Medical Device System for Breast Cancer Multidisciplinary Team Meetings Authors Aarzoo Dhiman, Farzana Haque, Kartikae Grover, Lydia Brian Smith, William Stephen Jones Published: 08.22.2026 Updated: 08.22.2026 Summary Breast Cancer Multidisciplinary Team (MDT) meetings manage increasingly complex cases under considerable time pressure, and documentation requirements can reduce clinical efficiency and decision quality. Existing AI based MDT workflows rely on cloud-based processing, limiting their use because patient discussions contain identifiable information. We developed a fully on-device AI pipeline using open-source Automatic Speech Recognition (ASR) and Large Language Models (LLMs) that transcribes breast cancer MDT discussions, structures clinical information, and generates treatment recommendations using retrieval-augmented generation (RAG) grounded in National Institute for Health and Care Excellence (NICE) guidance. The pipeline runs on a single NVIDIA Jetson AGX Orin, ensuring that patient audio, transcripts, and outputs remain within institutional infrastructure. Evaluation included two recorded simulated MDT discussions, ten clinically validated synthetic discussions, and 1,270 acoustically augmented recordings. Optimisation of Whisper large-v3 reduced word error rate by 20.7% and 24.4% on the recorded discussions and achieved performance within 0.58% WER and 1.58% word information lost of a commercial clinical ASR benchmark on augmented audio. MedGemma-RAG identified 2.3 times more MDT-concordant interventions than a proprietary cloud comparator (p = 0.020), with no significant difference in overall accuracy. Stakeholders identified automated documentation, treatment recommendation support, and case triage as the most credible near-term applications while highlighting workflow integration, governance, and clinician trust as key implementation challenges. These findings demonstrate the feasibility of privacy-preserving, fully on-device AI for MDT documentation and guideline-informed decision support, providing a foundation for prospective clinical evaluation. Source arXiv: 2608.22108v1
Identifiability and Estimation Precision in Quantum Network Tomography with Imperfect Bell-State Measurements Authors Athira Kalavampara Raghunadhan, Matheus Guedes De Andrade, Don Towsley, Indrakshi Dey, Daniel Kilper, Nicola Marchetti Published: 08.21.2026 Updated: 08.21.2026 Summary We study Quantum Network Tomography (QNT) for end-to-end link-error characterization under imperfect Bell-state measurements (BSMs), where multiplicative coupling between link and measurement parameters makes identifiability non-trivial. For an n-node star network, we design probes that ensure unique identifiability and derive closed-form expressions for the Fisher Information Matrix (FIM) and Maximum Likelihood Estimators (MLEs), and characterize estimation precision through the Cramer-Rao Bound (CRB). The results show that BSM imperfections degrade estimation precision, while the proposed probes maintain nearly stable precision for individual link parameters as the network size increases. Monte Carlo simulations further confirm that the Mean Squared Error (MSE) approaches the CRB with increasing sample size. Source arXiv: 2608.21692v1
Increased cyclicity of atomic transitions via coherent interference of decay paths Authors Eliza Cornell, Benjamin Pingault, Gergő Thiering, Neil Sinclair, Ádám Gali, Marko Lončar Published: 08.21.2026 Updated: 08.21.2026 Summary Optical readout is a fundamental tool in atomic state measurement, yet the fidelity of optical readout is frequently limited by imperfect photon collection. This can be mitigated when readout occurs on a cycling transition which continuously fluoresces under resonant excitation, thus increasing signal and enabling single-shot readout. We present a method to extend the cyclicity of atomic transitions via coherent destructive interference between spurious decay paths. We describe the characteristics of atomic systems in which this method can be implemented and model several examples in which the number of emitted photons is increased by multiple orders of magnitude. Source arXiv: 2608.21635v1
Hypothesis testing between quantum ensembles Authors Jian Yao, Quntao Zhuang Published: 08.21.2026 Updated: 08.21.2026 Summary Quantum state ensembles are important in quantum information processing. For example, quantum $t$-designs model highly entangled states in complex systems, while projected ensembles appear in generative quantum machine learning and studies of thermalization. With their sample state accompanied by a classical label, these ensembles contain operational information beyond their average density operators. Yet an ensemble differs from a classical-quantum state because it is invariant under permutations of labels. We formulate binary hypothesis testing between finite quantum ensembles and derive fundamental limits on error probability. Given an observed label pattern, we show that the joint sampled state can be described by power-weighted ensemble moments. This yields the Bayes-optimal measurement and exact finite-sample error, revealing that discrimination is governed by the full moment hierarchy up to the number of samples. In the many-sample limit, we derive Chernoff bounds and obtain exact error exponents for finite uniform pure-state ensembles. We apply these results to optical communication and $t$-designs. For finite uniform pure-state $t$-designs with large $t$, the maximal discrimination exponent scales sharply as $sim t^{-2}$, while equal-prior fixed-error testing requires $sim t^2$ samples. Source arXiv: 2608.21321v1
Attaining Fundamental Limits of Multiparameter Incoherent Optical Imaging Using Joint-Detection Quantum Measurements Authors Nico Deshler, Aakash Warke, Michael R. Grace, Amit Ashok, Saikat Guha Published: 08.20.2026 Updated: 08.20.2026 Summary Resolving extended incoherent objects below the diffraction limit poses an application-rich imaging challenge whose solution may enable a new generation of observational instruments and capabilities. In this work, we invoke a practical model for general imaging by approximating an arbitrary extended incoherent object as a finite grid of thermal point emitters parameterized by their brightnesses. We derive the quantum Fisher information matrix (QFIM) for simultaneous brightness estimation and show that the symmetric logarithmic derivatives weakly commute, indicating that the Helstrom bound furnishes the ultimate quantum limit on the estimation error for incoherent imaging. Furthermore, for deeply sub-diffraction scenes, we find numerical evidence of a gap between the Nagaoka-Hayashi (NH) bound and the Helstrom bound. This gap reveals that separable measurements, though more experimentally accessible, are insufficient to reach the quantum limit, and points to the prospective advantage of joint measurements acting on multiple state copies. Additionally, we show that spatial mode-demultiplexing (SPADE) often saturates the NH bound solidifying its status as a near-optimal separable measurement strategy that significantly outperforms direct imaging. Finally, we articulate two joint detection receivers implemented with bona fide quantum resources that asymptotically achieve the Helstrom bound. Source arXiv: 2608.19524v1
Cyber-Physical Systems for Accessibility and Ability Augmentation: Bridging Diverse Communities Authors Shuchang Xu, Riku Arakawa, Mina Huh, Nandi Zhang, Tianyu Zhang, Wazeer Zulfikar, Ruei-Che Chang, Yotam Sechayk, Huamin Qu, Amy Pavel, Franklin Mingzhe Li, Yukang Yan, Brian A. Smith, Pattie Maes Published: 08.19.2026 Updated: 08.19.2026 Summary The powerful convergence of wearables, robotics, extended reality, and smart environments is expanding the design space for cyber-physical systems (CPS) that support and augment human abilities in daily life. By sensing real-world contexts, modeling user needs, and providing situated assistance, these systems can improve accessibility for people with disabilities while enhancing broader human abilities such as perception, memory, learning, and mobility. However, realizing this potential requires addressing key challenges in context sensing, user modeling, adaptive interaction, privacy, and evaluation to ensure that CPS are reliable and effective in real-world contexts. This workshop will bring together researchers and practitioners across HCI, AI, wearables, robotics, XR, smart environments, accessibility, and ability augmentation to examine shared strategies and challenges for designing accessibility- and ability-centered CPS. Through panel discussions, interactive demos, and mixed-group design activities, participants will identify recurring design principles, technical challenges, and future directions for CPS that support and augment human abilities in real-world settings. For details, please visit: https://cps4all.github.io. Source arXiv: 2608.19422v1
Integer Linear Programming Decoder for Abelian and Non-Abelian Topological Codes Authors Dian Jing, Aubrey Zhang, Liang Jiang, Ruben Verresen Published: 08.19.2026 Updated: 08.19.2026 Summary Topological orders (TOs) are widely used as quantum error-correcting codes, with anyon excitations serving as error syndromes. For certain Abelian TOs, decoding can be performed by independently matching particle-antiparticle pairs of each species. However, matching-based decoders cannot handle more general fusion rules in either Abelian or non-Abelian TOs, nor account for noise that correlates different anyon species. While clustering decoders are more broadly applicable, they typically neglect anyon data and fusion properties, leading to poor performance in practice. In this work, we introduce a fundamentally different decoder for arbitrary TOs based on integer linear programming (ILP). The ILP formulation linearizes the error-correction problem through the introduction of auxiliary variables and encodes fusion rules as linear constraints. Classical optimization then identifies the minimum-weight error configuration. As concrete examples, we determine error-correction thresholds for three TOs: the Abelian $mathbb{Z}_2$ TO under depolarizing noise, where charge and flux errors are correlated; the Abelian $mathbb{Z}_3$ TO, which does not admit a pairwise matching decoder; and the non-Abelian $D_4$ TO under noise channels that generate all anyon species. We demonstrate the versatility of the ILP decoder by showing a clear performance advantage over most existing decoders in all three cases. We further extend the method to incorporate noisy syndrome measurements and propose a just-in-time variant for continuous error correction. Our results establish ILP as a natural framework for handling correlated errors and general anyon fusion rules, and as a powerful and flexible general-purpose decoder for incoherent anyon noise in arbitrary TOs, with applications to fault-tolerant quantum computation. Source arXiv: 2608.18512v1
Global precision bounds and success-probability guarantees in quantum parameter learning Authors Federico Belliardo, James W. Gardner, Liang Jiang, Aashish A. Clerk Published: 08.16.2026 Updated: 08.16.2026 Summary Quantum metrology offers the possibility of quantum enhancements of the precision of various sensing tasks. In this manuscript, we tackle two open problems in the theory of single-shot quantum parameter learning, going beyond the usual setting of local parameter estimation via repeated measurements. The first concerns the construction of global upper bounds on the learning precision. The second concerns rigorous guarantees on the success probability of parameter learning, namely, lower bounds on the probability of learning a parameter with a certain precision, given the constraints on the resources used for the quantum metrology task. We provide rigorous, practical, and global upper bounds and success-probability guarantees for quantum parameter learning. We demonstrate their versatility in a Rabi-frequency-learning example involving a driven qubit coupled to a bosonic environment and a collective-spin Hamiltonian learning problem. Together, the new global bounds and success-probability guarantees allow us to rule out unattainable precision and to certify attainable precision beyond what is possible via standard Fisher-information analysis or binary hypothesis testing bounds. They also allow one to tractably characterize the performance of various learning schemes, without the overhead of an explicit simulation. Source arXiv: 2608.15528v1
Global Precision Bounds and Success-Probability Guarantees in Quantum Parameter Learning Authors Federico Belliardo, James W. Gardner, Liang Jiang, Aashish A. Clerk Published: 08.16.2026 Updated: 09.03.2026 Summary Quantum metrology offers the possibility of quantum enhancements of the precision of various sensing tasks. In this manuscript, we tackle two open problems in the theory of single-shot quantum parameter learning, going beyond the usual setting of local parameter estimation via repeated measurements. The first concerns the construction of global upper bounds on the learning precision. The second concerns rigorous guarantees on the success probability of parameter learning, namely, lower bounds on the probability of learning a parameter with a certain precision, given the constraints on the resources used for the quantum metrology task. We provide rigorous, practical, and global upper bounds and success-probability guarantees for quantum parameter learning. Most importantly, we establish a fidelity-based learning guarantee for generic mixed-state models that can be viewed as the achievability-side analogue of the quantum Cramer-Rao bound. Whereas the latter provides a no-go constraint, based on the local curvature of the fidelities, our bound uses only pairwise fidelities between parameter-encoded states to certify that a prescribed precision is attainable with a guaranteed success probability. We demonstrate the versatility of the new bounds in a Rabi-frequency-learning example involving a driven qubit coupled to a bosonic environment and a collective-spin Hamiltonian learning problem. Together, the new global bounds and success-probability guarantees allow us to rule out unattainable precision and to certify attainable precision beyond what is possible via standard Fisher-information analysis or binary hypothesis testing bounds. They also allow one to tractably characterize the performance of various learning schemes, without the overhead of an explicit simulation. Source arXiv: 2608.15528v2
Quantum Tanner Codes at Moderate Blocklength Authors Feroz Ahmed Mian, Vaishnavi L. Addala, Arman Meraj, Adhiraj Chadha, Stefan Krastanov Published: 08.12.2026 Updated: 08.12.2026 Summary We present explicit constructions of quantum Tanner (QT) codes with good rate and distance, obtained through two complementary approaches: the left-right Cayley complex (LRCC) description and the “lifting” perspective, in which a seed Calderbank-Shor-Steane (CSS) code is lifted by commuting left-right regular actions of a finite group $mathcal{G}$. Through an extensive search over non-abelian groups from GAP’s SmallGrp library, we investigate the moderate-blocklength regime ($n in [500,1000]$) and identify several new code instances with distance upper bounds exceeding $20$. These include $[[480,8,(leq 21,leq 21)]]$, $[[504,4,(leq 36,leq 27)]]$, $[[672,4,(leq 48,leq 28)]]$, $[[720,6,(leq 30,leq 30)]]$, and $[[864,8,(leq 39,leq 31)]]$, with these bounds obtained using up to $350$ million trials of sQetch, a randomized distance estimator. The code instances presented have check weights ranging from $9$ to $20$. Using the Tesseract decoder, we estimate pseudo-thresholds of $3.6%$-$4.6%$ under phenomenological noise and $0.14%$-$0.27%$ under circuit-level noise, comparable to prior results at shorter code lengths. We also provide QuantumExpanders$.$jl, an open-source Julia library for constructing QT codes and explicit constructions of Ramanujan graphs. Source arXiv: 2608.12509v1
Spatially Dense, Continuous-Variable Quantum Computing with Solid State Spin Nonlinearities Authors Hamza Raniwala, Ethan G Arnault, Dirk R. Englund, Matthew E. Trusheim Published: 08.12.2026 Updated: 08.12.2026 Summary Nanomechanical structures have been investigated as a method of achieving long-lived quantum excitations at radio frequencies. Their high quality factors are especially intriguing as a medium for bosonic encoding of quantum information. However, to leading order, mechanical modes typically lack the nonlinearities necessary to achieve interaction between bosonic channels and thus are limited in their ability to scale to the many-qubit regime necessary for practical quantum computing. In this work, we propose and describe an approach for bosonic quantum information processing that uses strain-sensitive solid-state spins as nonlinear elements to produce the relevant nonclassical mechanical states. We outline the architecture required to achieve nearest-neighbor connectivity between mechanical cat-state qubits on-chip, as well as the control and readout architecture required for universal quantum computation. In addition, we show that this architecture can allow for a high spatial density of logical qubits by leveraging both the efficiency of bosonic error correction schemes and the small sizes of the constituent nanomechanical resonators and spin qubits. Finally, we identify the necessary performance metrics that will enable error-correction thresholds at high qubit densities, illuminating a path towards scalable quantum information processing. Source arXiv: 2608.12504v1
Full-Stack High-Volume Quantum Networking Architecture based on Photonic-Integrated Tin Vacancy Centers in Diamond Authors Hamza Raniwala, Ian Christen, Helaman Flores, David Starling, Ryan Murphy, Eric Bersin, Kevin Chen, Marc Davis, Maxim Sirotin, Mahmoud Jalali Mehrabad, Ethan G. Arnault, Matthew E. Trusheim, P. B. Dixon, Dirk R. Englund Published: 08.12.2026 Updated: 08.17.2026 Summary Solid state quantum emitters are a leading platform for photonic quantum networking with memory nodes. However, the inhomogeneous distribution of quantum emitters, as well as several environmental factors (i.e. strain and electric fields) spread the frequency spectrum of the qubits, making them distinguishable and therefore not a reliable resource for distributed quantum entanglement. In this paper, we demonstrate a full-stack approach to integrating nearly indistinguishable tin vacancy (SnV$^-$) quantum emitters on a frequency-tunable photonic interposer that overcomes the native distribution and static variation of quantum emitters for an indistinguishable photonic quantum networking platform. We demonstrate a silicon nitride-on-insulator photonic integrated circuit (PIC) with accompanying multiphysics digital twin (MPhDT) that guides discovery of SnV$^-$ strain-tuning parameters and informs construction of a multi-channel quantum repeater node. On this node, we achieve the first simultaneous demonstration of spectral tuning of the zero phonon line (ZPL) at GHz scale; coherent electron spin control with gate times of $<80$ ns; strongly- and weakly-coupled nuclear spin detection; and commercial fiber array-coupled readout of a SnV$^-$ center. Finally, we propose and simulate improvements to the architecture that achieve 99.96% connectivity of $ N sim 1000$ emitters spanning the inhomogeneous distribution of SnV$^-$ centers in strained diamond, where distributed quantum entanglement may be realized. Source arXiv: 2608.11630v2
Full-Stack High-Volume Quantum Networking Architecture based on Photonic-Integrated Tin Vacancy Centers in Diamond Authors Hamza Raniwala, Ian Christen, Helaman Flores, David Starling, Ryan Murphy, Eric Bersin, Kevin Chen, Marc Davis, Maxim Sirotin, Mahmoud Jalali Mehrabad, Ethan G. Arnault, Matthew E. Trusheim, P. B. Dixon, Dirk R. Englund Published: 08.12.2026 Updated: 08.12.2026 Summary Solid state quantum emitters are a leading platform for photonic quantum networking with memory nodes. However, the inhomogeneous distribution of quantum emitters, as well as several environmental factors (i.e. strain and electric fields) spread the frequency spectrum of the qubits, making them distinguishable and therefore not a reliable resource for distributed quantum entanglement. In this paper, we demonstrate a full-stack approach to integrating nearly indistinguishable tin vacancy (SnV$^-$) quantum emitters on a frequency-tunable photonic interposer that overcomes the native distribution and static variation of quantum emitters for an indistinguishable photonic quantum networking platform. We demonstrate a silicon nitride-on-insulator photonic integrated circuit (PIC) with accompanying multiphysics digital twin (MPhDT) that guides discovery of SnV$^-$ strain-tuning parameters and informs construction of a multi-channel quantum repeater node. On this node, we achieve the first simultaneous demonstration of spectral tuning of the zero phonon line (ZPL) at GHz scale; coherent electron spin control with gate times of $<80$ ns; strongly- and weakly-coupled nuclear spin detection; and commercial fiber array-coupled readout of a SnV$^-$ center. Finally, we propose and simulate improvements to the architecture that achieve 99.96% connectivity of $ N sim 1000$ emitters spanning the inhomogeneous distribution of SnV$^-$ centers in strained diamond, where distributed quantum entanglement may be realized. Source arXiv: 2608.11630v1
Trapping Sets of Detector Error Models Authors Michele Pacenti, Nithin Raveendran, Bane Vasic Published: 08.12.2026 Updated: 08.12.2026 Summary Message-passing decoders are among the most promising candidates for scalable quantum error correction, yet their behavior in the low-error-rate regime remains poorly understood under realistic circuit-level noise. In this work, we introduce a systematic framework for identifying the graph structures that govern decoder failures and for using them to predict the resulting error floor. We apply exhaustive trapping-set enumeration directly to the detector error model of a bivariate bicycle code and test all low-weight fault configurations supported on the resulting structures. This converts the analysis of extremely rare logical failures into a finite structural search, avoiding the prohibitive cost of direct Monte Carlo simulation. We evaluate the framework on three iterative decoders with substantially different architectures and decoding heuristics. Remarkably, for texttt{RelayBP}, the resulting prediction accurately reproduces the simulated error floor; for the others, it remains within the same order of magnitude. Despite their differences, leafless elementary trapping sets capture a substantial part of the low-weight error-floor contribution for all three decoders. Moreover, each decoder admits failures caused by fault configurations well below the correction capability implied by the circuit-level distance, revealing a substantial gap between code distance and practical iterative-decoding performance. These results establish trapping-set analysis as a practical framework for predicting error floors, exposing the structural weaknesses of iterative decoders, and guiding the joint design of decoding algorithms. Source arXiv: 2608.11516v1
Eliminating photon transport in long-baseline optical interferometry using quantum memories Authors Yousef K. Chahine, Chaohan Cui, William DeRocco, Daniel Gottesman, Saikat Guha, Emil T. Khabiboulline, Zhenning Liu, Brittany McClinton, Jayadev Rajagopal, Fredrik Rantakyro, J. Gabriel Richardson, Stephen Ridgway, Aqil Sajjad, Joohyung Song Published: 08.10.2026 Updated: 08.10.2026 Summary In this paper, we describe the fundamental operating mechanisms of optical interferometry using quantum memory and entanglement. We show how these remove the optical delay line bottleneck. Quantum memory is not without its own set of challenges, some of which include very small bandwidths as well as limitations in storage time. We examine the influence of timing artifacts on memory photon capture probability and interferometric complex visibility. We highlight keystone areas of technology that require further development and are essential to realizing these opportunities, as well as ongoing work to overcome these challenges. Source arXiv: 2608.10078v1
Quantum-Classical Coexistence Network Tomography Authors Xuchuang Wang, Joseph C. Chapman, Aneesh Ramaswamy, Matheus Guedes de Andrade, Yu-Zhen Janice Chen, Joseph M. Lukens, Gayane Vardoyan, Don Towsley Published: 08.10.2026 Updated: 08.10.2026 Summary Quantum-classical coexistence networks (QCNs) share optical fiber between quantum and classical signals via wavelength-division multiplexing, offering a practical path to quantum communication over existing telecom infrastructure. However, co- and counter-propagating classical traffic introduce distinct depolarization noise, complicating channel characterization. We develop a tomography framework that infers per-link channel parameters of a QCN from end-to-end measurements alone. We first model each coexisting fiber by decomposing the signal evolution into photon loss, successful transmission, and three direction-dependent depolarization components. We then derive closed-form link-level estimators, and extend the approach to star-topology networks through a system of multiplicative equations across end-node pairs, together with a simple classical-signal-direction-switching protocol that resolves the remaining unknowns. On single-link experimental testbed data, we recover per-link depolarization probabilities accurately, with estimated process fidelities closely tracking the Bayesian-process-tomography baseline across multiple fiber lengths and wavelengths; residual gaps reflect the depolarization-only approximation. Absent a multi-link coexistence testbed, we validate the star-network estimators on emulated paths built from measured single-link channels. We further extend the framework in two directions: (i) a channel model that factorizes the coexisting fiber into a depolarizing-with-loss signal channel and a Raman-noise-injection channel on separate optical modes — a completely-positive, trace-preserving tensor product — whose link observables reduce exactly to our basic model; and (ii) a generalization to arbitrary topologies via a peeling algorithm (trees) and a least-squares estimator (meshes), validated by Monte-Carlo simulations on tree and cyclic-mesh networks. Source arXiv: 2608.09364v1
A high-performance quantum pulse gate in thin-film lithium niobate Authors Silia Babel, Alejandra Alarcón, Laura Serino, Christian Golla, Laura Bollmers, Sebastian Lengeling, Jiayu Yang, Bernhard Reineke, Christof Eigner, Benjamin Brecht, Marko Lončar, Laura Padberg, Christine Silberhorn Published: 08.10.2026 Updated: 08.10.2026 Summary In this work, we demonstrate a quantum pulse gate (QPG) in thin-film lithium niobate. QPGs enable the selective manipulation and detection of temporal modes of quantum light and form the basis of numerous applications in photonic quantum technologies. To date, their widespread adaption is held back by two main limitations: restricted wavelength and polarization combinations of the involved fields and low normalized conversion efficiencies. We overcome these limitations through developing a QPG in thin-film lithium niobate. We design a waveguide geometry that provides the required dispersion properties for a highly efficient type-0 sum-frequency generation.We verify our design through mapping of the phase matching intensity, and demonstrate high-quality QPG operation by measuring a temporal-mode selectivity of (96.8$pm$1.7)% on par with existing QPGs. Thanks to the strong confinement in thin-film lithium niobate, we succeed in demonstrating an internal conversion efficiency of (89.6$pm$0.1)% for a pump power of only 20mW in front of our sample. This yields a lower-bound estimate for the normalized conversion efficiency of (1810$pm$10)$mathrm{W}^{-1}mathrm{cm}^{-2}$, three orders of magnitude higher than in previous QPGs. Our results establish thin-film lithium niobate as ideal platform for high-performance QPGs and are a major step towards practical QPGs for photonic quantum technologies. Source arXiv: 2608.09346v1
Multistage Rewinding Decoder for QLDPC Codes Authors Milad Taghipour, Dimitris Chytas, Bane Vasić Published: 08.07.2026 Updated: 08.07.2026 Summary In this paper, we propose a multistage decoding framework that leverages internal information produced by an underlying message-passing decoder. The proposed method targets the failure dynamics caused by both classical trapping sets and degenerate errors supported on symmetric stabilizers, which are among the primary limitations of iterative decoding for QLDPC codes. To identify unreliable variable nodes, we introduce a heuristic metric that combines several dynamical features of the decoder, including variable-node log likelihood reliabilities, hard-decision oscillations, the number of adjacent unsatisfied checks, and the soft information contributed by unsatisfied checks. Based on this ranking metric, the decoder performs guided rewinds by selectively forcing the initial log likelihood ratio values of the most suspicious variable nodes and restarting the message-passing decoder under the corresponding forced configuration. To manage the combinatorial growth of candidate configurations, the search is formulated within a beam- search framework with controlled beam width. In addition, we introduce a pruning metric based on the combination of the residual syndrome weight and a posteriori reliability of the decoder output, thereby retaining only the most promising search paths. Logical error rate results demonstrate that the proposed decoder significantly outperforms the normalized min- sum decoder and achieves competitive performance with belief propagation enhanced by order-10 ordered statistics decoding. Source arXiv: 2608.07783v1
Beyond the Quantum Promise: A Security Analysis of Classical Control in Quantum Key Distribution Authors Ali Hamza Malik, Raja Hasnain Anwar, Muhammad Taqi Raza Published: 08.07.2026 Updated: 08.07.2026 Summary Quantum Key Distribution (QKD) protocols provide information-theoretic security by using quantum mechanical principles. Yet QKD is fundamentally a hybrid protocol: its security depends on the correct integration of the quantum phase with classical post-processing. While ETSI and ITUT specifications standardize QKD architectures and interfaces, they evaluate protocol security in isolation, leaving cross-layer interactions as an underexplored attack surface. This paper introduces a formal verification framework that holistically models QKD protocols based on ETSI and ITUT QKD specifications. Our model is the first hybrid QKD protocol model that supports automated analysis of protocollevel security focusing on how classical operations influence the security guarantees provided by the quantum phase of the QKD protocol. We formalize a comprehensive symbolic model of QKD protocols, based on ETSI and ITU-T QKD specifications, in Tamarin, an automated protocol verifier. Applying this framework, we obtain formal evidence of three specification-level vulnerabilities in ETSI- and ITU-T-grounded protocol models under adversary Eve+: subverted entanglement injection, basis-deferred measurement, and message reflection. Each arises from a classical control-plane omission in the procedure text and is established under a symbolic abstraction rather than as a claim about all practical deployments. We introduce two protocol improvements: measurement commitment and identitybound message authentication codes (MACs). Tamarin verification confirms that these countermeasures eliminate the identified vulnerabilities under Eve+. We have communicated our results and recommendations to relevant standardization organizations. Source arXiv: 2608.07626v1
Quantum channel learning with limited parallel access Authors Mahadevan Subramanian, Hyukgun Kwon, Liang Jiang Published: 08.05.2026 Updated: 08.05.2026 Summary Quantum channels can characterized by their action on an orthogonal operator basis, where these operators are related to observable properties of the quantum system. For qudit and multimode bosonic systems, this is encoded respectively in the Heisenberg–Weyl transfer matrix estimated from the Choi state, and in the characteristic-function transfer function estimated from the Choi state generated by probing with a two-mode squeezed vacuum state. We derive sample-complexity bounds for estimating entries of these transfer matrix/function to additive accuracy $ε$ with success probability $geq1-δ$, under different resources: access to the complex-conjugate channel $mathcal{E}^*$ and/or simultaneous access to $c$ copies of the channel. In all settings, the learner uses parallel channel calls with adaptively chosen, ancilla-assisted input states and measurements. Absolute values of transfer-matrix entries can be learned efficiently with simultaneous access to $mathcal{E}$ and $mathcal{E}^*$, with tight scaling $ε^{-4}$. Without conjugate access, any $c<d$ copies are insufficient for efficient learning, requiring sample complexity exponential in the number of ($d$-level) qudits $n$ (for prime $d$). Efficiency is recovered at $c=d$, with tight scaling $ε^{-2d}$. For bosonic systems, exponential sample complexity persists for all $c=O(1/ε)$. Although the task is learning a particular state, these bounds carry stronger implications than standard state-learning bounds since the learner controls the inputs and ancillary assistance. This establishes a hierarchy of channel-learning resources: self-complex-conjugate channels require two-copy ancilla-assisted access for efficient learning, while for every square-free $d$, some channels require $d$-copy access. As a corollary, we bounds tighter lower bounds for state learning with limited multi-copy access. Source arXiv: 2608.05307v1
Quantum channel learning with limited parallel access Authors Mahadevan Subramanian, Hyukgun Kwon, Liang Jiang Published: 08.05.2026 Updated: 09.17.2026 Summary Quantum channels can be characterized by their action on an orthogonal operator basis, where these operators are related to observable properties of the quantum system. For qudit and multimode bosonic systems, this is encoded respectively in the Heisenberg–Weyl transfer matrix estimated from the Choi-state, and in the characteristic-function transfer map estimated from a two-mode squeezed vacuum based Choi-state. We derive sample-complexity bounds for estimating entries of the transfer matrix/map to additive accuracy $ε$ with success probability $ge1-δ$, under different resources: access to the complex-conjugate channel $mathcal{E}^*$ and/or parallel access to $c$ copies. In all settings, the learner uses parallel channel calls with adaptively chosen, ancilla-assisted input states and measurements. Absolute values of transfer-matrix entries can be learned efficiently with simultaneous access to $mathcal{E}$ and $mathcal{E}^*$, with tight scaling $ε^{-4}$. Without conjugate access, any $c<d$ copies are insufficient for efficient learning, requiring sample complexity exponential in the number of ($d$-level) qudits $n$ (for prime $d$). Efficiency is recovered at $c=d$, with tight scaling $ε^{-2d}$. For bosonic systems, exponential sample complexity holds in terms of an effective dimension induced by an energy constraint for all $c=O(1/ε)$. Although the task is learning a particular state, these bounds carry stronger implications than standard state-learning bounds since the learner controls the inputs and has ancillary assistance. This establishes a hierarchy of channel-learning resources: self-complex-conjugate channels require two-copy ancilla-assisted access for efficient learning, while for every square-free $d$, some channels require $d$-copy access. As a corollary, we derive tighter lower bounds for state learning with limited multi-copy access. Source arXiv: 2608.05307v2
Active-SWE: Benchmarking Coding Agents for Proactive Bug Fixing without Issue Reports Authors Haobin Li, Ping Deng, Weizhong Qian, Liang Jiang, Zhenyu Huang, Mouxing Yang, Xi Peng Published: 08.05.2026 Updated: 08.05.2026 Summary Coding agents powered by large language models (LLMs) are increasingly adopted in software engineering (SWE) scenarios, capable of fixing a specific bug in large-scale codebase. However, existing SWE benchmarks typically assume that high-quality issue reports with detailed information are always available, which is easily violated in practice due to the complexity of report acquisition and curation. To address this, we introduce Active-SWE, a benchmark for evaluating coding agents on proactively discovering and fixing multiple bugs without report guidance, covering 1,663 tasks across six bug categories and eight languages. Beyond shifting the focus from existing reactive bug fixing to proactive bug fixing, Active-SWE enables a more in-depth evaluation by expanding the scope from fixing a specific recorded bug to multiple-bug fixing and potential bug discovery scenarios. To construct Active-SWE, we propose a novel difficulty-aware task formulation pipeline with a dual-track evaluation framework, facilitating comprehensive evaluation of proactive bug-fixing capability. Extensive experiments reveal that most state-of-the-art coding agents struggle with proactive bug-fixing tasks, demonstrating limited performance in locating and resolving recorded bugs, handling multiple bug fixing scenarios, and discovering valid potential bugs. Source arXiv: 2608.04682v1
Active-SWE: Benchmarking Coding Agents for Proactive Bug Fixing without Issue Reports Authors Haobin Li, Ping Deng, Weizhong Qian, Liang Jiang, Zhenyu Huang, Mouxing Yang, Xi Peng Published: 08.05.2026 Updated: 09.29.2026 Summary Coding agents powered by large language models (LLMs) are increasingly adopted in software engineering (SWE) scenarios, capable of fixing a specific bug in large-scale codebase. However, existing SWE benchmarks typically assume that high-quality issue reports with detailed information are always available, which is easily violated in practice due to the complexity of report acquisition and curation. To address this, we introduce Active-SWE, a benchmark for evaluating coding agents on proactively discovering and fixing multiple bugs without report guidance, covering 1,663 tasks across six bug categories and eight languages. Beyond shifting the focus from existing reactive bug fixing to proactive bug fixing, Active-SWE enables a more in-depth evaluation by expanding the scope from fixing a specific recorded bug to multiple-bug fixing and potential bug discovery scenarios. To construct Active-SWE, we propose a novel difficulty-aware task formulation pipeline with a dual-track evaluation framework, facilitating comprehensive evaluation of proactive bug-fixing capability. Extensive experiments reveal that most state-of-the-art coding agents struggle with proactive bug-fixing tasks, demonstrating limited performance in locating and resolving recorded bugs, handling multiple bug fixing scenarios, and discovering valid potential bugs. Source arXiv: 2608.04682v2
Logical computation with canonical lifted product codes Authors Han Zheng, Guo Zheng, Liang Jiang, Qian Xu Published: 07.30.2026 Updated: 07.30.2026 Summary High-rate quantum low-density parity-check (qLDPC) codes encode many logical qubits with low physical-qubit overhead, but realizing efficient fault-tolerant computation on such dense encodings remains a major challenge. Generic, code-agnostic techniques such as code surgery and gate teleportation apply broadly, but are difficult to make modular, low-overhead, and fully certifiable on complex high-rate codes whose structure is left unexploited. Here we overcome these obstacles by co-designing the code together with its logical instruction set for a broad family of emph{canonical} lifted-product (LP) codes with cyclic symmetry. We show that these codes admit a emph{canonical logical basis}, in which conjugate logical operators are organized into rows and columns of cyclic orbits inherited directly from the underlying classical codes, analogous to the structure that makes hypergraph-product codes so tractable. This canonical basis unlocks a complete logical instruction set, including constant-depth automorphism and fold-transversal Clifford gates, modular graph code surgeries built from a constant number of reusable seed surgery gadgets or a compact canonical extractor, highly parallel logical Pauli-product measurements, and parallel magic-state injection. For example, a $[[1122,148,leq!20]]$ (resp. $[[4350,1224,leq!20]]$) LP code requires only two (resp. four) seed surgery gadgets, while arbitrary high-weight logical measurements can be implemented using a full extractor smaller than half of the data code block. These results advance the frontier of fault-tolerant quantum computation on ultra-high-rate quantum architectures. Source arXiv: 2607.28605v1
Efficient learning of bosonic unitaries beyond the Gaussian class Authors Xiaobin Zhao, Quntao Zhuang Published: 07.30.2026 Updated: 07.30.2026 Summary Multimode quantum processes are generally difficult to learn, due to the large dimensionality and complex entanglement structure beyond the Gaussian class. Here, we show that the fundamental obstruction is not non-Gaussianity itself, but the buildup of irreducible multimode non-Gaussian correlations. We establish a tractability frontier for bosonic unitary learning: a general $m$-mode unitary with input energy at most $E$ per mode requires at least $Ω(E^{2m})$ channel uses, whereas two broad non-Gaussian families—$t$-doped Gaussian unitaries and Gaussian-entanglable unitaries—can be learned with resources polynomial in $m$. The latter can exhibit both extensive non-Gaussianity and strong multimode entanglement. Our forward-only protocols use coherent-state probes, Gaussian operations, local heterodyne detection, and classical post-processing to identify the global Gaussian mixing and reduce the remaining task to single- or few-mode learning. The analysis also yields a multimode quantum Darmois–Skitovich theorem showing that mode-spreading passive networks preserve product structure only for Gaussian input states, an almost-sure activation theorem for non-Gaussian processes showing that non-Gaussian unitaries yield non-Gaussian outputs for almost all coherent input states, and a method for learning unitaries from uncalibrated coherent probes. Our results identify that complexity of learning arises from irreducible mixing of non-Gaussianity and entanglement, rather than either resource alone. Source arXiv: 2607.27534v1
From Pixels to PCells: A Neurosymbolic Approach to Photonic Component Creation Authors Aadarsh Agarwal, Kenaish Al Qubaisi, Dirk Englund Published: 07.29.2026 Updated: 07.29.2026 Summary We present PixCell, a neurosymbolic system in which multimodal agents convert a visually presented photonic component into a parametric program over a small domain-specific language (DSL) of geometric primitives. A system enabling deterministic visual verification renders evaluation asymmetrically cheaper than the generation attempt. While models using multi-seed sampling and iterative revision reach a mean best-turn IoU of only 0.416, multimodal agents through PixCell’s interface and verifier consistently exceed 0.9 mean IoU, with scores reaching 0.974 and 0.955 across eight component targets while also satisfying source contracts. These results demonstrate that frontier multimodal agents can reliably understand and render executable parametric representations from visual targets. Using these live parameters, cross-stack studies on an interferometer reconstruct primitive programs that satisfy an 8.0 nm free spectral range target and the original footprint constraint on modeled 220-nm SOI, 400-nm SiN, and 400-nm TFLN stacks. PixCell further carries a paper-derived splitter from visual reconstruction through SOI full-wave simulation, producing symmetric propagation and balanced outputs. Finally, the same executable verifier supplies a training reward and dataset used to train a Qwen3.6-35B-A3B model with LoRA and GRPO without supervised demonstrations. On eight training-excluded paper figures, its mean champion IoU rises from 0.422 after eight initial attempts to 0.491 after three verifier-guided revision rounds. These results therefore establish a controlled framework for measuring, retargeting, and improving visual-to-parametric photonic component design. Source arXiv: 2608.00084v1
Micro-electromechanical photonic integrated memristors Authors Matthew Zimmermann, Julia M. Boyle, Hardit Singh, Alex Witte, Kevin Palm, Thuy-Linh Le, Andrew J. Leenheer, Daniel Dominguez, Matt Eichenfield, Mark Dong Published: 07.23.2026 Updated: 07.23.2026 Summary Programmable optical memristors embedded in photonic integrated circuits (PICs) are emerging as an important technology for high-speed optical storage and in-memory optical computing applications. These devices provide multi-level, non-volatile storage of optical phases that can be interrogated at the speed of light, enabling parallel data readout or energy-efficient multiply-accumulate operations in artificial neural networks. However, there remains several outstanding challenges with existing optical memristor technology including durability, material-induced optical losses, large-scale reconfigurability, or fabrication yield for realistic applications. Here we introduce an analog-programmable photonic memristor based on photonic integrated micro-electromechanical (MEMS) cantilevers produced in a CMOS foundry. The memristor consists of low-loss silicon nitride waveguides, requires no additional back-end materials integration, and is all electrically programmed with electrostatic-piezoelectric forces. We demonstrate up to 5-bit phase storage levels, 50 kbit/s programming speeds, strain-assisted non-volatility lifetimes >1 hour, >1 billion cycle endurance, and stress-tested millions of write-read cycles with pseudorandom bit sequences. We further extend the memory lifetime to several days with simple electronic refresh circuits in a portable battery-powered module, demonstrating a proof-of-concept optical random-access memory in static or dynamic configurations. Our MEMS-photonics technology represents an important step toward practical optical memristors. Source arXiv: 2607.21693v1
Enhancing Entanglement Purification with Shared Randomness Authors Allen Zang, Bikun Li, Xinan Chen, Eric Chitambar, Liang Jiang, Martin Suchara, Tian Zhong Published: 07.23.2026 Updated: 07.23.2026 Summary Entanglement purification protocols (EPPs) are essential for improving entanglement fidelity to support fault-tolerant distributed quantum information processing. Practical entanglement sources are often heterogeneous and source labels may be unavailable at the EPP layer. We show that classical shared randomness, together with buffer memories, can enhance entanglement purification when source labels are unavailable, without state characterization or EPP circuit optimization. The strategy is to accumulate multiple entanglement distribution rounds and then use shared randomness to shuffle all the stored entangled states before packaging them as inputs to the EPP. For any $n$ Werner sources and any fixed $n$-to-1 bilocal Clifford EPP, we prove that accumulating and shuffling improves the expected success probability and the success-weighted output Bell fidelity over the baseline without accumulating and shuffling, for every $n$, for every finite number of accumulation rounds and in the asymptotic limit, and the improvement increases monotonically with the number of accumulation rounds. Source arXiv: 2607.21555v1
Strategic Plan for Neutral Atom Quantum Computation Authors Adrian J. Menssen, Tout Wang, Michael Gullans, Tom Manovitz, Jacob M. Taylor, Jason Cong, Josiah Sinclair, Ziv Aqua, Daniel J. Blumenthal, J. Pablo Bonilla Ataides, Johannes Borregaard, Antoine Browaeys, Paola Cappellaro, Soonwon Choi, Alexandre Cooper, Robin Côté, Jacob P. Covey, Alexandre Dauphin, Ivana Dimitrova, Matt Eichenfield, Dirk Englund, Jacob Freedman, Akihisa Goban, Brandon Grinkemeyer, Andi Gu, Ruonan Han, Dominik Hangleiter, Aram W. Harrow, Liang Jiang, Eun-ah Kim, Felix W. Knollmann, Aleksander Kubica, Thierry Lahaye, Lucas Lassabliere, Joonho Lee, Bingzhao Li, Mo Li, Wan-Hsuan Lin, Mikhail D. Lukin, Varun Menon, Thomas Propson, Akbar Safari, Mark Saffman, Pascal Scholl, Alexander Schuckert, Giulia Semeghini, Jonathan Simon, David Spierings, Daniel Bochen Tan, Shai Tsesses, Vladan Vuletic, Hanrui Wang, Hanyu Wang, Susanne Yelin, Johannes Zeiher, Hengyun Zhou Published: 07.23.2026 Updated: 07.23.2026 Summary We present a strategic plan for neutral atom quantum computation, bringing together hardware development and theory advancements to achieve the goal of practical quantum advantage. The concept of practical quantum advantage is defined, along with how to verify claims of advantage, and approaches to designing quantum algorithms that deliver practical advantage. Future directions for neutral atom quantum processor hardware are described: scaling-up system size, Qubit encodings and atomic platforms, going further below threshold with neutral-atom logical-qubit performance, continuous reloading of qubits, and fast readout. We also explore opportunities for scalable integrated photonic control technologies. Alongside hardware advancements, new developments in quantum error correction and compilation of quantum circuits are proposed. Finally, we examine the opportunity of networking multiple neutral atom quantum processors together to perform distributed quantum computing and overcome possible limitations of a single system. Source arXiv: 2607.21554v1
Sonic Stage: Auto-Generating Interactive Spatial Soundscapes to Facilitate Dialogue Video Comprehension for Blind Viewers Authors Shuchang Xu, Xiaofu Jin, Gaurav Jain, Wenshuo Zhang, Huamin Qu, Brian A. Smith, Yukang Yan Published: 07.23.2026 Updated: 07.30.2026 Summary Audio description (AD) makes film and television accessible to blind and low-vision (BLV) audiences by narrating characters’ actions. However, in scenes with lots of dialogue, AD often omits important actions because it is constrained not to overlap with speech. It is not yet known how to convey characters’ actions during dialogue. We present Sonic Stage, a system that transforms dialogue videos into interactive spatial soundscapes, enabling BLV audiences to intuitively understand characters’ actions and movements through immersive auditory cues. Sonic Stage conveys essential visual information during dialogue through three auditory techniques: (1) spatialized dialogue to represent spatial layout, (2) diegetic sound to convey character actions, and (3) interactive descriptions to provide context-specific visual details. Evaluation with 12 BLV viewers showed that Sonic Stage significantly improved video comprehension, spatial presence, and narrative engagement. We highlight opportunities for enhancing video accessibility across diverse genres through immersive, interactive audio representations. Source arXiv: 2607.20835v2
Sonic Stage: Automatically Generating Interactive Spatial Soundscapes to Facilitate Dialogue Video Comprehension for Blind Viewers Authors Shuchang Xu, Xiaofu Jin, Gaurav Jain, Wenshuo Zhang, Huamin Qu, Brian A. Smith, Yukang Yan Published: 07.23.2026 Updated: 07.23.2026 Summary Audio description (AD) makes film and television accessible to blind and low-vision (BLV) audiences by narrating characters’ actions. However, in scenes with lots of dialogue, AD often omits important actions because it is constrained not to overlap with speech. It is not yet known how to convey characters’ actions during dialogue. We present Sonic Stage, a system that transforms dialogue videos into interactive spatial soundscapes, enabling BLV audiences to intuitively understand characters’ actions and movements through immersive auditory cues. Sonic Stage conveys essential visual information during dialogue through three auditory techniques: (1) spatialized dialogue to represent spatial layout, (2) diegetic sound to convey character actions, and (3) interactive descriptions to provide context-specific visual details. Evaluation with 12 BLV viewers showed that Sonic Stage significantly improved video comprehension, spatial presence, and narrative engagement. We highlight opportunities for enhancing video accessibility across diverse genres through immersive, interactive audio representations. Source arXiv: 2607.20835v1
Dark matter searches with a 13 meV threshold superconducting sensor array Authors Christopher Albert, Lanqing Yuan, Jacob Harris, Ritoban Basu Thakur, Andrew Bear, Karl K. Berggren, Christopher Cappiello, Christopher Curwen, Peter Day, Byeong H. Eom, Arjun Ghosh, William Ho, Nikita Klimovich, Henry G. LeDuc, Karthik Ramanathan, Alejandro Simon Published: 07.21.2026 Updated: 07.23.2026 Summary Many well-motivated dark matter models predict meV-scale energy deposits in interactions with terrestrial experiments, but this regime is challenging to probe due to a lack of mature single-quantum detectors. Here we report results from QUALIPHIDE (QUAntum LImited PHotons In the Dark Experiment), a cryogenic dark matter search using a $41$-pixel array of energy-resolving microwave kinetic inductance detectors with a $13$ meV threshold, simultaneously used to look for both conversion photons from THz wavelength hidden photon dark matter and phonons from particle-like light dark matter interactions. The experimental design, with on- and off-focus pixels for the hidden photon search, allows for a data-driven background model, giving the experiment discovery potential. A blind analysis of $22$ hours of data shows no significant excess, setting the strongest constraints on the hidden photon kinetic mixing parameter $χ$ over the mass range of $13$-$90$ meV/$c^2$, reaching $1.5times10^{-12}$ at $50$ meV/$c^2$. These data also yield among the first terrestrial limits on dark matter scattering off nuclei and electrons, down to $5$ MeV/$c^2$ and $20$ keV/$c^2$, respectively. The low threshold also enables future study of the low-energy excess limiting cryogenic detectors and, as we project, will allow for a terahertz-scale QCD axion search with a magnetic field. Source arXiv: 2607.19319v2
Dark matter searches with a 13 meV threshold superconducting sensor array Authors Christopher Albert, Lanqing Yuan, Jacob Harris, Ritoban Basu Thakur, Andrew Bear, Karl K. Berggren, Christopher Cappiello, Christopher Curwen, Peter Day, Byeong H. Eom, Arjun Ghosh, William Ho, Nikita Klimovich, Henry G. LeDuc, Karthik Ramanathan, Alejandro Simon Published: 07.21.2026 Updated: 07.21.2026 Summary Many well-motivated dark matter models predict meV-scale energy deposits in interactions with terrestrial experiments, but this regime is challenging to probe due to a lack of mature single-quantum detectors. Here we report results from QUALIPHIDE (QUAntum LImited PHotons In the Dark Experiment), a cryogenic dark matter search using a $41$-pixel array of energy-resolving microwave kinetic inductance detectors with a $13$ meV threshold, simultaneously used to look for both conversion photons from THz wavelength hidden photon dark matter and phonons from particle-like light dark matter interactions. The experimental design, with on- and off-focus pixels for the hidden photon search, allows for a data-driven background model, giving the experiment discovery potential. A blind analysis of $22$ hours of data shows no significant excess, setting the strongest constraints on the hidden photon kinetic mixing parameter $χ$ over the mass range of $13$-$90$ meV/$c^2$, reaching $1.5times10^{-12}$ at $50$ meV/$c^2$. These data also yield among the first terrestrial limits on dark matter scattering off nuclei and electrons, down to $5$ MeV/$c^2$ and $20$ keV/$c^2$, respectively. The low threshold also enables future study of the low-energy excess limiting cryogenic detectors and, as we project, will allow for a terahertz-scale QCD axion search with a magnetic field. Source arXiv: 2607.19319v1
Foundry CMOS platform for multimodal quantum materials characterization Authors Sharad Kumar Yadav, Luca Nessi, Ondrej Dyck, Jinchen Wang, Bogdan Dryzhakov, Alex Melendez, Huan Zhao, Qian Song, Doha Amer, Cole Brabec, Saleh Alqazlan, Ruonan Han, Riccardo Comin, Stephen Jesse, Dirk Englund, Jawaher Almutlaq Published: 07.20.2026 Updated: 07.20.2026 Summary Quantum materials experiments increasingly rely on microwave, electrical, thermal, optical, and structural probes, but these capabilities are typically assembled from custom hardware that limits reproducibility and scalability. Here we show that a commercial 65-nm CMOS process can be repurposed as a passive, foundry-manufacturable characterization platform by functionally partitioning its metal stack into microwave, thermal, and electrical subsystems within a 1 mm2 footprint. The integrated RF architecture enables cryogenic magnetic susceptibility measurements of Fe3GeTe2 heterostructures at 1.75 K without sample-specific fabrication. We further demonstrate NV-center optically detected magnetic resonance (ODMR) with >20% contrast at 4-9 dBm microwave power, reducing power requirements by 20-25 dB relative to conventional antenna-based approaches while maintaining sensitivities of 2-3 uT/sqrt(Hz). We additionally confirm compatibility with in-situ electron-beam imaging, showing no measurable degradation in image quality upon device operation. These results establish a scalable, foundry-manufacturable platform for multimodal quantum sensing and materials characterization. Source arXiv: 2607.18059v1
Efficient routing and spectrum allocation in arbitrary flex-grid entanglement networks Authors Zachary Goisman, Matthew L. Stevens, Maxwell Goisman, Taman Truong, Gayane Vardoyan, Don Towsley, Nicholas A. Peters, Nageswara S. V. Rao, Guoliang Xue, Joseph M. Lukens Published: 07.16.2026 Updated: 07.16.2026 Summary As practical quantum networks approach large-scale deployment, the need for efficient user-to-user frequency allocation is increasing, yet current approaches only provide partial solutions to the routing and spectrum allocation problem for an arbitrary quantum network. We address this challenge for repeater-less flex-grid quantum networks based on hyperentangled photons using an efficient three-stage pipeline combining leading tools in classical networking with recent advances in numerical optimization. First, double instantiations of Yen’s algorithm obtain low-loss route candidates between each pair of users and the entanglement sources. Second, the advanced process optimizer (APOPT) obtains frequency channel allocations that maximize distribution rates under fidelity constraints. Finally, the constraint programming solver using satisfiability methods (CP-SAT) assigns specific frequency bins to each link, ensuring that there is no contention between frequencies from different sources. We numerically demonstrate this approach on a representative ring network and a Manhattan incumbent local exchange carrier topology, realizing significant improvements over prior genetic algorithm approaches in speed, accuracy, and scalability. Overall, this pipeline provides an efficient heuristic workflow for optimizing broadband entanglement distribution, applicable to arbitrarily connected quantum networks integrated within the existing lightwave infrastructure. Source arXiv: 2607.15465v1
Saturating the Bayesian Nagaoka-Hayashi bound within numerical precision for the depolarization SU(2) rotation channel Authors Leo Bia, Christos N. Gagatsos Published: 07.16.2026 Updated: 07.16.2026 Summary The Bayesian Nagaoka–Hayashi (NH) bound is a semidefinite lower bound on the Bayes risk of multiparameter estimation, tighter than the Bayesian symmertic logarithmic derivative (SLD) Cramér–Rao bounds, and whether it can be attained is an open problem. We study the single-shot estimation of a qubit rotation, all three parameters at once, under depolarizing noise and a uniform prior, with $k$ parallel uses of the channel. Rotational covariance reduces the joint optimization of probe, measurement, and estimator, and the NH bound itself, to small semidefinite programs, solvable through $k=4$. At every number of uses and noise strength the optimized strategy reaches the NH bound within the numerical precision of the calculation, numerical evidence that the bound is attained for this channel family, while the SLD bound lies strictly below and is never attained. As the noise grows the optimal probe collapses to the tensored Bell state. Source arXiv: 2607.15398v1
Ultrafast programmable Bragg reflection in photonic integrated circuits Authors Yunxiang Song, Pawan Ratra, Danxian Liu, Jiayu Yang, Zhongshu Liu, Urban Senica, Salma Mohideen, Mingjie Zhang, Xudong Li, Donald Witt, Joshua Mornhinweg, Norman Lippok, Eric Mazur, Federico Capasso, Marko Lončar Published: 07.16.2026 Updated: 07.16.2026 Summary Distributed Bragg reflectors (DBRs) are foundational building blocks of classical and quantum photonic technologies. However, their optical responses are typically fixed upon fabrication, limiting circuit robustness, reconfigurability, and functionality in applications from high-speed communications to quantum computing. Here, we demonstrate photonic chip-based programmable DBRs at telecommunications wavelengths, which are formed by electro-optically inducing refractive index contrast between periodic ferroelectric domains in thin-film lithium niobate waveguides. We achieve voltage-controlled Bragg reflection from zero to near-unity, and gigahertz-speed reflectivity modulation. Our results bring DBRs into the ultrafast programmable regime, opening new opportunities in topological photonics, cavity quantum electrodynamics, integrated lasers, and optical interconnects. The interplay between nanoscale ferroelectric domain engineering and strong electro-optic nonlinearity establishes a new design strategy for nanophotonic devices, otherwise inaccessible in bulk media. Source arXiv: 2607.14565v1
Towards a monolithic platform for coupling superconducting circuits to low-loss microwave phonons in AlScN on 4H-SiC Authors Yuanchen Deng, William W. Roberts, Sueli Skinner-Ramos, Dalton Anderson, Katherine Hewey, Xingyu Du, Michael Miller, Brandon Smith, Hwijong Lee, Pingping Chen, Charles Thomas Harris, Roy H. Olsson, Lisa Hackett, Rupert Lewis, Matt Eichenfield Published: 07.15.2026 Updated: 07.15.2026 Summary Hybrid superconducting-phonon quantum processing is promising for cavity QED, measurement-based quantum computing, and other quantum applications. Relative to microwave photons at the same frequency, phonons can provide ultra-compact footprints, extremely low losses, and greater connectivity. Phonons can also couple strongly to superconducting circuits through the piezoelectric effect. However, this promise rests on scalable platforms that achieve these benefits without degrading superconducting circuit performance. This motivates a monolithic platform combining low phononic loss, strong electromechanical coupling, and superconducting-circuit compatibility without requiring suspended phononics. Here, we characterize a monolithic quantum acoustic platform combining aluminum superconducting circuits on exposed silicon carbide (SiC) with piezoelectric aluminum scandium nitride (AlScN) on SiC for integrated phononics. This architecture is enabled by selective removal of AlScN from selected chip regions, allowing aluminum superconducting microwave resonators to be fabricated directly on the SiC while preserving adjacent AlScN-on-SiC regions for phonon transduction. The resulting Al-on-SiC resonators exhibit a coherent lifetime of 2.9 μs, demonstrating compatibility with aluminum superconducting quantum devices. In parallel, cryogenic surface acoustic delay-line measurements on the retained AlScN-on-SiC regions show low phononic propagation loss at 4.05 GHz, corresponding to an estimated phonon lifetime of 7.6 μs. Together with a previously demonstrated electromechanical coupling coefficient of about 4.3% and a theoretical upper bound of 8%, these results establish Al-on-SiC/AlScN-on-SiC as a promising monolithic platform for integrating superconducting microwave circuits with piezoelectric phononic components for quantum acoustic networking and hybrid quantum systems. Source arXiv: 2607.14319v1
Emulation of Entanglement Distribution Networks on a Quantum Computer Authors Ashley N. Tittelbaugh, Jerry Horgan, Rohan Bali, Marco Ruffini, Daniel C. Kilper, Shelbi L. Jenkins, Boulat A. Bash Published: 07.15.2026 Updated: 07.15.2026 Summary We investigate how quantum computers can be used to emulate quantum networks and study their performance under practical impairments. In particular, we evaluate how degraded entanglement and communication latency affect teleportation-based distributed multipartite-entanglement-state construction. We model imperfect Bell-pair sources using depolarizing noise channels and classical communication delays using thermal relaxation. We implement the depolarization using Stinespring dilation, randomly applied Pauli errors, and quasi-probability decompositions, evaluating the latter two on IQM quantum hardware and all three in simulation. We then study the performance of the entanglement distribution under noise generated by the aforementioned models. Although these noise models are mathematically equivalent, we find that hardware constraints result in profound differences in the corresponding results, highlighting the importance of careful experiment design. Source arXiv: 2607.14260v1
Emulation of Entanglement Distribution Networks on a Quantum Computer Authors Ashley N. Tittelbaugh, Jerry Horgan, Rohan Bali, Marco Ruffini, Daniel C. Kilper, Shelbi L. Jenkins, Boulat A. Bash Published: 07.15.2026 Updated: 07.17.2026 Summary We investigate how quantum computers can be used to emulate quantum networks and study their performance under practical impairments. In particular, we evaluate how degraded entanglement and communication latency affect teleportation-based distributed multipartite-entanglement-state construction. We model imperfect Bell-pair sources using depolarizing noise channels and classical communication delays using thermal relaxation. We implement the depolarization using Stinespring dilation, randomly applied Pauli errors, and quasi-probability decompositions, evaluating the latter two on IQM quantum hardware and all three in simulation. We then study the performance of the entanglement distribution under noise generated by the aforementioned models. Although these noise models are mathematically equivalent, we find that hardware constraints result in profound differences in the corresponding results, highlighting the importance of careful experiment design. Source arXiv: 2607.14260v2
Square-Root Law for Covert Communication with Warden-Favorable Side Information Authors Hossein Ahmadi, Christian Deppe, Boulat A. Bash, Eduard A. Jorswieck Published: 07.15.2026 Updated: 07.15.2026 Summary Covert communication enables Alice to transmit to Bob while making the transmission difficult for Willie to detect. We study a scalar Gaussian covert-overlay model in which Alice’s low-power covert signal is superimposed on an aggregate public component generated by Alice or other trackable sources. Willie is given all physically obtainable side information, including protocol details, timing, pilots, channel estimates, and calibration information, and subtracts his best estimate of the public component before testing. Covertness is imposed on the resulting residual through a relative-entropy constraint with budget $δ$ conditioned on Willie’s side information. In the stationary case, the residual under no covert transmission has variance $σ_0^2=σ_W^2+σ_e^2$, where $σ_W^2$ is Willie’s receiver-noise variance and $σ_e^2$ is the irreducible cancellation error. Over $n$ channel uses, the maximal reliably transmissible covert payload is $R_C^starsqrt{n}(1+o(1))$ bits, where $R_C^star=frac{σ_0^2}{σ_B^2ln 2}sqrtδ$, and $σ_B^2$ is Bob’s receiver-noise variance. Thus, the square-root-law (SRL) constant is governed by the variance at Willie’s actual detector input, not by receiver noise alone. Low-power Gaussian signaling achieves this constant, and a matching converse establishes first-order optimality within the conditioned additive Gaussian innovation model. For known time-varying conditioned residual variances, we also derive the first-order allocation, which assigns more covert power to larger residual variances. The results require a Gaussian post-cancellation null residual with known conditioned variance; non-Gaussian residuals and fixed non-vanishing variance uncertainty are outside the scope of this paper. Source arXiv: 2607.14013v1
Nonequilibrium thermodynamics of the acoustoelectric quantum vacuum Authors Ryan O. Behunin, Andrew Shepherd, Francesco Intravaia, Matt Eichenfield Published: 07.14.2026 Updated: 07.14.2026 Summary The quantum vacuum can assume thermal properties as a consequence of system kinematics, highlighting the nuance of our definition of particles in quantum field theory. Here, we explore this phenomenon in acoustoelectric systems, involving the interaction of phonons and plasmons, where the charge carriers drift at a constant velocity exceeding the speed of sound. Through an open quantum systems analysis, we show that the acoustoelectric quantum vacuum acquires a thermal character with a temperature defined by the drift velocity and the phonon wavevector. Realistic parameters yield effective temperatures of several Kelvin, establishing acoustoelectric systems as a promising platform for the investigation of quantum vacuum effects. Source arXiv: 2607.12228v1
Quantum-enhanced physical-layer threat detection in metropolitan-scale fiber networks Authors Yung-Cheng Kao, Siddharth Pal, Alex Forencich, Dylan Cirimelli-Low, Chaohan Cui, Jack Postlewaite, Pao-Kang Chen, Nicola Alic, Saikat Guha, Prithwish Basu, Linran Fan Published: 07.12.2026 Updated: 07.12.2026 Summary Network security is widely recognized as a key application of quantum technology. However, its large-scale deployment is hindered by the need for tight coordination between fundamentally different quantum and classical processing steps in conventional protocols. This requirement introduces strong cross-layer interdependencies that conflict with the modular, layered architectures enabling scalability in modern communication networks. Here, we present an alternative strategy that confines all quantum interventions to the physical layer and remains transparently compatible with existing network abstractions. This is achieved by directly embedding quantum features and classical information within the same optical field using bright squeezed light. Physical-layer signals are analyzed using a cumulative sum (CUSUM) method to enable quantum-enhanced threat detection. We validate the practicality of this approach through field deployment over a metropolitan-scale fiber network and further demonstrate network-level security functionalities enabled by physical-layer quantum-enhanced thread detection. These results establish a practical, scalable framework for seamlessly integrating quantum-enhanced security into large-scale communication infrastructure. Source arXiv: 2607.10799v1
Measurement-induced overconcentration in quantum generative models Authors Runzhe Mo, Bingzhi Zhang, Quntao Zhuang Published: 07.11.2026 Updated: 07.11.2026 Summary Quantum measurement is a key resource for quantum generative learning, providing intrinsic stochasticity for generating diverse quantum samples. However, in measurement-assisted state-ensemble resampling, repeated measurements can also induce overconcentration: under a fixed measurement trajectory, distinct input states progressively converge toward similar output states, suppressing input-dependent diversity. To diagnose this effect, we introduce three complementary metrics: accuracy, generative power, and input sensitivity. For Haar-random monitored circuits, we prove that one-step models retain input sensitivity up to dimension-suppressed corrections, whereas sequential monitored circuits exhibit a depth-dependent loss of input sensitivity. Motivated by this diagnosis, we propose a truncated quantum denoising diffusion probabilistic model (QuDDPM), which restricts the temporal depth of both the forward diffusion and reverse denoising processes. Numerical benchmarks show that truncated QuDDPM preserves stronger input sensitivity while maintaining accuracy and generative power comparable to the original model. These results identify measurement-induced overconcentration as a dynamical limitation of deep monitored quantum generative models and establish temporal depth as a design parameter for balancing measurement-induced randomness with input-dependent diversity. Source arXiv: 2607.10055v1
Quantum Sensors for Chemistry and Materials Science Authors Piotr Put, Arjun Pillai, Xuan Hoang Le, Mikhail D. Lukin, Hongkun Park Published: 07.08.2026 Updated: 07.08.2026 Summary The advancement of chemistry and materials science relies on transformative analytical tools which can overcome the sensitivity, spatial resolution, and throughput limitations of conventional techniques. This review explores the application of quantum sensors – specifically optically pumped magnetometers (OPMs) and nitrogen-vacancy (NV) centers in diamond – as robust platforms for molecular and materials analysis. We contrast the extreme magnetic sensitivity of macroscopic OPM ensembles with the atomic-scale resolution and multimodal capabilities of solid-state NV centers. We highlight their deployment in zero- to ultralow-field and nanoscale NMR spectroscopy, real-time reaction monitoring, and transient radical and pH detection. Furthermore, we discuss their integration into high-throughput chemical assays and non-destructive materials diagnostics, such as operando battery monitoring. With the ongoing commercialization of these technologies and advances in quantum-enhanced sensitivities, quantum sensors are poised to routinely address complex real-world analytical challenges. Source arXiv: 2607.07848v1
Design of optomechanical transducers for sub-micron resolution ultrasound imaging Authors Lisa Hackett, Chang Ge, Alex Miera, Brandon Smith, Matt Eichenfield Published: 07.03.2026 Updated: 07.03.2026 Summary Ultrasound is a noninvasive, real-time, and therefore widely used imaging modality; yet its application in cellular and sub-cellular biology is significantly limited by rapidly increasing acoustic losses in aqueous solutions with decreasing wavelength. Here we introduce a nano-optomechanical cavity transducer platform to generate and detect ultrasound in aqueous solutions with a sub-micron acoustic wavelength. We analyze the full signal pathway through a combination of finite element method modeling and the coupled differential equations that describe the dispersive optomechanical interaction. Our findings project a signal-to-noise ratio in the thousands at ~5 GHz, limited by diffraction losses and thermal-acoustic noise. This work establishes a viable path towards optomechanical ultrasound systems capable of label-free imaging at cellular and sub-cellular length scales while also providing a broader framework for optomechanical crystal device operation in aqueous environments relevant to biochemical sensing, medical diagnostics, underwater acoustic sensing, and nanoscale imaging. Source arXiv: 2607.02936v1
Monolithic Integration of Piezo-Optomechanical Photonics and CMOS Electronics Authors Matthew Zimmermann, Aileen Zhai, Andrew J. Leenheer, Julia Boyle, Mayank Mishra, Daniel Dominguez, Matthew Koppa, Wolf Jehle, Christopher Panuski, Mark Dong, Gerald Gilbert, Dirk Englund, Matt Eichenfield Published: 07.01.2026 Updated: 07.01.2026 Summary Next-generation photonic architectures for AI, sensing, and quantum computing require thousands to millions of reprogrammable photonic devices on a chip[1]. The monolithic integration of Electronically-backed Photonic Integrated Circuits (EPICs) allows for very high density electrical interconnection and electronic drivers that can scale with photonics. Piezo-optomechanical photonic integrated circuits (POMPICs) offer low power consumption, high speed modulation, cryogenic compatibility and broadband optical transparency from ultraviolet to infrared wavelengths[2,3], but have not been demonstrated with monolithically integrated CMOS electronics. Here, we show a fully monolithic, all-CMOS fabricated platform for POMPICs co-fabricated with commercial control electronics. 200 millimeter photonic wafers are constructed directly on completed CMOS driver wafers by back-end-of-line processing, connecting integrated piezoelectric actuators under broadband silicon nitride waveguides to a high-density digital backplane comprising >2 million electrical connections per die with 6.4×6.4 micron electrode pitch. We introduce segmented POMPIC components as Photonic Digital-to-Analog converters (PDACs) that convert low-voltage digital electronic signals to multi-bit analog optical phase and amplitude modulation, and we demonstrate parallel control of optical phase shifters, Mach-Zehnder interferometers, optical routing trees, and tunable ring resonators using a standard HDMI interface to program CMOS electronics. We test multiple reticles and perform electronic and photonic characterization across the entire wafer to establish uniformity and yield, demonstrating wafer-scale integration of POMPICs on an electronic backplane and enabling dense, scalable electronic control of piezo-optomechanical circuits. Source arXiv: 2607.01514v1
When AI meets quantum information: A comprehensive review Authors Min Chen, Yu Gan, Xin Jin, Yuqing Li, Junqi Wang, Zeguan Wu, Yunfei Wang, Bingzhi Zhang, Priyam Srivastava, Tianlong Chen, Ankit Kulshrestha, Yuan Liu, Juan José Mendoza-Arenas, Kaushik P. Seshadreesan, Sarvagya Upadhyay, Xueyue Zhang, Quntao Zhuang, Junyu Liu Published: 07.01.2026 Updated: 07.01.2026 Summary Artificial intelligence (AI) and quantum information (QI) are rapidly co-evolving. AI is becoming a practical tool for learning, designing, controlling, and verifying quantum systems, while QI offers new computational models, representational structures, and learning-theoretic questions for AI. This survey reviews the interface from both directions. In the AI for QI direction, we organize recent progress around the central tasks of extracting information from limited measurements, training and discovering quantum algorithms, stabilizing noisy hardware, automating experimental and programming workflows, and extending learning-based methods to sensing and networking. In the QI for AI direction, we examine how quantum computation and quantum-inspired structures affect learning through algorithmic speedups, expressivity, trainability, generalization, neural-network design, and tensor-network representations. We close by identifying cross-cutting challenges in reproducibility, scalability, hardware realism, and co-design, arguing that progress will depend on tighter integration of theory, experiment, and hybrid quantum–classical systems. Source arXiv: 2607.00365v1
PPT-Eval: A Benchmark for Computer-Use Agents on PowerPoint Tasks Authors Apurva Gandhi, Vishwas Suryanarayanan, Raja Hasnain Anwar, Firoz Shaik, Shubhang Desai, Thong Q. Nguyen, Muhammad Taqi Raza, Vishal Chowdhary, Graham Neubig Published: 06.30.2026 Updated: 06.30.2026 Summary Creating and editing slides is a rich, multimodal activity that is ubiquitous in professional and educational settings, making it an ideal testbed for real-world computer-use agents. Microsoft PowerPoint is among the most widely adopted and feature-rich environments for presentation creation. We introduce PPT-Eval, a benchmark of 120 PowerPoint tasks across 12 files that cover both content creation and presentation editing scenarios, organized by difficulty. A central challenge in this domain is evaluation: tasks are complex, multimodal, and often admit many valid solutions. Moreover, today’s agents frequently make only partial progress, which binary success metrics fail to capture. To address this, we design a robust evaluation framework to help create task-specific rubrics for PowerPoint tasks, taking inspiration from and building on past works for rubric-based evaluation. These rubrics award partial credit for intermediate steps, penalize unnecessary changes and poor aesthetics, and provide natural language feedback. This nuanced approach proves highly effective, achieving a Kendall’s τ-b correlation of 0.77 with human judgments. We find that existing frontier agents still struggle with solving PowerPoint tasks, with strong models like Claude-4.5-Opus achieving only a 45% success rate and an average partial score of 57%. The benchmark is located at: https://microsoft.github.io/ppteval. Source arXiv: 2606.31154v1
Experimental Realization of Synthetic Magnonic Lattice via Floquet Engineering Authors Amin Pishehvar, Jayakrishnan M. P. Nair, Zhaoyou Wang, Zixin Yan, Yu Jiang, Liang Jiang, Benedetta Flebus, Xufeng Zhang Published: 06.29.2026 Updated: 06.29.2026 Summary Magnonic systems, which exploit spin-wave excitations in magnetic materials, offer a promising platform for coherent information processing due to their low dissipation, strong nonlinearities, and intrinsic nonreciprocity. However, scaling magnonic circuits remains challenging, particularly with low-loss insulators such as yttrium iron garnet (YIG), which are difficult to pattern. Here, we experimentally realize a synthetic dimension in a magnonic system by coupling multimode magnon resonances in the frequency domain using time-periodic Floquet modulation. This approach enables electronically tunable interactions between discrete modes within a single YIG device, forming a reconfigurable mode-space lattice that supports functionalities such as Bloch oscillation. Our results demonstrate that high-dimensional magnonic dynamics can be achieved without increasing device footprint, establishing synthetic dimensions as a scalable and programmable route for integrated magnonic technologies. This advancement positions magnonic systems as promising platforms for engineering emergent phenomena that are inaccessible at equilibrium. Source arXiv: 2606.30845v1
A Machine-Verified Proof of a Quantum-Optimization Conjecture Authors Uri Kol, Maor Ben-Shahar, Kfir Sulimany, Dirk Englund Published: 06.29.2026 Updated: 06.29.2026 Summary We report a machine-verified resolution of a problem open for over a decade in quantum optimization: the Farhi, Goldstone and Gutmann (FGG) conjecture that depth-$p$ Quantum Approximate Optimization Algorithm (QAOA) on the ring of disagrees attains approximation ratio $(2p+1)/(2p+2)$ exactly. We found the proof using a large language model, Claude Fable 5, and verified its correctness end-to-end by the Lean 4 proof assistant. Our methodology includes several ingredients: building on a substantial Lean library of quantum information, we formalized the QAOA components and the known parts of the problem, and reduced the conjecture to a single open mathematical statement. The model was then handed the library and our agentic toolkit, and tasked with closing that gap by constructing a proof in Lean. The resulting process is a feedback loop between the model’s natural-language reasoning and Lean’s mechanical verification, which converged to a machine-verified proof. Human verification is required only for the structural scaffolding – that the formal statement faithfully encodes the intended claim – while the proof itself is supplied by the model and certified mechanically by Lean. The proof is nevertheless striking – the model uncovered a hidden dynamical symmetry of the problem and exploited it, borrowing tools and machinery from an adjacent field to turn a hard existence problem into an explicit construction. This work paves the way for resolving open conjectures in quantum information science and beyond. Source arXiv: 2606.29687v1
Exploring dynamics of individual vortices in a superconductor via a levitated magnetic transducer Authors Yiqi Wang, Trisha Madhavan, J. DaLi Schaefer, Addison NewRingeisen, Frankie Fung, Mikhail D. Lukin Published: 06.25.2026 Updated: 08.18.2026 Summary Trapped vortices determine fundamental properties of superconductors and play an important role in many practical applications such as magnetic levitation, however their complex dynamics remain poorly understood. Here, we use the mechanical motion of micron-scale levitated magnetic particles to probe the dynamics of individual vortices. Specifically, we show that the dynamics of levitated magnets are strongly influenced by vortices trapped in the YBCO superconducting film. We observe random telegraph signals in the mechanical frequency, dissipation rate, and energy of levitated particles, which we attribute to random tunneling of individual vortices. The nonlinearity of vortex-defect interaction manifests as non-exponential decay in ringdown measurements, revealing a complex underlying potential landscape. Our results provide insights into elusive dissipation mechanisms in superconducting levitated systems, open new avenues for using levitated magnets as sensitive probes of static and dynamic properties of individual vortices in superconductors and their interactions with material disorder, and point toward novel routes for using magnetic particles as highly coherent mechanical transducers. Source arXiv: 2606.27297v2
Exploring dynamics of individual vortices in a superconductor via a levitated magnetic transducer Authors Yiqi Wang, Trisha Madhavan, J. DaLi Schaefer, Addison NewRingeisen, Frankie Fung, Mikhail D. Lukin Published: 06.25.2026 Updated: 06.25.2026 Summary Trapped vortices determine fundamental properties of superconductors and play an important role in many practical applications such as magnetic levitation, however their complex dynamics remain poorly understood. Here, we use the mechanical motion of micron-scale levitated magnetic particles to probe the dynamics of individual vortices. Specifically, we show that the dynamics of levitated magnets are strongly influenced by vortices trapped in the YBCO superconducting film. We observe random telegraph signals in the mechanical frequency, dissipation rate, and energy of levitated particles, which we attribute to random tunneling of individual vortices. The nonlinearity of vortex-defect interaction manifests as non-exponential decay in ringdown measurements, revealing a complex underlying potential landscape. Our results provide insights into elusive dissipation mechanisms in superconducting levitated systems, open new avenues for using levitated magnets as sensitive probes of static and dynamic properties of individual vortices in superconductors and their interactions with material disorder, and point toward novel routes for using magnetic particles as highly coherent mechanical transducers. Source arXiv: 2606.27297v1
Restoring Incentive Compatibility in Two-Stage Energy Markets with Prosumers Authors Nikolas Koumpis, Koushik Kar, Leandros Tassiulas, Manolis Zampetakis Published: 06.24.2026 Updated: 06.24.2026 Summary A central challenge in modern energy market design is the formulation of a strategy-proof imbalance settlement layer that secures both the economic efficiency of the institution and the stability of the power grid. Public data reveals that the day-ahead market is strategically biased below actual consumer demand. Such empirical observations are explained by active prosumers which provide implementable incentives for demand under-reporting. Active prosumers buy energy in the day-ahead market and sell energy in the real-time market for balancing real-time energy deviations. By under-reporting their demand for the day ahead they inflate real-time imbalances and, under uniform pricing, they dispatch their generation assets more profitably. We model the two-stage institution under linear preferences and benchmark it against its associated competitive equilibria. We show that although consumers’ incentives for demand under-reporting vanish when the day-ahead market scales, prosumers’ incentives remain lower bounded by a positive gain which depends only on the real-time market generation stack and their shares over it. To restore incentive compatibility under the existing informational constraints, we design a leave-one-out contrastive scoring rule-based penalty that is implemented by the day-ahead market operator, incentivizes prosumers to report their demand truthfully and ensures small charges when participating honestly. We illustrate these results with numerical simulations on synthetic data and evaluate our mechanism on real-market data by first rationalizing demand reports as subjective equilibria of the induced game. Our mechanism demonstrates strong incentive alignment while retaining a low cost for honest participation. Source arXiv: 2606.25910v1
High-Rate and Resource-Efficient All-Photonic Quantum Repeater Architectures with 9 km Repeater Spacing Authors Ryosuke Shiina, Kenneth Goodenough, Nathan Arnold, Filip Rozpędek Published: 06.24.2026 Updated: 08.05.2026 Summary Quantum communication between two distant parties will serve as a cornerstone of the future quantum internet. However, generating enough entangled Bell pairs over long distances is a critical bottleneck. Although photons are ideal carriers of quantum information, overcoming photon loss and the exponential attenuation of signals remains a major challenge. We propose an all-photonic quantum repeater architecture that enables quantum communication over 1,000 km with an equidistant repeater spacing of 9 km. This repeater spacing is enabled by elementary entangled Bell pairs protected through the concatenation of continuous-variable and discrete-variable quantum error correction codes, namely, the bosonic Gottesman-Kitaev-Preskill (GKP) code and the [[7,1,3]] Steane code, whose combination yields a synergistic improvement in robustness against photon loss. This architecture incorporates a new ranking criterion and a multi-reflection mirror-based optical cavity as a free-space photonic memory module, which we model in terms of its length and mirror-reflection efficiency. Additionally, we propose two heuristic construction methods for the elementary entangled Bell pairs. One method introduces up to two-qubit correlated errors within each logical qubit but requires a large number of GKP qubits, while the other allows up to three-qubit correlated errors within each logical qubit but requires fewer GKP qubits. To more accurately capture realistic physical conditions during photonic resource preparation, we include switching-induced imperfections in our simulations, in addition to other standard optical imperfections. In the presence of these imperfections, our realization requires only a few thousand GKP qubits per repeater station per protocol run, a resource requirement significantly smaller than the corresponding resource requirements of prior third-generation all-photonic repeater proposals. Source arXiv: 2606.25314v2
High-Rate and Resource-Efficient All-Photonic Quantum Repeater Architectures with 9 km Repeater Spacing Authors Ryosuke Shiina, Kenneth Goodenough, Nathan Arnold, Filip Rozpędek Published: 06.24.2026 Updated: 06.24.2026 Summary Quantum communication between two distant parties will serve as a cornerstone of the future quantum internet. However, generating enough entangled Bell pairs over long distances is a critical bottleneck. Although photons are ideal carriers of quantum information, overcoming photon loss and the exponential attenuation of signals remains a major challenge. We propose an all-photonic quantum repeater architecture that enables quantum communication over 1,000 km with an equidistant repeater spacing of 9 km. This repeater spacing is enabled by elementary entangled Bell pairs protected through the concatenation of continuous-variable and discrete-variable quantum error correction codes, namely, the bosonic Gottesman-Kitaev-Preskill (GKP) code and the [[7,1,3]] Steane code, whose combination yields a synergistic improvement in robustness against photon loss. This architecture incorporates a new ranking criterion and a multi-reflection mirror-based optical cavity as a free-space photonic memory module, which we model in terms of its length and mirror-reflection efficiency. Additionally, we propose two heuristic construction methods for the elementary entangled Bell pairs. One method introduces up to two-qubit correlated errors within each logical qubit but requires a large number of GKP qubits, while the other allows up to three-qubit correlated errors within each logical qubit but requires fewer GKP qubits. To more accurately capture realistic physical conditions during photonic resource preparation, we include switching-induced imperfections in our simulations, in addition to other standard optical imperfections. In the presence of these imperfections, our realization requires only a few thousand GKP qubits per repeater station per protocol run, a resource requirement significantly smaller than the corresponding resource requirements of prior third-generation all-photonic repeater proposals. Source arXiv: 2606.25314v1
Efficient Graph State Purification with Factorized Graph-Preserving Operations across Local Clifford Orbits Authors Mingyuan Wang, Guus Avis, Kenneth Goodenough, Stefan Krastanov Published: 06.22.2026 Updated: 06.22.2026 Summary Graph states form a broad class of multipartite entangled states underlying measurement-based quantum computation, quantum networks, and stabilizer codes. However, systematic entanglement distillation for arbitrary graph states remains challenging because the circuit design space grows rapidly with the number of parties. We introduce a group of Clifford operations that we call “factorized graph-preserving”. It enables us to efficiently enumerate and optimize graph-state purification circuits at finite size for realistic noisy hardware. These operations map products of graph-basis states to products of graph-basis states, so their action can be represented as permutations of graph-basis labels. Moreover, this useful gate set admits a compact factorized description determined by simple graph-theoretic features. This structure also allows, after some initial cached precomputation, drastically lower computational complexity for simulating a gate. We further organize these operations over local-complementation (LC) orbits using minimum-edge representatives (MERs), which let us design purification circuits that apply to all locally equivalent graph states (up to a basis change). Using this framework, we optimize noisy finite-size multipartite distillation circuits for several graph-state families. Numerical results show that the resulting graph-preserving circuits can outperform standard recurrence-based purification protocols under realistic gate and measurement noise. Our results establish LC-orbit structure and factorized graph-preserving operations as practical tools for scalable, topology-aware and hardware-constrained graph-state distillation protocol design. Our work can also be interpreted as a graph-based heuristic for finding transversal gates. Source arXiv: 2606.23809v1
Persistent structural distortions and absent superconductivity in trilayer nickelate thin films Authors Abigail Y. Jiang, Maria Bambrick-Santoyo, Lopa Bhatt, Kyeong-Yoon Baek, Yi-Feng Zhao, Dan Ferenc Segedin, Ari B. Turkiewicz, Jenna Hatmin, Grace A. Pan, Suchismita Sarker, Donald A. Walko, Charles M. Brooks, David A. Muller, Berit H. Goodge, Hua Zhou, Antia S. Botana, Julia A. Mundy Published: 06.18.2026 Updated: 06.18.2026 Summary A new family of high-temperature superconductors was recently discovered in the $n=2,3$ Ruddlesden-Popper nickelates, where superconductivity emerges concomitant with suppression of parent density waves and structural octahedral rotations under hydrostatic pressure. Intriguingly, compressive strain mimics the structural effects of pressure in the $n=2$ phase, yielding ambient-pressure superconductivity. However, analogous strain-stabilized superconductivity has not been realized in the $n=3$. Here, we use atomically-precise synthesis, transport, picoscale electron microscopy, and synchrotron X-ray diffraction to probe $n=3$ La$_4$Ni$_3$O$_{10}$ thin films. Although compressive strain suppresses density wave order, we do not observe superconductivity even under the largest strain state. Importantly, we identify a structural distortion unique to strained $n=3$ thin films that may inhibit superconductivity: persistent, layer-inequivalent octahedral rotations around the $c$-axis. Our results highlight key differences between the $n=3$ and $n=2$ systems, suggesting that ambient-pressure superconductivity in the $n=3$ may require new methods beyond epitaxial strain engineering. Source arXiv: 2606.20941v1
Impulse Decoding of Quantum LDPC Codes: Equivalence of Degeneracy and Code-Shortening Authors Shobhit Bhatnagar, Michele Pacenti, Nithin Raveendran, David Declercq, Bane Vasić Published: 06.16.2026 Updated: 06.16.2026 Summary Quantum error correction is essential for building scalable quantum computers. Within the stabilizer formalism, the Calderbank-Shor-Steane framework constructs quantum codes from pairs of classical linear codes. A distinctive feature in this setting is degeneracy, where multiple equivalent error estimates exist-a phenomenon that has no classical counterpart, and the lack of a meaningful classical coding-theoretic interpretation of which has remained a gap in the literature. In this paper, we demonstrate that degeneracy is closely related to the classical operation of shortening of a linear block code. Interestingly, the shortening here takes place at the decoder rather than at the encoder. Leveraging this insight, we present a parallel decoding scheme for quantum low-density parity-check codes, which we term impulse decoding, that significantly outperforms belief propagation with ordered statistics decoding, as well as several other existing techniques, under both code-capacity and circuit-level noise, with significantly lesser complexity. We then present another algorithm based on decoding of residual errors, which when combined with impulse decoding achieves further performance improvement under circuit-level noise. Source arXiv: 2606.18240v1
Optimal Probe State for Phase Estimation Under Covariant Measurement Authors Qipeng Qian, Christos N. Gagatsos Published: 06.16.2026 Updated: 06.16.2026 Summary We study the optimization of input states for phase estimation under covariant measurements. Building on Holevo’s framework, which provides the optimal covariant measurement for a fixed input state, we further optimize over the input state itself. For a general even $2π$-periodic cost function with non-negative Fourier coefficients, we derive a necessary and sufficient condition for the optimal input state: Its Fock coefficients are determined, up to arbitrary phases, by the eigenvector corresponding to the largest eigenvalue of a Toeplitz matrix defined by the cost function. This characterization yields an explicit expression for the attainable lower bound of the average cost under optimal covariant measurements and shows that this bound asymptotically approaches zero in the infinite-energy limit. For the specific cost function $W(θ,tildeθ)=4sin^2[(θ-tildeθ)/2]$, we obtain the optimal input state and the corresponding minimum average cost in closed form, demonstrating Heisenberg scaling with respect to the mean photon number. Source arXiv: 2606.18169v1
Probing La-based nickelates with Ni 1$s$ core-level photoelectron spectroscopy Authors Daisuke Takegami, Naoki Ito, Koto Fujinuma, Masato Yoshimura, Grace A. Pan, Dan Ferenc Segedin, Qi Song, Hanjong Paik, Charles M. Brooks, Hanjie Guo, Alexander C. Komarek, Takanori Taniguchi, Masaki Fujita, Julia A. Mundy, Takashi Mizokawa, Liu Hao Tjeng, Berit H. Goodge, Atsushi Hariki Published: 06.16.2026 Updated: 06.16.2026 Summary We present a comparative Ni core level photoemission study of La$_3$Ni$_2$O$_7$, Nd$_3$Ni$_2$O$_7$, and LaNiO$_3$ using both the Ni $2p$ and the Ni $1s$. We address the challenges in analyzing the widely investigated Ni $2p$ spectra arising from the substantial overlap in energy of the Ni $2p$ with the La $3d$. We show that on the other hand the deep Ni $1s$ core level does provide a clean view on the intrinsic electronic excitations and we highlight its potential to resolve detailed differences in the electronic structure within the strongly correlated Ruddlesden-Popper series La$_{n+1}$Ni$_n$O$_{3n+1}$. Source arXiv: 2606.17663v1
Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale Authors Ang Li, Ben Liu, Bin Han, Bin Hu, Bin Jing, Binbin Hu, Bing Li, Cai Chen, Caizhi Tang, Changxin Tian, Chao Huang, Chao Zhang, Chen Liang, Chen Qian, Chengfu Tang, Chengyao Wen, Chilin Fu, Chunwei Wu, Cong Zhang, Cunyin Peng, Daixin Wang, Dalong Zhang, Deng Zhao, Dingnan Jin, Dingyuan Zhu, Donghao Zhang, Fan Yuan, Fangzheng Zhao, Fanzhuang Meng, Feifan Wu, Feng Xu, Fengbin Fang, Gangshan Wang, Guodong Yang, Hailin Zhao, Haitao Wang, Haitao Zhang, Hanxiao Zhang, Hanzi Wang, Hao Dai, Hao Liu, Hao Qian, Hao Wu, Haoxiong Liu, Haoyu Xu, Heng Zhang, Hong Liu, Hongliang Zhang, Hongrui Liu, Hongxun Li, Hongzhi Ruan, Huaidong Xiong, Huihuang Zheng, Huikang Tang, Jia Guo, Jia Li, Jia Liu, Jiameng Wang, Jiaming Liu, Jiannan Shi, Jianping Wei, Jiaolong Yang, Jiapeng Wang, Jie Gao, Jie Wang, Jiewei Wu, Jin Yang, Jinjin Li, Jinjing Huang, Jinquan Sun, Jinyao Chen, Juanhui Tu, Jun Liu, Jun Mei, Jun Xu, Jun Zhou, Junjie Ou, Junnan Sipan, Junpeng Fang, Kaihong Zhang, Kaiqin Hu, Ke Shi, Kuan Xu, Kun Tang, Kunlong Chen, Lanyin Mei, Lei Chen, Lei Liang, Lei Xu, Li Tang, Liang Jiang, Liangcheng Fu, Lihui Zhang, Linfeng Shi, Lintao Ma, Liyuan Liu, Longfei Li, Longfei Zheng, Lu Liu, Lu Yu, Man Li, Meiqi Zhu, Meng Li, Mengjie Gao, Mengshu Sun, Mingming Yin, Mingyang Zhang, Mingyuan Fan, Nuo Xu, Pan Tang, Peijie Jiang, Peilong Zhao, Peng Lin, Pingping Liu, Qi Zuo, Qian Zhao, Qiang Cheng, Qianggang Cao, Qiaoben Bao, Qing Cui, Qingyuan Yang, Qitao Shi, Qiyin Huang, Qizheng Zhou, Quan Wan, Runyuan Zhao, Shaomian Zheng, Shaowei Wei, Shengnan Zhang, Shuaicheng Li, Shujie Li, Shuo Zhang, Sikang Bian, Tianchu Yao, Tiange Xu, Tianshu Wang, Ting Guo, Tinghao Wang, Tingwei Huang, Tong Zhao, Tongkai Yang, Wang Hong, Wanli Gu, Wei Lu, Weichang Wu, Weiguang Han, Weiquan Li, Wenbo Shen, Wenjing Fang, Wenzhi Tang, Xiang Shu, Xiao Shi, Xiaodong Yan, Xiaolu Zhang, Xiaopei Wan, Xiaqing Sun, Xin Zhao, Xingyu Lu, Xinxing Yang, Xinyao Tang, Xinyu Kong, Xinyu Liu, Xiong Xu, Xuan Sun, Xudong Han, Xudong Wang, Xujie Shen, Yalin Zhang, Yangyang Hou, Yankun Ren, Yao Zhao, Ye Chen, Yeyang Chen, Yibo Cao, Yifan Zuo, Yijie Chen, Ying Li, Yingjie Song, Yingxue Li, Yiqi Wang, Yixuan Sun, Yizhu Xiao, Yongfei Xu, Yu Liu, Yuchen Fang, Yue Gao, Yue Yu, Yue Zhang, Yuqi Zhang, Yuxiao He, Yuxiao Lu, Yuxin Tian, Yuxuan Li, Yuzhuo Fu, Zhankai Xu, Zhaoxin Huan, Zhenduo Zhang, Zhengke Gui, Zhengyu Huang, Zhenjun Ma, Zhenxuan Pan, Zheping Qu, Zhibo Zhu, Zhidong Fan, Zhigang Huangfu, Zhihao Wang, Zhiqiang Zhang, Zhizhen Liu, Zhuyan Zhou, Zibin Lin, Zihang Zeng, Zihao Wang, Zilong Wang, Ziqi Liu, Zitao Xuan, Zixuan Cheng, Zujie Wen, Zuoli Tang Published: 06.13.2026 Updated: 06.13.2026 Summary Efficient and scalable agentic intelligence requires models that can deliver both low-latency responses and strong reasoning capabilities while remaining practical to train, serve, and deploy. In this report, we present Ling-2.6 and Ring-2.6, a family of models designed to address this challenge at scale. Ling-2.6 is optimized for instant response generation and high capability per output token, whereas Ring-2.6 is tailored for deeper reasoning and more advanced agentic workflows. Instead of training from scratch, we upgrade the Ling-2.0 base model through architectural migration pre-training and large-scale post-training. This upgrade is guided by a unified co-design of model architecture, optimization objectives, serving systems, and agent training environments, enabling improvements in both model capability and deployment efficiency. At the architectural level, we introduce a hybrid linear attention design that integrates Lightning Attention with MLA, improving the efficiency of long-context training and decoding. To further enhance token efficiency, we optimize capability per output token through Evolutionary Chain-of-Thought, Linguistic Unit Policy Optimization, bidirectional preference alignment, and shortest-correct-response distillation. For agentic capabilities, we propose KPop, a reinforcement learning framework designed to support stable training of Ring-2.6-1T on large-scale environment-grounded data. KPop improves training efficiency through asynchronous scheduling across coding, search, tool use, and workflow execution, enabling scalable learning from complex agent-environment interactions. Together, Ling-2.6 and Ring-2.6 provide a practical pathway toward efficient, scalable, and open agentic systems. We open-source all checkpoints in the 2.6 family to support further research and development in practical agentic intelligence. Source arXiv: 2606.15079v1
Fundamental Limit for One versus Two Point Sources Detection using Direct Imaging Authors Parth Hemant Darekar, Amit Kumar Jha, Michael R. Grace, Aqil Sajjad, Saikat Guha Published: 05.31.2026 Updated: 05.31.2026 Summary We consider the task of distinguishing between a single weak incoherent optical point source and two weak incoherent optical point sources located symmetrically about the first source. $θ$ is the separation between the two point sources scaled to the Point Spread Function (PSF) width in the image plane. Using an ideal focal plane array of intensity detectors (ideal direct imaging), we quantify the performance using the Bhattacharyya distance and find the scaling of its leading order term in terms of $θ$ in the sub-Rayleigh regime. A suite of previous analyses of this problem lacked a comprehensive analysis for when the amplitude spread function (ASF) of the imaging system has zeros and reported a scaling that we find to be incorrect. We complete this analysis by explicitly calculating the leading order term of the Bhattacharyya distance for ideal direct imaging with any ASF, for small $θ$ and show the difference in scaling based on the presence or absence of zeros in the ASF. This is similar to the ASF dependent performance in the task of estimating the separation between the two point sources and the task of detecting a change to an object. We then apply our results to the specific example of a Gaussian and a Sinc ASF and show good agreement with numerical calculations. Our results allow the accurate comparison of other measurement schemes with ideal direct imaging, and to the quantum limit. Source arXiv: 2606.00968v1
Learning Mid-circuit Measurement Backaction from Three Repeated Measurements Authors Chia-Tung Chu, Su-un Lee, Han Zheng, Senrui Chen, Bibek Pokharel, Alireza Seif, Liang Jiang Published: 05.29.2026 Updated: 09.30.2026 Summary Accurate modeling of mid-circuit measurements (MCMs) is essential for dynamic-circuit operations such as syndrome extraction, measurement-based reset, and the separation of state-preparation and measurement (SPAM) error. Unlike terminal measurement, a noisy MCM both produces a classical outcome and alters the incoming quantum state, thereby influencing subsequent circuit operations. This makes conventional confusion-matrix or fidelity-level characterization insufficient. Here we introduce an efficient, self-consistent protocol for learning a single-qubit Z-twirled MCM instrument, retaining the readout-backaction correlations and excitation-decay asymmetry that are erased in Pauli-error descriptions. Remarkably, readout bit strings from only three repeated MCMs on a maximally mixed input determine all learnable parameters of the reduced instrument, up to a single unidentifiable gauge degree of freedom. Physicality constraints convert this non-identifiability into narrow, gauge-aware error intervals. Implemented on IBM superconducting processors, the learned instrument improves Pauli-observable prediction by ${sim}100times$ over a conventional confusion-matrix model and reveals a $T_1$-decay dominated backaction. Our protocol provides a compact characterization layer for SPAM error separation, reset optimization, and noise-aware quantum error correction. Source arXiv: 2606.00433v2
Learning Mid-circuit Measurement Backaction from Three Repeated Measurements Authors Chia-Tung Chu, Su-un Lee, Han Zheng, Senrui Chen, Bibek Pokharel, Alireza Seif, Liang Jiang Published: 05.29.2026 Updated: 05.29.2026 Summary Accurate modeling of mid-circuit measurements (MCMs) is essential for dynamic-circuit operations such as syndrome extraction, measurement-based reset, and the separation of state-preparation and measurement (SPAM) error. Unlike terminal measurement, a noisy MCM both produces a classical outcome and alters the incoming quantum state, thereby influencing subsequent circuit operations. This makes conventional confusion-matrix or fidelity-level characterization insufficient. Here we introduce an efficient, self-consistent protocol for learning a single-qubit Z-twirled MCM instrument, retaining the readout-backaction correlations and excitation-decay asymmetry that are erased in Pauli-error descriptions. Remarkably, readout bit strings from only three repeated MCMs on a maximally mixed input determine all learnable parameters of the reduced instrument, up to a single unidentifiable gauge degree of freedom. Physicality constraints convert this non-identifiability into narrow, gauge-aware error intervals. Implemented on IBM superconducting processors, the learned instrument improves Pauli-observable prediction by ${sim}100times$ over a conventional confusion-matrix model and reveals a $T_1$-decay dominated backaction. Our protocol provides a compact characterization layer for SPAM error separation, reset optimization, and noise-aware quantum error correction. Source arXiv: 2606.00433v1
No-Go Theorem for Ancilla-Assisted Gaussian Enhancement in Passive-Unitary Estimation Authors Zihao Gong, Saikat Guha Published: 05.29.2026 Updated: 05.29.2026 Summary We study the maximum quantum Fisher information (QFI) for estimating a single parameter embedded in a generic multimode lossless passive Gaussian unitary using general Gaussian probes under a signal-energy constraint. Unlike previous work, which imposed a total energy constraint on the full probe, we constrain only the transmitted signal modes while allowing an arbitrary number of locally retained ancilla modes with arbitrarily large energy. We prove that this additional freedom does not increase the maximum achievable QFI; the optimum remains identical to that attainable without extra ancilla energy. The same conclusion also extends to the sequential setting under a total energy constraint. We also characterize the family of optimal probe states and show that entanglement is not necessary to attain the optimum in the lossless setting. This extends the result of Matsubara et al. to the physically motivated signal-energy-constrained scenario and establishes a no-go theorem for ancilla-assisted Gaussian enhancement in noiseless passive-unitary estimation. Source arXiv: 2606.00256v1
