To Offload or Not To Offload: Model-driven Comparison of Edge-native and On-device Processing Authors Nathan Ng, David Irwin, Ananthram Swami, Don Towsley, Prashant Shenoy Published: 04.21.2025 Updated: 04.21.2025 Summary Computational offloading is a promising approach for overcoming resource constraints on client devices by moving some or all of an application’s computations to remote servers. With the advent of specialized hardware accelerators, client devices are now able to perform fast local processing of specific tasks, such as machine learning inference, reducing the need for offloading computations. However, edge servers with accelerators also offer faster processing for offloaded tasks than was previously possible. In this paper, we present an analytic and experimental comparison of on-device processing and edge offloading for a range of accelerator, network, and application workload scenarios, with the goal of understanding when to use local on-device processing and when to offload computations. We present models that leverage analytical queuing results to capture the effects of dynamic factors such as the performance gap between the device and edge server, network variability, server load, and multi-tenancy on the edge server. We experimentally demonstrate the accuracy of our models for a range of hardware and application scenarios and show that our models achieve a mean absolute percentage error of 2.2% compared to observed latencies. We use our models to develop an adaptive resource manager for intelligent offloading and show its efficacy in the presence of variable network conditions and dynamic multi-tenant edge settings. Source arXiv: 2504.15162v1
Micro-Ring Perceptron Sensor for High-Speed, Low-Power Radio-Frequency Signal Authors Bo-Han Wu, Shi-Yuan Ma, Sri Krishna Vadlamani, Hyeongrak Choi, Dirk Englund Published: 04.19.2025 Updated: 04.19.2025 Summary Radio-frequency (RF) sensing enables long-range, high-resolution detection for applications such as radar and wireless communication. RF photonic sensing mitigates the bandwidth limitations and high transmission losses of electronic systems by transducing the detected RF signals into broadband optical carriers. However, these sensing systems remain limited by detector noise and Nyquist rate sampling with analog-to-digital converters, particularly under low-power and high-data rate conditions. To overcome these limitations, we introduce the micro-ring perceptron (MiRP) sensor, a physics-inspired AI framework that integrates the micro-ring (MiR) dynamics-based analog processor with a machine-learning-driven digital backend. By embedding the nonlinear optical dynamics of MiRs into an end-to-end architecture, MiRP sensing maps the input signal into a learned feature space for the subsequent digital neural network. The trick is to encode the entire temporal structure of the incoming signal into each output sample in order to enable effectively sub-Nyquist sampling without loss of task-relevant information. Evaluations of three target classification datasets demonstrate the performance advantages of MiRP sensing. For example, on MNIST, MiRP detection achieves $94pm0.1$% accuracy at $1/49$ the Nyquist rate at the input RF signal of $1$~ pW, compared to $11pm0.4$% for the conventional RF detection method. Thus, our sensor framework provides a robust and efficient solution for the detection of low-power and high-speed signals in real-world sensing applications. Source arXiv: 2504.16119v1
Restoring Heisenberg scaling in time via autonomous quantum error correction Authors Hyukgun Kwon, Uwe R. Fischer, Seung-Woo Lee, Liang Jiang Published: 04.17.2025 Updated: 04.17.2025 Summary We establish a sufficient condition under which autonomous quantum error correction (AutoQEC) can effectively restore Heisenberg scaling (HS) in quantum metrology. Specifically, we show that if all Lindblad operators associated with the noise commute with the signal Hamiltonian and a particular constrained linear equation admits a solution, then an ancilla-free AutoQEC scheme with finite $R$ (where $R$ represents the ratio between the engineered dissipation rate for AutoQEC and the noise rate,) can approximately preserve HS with desired small additive error $epsilon > 0$ over any time interval $0 leq t leq T$. We emphasize that the error scales as $ epsilon = O(kappa T / R^c) $ with $c geq 1$, indicating that the required $R$ decreases significantly with increasing $c$ to achieve a desired error. Furthermore, we discuss that if the sufficient condition is not satisfied, logical errors may be induced that cannot be efficiently corrected by the canonical AutoQEC framework. Finally, we numerically verify our analytical results by employing the concrete example of phase estimation under dephasing noise. Source arXiv: 2504.13168v1
Hardware Co-Designed Optimal Control for Programmable Atomic Quantum Processors via Reinforcement Learning Authors Qian Ding, Dirk Englund Published: 04.16.2025 Updated: 04.16.2025 Summary Developing scalable, fault-tolerant atomic quantum processors requires precise control over large arrays of optical beams. This remains a major challenge due to inherent imperfections in classical control hardware, such as inter-channel crosstalk and beam leakage. In this work, we introduce a hardware co-designed intelligent quantum control framework to address these limitations. We construct a mathematical model of the photonic control hardware, integrate it into the quantum optimal control (QOC) framework, and apply reinforcement learning (RL) techniques to discover optimal control strategies. We demonstrate that the proposed framework enables robust, high-fidelity parallel single-qubit gate operations under realistic control conditions, where each atom is individually addressed by an optical beam. Specifically, we implement and benchmark three optimization strategies: a classical hybrid Self-Adaptive Differential Evolution-Adam (SADE-Adam) optimizer, a conventional RL approach based on Proximal Policy Optimization (PPO), and a novel end-to-end differentiable RL method. Using SADE-Adam as a baseline, we find that while PPO performance degrades as system complexity increases, the end-to-end differentiable RL consistently achieves gate fidelities above 99.9$%$, exhibits faster convergence, and maintains robustness under varied channel crosstalk strength and randomized dynamic control imperfections. Source arXiv: 2504.11737v1
Adaptive Error Correction for Entanglement Distillation Authors Sijie Cheng, Narayanan Rengaswamy Published: 04.15.2025 Updated: 04.15.2025 Summary Quantum network applications impose a variety of requirements on entanglement resources in terms of rate, fidelity, latency, and more. The repeaters in the quantum network must combine good methods for entanglement generation, effective entanglement distillation, and smart routing protocols to satisfy these application requirements. In this work, we focus on quantum error correction-based entanglement distillation in a linear chain of quantum repeaters. While conventional approaches reuse the same distillation scheme over multiple hop lengths after entanglement swaps, we propose a novel adaptive error correction scheme that boosts end-to-end metrics. Specifically, depending on the network operation point, we adapt the code used in distillation over successive rounds to monotonically increase the rate while also improving fidelity. We demonstrate the effectiveness of this strategy using three codes: [[9,1,3]], [[9,2,3]], [[9,3,3]]. We compare the performance of four different protocols that combine the codes in different ways, where we define a new performance metric, efficiency, that incorporates both overall rate and fidelity. While we highlight our innovation under minimal assumptions on noise, the method can be easily generalized to realistic network settings. By combining our approach with good entanglement generation methods and smart routing protocols, we can achieve application requirements in a systematic, resource-efficient, way. Source arXiv: 2504.11670v1
Fault Tolerant Quantum Simulation via Symplectic Transvections Authors Zhuangzhuang Chen, Jack Owen Weinberg, Narayanan Rengaswamy Published: 04.15.2025 Updated: 04.15.2025 Summary Conventional approaches to fault-tolerant quantum computing realize logical circuits gate-by-gate, synthesizing each gate independently on one or more code blocks. This incurs excess overhead and doesn’t leverage common structures in quantum algorithms. In contrast, we propose a framework that enables the execution of entire logical circuit blocks at once, preserving their global structure. This whole-block approach allows for the direct implementation of logical Trotter circuits – of arbitrary rotation angles – on any stabilizer code, providing a powerful new method for fault tolerant Hamiltonian simulation within a single code block. At the heart of our approach lies a deep structural correspondence between symplectic transvections and Trotter circuits. This connection enables both logical and physical circuits to share the Trotter structure while preserving stabilizer centralization and circuit symmetry even in the presence of non-Clifford rotations. We discuss potential approaches to fault tolerance via biased noise and code concatenation. While we illustrate the key principles using a $[[8,3,3]]$ code, our simulations show that the framework applies to Hamiltonian simulation on even good quantum LDPC codes. These results open the door to new algorithm-tailored, block-level strategies for fault tolerant circuit design, especially in quantum simulation. Source arXiv: 2504.11444v1
A Quantum Advantage in Localizing Transmission Loss Change in Optical Networks Authors Yufei Zheng, Yu-Zhen Janice Chen, Prithwish Basu, Don Towsley Published: 04.15.2025 Updated: 04.15.2025 Summary The ability to localize transmission loss change to a subset of links in optical networks is crucial for maintaining network reliability, performance and security. emph{Quantum probes}, implemented by sending blocks of $n$ coherent-state pulses augmented with continuous-variable (CV) squeezing ($n=1$) or weak temporal-mode entanglement ($n>1$) over a lossy channel to a receiver with homodyne detection capabilities, are known to be more sensitive than their quasi-classical counterparts in detecting a sudden increase in channel loss. The enhanced sensitivity can be characterized by the increased Kullback-Leibler (KL) divergence of the homodyne output, before and after the loss change occurs. When combined with the theory of quickest change detection (QCD), the increase in KL divergence translates into a decrease in detection latency. In this work, we first revisit quantum probes over a channel, generalizing previous results on $n=1$ (CV squeezed states) to arbitrary values of $n$. Assuming a subset of nodes in an optical network is capable of sending and receiving such probes through intermediate nodes with all-optical switching capabilities, we present a scheme for quickly detecting the links that have suffered a sudden drop in transmissivity. Since quantum probes lose their sensitivity with increasing loss in the channel, we first propose a probe construction algorithm that makes the set of links suffering transmission loss change identifiable, while minimizing the longest distance a probe traverses. We then introduce new cumulative sum (CUSUM) statistics with a stopping rule, which allows us to run the CUSUM algorithm to quickly localize the lossy links using our constructed probes. Finally, we show that the proposed scheme achieves a quantum advantage in decreasing the detection delay. Source arXiv: 2504.10882v1
Holistic Capability Preservation: Towards Compact Yet Comprehensive Reasoning Models Authors Ling Team, Caizhi Tang, Chilin Fu, Chunwei Wu, Jia Guo, Jianwen Wang, Jingyu Hu, Liang Jiang, Meng Li, Peng Jiao, Pingping Liu, Shaomian Zheng, Shiwei Liang, Shuaicheng Li, Yalin Zhang, Yingting Wu, Yongkang Liu, Zhenyu Huang Published: 04.09.2025 Updated: 04.11.2025 Summary This technical report presents Ring-Lite-Distill, a lightweight reasoning model derived from our open-source Mixture-of-Experts (MoE) Large Language Models (LLMs) Ling-Lite. This study demonstrates that through meticulous high-quality data curation and ingenious training paradigms, the compact MoE model Ling-Lite can be further trained to achieve exceptional reasoning capabilities, while maintaining its parameter-efficient architecture with only 2.75 billion activated parameters, establishing an efficient lightweight reasoning architecture. In particular, in constructing this model, we have not merely focused on enhancing advanced reasoning capabilities, exemplified by high-difficulty mathematical problem solving, but rather aimed to develop a reasoning model with more comprehensive competency coverage. Our approach ensures coverage across reasoning tasks of varying difficulty levels while preserving generic capabilities, such as instruction following, tool use, and knowledge retention. We show that, Ring-Lite-Distill’s reasoning ability reaches a level comparable to DeepSeek-R1-Distill-Qwen-7B, while its general capabilities significantly surpass those of DeepSeek-R1-Distill-Qwen-7B. The models are accessible at https://huggingface.co/inclusionAI Source arXiv: 2504.07158v2
Holistic Capability Preservation: Towards Compact Yet Comprehensive Reasoning Models Authors Ling Team, Caizhi Tang, Chilin Fu, Chunwei Wu, Jia Guo, Jianwen Wang, Jingyu Hu, Liang Jiang, Meng Li, Peng Jiao, Pingping Liu, Shaomian Zheng, Shiwei Liang, Shuaicheng Li, Yalin Zhang, Yingting Wu, Yongkang Liu, Zhenyu Huang Published: 04.09.2025 Updated: 04.09.2025 Summary This technical report presents Ring-Lite-Distill, a lightweight reasoning model derived from our open-source Mixture-of-Experts (MoE) Large Language Models (LLMs) Ling-Lite. This study demonstrates that through meticulous high-quality data curation and ingenious training paradigms, the compact MoE model Ling-Lite can be further trained to achieve exceptional reasoning capabilities, while maintaining its parameter-efficient architecture with only 2.75 billion activated parameters, establishing an efficient lightweight reasoning architecture. In particular, in constructing this model, we have not merely focused on enhancing advanced reasoning capabilities, exemplified by high-difficulty mathematical problem solving, but rather aimed to develop a reasoning model with more comprehensive competency coverage. Our approach ensures coverage across reasoning tasks of varying difficulty levels while preserving generic capabilities, such as instruction following, tool use, and knowledge retention. We show that, Ring-Lite-Distill’s reasoning ability reaches a level comparable to DeepSeek-R1-Distill-Qwen-7B, while its general capabilities significantly surpass those of DeepSeek-R1-Distill-Qwen-7B. The models are accessible at https://huggingface.co/inclusionAI Source arXiv: 2504.07158v1
Superresolution imaging with entanglement-enhanced telescopy Authors Isack Padilla, Aqil Sajjad, Babak N. Saif, Saikat Guha Published: 04.04.2025 Updated: 04.04.2025 Summary Long-baseline interferometry will be possible using pre-shared entanglement between two telescope sites to mimic the standard phase-scanning interferometer, but without physical beam combination. We show that spatial-mode sorting at each telescope, along with pre-shared entanglement, can be used to realize the most general multimode interferometry on light collected by any number of telescopes, enabling achieving quantitative-imaging performance at the ultimate limit pursuant to the baseline as afforded by quantum theory. We work out an explicit example involving two telescopes imaging two point sources. Source arXiv: 2504.03117v1
Linear Time Iterative Decoders for Hypergraph-Product and Lifted-Product Codes Authors Asit Kumar Pradhan, Nithin Raveendran, Narayanan Rengaswamy, Bane Vasić Published: 04.02.2025 Updated: 04.02.2025 Summary Quantum low-density parity-check (QLDPC) codes with asymptotically non-zero rates are prominent candidates for achieving fault-tolerant quantum computation, primarily due to their syndrome-measurement circuit’s low operational depth. Numerous studies advocate for the necessity of fast decoders to fully harness the capabilities of QLDPC codes, thus driving the focus towards designing low-complexity iterative decoders. However, empirical investigations indicate that such iterative decoders are susceptible to having a high error floor while decoding QLDPC codes. The main objective of this paper is to analyze the decoding failures of the emph{hypergraph-product} and emph{lifted-product} codes and to design decoders that mitigate these failures, thus achieving a reduced error floor. The suboptimal performance of these codes can predominantly be ascribed to two structural phenomena: (1) stabilizer-induced trapping sets, which are subgraphs formed by stabilizers, and (2) classical trapping sets, which originate from the classical codes utilized in the construction of hypergraph-product and lifted-product codes. The dynamics of stabilizer-induced trapping sets is examined and a straightforward modification of iterative decoders is proposed to circumvent these trapping sets. Moreover, this work proposes a systematic methodology for designing decoders that can circumvent classical trapping sets in both hypergraph product and lifted product codes, from decoders capable of avoiding their trapping set in the parent classical LDPC code. When decoders that can avoid stabilizer-induced trapping sets are run in parallel with those that can mitigate the effect of classical TS, the logical error rate improves significantly in the error-floor region. Source arXiv: 2504.01728v1
Single-Shot Matrix-Matrix Multiplication Optical Tensor Processor for Deep Learning Authors Chao Luan, Ronald Davis III, Zaijun Chen, Dirk Englund, Ryan Hamerly Published: 03.31.2025 Updated: 03.31.2025 Summary The ever-increasing data demand craves advancements in high-speed and energy-efficient computing hardware. Analog optical neural network (ONN) processors have emerged as a promising solution, offering benefits in bandwidth and energy consumption. However, existing ONN processors exhibit limited computational parallelism, and while certain architectures achieve high parallelism, they encounter serious scaling roadblocks for large-scale implementation. This restricts the throughput, latency, and energy efficiency advantages of ONN processors. Here, we introduce a spatial-wavelength-temporal hyper-multiplexed ONN processor that supports high data dimensionality, high computing parallelism and is feasible for large-scale implementation, and in a single time step, a three-dimensional matrix-matrix multiplication (MMM) optical tensor processor is demonstrated. Our hardware accelerates convolutional neural networks (CNNs) and deep neural networks (DNNs) through parallel matrix multiplication. We demonstrate benchmark image recognition using a CNN and a subsequently fully connected DNN in the optical domain. The network works with 292,616 weight parameters under ultra-low optical energy of 20 attojoules (aJ) per multiply and accumulate (MAC) at 96.4% classification accuracy. The system supports broad spectral and spatial bandwidths and is capable for large-scale demonstration, paving the way for highly efficient large-scale optical computing for next-generation deep learning. Source arXiv: 2503.24356v1
Ethereum Price Prediction Employing Large Language Models for Short-term and Few-shot Forecasting Authors Eftychia Makri, Georgios Palaiokrassas, Sarah Bouraga, Antigoni Polychroniadou, Leandros Tassiulas Published: 03.29.2025 Updated: 03.29.2025 Summary Cryptocurrencies have transformed financial markets with their innovative blockchain technology and volatile price movements, presenting both challenges and opportunities for predictive analytics. Ethereum, being one of the leading cryptocurrencies, has experienced significant market fluctuations, making its price prediction an attractive yet complex problem. This paper presents a comprehensive study on the effectiveness of Large Language Models (LLMs) in predicting Ethereum prices for short-term and few-shot forecasting scenarios. The main challenge in training models for time series analysis is the lack of data. We address this by leveraging a novel approach that adapts existing pre-trained LLMs on natural language or images from billions of tokens to the unique characteristics of Ethereum price time series data. Through thorough experimentation and comparison with traditional and contemporary models, our results demonstrate that selectively freezing certain layers of pre-trained LLMs achieves state-of-the-art performance in this domain. This approach consistently surpasses benchmarks across multiple metrics, including Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE), demonstrating its effectiveness and robustness. Our research not only contributes to the existing body of knowledge on LLMs but also provides practical insights in the cryptocurrency prediction domain. The adaptability of pre-trained LLMs to handle the nature of Ethereum prices suggests a promising direction for future research, potentially including the integration of sentiment analysis to further refine forecasting accuracy. Source arXiv: 2503.23190v1
Strongly Electromechanical Coupled Phononic Waveguides in Aluminum Scandium Nitride on Silicon Carbide Authors Yuanchen Deng, Dalton Anderson, Xingyu Du, Will Roberts, Michael Miller, Brandon Smith, Lisa Hackett, Troy Olsson, Matt Eichenfield Published: 03.23.2025 Updated: 03.23.2025 Summary Guided phonons have become an increasingly important platform for classical and quantum information processing. While conventional surface acoustic wave systems are typically only guided in the vertical direction, two-dimensionally confined waveguide systems offer significant advantages in terms of density of phononic circuit components and much higher intensities of strain and piezoelectric fields, which make them promising candidates for advancing acoustoelectric and quantum phononic applications. One such material system for generating and guiding phonons at gigahertz frequencies is AlScN on SiC, which can be synthesized by sputter depositing AlScN directly onto SiC wafers. The AlScN on SiC platform allows for tightly vertically confined acoustic modes with high electromechanical coupling, high speed of sound, and simple fabrication of strip and rib waveguides. Until now, this system has only been studied as a slab waveguide platform, i.e., without any lateral waveguiding. Here, we present a 2D-confined phononic waveguide architecture in AlScN on SiC with strongly electromechanically coupled modes that could serve as a platform for phononic routing, power-efficient active and nonlinear phononic devices such as amplifiers, mixers, and oscillators, as well as for interacting with quantum systems such as vacancy centers, charge carriers, photons, and spins. We study two distinct gigahertz frequency waveguide mode families using impedance matched interdigital transducers and characterize their electromechanical coupling and propagation losses. Additionally, we analyze how these waveguides could interact with various important quantum and classical systems that can be either embedded in SiC or heterogeneously integrated on the surface. Source arXiv: 2503.18113v1
PT-PINNs: A Parametric Engineering Turbulence Solver based on Physics-Informed Neural Networks Authors Liang Jiang, Yuzhou Cheng, Kun Luo, Jianren Fan Published: 03.22.2025 Updated: 03.22.2025 Summary Physics-informed neural networks (PINNs) demonstrate promising potential in parameterized engineering turbulence optimization problems but face challenges, such as high data requirements and low computational accuracy when applied to engineering turbulence problems. This study proposes a framework that enhances the ability of PINNs to solve parametric turbulence problems without training datasets from experiments or CFD-Parametric Turbulence PINNs (PT-PINNs)). Two key methods are introduced to improve the accuracy and robustness of this framework. The first is a soft constraint method for turbulent viscosity calculation. The second is a pre-training method based on the conservation of flow rate in the flow field. The effectiveness of PT-PINNs is validated using a three-dimensional backward-facing step (BFS) turbulence problem with two varying parameters (Re = 3000-200000, ER = 1.1-1.5). PT-PINNs produce predictions that closely match experimental data and computational fluid dynamics (CFD) results across various conditions. Moreover, PT-PINNs offer a computational efficiency advantage over traditional CFD methods. The total time required to construct the parametric BFS turbulence model is 39 hours, one-sixteenth of the time required by traditional numerical methods. The inference time for a single-condition prediction is just 40 seconds-only 0.5% of a single CFD computation. These findings highlight the potential of PT-PINNs for future applications in engineering turbulence optimization problems. Source arXiv: 2503.17704v1
Criteria for unbiased estimation: applications to noise-agnostic sensing and learnability of quantum channel Authors Hyukgun Kwon, Kento Tsubouchi, Chia-Tung Chu, Liang Jiang Published: 03.21.2025 Updated: 03.21.2025 Summary We establish the necessary and sufficient conditions for unbiased estimation in multi-parameter estimation tasks. More specifically, we first consider quantum state estimation, where multiple parameters are encoded in a quantum state, and derive two equivalent necessary and sufficient conditions for an unbiased estimation: one formulated in terms of the quantum Fisher information matrix (QFIM) and the other based on the derivatives of the encoded state. Furthermore, we introduce a generalized quantum Cram’er-Rao bound, which provides a fundamental achievable lower bound on the estimation error even when the QFIM is non-invertible. To demonstrate the utility of our framework, we consider phase estimation under unknown Pauli noise. We show that while unbiased phase estimation is infeasible with a naive scheme, employing an entangled probe with a noiseless ancilla enables unbiased estimation. Next, we extend our analysis to quantum channel estimation (equivalently, quantum channel learning), where the goal is to estimate parameters characterizing an unknown quantum channel. We establish the necessary and sufficient condition for unbiased estimation of these parameters. Notably, by interpreting unbiased estimation as learnability, our result applies to the fundamental learnability of parameters in general quantum channels. As a concrete application, we investigate the learnability of noise affecting non-Clifford gates via cycle benchmarking. Source arXiv: 2503.17362v1
MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering Authors Jialin Chen, Aosong Feng, Ziyu Zhao, Juan Garza, Gaukhar Nurbek, Cheng Qin, Ali Maatouk, Leandros Tassiulas, Yifeng Gao, Rex Ying Published: 03.21.2025 Updated: 03.21.2025 Summary Understanding the relationship between textual news and time-series evolution is a critical yet under-explored challenge in applied data science. While multimodal learning has gained traction, existing multimodal time-series datasets fall short in evaluating cross-modal reasoning and complex question answering, which are essential for capturing complex interactions between narrative information and temporal patterns. To bridge this gap, we introduce Multimodal Time Series Benchmark (MTBench), a large-scale benchmark designed to evaluate large language models (LLMs) on time series and text understanding across financial and weather domains. MTbench comprises paired time series and textual data, including financial news with corresponding stock price movements and weather reports aligned with historical temperature records. Unlike existing benchmarks that focus on isolated modalities, MTbench provides a comprehensive testbed for models to jointly reason over structured numerical trends and unstructured textual narratives. The richness of MTbench enables formulation of diverse tasks that require a deep understanding of both text and time-series data, including time-series forecasting, semantic and technical trend analysis, and news-driven question answering (QA). These tasks target the model’s ability to capture temporal dependencies, extract key insights from textual context, and integrate cross-modal information. We evaluate state-of-the-art LLMs on MTbench, analyzing their effectiveness in modeling the complex relationships between news narratives and temporal patterns. Our findings reveal significant challenges in current models, including difficulties in capturing long-term dependencies, interpreting causality in financial and weather trends, and effectively fusing multimodal information. Source arXiv: 2503.16858v1
Extending the HNLS Condition to Robust Quantum Metrology Authors Oskar Novak, Narayanan Rengaswamy Published: 03.19.2025 Updated: 03.19.2025 Summary Quantum sensing holds great promise for high-precision magnetic field measurements. However, its performance is significantly limited by noise. In this work, we develop a quantum sensing protocol to estimate a parameter $theta$, associated with a magnetic field, under full-rank Markovian noise. Our approach uses a probe state constructed from a CSS code that evolves under the parameter’s Hamiltonian for a short time, but without any active error correction. Then we measure the code’s $hat{X}$ stabilizers to infer $theta$. Given $N$ copies of the probe state, we derive the probability that all stabilizer measurements return $+1$, which depends on $theta$. The uncertainty in $theta$ (estimated from these measurements) is bounded by a new quantity, the Robustness Bound, which characterizes how the structure of the quantum code affects the Quantum Fisher Information of the measurement. Using this bound, we establish a strong no-go result: a nontrivial CSS code can achieve Heisenberg scaling if and only if the Hamiltonian is orthogonal to the span of the noise channel’s Lindblad operators. This result extends the well-known HNLS condition under infinite rounds of error correction to the robust quantum sensing setting that does not use active error correction. Our finding suggests fundamental limitations in the use of linear quantum codes for dephased magnetic field sensing applications both in the near-term robust sensing regime and in the long-term fault tolerant era. Source arXiv: 2503.15743v1
Scalable low loss cryogenic packaging of quantum memories in CMOS-foundry processed photonic chips Authors Robert Bernson, Alex Witte, Genevieve Clark, Kamil Gradkowski, Jeffrey Yang, Matt Saha, Matthew Zimmermann, Andrew Leenheer, Kevin Chen, Gerald Gilbert, Matt Eichenfield, Dirk Englund, Peter O'Brien Published: 03.18.2025 Updated: 03.18.2025 Summary Optically linked solid-state quantum memories such as color centers in diamond are a promising platform for distributed quantum information processing and networking. Photonic integrated circuits (PICs) have emerged as a crucial enabling technology for these systems, integrating quantum memories with efficient electrical and optical interfaces in a compact and scalable platform. Packaging these hybrid chips into deployable modules while maintaining low optical loss and resiliency to temperature cycling is a central challenge to their practical use. We demonstrate a packaging method for PICs using surface grating couplers and angle-polished fiber arrays that is robust to temperature cycling, offers scalable channel count, applies to a wide variety of PIC platforms and wavelengths, and offers pathways to automated high-throughput packaging. Using this method, we show optically and electrically packaged quantum memory modules integrating all required qubit controls on chip, operating at millikelvin temperatures with < 3dB losses achievable from fiber to quantum memory. Source arXiv: 2503.14704v1
Virtual purification complements quantum error correction in quantum metrology Authors Hyukgun Kwon, Changhun Oh, Youngrong Lim, Hyunseok Jeong, Seung-Woo Lee, Liang Jiang Published: 03.16.2025 Updated: 03.16.2025 Summary A practical realization of quantum metrology, enhancing the sensitivity of parameter estimation beyond the classical limit, is significantly hindered by the effect of noise. To tackle this challenge, quantum error correction (QEC) has been considered, however, indistinguishable noise from the signal and the bias induced by unknown noise prevents it from recovering the enhanced precision in practice. Meanwhile, virtual purification (VP), an error mitigation technique, has been recently shown to mitigate the bias induced by noise in quantum metrology. In this work, we comparatively analyze the performance of QEC and VP in a realistic quantum metrology scenario. We show that while an ideal QEC setup fails to correct indistinguishable noise from the signal and induces bias, VP can mitigate such indistinguishable noise and bias, resulting in more accurate estimations. We then demonstrate that VP with a stabilizer state probe in $5$-qubit GHZ state and $7$-qubit Steane code state can efficiently suppress the bias under local depolarizing noise. Our result highlights that VP along with encoded probe states can effectively suppress the effect of noise in realistic setups, where error distinguishability poses significant challenges. Source arXiv: 2503.12614v1
Quantum-enhanced quickest change detection of transmission loss Authors Saikat Guha, Tiju Cherian John, Prithwish Basu Published: 03.15.2025 Updated: 03.15.2025 Summary A sudden increase of loss in an optical communications channel can be caused by a malicious wiretapper, or for a benign reason such as inclement weather in a free-space channel or an unintentional bend in an optical fiber. We show that adding a small amount of squeezing to bright phase-modulated coherent-state pulses can dramatically increase the homodyne detection receiver’s sensitivity to change detection in channel loss, without affecting the communications rate. We further show that augmenting blocks of $n$ pulses of a coherent-state codeword with weak continuous-variable entanglement generated by splitting squeezed vacuum pulses in a temporal $n$-mode equal splitter progressively enhances this change-detection sensitivity as $n$ increases; the aforesaid squeezed-light augmentation being the $n=1$ special case. For $n$ high enough, an arbitrarily small amount of quantum-augmented photons per pulse diminishes the change-detection latency by the inverse of the pre-detection channel loss. This superadditivity-like phenomenon in the entanglement-augmented relative entropy rate, which quantifies the latency of change-point detection, may find other uses. We discuss the quantum limit of quickest change detection and a receiver that achieves it, tradeoffs between continuous and discrete-variable quantum augmentation, and the broad problem of joint classical-and-quantum communications and channel-change-detection that our study opens up. Source arXiv: 2503.12276v1
Fast Sideband Control of a Weakly Coupled Multimode Bosonic Memory Authors Jordan Huang, Thomas J. DiNapoli, Gavin Rockwood, Ming Yuan, Prathyankara Narasimhan, Eesh Gupta, Mustafa Bal, Francesco Crisa, Sabrina Garattoni, Yao Lu, Liang Jiang, Srivatsan Chakram Published: 03.13.2025 Updated: 03.13.2025 Summary Circuit quantum electrodynamics (cQED) with superconducting cavities coupled to nonlinear circuits like transmons offers a promising platform for hardware-efficient quantum information processing. We address critical challenges in realizing this architecture by weakening the dispersive coupling while also demonstrating fast, high-fidelity multimode control by dynamically amplifying gate speeds through transmon-mediated sideband interactions. This approach enables transmon-cavity SWAP gates, for which we achieve speeds up to 30 times larger than the bare dispersive coupling. Combined with transmon rotations, this allows for efficient, universal state preparation in a single cavity mode, though achieving unitary gates and extending control to multiple modes remains a challenge. In this work, we overcome this by introducing two sideband control strategies: (1) a shelving technique that prevents unwanted transitions by temporarily storing populations in sideband-transparent transmon states and (2) a method that exploits the dispersive shift to synchronize sideband transition rates across chosen photon-number pairs to implement transmon-cavity SWAP gates that are selective on photon number. We leverage these protocols to prepare Fock and binomial code states across any of ten modes of a multimode cavity with millisecond cavity coherence times. We demonstrate the encoding of a qubit from a transmon into arbitrary vacuum and Fock state superpositions, as well as entangled NOON states of cavity mode pairstextemdash a scheme extendable to arbitrary multimode Fock encodings. Furthermore, we implement a new binomial encoding gate that converts arbitrary transmon superpositions into binomial code states in $qty{4}{microsecond}$ (less than $1/chi$), achieving an average post-selected final state fidelity of $qty{96.3}{percent}$ across different fiducial input states. Source arXiv: 2503.10623v1
Observation of the acoustic Purcell effect with a color-center and a nanomechanical resonator Authors Graham Joe, Michael Haas, Kazuhiro Kuruma, Chang Jin, Dongyeon Daniel Kang, Sophie Ding, Cleaven Chia, Hana Warner, Benjamin Pingault, Bartholomeus Machielse, Srujan Meesala, Marko Loncar Published: 03.13.2025 Updated: 03.13.2025 Summary The radiative properties of atoms are inherently linked to their surrounding environment. Placing an electromagnetic resonator around atoms can enhance spontaneous emission, as shown by Purcell in the 1940s. This approach is now routinely used in quantum computing and communication to channel photons emitted by atoms into well-defined modes and control atom-photon interactions. For solid-state artificial atoms, such as color-centers, the host lattice introduces an acoustic environment, allowing excited atoms to relax by emitting phonons. Here we observe the acoustic Purcell effect by constructing a specially engineered, microwave-frequency nanomechanical resonator around a color-center spin qubit in diamond. Using a co-localized optical mode of the structure that strongly couples to the color-center’s excited state, we perform single-photon-level laser spectroscopy at milliKelvin temperatures and observe ten-fold faster spin relaxation when the spin qubit is tuned into resonance with a 12 GHz acoustic mode. Additionally, we use the color-center as an atomic-scale probe to measure the broadband phonon spectrum of the nanostructure up to a frequency of 28 GHz. Our work establishes a new regime of control for quantum defects in solids and paves the way for interconnects between atomic-scale quantum memories and qubits encoded in acoustic and superconducting devices. Source arXiv: 2503.09946v1
Observation of the acoustic Purcell effect with a color-center and a nanomechanical resonator Authors Graham Joe, Michael Haas, Kazuhiro Kuruma, Chang Jin, Dongyeon Daniel Kang, Sophie Ding, Cleaven Chia, Hana Warner, Benjamin Pingault, Bartholomeus Machielse, Srujan Meesala, Marko Loncar Published: 03.13.2025 Updated: 03.21.2025 Summary The radiative properties of atoms are inherently linked to their surrounding environment. Placing an electromagnetic resonator around atoms can enhance spontaneous emission, as shown by Purcell in the 1940s. This approach is now routinely used in quantum computing and communication to channel photons emitted by atoms into well-defined modes and control atom-photon interactions. For solid-state artificial atoms, such as color-centers, the host lattice introduces an acoustic environment, allowing excited atoms to relax by emitting phonons. Here we observe the acoustic Purcell effect by constructing a specially engineered, microwave-frequency nanomechanical resonator around a color-center spin qubit in diamond. Using a co-localized optical mode of the structure that strongly couples to the color-center’s excited state, we perform single-photon-level laser spectroscopy at milliKelvin temperatures and observe ten-fold faster spin relaxation when the spin qubit is tuned into resonance with a 12 GHz acoustic mode. Additionally, we use the color-center as an atomic-scale probe to measure the broadband phonon spectrum of the nanostructure up to a frequency of 28 GHz. Our work establishes a new regime of control for quantum defects in solids and paves the way for interconnects between atomic-scale quantum memories and qubits encoded in acoustic and superconducting devices. Source arXiv: 2503.09946v2
On the Minimum Distances of Finite-Length Lifted Product Quantum LDPC Codes Authors Nithin Raveendran, David Declercq, Bane Vasić Published: 03.10.2025 Updated: 03.10.2025 Summary Quantum error correction (QEC) is critical for practical realization of fault-tolerant quantum computing, and recently proposed families of quantum low-density parity-check (QLDPC) code are prime candidates for advanced QEC hardware architectures and implementations. This paper focuses on the finite-length QLDPC code design criteria, specifically aimed at constructing degenerate quasi-cyclic symmetric lifted-product (LP-QLDPC) codes. We describe the necessary conditions such that the designed LP-QLDPC codes are guaranteed to have a minimum distance strictly greater than the minimum weight stabilizer generators, ensuring superior error correction performance on quantum channels. The focus is on LP-QLDPC codes built from quasi-cyclic base codes belonging to the class of type-I protographs, and the necessary constraints are efficiently expressed in terms of the row and column indices of the base code. Specifically, we characterize the combinatorial constraints on the classical quasi-cyclic base matrices that guarantee construction of degenerate LP-QLDPC codes. Minimal examples and illustrations are provided to demonstrate the usefulness and effectiveness of the code construction approach. The row and column partition constraints derived in the paper simplify the design of degenerate LP-QLDPC codes and can be incorporated into existing classical and quantum code design approaches. Source arXiv: 2503.07567v1
Engineering Andreev Bound States for Thermal Sensing in Proximity Josephson Junctions Authors Woochan Jung, Ethan G Arnault, Bevin Huang, Jinho Park, Seong Jang, Kenji Watanabe, Takashi Taniguchi, Dirk Englund, Kin Chung Fong, Gil-Ho Lee Published: 03.10.2025 Updated: 03.10.2025 Summary The thermal response of proximity Josephson junctions (JJs) is governed by the temperature ($T$)-dependent occupation of Andreev bound states (ABS), making them promising candidates for sensitive thermal detection. In this study, we systematically engineer ABS to enhance the thermal sensitivity of the critical current ($I_c$) of proximity JJs, quantified as $|,dI_c/dT,|$ for the threshold readout scheme and $|,dI_c/dT cdot I_c^{-1},|$ for the inductive readout scheme. Using a gate-tunable graphene-based JJ platform, we explore the impact of key parameters — including channel length, transparency, carrier density, and superconducting material — on the thermal response. Our results reveal that the proximity-induced superconducting gap plays a crucial role in optimizing thermal sensitivity. Notably, we see a maximum $|,dI_c/dT cdot I_c^{-1},|$ value of $0.6,mathrm{K}^{-1}$ at low temperatures with titanium-based graphene JJs. By demonstrating a systematic approach to engineering ABS in proximity JJs, this work establishes a versatile framework for optimizing thermal sensors and advancing the study of ABS-mediated transport. Source arXiv: 2503.06850v1
Blockwise Post-processing in Satellite-based Quantum Key Distribution Authors Minu J. Bae, Nitish K. Panigrahy, Prajit Dhara, Md Zakir Hossain, Walter O. Krawec, Alexander Russell, Don Towsley, Bing Wang Published: 03.08.2025 Updated: 03.08.2025 Summary Free-space satellite communication has significantly lower photon loss than terrestrial communication via optical fibers. Satellite-based quantum key distribution (QKD) leverages this advantage and provides a promising direction in achieving long-distance QKD. While the technological feasibility of satellite-based QKD has been demonstrated experimentally, optimizing the key rate remains a significant challenge. In this paper, we argue that improving classical post-processing is an important direction in increasing key rate in satellite-based QKD, while it can also be easily incorporated in existing satellite systems. In particular, we explore one direction, blockwise post-processing, to address highly dynamic satellite channel conditions due to various environmental factors. This blockwise strategy divides the raw key bits into individual blocks that have similar noise characteristics, and processes them independently, in contrast to traditional non-blockwise strategy that treats all the raw key bits as a whole. Using a case study, we discuss the choice of blocks in blockwise strategy, and show that blockwise strategy can significantly outperform non-blockwise strategy. Our study demonstrates the importance of post-processing in satellite QKD systems, and presents several open problems in this direction. Source arXiv: 2503.06031v1
Implementation of a quantum addressable router using superconducting qubits Authors Connie Miao, Sébastien Léger, Ziqian Li, Gideon Lee, Liang Jiang, David I. Schuster Published: 03.06.2025 Updated: 04.03.2025 Summary The implementation of a quantum router capable of performing both quantum signal routing and quantum addressing (a Q2-router) represents a key step toward building quantum networks and quantum random access memories. We realize a Q2-router that uses fixed-frequency transmon qubits to implement a routing protocol based on two native controlled-iSWAP gates. These gates leverage a large ZZ interaction to selectively route information according to a quantum address. We find an estimated average routing fidelity of 95.3%, with errors arising primarily from decoherence or state preparation and measurement. We present a comprehensive calibration and characterization of both the c-iSWAP gates and the overall routing protocol through randomized benchmarking techniques and state tomography. Source arXiv: 2503.04295v2
Implementation of a quantum addressable router using superconducting qubits Authors Connie Miao, Sébastien Léger, Ziqian Li, Gideon Lee, Liang Jiang, David I. Schuster Published: 03.06.2025 Updated: 03.06.2025 Summary The implementation of a quantum router capable of performing both quantum signal routing and quantum addressing (a Q2-router) represents a key step toward building quantum networks and quantum random access memories. We realize a Q2-router that uses fixed-frequency transmon qubits to implement a routing protocol based on two native controlled-iSWAP gates. These gates leverage a large ZZ interaction to selectively route information according to a quantum address. We find an estimated average routing fidelity of 94.8%, with errors arising primarily from decoherence or state preparation and measurement. We present a comprehensive calibration and characterization of both the c-iSWAP gates and the overall routing protocol through randomized benchmarking techniques and state tomography. Source arXiv: 2503.04295v1
Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences Authors Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi, Ahmed Elbakary, Alexandros Nikou, Ali Maatouk, Ali Mokh, Amirreza Kazemi, Antonio De Domenico, Athanasios Karapantelakis, Bo Cheng, Bo Yang, Bohao Wang, Carlo Fischione, Chao Zhang, Chaouki Ben Issaid, Chau Yuen, Chenghui Peng, Chongwen Huang, Christina Chaccour, Christo Kurisummoottil Thomas, Dheeraj Sharma, Dimitris Kalogiros, Dusit Niyato, Eli De Poorter, Elissa Mhanna, Emilio Calvanese Strinati, Faouzi Bader, Fathi Abdeldayem, Fei Wang, Fenghao Zhu, Gianluca Fontanesi, Giovanni Geraci, Haibo Zhou, Hakimeh Purmehdi, Hamed Ahmadi, Hang Zou, Hongyang Du, Hoon Lee, Howard H. Yang, Iacopo Poli, Igor Carron, Ilias Chatzistefanidis, Inkyu Lee, Ioannis Pitsiorlas, Jaron Fontaine, Jiajun Wu, Jie Zeng, Jinan Li, Jinane Karam, Johny Gemayel, Juan Deng, Julien Frison, Kaibin Huang, Kehai Qiu, Keith Ball, Kezhi Wang, Kun Guo, Leandros Tassiulas, Lecorve Gwenole, Liexiang Yue, Lina Bariah, Louis Powell, Marcin Dryjanski, Maria Amparo Canaveras Galdon, Marios Kountouris, Maryam Hafeez, Maxime Elkael, Mehdi Bennis, Mehdi Boudjelli, Meiling Dai, Merouane Debbah, Michele Polese, Mohamad Assaad, Mohamed Benzaghta, Mohammad Al Refai, Moussab Djerrab, Mubeen Syed, Muhammad Amir, Na Yan, Najla Alkaabi, Nan Li, Nassim Sehad, Navid Nikaein, Omar Hashash, Pawel Sroka, Qianqian Yang, Qiyang Zhao, Rasoul Nikbakht Silab, Rex Ying, Roberto Morabito, Rongpeng Li, Ryad Madi, Salah Eddine El Ayoubi, Salvatore D'Oro, Samson Lasaulce, Serveh Shalmashi, Sige Liu, Sihem Cherrared, Swarna Bindu Chetty, Swastika Dutta, Syed A. R. Zaidi, Tianjiao Chen, Timothy Murphy, Tommaso Melodia, Tony Q. S. Quek, Vishnu Ram, Walid Saad, Wassim Hamidouche, Weilong Chen, Xiaoou Liu, Xiaoxue Yu, Xijun Wang, Xingyu Shang, Xinquan Wang, Xuelin Cao, Yang Su, Yanping Liang, Yansha Deng, Yifan Yang, Yingping Cui, Yu Sun, Yuxuan Chen, Yvan Pointurier, Zeinab Nehme, Zeinab Nezami, Zhaohui Yang, Zhaoyang Zhang, Zhe Liu, Zhenyu Yang, Zhu Han, Zhuang Zhou, Zihan Chen, Zirui Chen, Zitao Shuai Published: 03.06.2025 Updated: 03.06.2025 Summary This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions and user experiences, especially in the context of 6G systems. It highlights the development and deployment of Large Telecom Models (LTMs), which are tailored AI models designed to address the complex challenges faced by modern telecom networks. The paper covers a wide range of topics, from the architecture and deployment strategies of LTMs to their applications in network management, resource allocation, and optimization. It also explores the regulatory, ethical, and standardization considerations for LTMs, offering insights into their future integration into telecom infrastructure. The goal is to provide a comprehensive roadmap for the adoption of LTMs to enhance scalability, performance, and user-centric innovation in telecom networks. Source arXiv: 2503.04184v1
Construction and Decoding of Quantum Margulis Codes Authors Michele Pacenti, Dimitris Chytas, Bane Vasic Published: 03.05.2025 Updated: 03.05.2025 Summary Quantum low-density parity-check codes are a promising approach to fault-tolerant quantum computation, offering potential advantages in rate and decoding efficiency. In this work, we introduce quantum Margulis codes, a new class of QLDPC codes derived from Margulis’ classical LDPC construction via the two-block group algebra framework. We show that quantum Margulis codes, unlike bivariate bicycle codes which require ordered statistics decoding for effective error correction, can be efficiently decoded using a standard min-sum decoder with linear complexity, when decoded under depolarizing noise. This is attributed to their Tanner graph structure, which does not exhibit group symmetry, thereby mitigating the well-known problem of error degeneracy in QLDPC decoding. To further enhance performance, we propose an algorithm for constructing 2BGA codes with controlled girth, ensuring a minimum girth of 6 or 8, and use it to generate several quantum Margulis codes of length 240 and 642. We validate our approach through numerical simulations, demonstrating that quantum Margulis codes behave significantly better than BB codes in the error floor region, under min-sum decoding. Source arXiv: 2503.03936v1
Acoustic phonon phase gates with number-resolving phonon detection Authors Hong Qiao, Zhaoyou Wang, Gustav Andersson, Alexander Anferov, Christopher R. Conner, Yash J. Joshi, Shiheng Li, Jacob M. Miller, Xuntao Wu, Haoxiong Yan, Liang Jiang, Andrew N. Cleland Published: 03.05.2025 Updated: 03.05.2025 Summary Linear optical quantum computing (LOQC) provides a compelling approach to quantum information processing, with a short list of physical requirements; however, experimental implementations have faced significant challenges. Itinerant phonons in quantum acoustics, combined with superconducting qubits, offer a compelling alternative to the quantum optics approach. Here we demonstrate key advances in the ability to manipulate and measure acoustic phonon quantum states: First, we demonstrate deterministic phase control of itinerant one- and two-phonon qubit states, measured using an acoustic Mach-Zehnder interferometer. We implement phonon phase control using the frequency-dependent scattering of phonon states from a superconducting transmon qubit. The acoustic interferometer used to measure the resulting phonon phase achieves a noise-floor-limited Hong-Ou-Mandel (HOM) interference visibility of 98.1%, representing a significant improvement over our previous demonstration. Additionally, we propose and implement a multi-phonon detection scheme that enables coherent conversion between itinerant one- and two-phonon Fock states and transmon qutrit states, transforming for example the Hong-Ou-Mandel two-phonon entangled output state $|02rangle – |20rangle$ into the entangled state of two transmons. The tight integration of quantum acoustics with superconducting circuits native to our implementation promises further advances, including deterministic phonon quantum gates with direct applications to quantum computing. Source arXiv: 2503.03898v1
Quantum-enhanced radio-frequency photonic distributed imaging Authors Haowei Shi, Christopher M. Jones, Mengjie Yu, Zheshen Zhang, Quntao Zhuang Published: 03.05.2025 Updated: 03.05.2025 Summary Quantum physics has brought enhanced capability in various sensing applications. Despite challenges from noise and loss in the radio-frequency (RF) domain, [Phys. Rev. Lett. 124, 150502 (2020)] demonstrates a route for enhanced RF-receiver empowered by quantum squeezing and entanglement. In this work, we further explore the quantum advantage of imaging in the weak coupling scenario of the RF-photonic receiver. The proposed imaging receiver applies transducer to upconvert the RF signal to optical to enable high-efficiency connection via low-loss fiber networks. The efficient connection therefore increases the synthetic aperture and improves the resolution of the distributed imaging system. To overcome the challenge from low transduction efficiency in existing devices limited by weak photon interaction, we propose the use of squeezed-state optical sources to suppress the noise. We numerically evaluate the quantum advantage in synthetic aperture radar imaging, where the images are generated from the standard resolution test chart via a Gaussian point spread function with added Gaussian noise. We apply the Wiener filter on the images to restore the objects and find that stronger squeezing significantly improves the quality of the restored image. Our findings push quantum squeezing advantage to real-world applications. Source arXiv: 2503.03075v1
Purcell-enhanced emissions from diamond color centers in slow light photonic crystal waveguides Authors Sophie W. Ding, Chang Jin, Kazuhiro Kuruma, Xinghan Guo, Michael Haas, Boris Korzh, Andrew Beyer, Matt Shaw, Neil Sinclair, David D. Awschalom, F. Joseph Heremans, Nazar Delegan, Alexander A. High, Marko Loncar Published: 03.03.2025 Updated: 03.03.2025 Summary Quantum memories based on emitters with optically addressable spins rely on efficient photonic interfaces, often implemented as nanophotonic cavities with ideally narrow spectral linewidths and small mode volumes. However, these approaches require nearly perfect spectral and spatial overlap between the cavity mode and quantum emitter, which can be challenging. This is especially true in the case of solid-state quantum emitters that are often randomly positioned and can suffer from significant inhomogeneous broadening. An alternative approach to mitigate these challenges is to use slow-light waveguides that can enhance light-matter interaction across large optical bandwidths and large areas. Here, we demonstrate diamond slow light photonic crystal (PhC) waveguides that enable broadband optical coupling to embedded silicon-vacancy (SiV) color centers. We take advantage of the recently demonstrated thin-film diamond photonic platform to fabricate fully suspended two-dimensional PhC waveguides. Using this approach, we demonstrate waveguide modes with high group indices up to 70 and observe Purcell-enhanced emissions of the SiVs coupled to the waveguide mode. Our approach represents a practical diamond platform for robust spin-photon interfaces with color centers. Source arXiv: 2503.01149v1
Efficient quantum tomography of a polynomial subspace Authors Yat Wong, Ming Yuan, Kevin He, Srivatsan Chakram, Alireza Seif, David I. Schuster, Liang Jiang Published: 03.01.2025 Updated: 03.01.2025 Summary Quantum tomography is crucial for characterizing the quantum states of multipartite systems, but its practicality is often limited by the exponentially large dimension of the Hilbert space. Most existing approaches, such as compressed sensing and tensor network-based tomography, impose structural constraints on the state to enable more resource-efficient characterization. However, not all physical states can be well-approximated with highly structured states. Here, we develop a partial quantum tomography method based on direct fidelity estimation (DFE) that focuses on a neighborhood subspace — the subspace spanned by states physically close to a given target state. Using this generalized DFE method, we estimate elements of the density operator within this subspace in a self-verifying manner. We investigate the efficiency of this approach under different sets of available measurements for various states and find that the set of available measurements significantly impacts the cost of DFE. For example, we show that Pauli measurements alone are insufficient for performing efficient DFE on all product states, whereas the full set of product measurements is sufficient. This method can be applied in many situations, including characterizing quantum systems with confined dynamics and verifying preparations of quantum states and processes. Source arXiv: 2503.00255v1
Multimode operation of a superconducting nanowire switch in the nanosecond regime Authors Zoltán Scherübl, Mátyás Kocsis, Tosson Elalaily, Lőrinc Kupás, Martin Berke, Gergő Fülöp, Thomas Kanne, Karl Berggren, Jesper Nygård, Szabolcs Csonka, Péter Makk Published: 02.25.2025 Updated: 02.25.2025 Summary Superconducting circuits are promising candidates for future computational architectures, however, practical applications require fast operation. Here, we demonstrate fast, gate-based switching of an Al nanowire-based superconducting switch in time-domain experiments. We apply voltage pulses on the gate while monitoring the microwave transmission of the device. Utilizing the usual leakage-based operation these measurements yield a fast, 1–2~ns switching time to the normal state, possibly limited by the bandwidth of our setup, and a 10–20~ns delay in the normal to superconducting transition. However, having a significant capacitance between the gate and the device allows for a novel operation, where the displacement current, induced by the fast gate pulses, drives the transition. The switching from superconducting to the normal state yields a similar fast timescale, while in the opposite direction the switching is significantly faster (4–6~ns) than the leakage based operation, which may be further improved by better thermal design. The measured short timescales and novel switching operation open the way for future fast and low-power-consumption applications. Source arXiv: 2502.17980v1
Gigahertz- and mmWave-repetition-rate soliton microcombs on X-cut lithium niobate Authors Yunxiang Song, Xinrui Zhu, Xiangying Zuo, Guanhao Huang, Marko Loncar Published: 02.18.2025 Updated: 02.18.2025 Summary Soliton microcombs are a cornerstone of integrated frequency comb technologies, with applications spanning photonic computing, ranging, microwave synthesis, optical communications, and quantum light generation. In nearly all such applications, electro-optic (EO) components play a critical role in generating, monitoring, stabilizing, and modulating the solitons. Towards building photonic integrated circuits for next-generation applications, that will simultaneously maximize system performance and minimize size, weight, and power consumption metrics, achieving soliton microcombs and efficient EO modulation on a chip is essential. X-cut thin-film lithium niobate (TFLN) has emerged as a leading photonic platform for the realization of high-performance integrated EO devices and systems. However, despite extensive research, soliton microcombs have remained elusive to X-cut TFLN due to its multiple strong Raman-active modes, in-plane refractive index anisotropy, and photorefractive effects. Here, we address this long-standing challenge and demonstrate versatile soliton microcombs on X-cut TFLN, with repetition-rates spanning from the gigahertz (~26 GHz) up to the millimeter-wave (~0.156 THz) regime. Our finding broadly advances both the fundamental science and practical applications of integrated comb sources by enabling efficient EO modulation and broadband coherent solitons to be monolithically combined on the same chip. Source arXiv: 2502.12480v1
Stable gigahertz- and mmWave-repetition-rate soliton microcombs on X-cut lithium niobate Authors Yunxiang Song, Xinrui Zhu, Xiangying Zuo, Guanhao Huang, Marko Loncar Published: 02.18.2025 Updated: 03.14.2025 Summary Soliton microcombs are a cornerstone of integrated frequency comb technologies, with applications spanning photonic computing, ranging, microwave synthesis, optical communications, and quantum light generation. In nearly all such applications, electro-optic (EO) components play a critical role in generating, monitoring, stabilizing, and modulating the solitons. Towards building photonic integrated circuits for next-generation applications, that will simultaneously maximize system performance and minimize size, weight, and power consumption metrics, achieving soliton microcombs and efficient EO modulation on a chip is essential. X-cut thin-film lithium niobate (TFLN) has emerged as a leading photonic platform for the realization of high-performance integrated EO devices and systems. However, despite extensive research, soliton microcombs have remained elusive to X-cut TFLN due to its multiple strong Raman-active modes, in-plane refractive index anisotropy, and photorefractive effects. Here, we address this long-standing challenge and demonstrate versatile soliton microcombs on X-cut TFLN, with repetition-rates spanning from the gigahertz (~26 GHz) up to the millimeter-wave (~0.156 THz) regime. The combs feature exceptional long-term stability, maintaining a direct injection-locked state for over 90 minutes (manually terminated), with repetition-rate phase noise closely tracking that of a high-quality electronic microwave synthesizer. Our finding broadly advances both the fundamental science and practical applications of integrated comb sources by enabling efficient EO modulation and broadband coherent solitons to be monolithically combined on the same chip. Source arXiv: 2502.12480v2
Measurement-Based Entanglement Distillation and Constant-Rate Quantum Repeaters over Arbitrary Distances Authors Yu Shi, Ashlesha Patil, Saikat Guha Published: 02.16.2025 Updated: 02.16.2025 Summary Measurement-based quantum repeaters employ entanglement distillation and swapping across links using locally prepared resource states of minimal size and local Bell measurements. In this paper, we introduce a systematic protocol for measurement-based entanglement distillation and its application to repeaters that can leverage any stabilizer code. Given a code, we explicitly define the corresponding resource state and derive an error-recovery operation based on all Bell measurement outcomes. Our approach offers deeper insights into the impact of resource state noise on repeater performance while also providing strategies for efficient preparation and fault-tolerant preservation of resource states. As an application, we propose a measurement-based repeater protocol based on quantum low-density parity-check (QLDPC) codes, enabling constant-yield Bell state distribution over arbitrary distances. Numerical simulations confirm exponential suppression of infidelity with increasing code size while maintaining a fixed code rate. This work establishes a scalable backbone for future global-scale fault-tolerant quantum networks. Source arXiv: 2502.11174v1
Constant-Overhead Fault-Tolerant Bell-Pair Distillation using High-Rate Codes Authors J. Pablo Bonilla Ataides, Hengyun Zhou, Qian Xu, Gefen Baranes, Bikun Li, Mikhail D. Lukin, Liang Jiang Published: 02.13.2025 Updated: 02.13.2025 Summary We present a fault-tolerant Bell-pair distillation scheme achieving constant overhead through high-rate quantum low-density parity-check (qLDPC) codes. Our approach maintains a constant distillation rate equal to the code rate – as high as $1/3$ in our implementations – while requiring no additional overhead beyond the physical qubits of the code. Full circuit-level analysis demonstrates fault-tolerance for input Bell pair infidelities below a threshold $sim 5%$, readily achievable with near-term capabilities. Unlike previous proposals, our scheme keeps the output Bell pairs encoded in qLDPC codes at each node, eliminating decoding overhead and enabling direct use in distributed quantum applications through recent advances in qLDPC computation. These results establish qLDPC-based distillation as a practical route toward resource-efficient quantum networks and distributed quantum computing. Source arXiv: 2502.09542v1
Quantum communication over bandwidth-and-time-limited channels Authors Aditya Gandotra, Zhaoyou Wang, Aashish A. Clerk, Liang Jiang Published: 02.12.2025 Updated: 02.12.2025 Summary Standard communication systems have transmission spectra that characterize their ability to perform frequency multiplexing over a finite bandwidth. Realistic quantum signals in quantum communication systems like transducers are inherently limited in time due to intrinsic decoherence and finite latency, which hinders the direct implementation of frequency-multiplexed encoding. We investigate quantum channel capacities for bandwidth-and-time-limited (BTL) channels to establish the optimal communication strategy in a realistic setting. For pure-loss bosonic channels, we derive analytical solutions of the optimal encoding and decoding modes for Lorentzian and box transmission spectra, along with numerical solutions for various other transmissions. Our findings reveal a general feature of sequential activation of quantum channels as the input signal duration increases, as well as the existence of optimal signal length for scenarios where only a limited number of channels are in use. Source arXiv: 2502.08831v1
Gigahertz-Frequency, Acousto-Optic Phase Modulation of Visible Light in a CMOS-Fabricated Photonic Circuit Authors Jacob M. Freedman, Matthew J. Storey, Daniel Dominguez, Andrew Leenheer, Sebastian Magri, Nils T. Otterstrom, Matt Eichenfield Published: 02.11.2025 Updated: 02.11.2025 Summary Here we present an efficient, visible-light, gigahertz-frequency acousto-optic modulator fabricated on a 200 mm wafer in a volume CMOS foundry. Our device combines a piezoelectric transducer and a photonic waveguide within a single microstructure that confines both a propagating optical mode and an electrically excitable breathing-mode mechanical resonance. By tuning the device’s geometry to optimize the optomechanical interaction, we achieve modulation depths exceeding 2 rad with 15 mW applied microwave power at 2.31 GHz in a 2 mm long device. This corresponds to a modulation figure of merit of $V_{pi}cdot L$ = 0.26 Vcm in a visible-light, integrated acousto-optics platform that can be straightforwardly extended to a wide range of optical wavelengths and modulation frequencies. For the important class of gigahertz-frequency modulators that can handle hundreds of milliwatts of visible-light optical power, which are critical for scalable quantum control systems, this represents a 15x decrease in $V_{pi}$ and a 100x decrease in required microwave power compared to the commercial state-of-the-art and existing work in the literature. Source arXiv: 2502.08012v1
Quantum learning advantage on a scalable photonic platform Authors Zheng-Hao Liu, Romain Brunel, Emil E. B. Østergaard, Oscar Cordero, Senrui Chen, Yat Wong, Jens A. H. Nielsen, Axel B. Bregnsbo, Sisi Zhou, Hsin-Yuan Huang, Changhun Oh, Liang Jiang, John Preskill, Jonas S. Neergaard-Nielsen, Ulrik L. Andersen Published: 02.11.2025 Updated: 02.11.2025 Summary Recent advancements in quantum technologies have opened new horizons for exploring the physical world in ways once deemed impossible. Central to these breakthroughs is the concept of quantum advantage, where quantum systems outperform their classical counterparts in solving specific tasks. While much attention has been devoted to computational speedups, quantum advantage in learning physical systems remains a largely untapped frontier. Here, we present a photonic implementation of a quantum-enhanced protocol for learning the probability distribution of a multimode bosonic displacement process. By harnessing the unique properties of continuous-variable quantum entanglement, we obtain a massive advantage in sample complexity with respect to conventional methods without entangled resources. With approximately 5 dB of two-mode squeezing — corresponding to imperfect Einstein–Podolsky–Rosen (EPR) entanglement — we learn a 100-mode bosonic displacement process using 11.8 orders of magnitude fewer samples than a conventional scheme. Our results demonstrate that even with non-ideal, noisy entanglement, a significant quantum advantage can be realized in continuous-variable quantum systems. This marks an important step towards practical quantum-enhanced learning protocols with implications for quantum metrology, certification, and machine learning. Source arXiv: 2502.07770v1
Quantum learning advantage on a scalable photonic platform Authors Zheng-Hao Liu, Romain Brunel, Emil E. B. Østergaard, Oscar Cordero, Senrui Chen, Yat Wong, Jens A. H. Nielsen, Axel B. Bregnsbo, Sisi Zhou, Hsin-Yuan Huang, Changhun Oh, Liang Jiang, John Preskill, Jonas S. Neergaard-Nielsen, Ulrik L. Andersen Published: 02.11.2025 Updated: 02.16.2025 Summary Recent advancements in quantum technologies have opened new horizons for exploring the physical world in ways once deemed impossible. Central to these breakthroughs is the concept of quantum advantage, where quantum systems outperform their classical counterparts in solving specific tasks. While much attention has been devoted to computational speedups, quantum advantage in learning physical systems remains a largely untapped frontier. Here, we present a photonic implementation of a quantum-enhanced protocol for learning the probability distribution of a multimode bosonic displacement process. By harnessing the unique properties of continuous-variable quantum entanglement, we obtain a massive advantage in sample complexity with respect to conventional methods without entangled resources. With approximately 5 dB of two-mode squeezing — corresponding to imperfect Einstein–Podolsky–Rosen (EPR) entanglement — we learn a 100-mode bosonic displacement process using 11.8 orders of magnitude fewer samples than a conventional scheme. Our results demonstrate that even with non-ideal, noisy entanglement, a significant quantum advantage can be realized in continuous-variable quantum systems. This marks an important step towards practical quantum-enhanced learning protocols with implications for quantum metrology, certification, and machine learning. Source arXiv: 2502.07770v2
Out-of-distribution generalisation for learning quantum channels with low-energy coherent states Authors Jason L. Pereira, Quntao Zhuang, Leonardo Banchi Published: 02.06.2025 Updated: 02.06.2025 Summary When experimentally learning the action of a continuous variable quantum process by probing it with inputs, there will often be some restriction on the input states used. One experimentally simple way to probe the channel is using low-energy coherent states. Learning a quantum channel in this way presents difficulties, due to the fact that two channels may act similarly on low energy inputs but very differently for high energy inputs. They may also act similarly on coherent state inputs but differently on non-classical inputs. Extrapolating the behaviour of a channel for more general input states from its action on the far more limited set of low energy coherent states is a case of out-of-distribution generalisation. To be sure that such generalisation gives meaningful results, one needs to relate error bounds for the training set to bounds that are valid for all inputs. We show that for any pair of channels that act sufficiently similarly on low energy coherent state inputs, one can bound how different the input-output relations are for any (high energy or highly non-classical) input. This proves out-of-distribution generalisation is always possible for learning quantum channels using low energy coherent states. Source arXiv: 2502.04454v1
Spectral tuning and nanoscale localization of single color centers in silicon via controllable strain Authors Alessandro Buzzi, Camille Papon, Matteo Pirro, Odiel Hooybergs, Hamza Raniwala, Valeria Saggio, Carlos Errando-Herranz, Dirk Englund Published: 01.28.2025 Updated: 01.28.2025 Summary The development of color centers in silicon enables scalable quantum technologies by combining telecom-wavelength emission and compatibility with mature silicon fabrication. However, large-scale integration requires precise control of each emitter’s optical transition to generate indistinguishable photons for quantum networking. Here, we demonstrate a foundry-fabricated photonic integrated circuit (PIC) combining suspended silicon waveguides with a microelectromechanical (MEMS) cantilever to apply local strain and spectrally tune individual G-centers. Applying up to 35 V between the cantilever and the substrate induces a reversible wavelength shift of the zero-phonon line exceeding 100 pm, with no loss in brightness. Moreover, by modeling the strain-induced shifts with a `digital twin’ physical model, we achieve vertical localization of color centers with sub-3 nm vertical resolution, directly correlating their spatial position, dipole orientation, and spectral behavior. This method enables on-demand, low-power control of emission spectrum and nanoscale localization of color centers, advancing quantum networks on a foundry-compatible platform. Source arXiv: 2501.17290v1
Spectral tuning and nanoscale localization of single color centers in silicon via controllable strain Authors Alessandro Buzzi, Camille Papon, Matteo Pirro, Odiel Hooybergs, Hamza Raniwala, Valeria Saggio, Carlos Errando-Herranz, Dirk Englund Published: 01.28.2025 Updated: 02.03.2025 Summary The development of color centers in silicon enables scalable quantum technologies by combining telecom-wavelength emission and compatibility with mature silicon fabrication. However, large-scale integration requires precise control of each emitter’s optical transition to generate indistinguishable photons for quantum networking. Here, we demonstrate a foundry-fabricated photonic integrated circuit (PIC) combining suspended silicon waveguides with a microelectromechanical (MEMS) cantilever to apply local strain and spectrally tune individual G-centers. Applying up to 35 V between the cantilever and the substrate induces a reversible wavelength shift of the zero-phonon line exceeding 100 pm, with no loss in brightness. Moreover, by modeling the strain-induced shifts with a `digital twin’ physical model, we achieve vertical localization of color centers with sub-3 nm vertical resolution, directly correlating their spatial position, dipole orientation, and spectral behavior. This method enables on-demand, low-power control of emission spectrum and nanoscale localization of color centers, advancing quantum networks on a foundry-compatible platform. Source arXiv: 2501.17290v2
End-to-end physics-based modeling of laser-activated color centers in silicon Authors Qiushi Gu, Valeria Saggio, Camille Papon, Alessandro Buzzi, Ian Christen, Christopher Panuski, Carlos Errando-Herranz, Dirk Englund Published: 01.28.2025 Updated: 01.28.2025 Summary Color centers are among the most promising candidates for quantum information processing. Central requirements for their practical applications include controlled and efficient local activation in nanophotonic devices and identical spectral features. However, producing color centers in a controlled and reliable way is inherently challenging due to the lack of comprehensive theoretical insights into their formation and the difficulty of streamlining the generation process for rapid in-situ optimization. We address these challenges by developing an end-to-end first-principles model that captures the underlying formation process of color centers. Emitters are activated through laser annealing, which allows for in-situ creation and the possibility of model-based control. Notably, our model enables the estimation of the emitters’ inhomogeneous broadening down to 16 GHz in bare silicon, which translates into the creation of emitters with highly similar spectral properties. Finally, we address the challenge of in-situ deterministic activation of color centers in nanophotonic devices by going beyond bare silicon and demonstrating successful laser writing in photonic crystal optical cavities. These results lay the foundation for deterministic and large-scale integration of color centers within quantum photonic platforms. Source arXiv: 2501.17240v1
Entanglement-Assisted Coding for Arbitrary Linear Computations Over a Quantum MAC Authors Lei Hu, Mohamed Nomeir, Alptug Aytekin, Yu Shi, Sennur Ulukus, Saikat Guha Published: 01.27.2025 Updated: 01.27.2025 Summary We study a linear computation problem over a quantum multiple access channel (LC-QMAC), where $S$ servers share an entangled state and separately store classical data streams $W_1,cdots, W_S$ over a finite field $mathbb{F}_d$. A user aims to compute $K$ linear combinations of these data streams, represented as $Y = mathbf{V}_1 W_1 + mathbf{V}_2 W_2 + cdots + mathbf{V}_S W_S in mathbb{F}_d^{K times 1}$. To this end, each server encodes its classical information into its local quantum subsystem and transmits it to the user, who retrieves the desired computations via quantum measurements. In this work, we propose an achievable scheme for LC-QMAC based on the stabilizer formalism and the ideas from entanglement-assisted quantum error-correcting codes (EAQECC). Specifically, given any linear computation matrix, we construct a self-orthogonal matrix that can be implemented using the stabilizer formalism. Also, we apply precoding matrices to minimize the number of auxiliary qudits required. Our scheme achieves more computations per qudit, i.e., a higher computation rate, compared to the best-known methods in the literature, and attains the capacity in certain cases. Source arXiv: 2501.16296v1
Advancing quantum imaging through learning theory Authors Yunkai Wang, Changhun Oh, Junyu Liu, Liang Jiang, Sisi Zhou Published: 01.26.2025 Updated: 01.26.2025 Summary We quantify performance of quantum imaging by modeling it as a learning task and calculating the Resolvable Expressive Capacity (REC). Compared to the traditionally applied Fisher information matrix approach, REC provides a single-parameter interpretation of overall imaging quality for specific measurements that applies in the regime of finite samples. We first examine imaging performance for two-point sources and generally distributed sources, referred to as compact sources, both of which have intensity distributions confined within the Rayleigh limit of the imaging system. Our findings indicate that REC increases stepwise as the sample number reaches certain thresholds, which are dependent on the source’s size. Notably, these thresholds differ between direct imaging and superresolution measurements (e.g., spatial-mode demultiplexing (SPADE) measurement in the case of Gaussian point spread functions (PSF)). REC also enables the extension of our analysis to more general scenarios involving multiple compact sources, beyond the previously studied scenarios. For closely spaced compact sources with Gaussian PSFs, our newly introduced orthogonalized SPADE method outperforms the naively separate SPADE method, as quantified by REC. Source arXiv: 2501.15685v1
Achievability of Covert Quantum Communication Authors Evan J. D. Anderson, Michael S. Bullock, Filip Rozpędek, Boulat A. Bash Published: 01.22.2025 Updated: 01.22.2025 Summary We explore covert communication of qubits over the general quantum channel. Covert communication conceals the transmissions in the channel noise, ensuring that an adversary is unable to detect their presence. We show achievability of a emph{square root law} (SRL) for quantum covert communication similar to that for classical: $M(n)proptosqrt{n}$ qubits can be transmitted covertly and reliably over $n$ uses of a general quantum channel. We lower bound $M(n)$ with and without the assistance from a full-duplex covert classical channel. In the former case, we quantify the number of classical covert bits sufficient for our protocol. Source arXiv: 2501.13103v1
Achievability of Covert Quantum Communication Authors Evan J. D. Anderson, Michael S. Bullock, Filip Rozpędek, Boulat A. Bash Published: 01.22.2025 Updated: 01.26.2025 Summary We explore covert communication of qubits over an arbitrary quantum channel. Covert communication conceals the transmissions in the channel noise, ensuring that an adversary is unable to detect their presence. We show the achievability of a $textit{square root law}$ (SRL) for quantum covert communication similar to that for classical: $M(n)proptosqrt{n}$ qubits can be transmitted covertly and reliably over $n$ uses of a general quantum channel. We lower bound $M(n)$ with and without assistance from a two-way covert classical channel. In the former case, we quantify the number of classical covert bits sufficient for our protocol. Source arXiv: 2501.13103v2
Optimizing compilation of error correction codes for 2xN quantum dot arrays and its NP-hardness Authors Anthony Micciche, Anasua Chatterjee, Andrew McGregor, Stefan Krastanov Published: 01.15.2025 Updated: 01.15.2025 Summary The ability to physically move qubits within a register allows the design of hardware-specific error correction codes which can achieve fault-tolerance while respecting other constraints. In particular, recent advancements have demonstrated the shuttling of electron and hole spin qubits through a quantum dot array with high fidelity. Exploiting this, we design an error correction architecture, consisting merely of two parallel quantum dot arrays, an experimentally validated architecture compatible with classical wiring and control constraints. We develop a suite of heuristic methods for compiling any stabilizer error-correcting code’s syndrome-extraction circuit to run with a minimal number of shuttling operations. In simulation, these heuristics show that fault tolerance can be achieved on several contemporary quantum error-correcting codes requiring only modestly-optimistic noise parameters. Furthermore, we demonstrate how constant column-weight qLDPC codes can be compiled in a provably minimal number of shuttles that scales constantly with code size using Shor-style syndrome extraction. In addition, we provide a proof of the NP hardness of minimizing the number of shuttle operations for codes not in that class. Source arXiv: 2501.09061v1
Optimization of Quantum-Repeater Networks using Stochastic Automatic Differentiation Authors Guus Avis, Stefan Krastanov Published: 01.10.2025 Updated: 01.10.2025 Summary Quantum repeaters are envisioned to enable long-distance entanglement distribution. Analysis of quantum-repeater networks could hasten their realization by informing design decisions and research priorities. Determining derivatives of network properties is crucial towards that end, facilitating optimizations and revealing parameter sensitivity. Doing so, however, is difficult because the networks are discretely random. Here we use a recently developed technique, stochastic automatic differentiation, to automatically extract derivatives from discrete Monte Carlo simulations of repeater networks. With these derivatives, we optimize rate-fidelity tradeoffs in a repeater chain, determine the chain’s sensitivity with respect to the coherence times of different nodes, and finally choose the locations of quantum repeaters in a two-dimensional plane to optimize the guaranteed quality of service between four end nodes. In particular, the technique enabled us to discover how the best achievable quality of service, the minimal number of repeaters required to improve a network, and the number of repeaters required to saturate the network scale with the physical size of the network. Source arXiv: 2501.06291v1
Enhanced Min-Sum Decoding of Quantum Codes Using Previous Iteration Dynamics Authors Dimitris Chytas, Nithin Raveendran, Bane Vasic Published: 01.09.2025 Updated: 01.09.2025 Summary In this paper, we propose a novel message-passing decoding approach that leverages the degeneracy of quantum low-density parity-check codes to enhance decoding performance, eliminating the need for serial scheduling or post-processing. Our focus is on two-block Calderbank-Shor-Steane (CSS) codes, which are composed of symmetric stabilizers that hinder the performance of conventional iterative decoders with uniform update rules. Specifically, our analysis shows that, under the isolation assumption, the min-sum decoder fails to converge when constant-weight errors are applied to symmetric stabilizers, as variable-to-check messages oscillate in every iteration. To address this, we introduce a decoding technique that exploits this oscillatory property by applying distinct update rules: variable nodes in one block utilize messages from previous iterations, while those in the other block are updated conventionally. 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-zero ordered statistics decoding, all while maintaining linear complexity in the code’s block length. Source arXiv: 2501.05021v1
Entangled dual-comb spectroscopy Authors Abdulkarim Hariri, Shuai Liu, Haowei Shi, Quntao Zhuang, Xudong Fan, Zheshen Zhang Published: 12.27.2024 Updated: 12.27.2024 Summary Optical frequency combs have emerged as a cornerstone for a wide range of areas, including spectroscopy, ranging, optical clocks, time and frequency transfer, waveform synthesis, and communications. However, quantum mechanical fluctuations of the optical carrier impose fundamental performance limits on the precision of traditional classical laser frequency combs, particularly in their use for interferometry and spectroscopy. Entanglement, as a quintessential quantum resource, allows for surpassing the fundamental limits of classical systems. Here, we introduce and experimentally demonstrate entangled dual-comb spectroscopy (EDCS) that surmounts the fundamental limits of classical DCS. EDCS builds on tailored entangled spectral structures of the frequency combs, enabling simultaneous detection of all comb lines below the standard quantum limit of classical DCS. Applying EDCS in gas detection, we achieve a 2.6 dB enhancement in signal-to-noise ratio and a 1.7-fold reduction in integration time over classical DCS, rendering EDCS particularly suited for dynamic chemical and biological sensing, where fast, precise measurements subject to power constraints are required. EDCS represents a new paradigm for quantum frequency combs, underscoring their prospects in a plethora of applications in precision metrology, spectroscopy, and timekeeping. Source arXiv: 2412.19800v1
Derandomized shallow shadows: Efficient Pauli learning with bounded-depth circuits Authors Katherine Van Kirk, Christian Kokail, Jonathan Kunjummen, Hong-Ye Hu, Yanting Teng, Madelyn Cain, Jacob Taylor, Susanne F. Yelin, Hannes Pichler, Mikhail Lukin Published: 12.25.2024 Updated: 12.25.2024 Summary Efficiently estimating large numbers of non-commuting observables is an important subroutine of many quantum science tasks. We present the derandomized shallow shadows (DSS) algorithm for efficiently learning a large set of non-commuting observables, using shallow circuits to rotate into measurement bases. Exploiting tensor network techniques to ensure polynomial scaling of classical resources, our algorithm outputs a set of shallow measurement circuits that approximately minimizes the sample complexity of estimating a given set of Pauli strings. We numerically demonstrate systematic improvement, in comparison with state-of-the-art techniques, for energy estimation of quantum chemistry benchmarks and verification of quantum many-body systems, and we observe DSS’s performance consistently improves as one allows deeper measurement circuits. These results indicate that in addition to being an efficient, low-depth, stand-alone algorithm, DSS can also benefit many larger quantum algorithms requiring estimation of multiple non-commuting observables. Source arXiv: 2412.18973v1
Age Optimal Sampling for Unreliable Channels under Unknown Channel Statistics Authors Hongyi He, Haoyue Tang, Jiayu Pan, Jintao Wang, Jian Song, Leandros Tassiulas Published: 12.24.2024 Updated: 12.24.2024 Summary In this paper, we study a system in which a sensor forwards status updates to a receiver through an error-prone channel, while the receiver sends the transmission results back to the sensor via a reliable channel. Both channels are subject to random delays. To evaluate the timeliness of the status information at the receiver, we use the Age of Information (AoI) metric. The objective is to design a sampling policy that minimizes the expected time-average AoI, even when the channel statistics (e.g., delay distributions) are unknown. We first review the threshold structure of the optimal offline policy under known channel statistics and then reformulate the design of the online algorithm as a stochastic approximation problem. We propose a Robbins-Monro algorithm to solve this problem and demonstrate that the optimal threshold can be approximated almost surely. Moreover, we prove that the cumulative AoI regret of the online algorithm increases with rate $mathcal{O}(ln K)$, where $K$ is the number of successful transmissions. In addition, our algorithm is shown to be minimax order optimal, in the sense that for any online learning algorithm, the cumulative AoI regret up to the $K$-th successful transmissions grows with the rate at least $Omega(ln K)$ in the worst case delay distribution. Finally, we improve the stability of the proposed online learning algorithm through a momentum-based stochastic gradient descent algorithm. Simulation results validate the performance of our proposed algorithm. Source arXiv: 2412.18119v1
Age Optimal Sampling for Unreliable Channels under Unknown Channel Statistics Authors Hongyi He, Haoyue Tang, Jiayu Pan, Jintao Wang, Jian Song, Leandros Tassiulas Published: 12.24.2024 Updated: 02.24.2025 Summary In this paper, we study a system in which a sensor forwards status updates to a receiver through an error-prone channel, while the receiver sends the transmission results back to the sensor via a reliable channel. Both channels are subject to random delays. To evaluate the timeliness of the status information at the receiver, we use the Age of Information (AoI) metric. The objective is to design a sampling policy that minimizes the expected time-average AoI, even when the channel statistics (e.g., delay distributions) are unknown. We first review the threshold structure of the optimal offline policy under known channel statistics and then reformulate the design of the online algorithm as a stochastic approximation problem. We propose a Robbins-Monro algorithm to solve this problem and demonstrate that the optimal threshold can be approximated almost surely. Moreover, we prove that the cumulative AoI regret of the online algorithm increases with rate $mathcal{O}(ln K)$, where $K$ is the number of successful transmissions. In addition, our algorithm is shown to be minimax order optimal, in the sense that for any online learning algorithm, the cumulative AoI regret up to the $K$-th successful transmissions grows with the rate at least $Omega(ln K)$ in the worst case delay distribution. Finally, we improve the stability of the proposed online learning algorithm through a momentum-based stochastic gradient descent algorithm. Simulation results validate the performance of our proposed algorithm. Source arXiv: 2412.18119v2
Correlated Noise Estimation with Quantum Sensor Networks Authors Anthony J. Brady, Yu-Xin Wang, Victor V. Albert, Alexey V. Gorshkov, Quntao Zhuang Published: 12.23.2024 Updated: 12.23.2024 Summary In this article, we address the metrological problem of estimating collective stochastic properties of a many-body quantum system. Canonical examples include center-of-mass quadrature fluctuations in a system of bosonic modes and correlated dephasing in an ensemble of qubits (e.g., spins) or fermions. We develop a theoretical framework to determine the limits of correlated (weak) noise estimation with quantum sensor networks and unveil the requirements for entanglement advantage. Notably, an advantage emerges from the synergistic interplay between quantum correlations of the sensors and classical (spatial) correlations of the noises. We determine optimal entangled probe states and identify a sensing protocol, reminiscent of a many-body echo sequence, that achieves the fundamental limits of measurement sensitivity for a broad class of problems. Source arXiv: 2412.17903v1
On-Demand Magnon Resonance Isolation in Cavity Magnonics Authors Amin Pishehvar, Zhaoyou Wang, Yujie Zhu, Yu Jiang, Zixin Yan, Fangxin Li, Josep M. Jornet, Jia-Mian Hu, Liang Jiang, Xufeng Zhang Published: 12.20.2024 Updated: 12.20.2024 Summary Cavity magnonics is a promising field focusing the interaction between spin waves (magnons) and other types of signals. In cavity magnonics, the function of isolating magnons from the cavity to allow signal storage and processing fully in the magnonic domain is highly desired, but its realization is often hindered by the lack of necessary tunability on the interaction. This work shows that by utilizing the collective mode of two YIG spheres and adopting Floquet engineering, magnonic signals can be switched on-demand to a magnon dark mode that is protected from the environment, enabling a variety of manipulation over the magnon dynamics. Our demonstration can be scaled up to systems with an array of magnonic resonators, paving the way for large-scale programmable hybrid magnonic circuits. Source arXiv: 2412.15600v1
Space-time Peer-to-Peer Distribution of Multi-party Entanglement for Any Quantum Network Authors Yuexun Huang, Xiangyu Ren, Bikun Li, Yat Wong, Zhiding Liang, Liang Jiang Published: 12.19.2024 Updated: 04.05.2025 Summary Graph states are a class of important multiparty entangled states, of which bell pairs are the special case. Realizing a robust and fast distribution of arbitrary graph states in the downstream layer of the quantum network can be essential for further large-scale quantum networks. We propose a novel quantum network protocol called P2PGSD inspired by the classical Peer-to-Peer (P2P) network to efficiently implement the general graph state distribution in the network layer, which demonstrates advantages in resource efficiency and scalability over existing methods for sparse graph states. An explicit mathematical model for a general graph state distribution problem has also been constructed, above which the intractability for a wide class of resource minimization problems is proved and the optimality of the existing algorithms is discussed. In addition, we leverage the spacetime quantum network inspired by the symmetry from relativity for memory management in network problems and used it to improve our proposed algorithm. The advantages of our protocols are confirmed by numerical simulations showing an improvement of up to 50% for general sparse graph states, paving the way for a resource-efficient multiparty entanglement distribution across any network topology. Source arXiv: 2412.14757v3
Space-time Peer-to-Peer Distribution of Multi-party Entanglement for Any Quantum Network Authors Yuexun Huang, Xiangyu Ren, Bikun Li, Yat Wong, Liang Jiang Published: 12.19.2024 Updated: 12.24.2024 Summary Graph states are a class of important multiparty entangled states, of which bell pairs are the special case. Realizing a robust and fast distribution of arbitrary graph states in the downstream layer of the quantum network can be essential for further large-scale quantum networks. We propose a novel quantum network protocol called P2PGSD inspired by the classical Peer-to-Peer (P2P) network to efficiently implement the general graph state distribution in the network layer, which demonstrates advantages in resource efficiency and scalability over existing methods for sparse graph states. An explicit mathematical model for a general graph state distribution problem has also been constructed, above which the intractability for a wide class of resource minimization problems is proved and the optimality of the existing algorithms is discussed. In addition, we leverage the spacetime quantum network inspired by the symmetry from relativity for memory management in network problems and used it to improve our proposed algorithm. The advantages of our protocols are confirmed by numerical simulations showing an improvement of up to 50% for general sparse graph states, paving the way for a resource-efficient multiparty entanglement distribution across any network topology. Source arXiv: 2412.14757v2
Space-time Peer-to-Peer Distribution of Multi-party Entanglement for Any Quantum Network Authors Yuexun Huang, Xiangyu Ren, Bikun Li, Yat Wong, Liang Jiang Published: 12.19.2024 Updated: 12.19.2024 Summary Graph states are a class of important multiparty entangled states, of which bell pairs are the special case. Realizing a robust and fast distribution of arbitrary graph states in the downstream layer of the quantum network can be essential for further large-scale quantum networks. We propose a novel quantum network protocol called P2PGSD inspired by the classical Peer-to-Peer (P2P) network to efficiently implement the general graph state distribution in the network layer, which demonstrates advantages in resource efficiency and scalability over existing methods for sparse graph states. An explicit mathematical model for a general graph state distribution problem has also been constructed, above which the intractability for a wide class of resource minimization problems is proved and the optimality of the existing algorithms is discussed. In addition, we proposed the spacetime network inspired by the symmetry from relativity for memory management in network problems and used it to improve our proposed algorithm. The advantages of our protocols are confirmed by numerical simulations showing an improvement of up to 50% for general sparse graph states, paving the way for a resource-efficient multiparty entanglement distribution across any network topology. Source arXiv: 2412.14757v1
WaveguideQED.jl: An Efficient Framework for Simulating Non-Markovian Waveguide Quantum Electrodynamics Authors Matias Bundgaard-Nielsen, Dirk Englund, Mikkel Heuck, Stefan Krastanov Published: 12.17.2024 Updated: 04.11.2025 Summary In this paper, we introduce a numerical framework designed to solve problems within the emerging field of Waveguide Quantum Electrodynamics (WQED). The framework is based on collision quantum optics, where a localized quantum system interacts sequentially with individual time-bin modes. This approach provides a physically intuitive model that allows researchers familiar with tools such as QuTiP in Python, Quantum Optics Toolbox for Matlab, or QuantumOptics.jl in Julia to efficiently set up and execute WQED simulations. Despite its conceptual simplicity, we demonstrate the framework’s robust ability to handle complex WQED scenarios. These applications include the scattering of single- or two-photon pulses by quantum emitters or cavities, as well as the exploration of non-Markovian dynamics, where emitted photons are reflected back, thereby introducing feedback mechanisms. Source arXiv: 2412.13332v2
WaveguideQED.jl: An Efficient Framework for Simulating Non-Markovian Waveguide Quantum Electrodynamics Authors Matias Bundgaard-Nielsen, Dirk Englund, Mikkel Heuck, Stefan Krastanov Published: 12.17.2024 Updated: 12.17.2024 Summary In this paper, we introduce a numerical framework designed to solve problems within the emerging field of Waveguide Quantum Electrodynamics (WQED). The framework is based on collision quantum optics, where a localized quantum system interacts sequentially with individual time-bin modes. This approach provides a physically intuitive model that allows researchers familiar with tools such as QuTiP in Python, Quantum Optics Toolbox for Matlab, or QuantumOptics.jl in Julia to efficiently set up and execute WQED simulations. Despite its conceptual simplicity, we demonstrate the framework’s robust ability to handle complex WQED scenarios. These applications include the scattering of single- or two-photon pulses by quantum emitters or cavities, as well as the exploration of non-Markovian dynamics, where emitted photons are reflected back, thereby introducing feedback mechanisms. Source arXiv: 2412.13332v1
Symmetry-mediated quantum coherence of $W^{5+}$ spins in an oxygen-deficient double perovskite Authors Shannon Bernier, Danna E. Freedman, Tyrel M. McQueen, Paul Oyala, Tyler J. Pearson, W. Adam Phelan, Maxime A. Siegler, Mekhola Sinha, Peter V. Sushko Published: 12.17.2024 Updated: 12.17.2024 Summary Elucidating the factors limiting quantum coherence in real materials is essential to the development of quantum technologies. Here we report a strategic approach to determine the effect of lattice dynamics on spin coherence lifetimes using oxygen deficient double perovskites as host materials. In addition to obtaining millisecond $T_1$ spin-lattice lifetimes at T ~ 10 K, measurable quantum superpositions were observed up to room temperature. We determine that $T_2$ enhancement in $Sr_2CaWO_{6-delta}$ over previously studied $Ba_2CaWO_{6-delta}$ is caused by a dynamically-driven increase in effective site symmetry around the dominant paramagnetic site, assigned as $W^{5+}$ via electron paramagnetic resonance spectroscopy. Further, a combination of experimental and computational techniques enabled quantification of the relative strength of spin-phonon coupling of each phonon mode. This analysis demonstrates the effect of thermodynamics and site symmetry on the spin lifetimes of $W^{5+}$ paramagnetic defects, an important step in the process of reducing decoherence to produce longer-lived qubits. Source arXiv: 2412.13278v1
Symmetry-mediated quantum coherence of $W^{5+}$ spins in an oxygen-deficient double perovskite Authors Shannon Bernier, Mekhola Sinha, Tyler J. Pearson, Peter V. Sushko, Paul H. Oyala, Maxime A. Siegler, W. Adam Phelan, Abby N. Neill, Danna E. Freedman, Tyrel M. McQueen Published: 12.17.2024 Updated: 02.13.2025 Summary Elucidating the factors limiting quantum coherence in real materials is essential to the development of quantum technologies. Here we report a strategic approach to determine the effect of lattice dynamics on spin coherence lifetimes using oxygen deficient double perovskites as host materials. In addition to obtaining millisecond $T_1$ spin-lattice lifetimes at T ~ 10 K, measurable quantum superpositions were observed up to room temperature. We determine that $T_2$ enhancement in $Sr_2CaWO_{6-delta}$ over previously studied $Ba_2CaWO_{6-delta}$ is caused by a dynamically-driven increase in effective site symmetry around the dominant paramagnetic site, assigned as $W^{5+}$ via electron paramagnetic resonance spectroscopy. Further, a combination of experimental and computational techniques enabled quantification of the relative strength of spin-phonon coupling of each phonon mode. This analysis demonstrates the effect of thermodynamics and site symmetry on the spin lifetimes of $W^{5+}$ paramagnetic defects, an important step in the process of reducing decoherence to produce longer-lived qubits. Source arXiv: 2412.13278v2
Analysis and Suppression of Errors in Quantum Random Access Memory under Extended Noise Models Authors Rohan Mehta, Gideon Lee, Liang Jiang Published: 12.13.2024 Updated: 12.17.2024 Summary Quantum random access memory (QRAM) is required for numerous quantum algorithms and network architectures. Previous work has shown that the ubiquitous bucket-brigade QRAM is highly resilient to arbitrary local incoherent noise channels occurring during the operation of the QRAM [PRX Quantum 2, 020311 (2021)], with query infidelities growing only polylogarithmically with memory width when errors are assumed to only occur on individual routers. We extend this result to a large class of generalized settings that arise in realistic situations, including arbitrary initialization errors, spatially correlated errors, as well as coherent errors, maintaining the polylogarithmic scaling in all instances. Fully quantifying the extent to which QRAM’s noise resilience holds may provide a guide for the design of QRAM architectures – for instance, the resilience to initialization errors indicates that a reset protocol between successive queries may not be necessary. In the case of coherent errors, we find an up-to-quadratic increase in the infidelity bound, and therefore discuss generalizations to randomized compiling schemes, which usually are rendered inapplicable in the QRAM setting, to tailor these errors into more favorable stochastic noise. Source arXiv: 2412.10318v2
Analysis and suppression of errors in quantum random access memory errors under extended noise models Authors Rohan Mehta, Gideon Lee, Liang Jiang Published: 12.13.2024 Updated: 12.13.2024 Summary Quantum random access memory (QRAM) is required for numerous quantum algorithms and network architectures. Previous work has shown that the ubiquitous bucket-brigade QRAM is highly resilient to arbitrary local incoherent noise channels occurring during the operation of the QRAM [PRX Quantum 2, 020311 (2021)], with query infidelities growing only polylogarithmically with memory width when errors are assumed to only occur on individual routers. We extend this result to a large class of generalized settings that turn up in realistic situations, including arbitrary initialization errors, spatially correlated errors, as well as coherent errors, maintaining the polylogarithmic scaling in all instances. Fully quantifying the extent to which QRAM’s noise resilience holds may provide a guide for the design of QRAM architectures – for instance, the resilience to initialization errors indicates that a reset protocol between successive queries may not be necessary. In the case of coherent errors, we find an up to quadratic increase in the infidelity bound, and therefore discuss generalizations to randomized compiling schemes, which usually are rendered inapplicable in the QRAM setting, to tailor these errors into more favorable stochastic noise. Source arXiv: 2412.10318v1
Performance and achievable rates of the Gottesman-Kitaev-Preskill code for pure-loss and amplification channels Authors Guo Zheng, Wenhao He, Gideon Lee, Kyungjoo Noh, Liang Jiang Published: 12.09.2024 Updated: 12.09.2024 Summary Quantum error correction codes protect information from realistic noisy channels and lie at the heart of quantum computation and communication tasks. Understanding the optimal performance and other information-theoretic properties, such as the achievable rates, of a given code is crucial, as these factors determine the fundamental limits imposed by the encoding in conjunction with the noise channel. Here, we use the transpose channel to analytically obtain the near-optimal performance of any Gottesman-Kitaev-Preskill (GKP) code under pure loss and pure amplification. We present rigorous connections between GKP code’s near-optimal performance and its dual lattice geometry and average input energy. With no energy constraint, we show that when $vertfrac{tau}{1 – tau}vert$ is an integer, specific families of GKP codes simultaneously achieve the loss and amplification capacity. $tau$ is the transmissivity (gain) for loss (amplification). Our results establish GKP code as the first structured bosonic code family that achieves the capacity of loss and amplification. Source arXiv: 2412.06715v1
Bayesian quantum estimation of the separation of two incoherent point sources Authors Boyu Zhou, Saikat Guha, Christos N. Gagatsos Published: 12.06.2024 Updated: 12.06.2024 Summary We address the estimation problem of the separation of two arbitrarily close incoherent point sources from the quantum Bayesian point of view, i.e., when a prior probability distribution function (PDF) on the separation is available. For the non-dispalced and displaced half-Gaussian prior PDF, we compare the performance of SPADE and direct imaging (DI) with the Bayesian minimum mean square error and by varying the prior PDF’s parameters we discuss the regimes of superiority of either SPADE or DI. Source arXiv: 2412.05245v1
Universal distributed blind quantum computing with solid-state qubits Authors Yan-Cheng Wei, Pieter-Jan Stas, Aziza Suleymanzade, Gefen Baranes, Francisco Machado, Yan Qi Huan, Can M. Knaut, Weiyi Sophie Ding, Moritz Merz, Erik N Knall, Umut Yazlar, Maxim Sirotin, Iria W. Wang, Bart Machielse, Susanne F. Yelin, Johannes Borregaard, Hongkun Park, Marko Loncar, Mikhail D. lukin Published: 12.04.2024 Updated: 12.04.2024 Summary Blind quantum computing (BQC) is a promising application of distributed quantum systems, where a client can perform computations on a remote server without revealing any details of the applied circuit. While the most promising realizations of quantum computers are based on various matter qubit platforms, implementing BQC on matter qubits remains an outstanding challenge. Using silicon-vacancy (SiV) centers in nanophotonic diamond cavities with an efficient optical interface, we experimentally demonstrate a universal quantum gate set consisting of single- and two-qubit blind gates over a distributed two-node network. Using these ingredients, we perform a distributed algorithm with blind operations across our two-node network, paving the way towards blind quantum computation with matter qubits in distributed, modular architectures. Source arXiv: 2412.03020v1
Universal distributed blind quantum computing with solid-state qubits Authors Yan-Cheng Wei, Pieter-Jan Stas, Aziza Suleymanzade, Gefen Baranes, Francisco Machado, Yan Qi Huan, Can M. Knaut, Weiyi Sophie Ding, Moritz Merz, Erik N Knall, Umut Yazlar, Maxim Sirotin, Iria W. Wang, Bart Machielse, Susanne F. Yelin, Johannes Borregaard, Hongkun Park, Marko Loncar, Mikhail D. Lukin Published: 12.04.2024 Updated: 12.09.2024 Summary Blind quantum computing (BQC) is a promising application of distributed quantum systems, where a client can perform computations on a remote server without revealing any details of the applied circuit. While the most promising realizations of quantum computers are based on various matter qubit platforms, implementing BQC on matter qubits remains an outstanding challenge. Using silicon-vacancy (SiV) centers in nanophotonic diamond cavities with an efficient optical interface, we experimentally demonstrate a universal quantum gate set consisting of single- and two-qubit blind gates over a distributed two-node network. Using these ingredients, we perform a distributed algorithm with blind operations across our two-node network, paving the way towards blind quantum computation with matter qubits in distributed, modular architectures. Source arXiv: 2412.03020v2
Loss tolerant cross-Kerr enhancement via modulated squeezing Authors Ankit Tiwari, Daniel Burgarth, Linran Fan, Saikat Guha, Christian Arenz Published: 12.03.2024 Updated: 12.03.2024 Summary We develop squeezing protocols to enhance cross-Kerr interactions. We show that through alternating between squeezing along different quadratures of a single photonic mode, the cross-Kerr interaction strength can be generically amplified. As an application of the squeezing protocols we discuss speeding up the deterministic implementation of controlled phase gates in photonic quantum computing architectures. We develop bounds that characterize how fast and strong single-mode squeezing has to be applied to achieve a desired gate error and show that the protocols can overcome photon losses. Finally, we discuss experimental realizations of the squeezing strategies in optical fibers and nanophotonic waveguides. Source arXiv: 2412.02909v1
Mixed-State Quantum Denoising Diffusion Probabilistic Model Authors Gino Kwun, Bingzhi Zhang, Quntao Zhuang Published: 11.26.2024 Updated: 11.26.2024 Summary Generative quantum machine learning has gained significant attention for its ability to produce quantum states with desired distributions. Among various quantum generative models, quantum denoising diffusion probabilistic models (QuDDPMs) [Phys. Rev. Lett. 132, 100602 (2024)] provide a promising approach with stepwise learning that resolves the training issues. However, the requirement of high-fidelity scrambling unitaries in QuDDPM poses a challenge in near-term implementation. We propose the textit{mixed-state quantum denoising diffusion probabilistic model} (MSQuDDPM) to eliminate the need for scrambling unitaries. Our approach focuses on adapting the quantum noise channels to the model architecture, which integrates depolarizing noise channels in the forward diffusion process and parameterized quantum circuits with projective measurements in the backward denoising steps. We also introduce several techniques to improve MSQuDDPM, including a cosine-exponent schedule of noise interpolation, the use of single-qubit random ancilla, and superfidelity-based cost functions to enhance the convergence. We evaluate MSQuDDPM on quantum ensemble generation tasks, demonstrating its successful performance. Source arXiv: 2411.17608v1
Mixed-State Quantum Denoising Diffusion Probabilistic Model Authors Gino Kwun, Bingzhi Zhang, Quntao Zhuang Published: 11.26.2024 Updated: 03.04.2025 Summary Generative quantum machine learning has gained significant attention for its ability to produce quantum states with desired distributions. Among various quantum generative models, quantum denoising diffusion probabilistic models (QuDDPMs) [Phys. Rev. Lett. 132, 100602 (2024)] provide a promising approach with stepwise learning that resolves the training issues. However, the requirement of high-fidelity scrambling unitaries in QuDDPM poses a challenge in near-term implementation. We propose the textit{mixed-state quantum denoising diffusion probabilistic model} (MSQuDDPM) to eliminate the need for scrambling unitaries. Our approach focuses on adapting the quantum noise channels to the model architecture, which integrates depolarizing noise channels in the forward diffusion process and parameterized quantum circuits with projective measurements in the backward denoising steps. We also introduce several techniques to improve MSQuDDPM, including a cosine-exponent schedule of noise interpolation, the use of single-qubit random ancilla, and superfidelity-based cost functions to enhance the convergence. We evaluate MSQuDDPM on quantum ensemble generation tasks, demonstrating its successful performance. Source arXiv: 2411.17608v2
Optimized four-qubit quantum error correcting code for amplitude damping channel Authors Xuanhui Mao, Qian Xu, Liang Jiang Published: 11.20.2024 Updated: 11.20.2024 Summary Quantum error correction (QEC) is essential for reliable quantum information processing. Targeting a particular error channel, both the encoding and the recovery channel can be optimized through a biconvex optimization to give a high-performance, noise-adapted QEC scheme. We solve the biconvex optimization by the technique of alternating semi-definite programming and identify a new four-qubit code for amplitude damping channel, one major noise in superconducting circuits and a good model for spontaneous emission and energy dissipation. We also construct analytical encoding and recovery channels that are close to the numerically optimized ones. We show that the new code notably outperforms the Leung-Nielsen-Chuang-Yamamoto four-qubit code in terms of the entanglement fidelity over an amplitude damping channel. Source arXiv: 2411.12952v1
SANDWICH: Towards an Offline, Differentiable, Fully-Trainable Wireless Neural Ray-Tracing Surrogate Authors Yifei Jin, Ali Maatouk, Sarunas Girdzijauskas, Shugong Xu, Leandros Tassiulas, Rex Ying Published: 11.13.2024 Updated: 11.13.2024 Summary Wireless ray-tracing (RT) is emerging as a key tool for three-dimensional (3D) wireless channel modeling, driven by advances in graphical rendering. Current approaches struggle to accurately model beyond 5G (B5G) network signaling, which often operates at higher frequencies and is more susceptible to environmental conditions and changes. Existing online learning solutions require real-time environmental supervision during training, which is both costly and incompatible with GPU-based processing. In response, we propose a novel approach that redefines ray trajectory generation as a sequential decision-making problem, leveraging generative models to jointly learn the optical, physical, and signal properties within each designated environment. Our work introduces the Scene-Aware Neural Decision Wireless Channel Raytracing Hierarchy (SANDWICH), an innovative offline, fully differentiable approach that can be trained entirely on GPUs. SANDWICH offers superior performance compared to existing online learning methods, outperforms the baseline by 4e^-2 radian in RT accuracy, and only fades 0.5 dB away from toplined channel gain estimation. Source arXiv: 2411.08767v1
SANDWICH: Towards an Offline, Differentiable, Fully-Trainable Wireless Neural Ray-Tracing Surrogate Authors Yifei Jin, Ali Maatouk, Sarunas Girdzijauskas, Shugong Xu, Leandros Tassiulas, Rex Ying Published: 11.13.2024 Updated: 02.20.2025 Summary Wireless ray-tracing (RT) is emerging as a key tool for three-dimensional (3D) wireless channel modeling, driven by advances in graphical rendering. Current approaches struggle to accurately model beyond 5G (B5G) network signaling, which often operates at higher frequencies and is more susceptible to environmental conditions and changes. Existing online learning solutions require real-time environmental supervision during training, which is both costly and incompatible with GPU-based processing. In response, we propose a novel approach that redefines ray trajectory generation as a sequential decision-making problem, leveraging generative models to jointly learn the optical, physical, and signal properties within each designated environment. Our work introduces the Scene-Aware Neural Decision Wireless Channel Raytracing Hierarchy (SANDWICH), an innovative offline, fully differentiable approach that can be trained entirely on GPUs. SANDWICH offers superior performance compared to existing online learning methods, outperforms the baseline by 4e^-2 radian in RT accuracy, and only fades 0.5 dB away from toplined channel gain estimation. Source arXiv: 2411.08767v2
Multiplexed bi-layered realization of fault-tolerant quantum computation over optically networked trapped-ion modules Authors Nitish K. Chandra, Saikat Guha, Kaushik P. Seshadreesan Published: 11.13.2024 Updated: 11.13.2024 Summary We study an architecture for fault-tolerant measurement-based quantum computation (FT-MBQC) over optically-networked trapped-ion modules. The architecture is implemented with a finite number of modules and ions per module, and leverages photonic interactions for generating remote entanglement between modules and local Coulomb interactions for intra-modular entangling gates. We focus on generating the topologically protected Raussendorf-Harrington-Goyal (RHG) lattice cluster state, which is known to be robust against lattice bond failures and qubit noise, with the modules acting as lattice sites. To ensure that the remote entanglement generation rates surpass the bond-failure tolerance threshold of the RHG lattice, we employ spatial and temporal multiplexing. For realistic system timing parameters, we estimate the code cycle time of the RHG lattice and the ion resources required in a bi-layered implementation, where the number of modules matches the number of sites in two lattice layers, and qubits are reinitialized after measurement. For large distances between modules, we incorporate quantum repeaters between sites and analyze the benefits in terms of cumulative resource requirements. Finally, we derive and analyze a qubit noise-tolerance threshold inequality for the RHG lattice generation in the proposed architecture that accounts for noise from various sources. This includes the depolarizing noise arising from the photonically-mediated remote entanglement generation between modules due to finite optical detection efficiency, limited visibility, and the presence of dark clicks, in addition to the noise from imperfect gates and measurements, and memory decoherence with time. Our work thus underscores the hardware and channel threshold requirements to realize distributed FT-MBQC in a leading qubit platform today — trapped ions. Source arXiv: 2411.08616v1
Quantum limited imaging of a nanomechanical resonator with a spatial mode sorter Authors Morgan Choi, Christian Pluchar, Wenhua He, Saikat Guha, Dalziel Wilson Published: 11.07.2024 Updated: 11.07.2024 Summary We explore the use of a spatial mode sorter to image a nanomechanical resonator, with the goal of studying the quantum limits of active imaging and extending the toolbox for optomechanical force sensing. In our experiment, we reflect a Gaussian laser beam from a vibrating nanoribbon and pass the reflected beam through a commercial spatial mode demultiplexer (Cailabs Proteus). The intensity in each demultiplexed channel depends on the mechanical mode shapes and encodes information about their displacement amplitudes. As a concrete demonstration, we monitor the angular displacement of the ribbon’s fundamental torsion mode by illuminating in the fundamental Hermite-Gauss mode (HG$_{00}$) and reading out in the HG$_{01}$ mode. We show that this technique permits readout of the ribbon’s torsional vibration with a precision near the quantum limit. Our results highlight new opportunities at the interface of quantum imaging and quantum optomechanics. Source arXiv: 2411.04980v1
Integrated electro-optic digital-to-analog link for efficient computing and arbitrary waveform generation Authors Yunxiang Song, Yaowen Hu, Xinrui Zhu, Keith Powell, Letícia Magalhães, Fan Ye, Hana Warner, Shengyuan Lu, Xudong Li, Dylan Renaud, Norman Lippok, Di Zhu, Benjamin Vakoc, Mian Zhang, Neil Sinclair, Marko Lončar Published: 11.07.2024 Updated: 11.07.2024 Summary The rapid growth in artificial intelligence and modern communication systems demands innovative solutions for increased computational power and advanced signaling capabilities. Integrated photonics, leveraging the analog nature of electromagnetic waves at the chip scale, offers a promising complement to approaches based on digital electronics. To fully unlock their potential as analog processors, establishing a common technological base between conventional digital electronic systems and analog photonics is imperative to building next-generation computing and communications hardware. However, the absence of an efficient interface has critically challenged comprehensive demonstrations of analog advantage thus far, with the scalability, speed, and energy consumption as primary bottlenecks. Here, we address this challenge and demonstrate a general electro-optic digital-to-analog link (EO-DiAL) enabled by foundry-based lithium niobate nanophotonics. Using purely digital inputs, we achieve on-demand generation of (i) optical and (ii) electronic waveforms at information rates up to 186 Gbit/s. The former addresses the digital-to-analog electro-optic conversion challenge in photonic computing, showcasing high-fidelity MNIST encoding while consuming 0.058 pJ/bit. The latter enables a pulse-shaping-free microwave arbitrary waveform generation method with ultrabroadband tunable delay and gain. Our results pave the way for efficient and compact digital-to-analog conversion paradigms enabled by integrated photonics and underscore the transformative impact analog photonic hardware may have on various applications, such as computing, optical interconnects, and high-speed ranging. Source arXiv: 2411.04395v1
Holographic deep thermalization Authors Bingzhi Zhang, Peng Xu, Xiaohui Chen, Quntao Zhuang Published: 11.06.2024 Updated: 11.06.2024 Summary Random quantum states play a critical role in quantum information processing. While random quantum circuits typically provide pseudo-random states, deep thermalization introduces quantum measurement to generate genuinely random states. However, the requirement of large ancillae in conventional deep thermalization poses a challenge to scale up the system size. We introduce holographic deep thermalization to substantially reduce the required ancillae to a system-size independent constant. Our circuit design trades space with time, via adopting a sequential application of an scrambling-measure-reset process on a small number of ancillae. Via tuning the ancilla size and number of time steps, holographic deep thermalization allows a continuous trade-off between the total quantum circuit size and the ancilla size. In the case of finite-size systems, we further enhance the performance of holographic deep thermalization via generative quantum machine learning, which leads to constant-factor advantages in the convergence towards Haar random. The theoretical predictions are verified with IBM Quantum noisy simulations. Source arXiv: 2411.03587v1
Holographic deep thermalization: theory and experimentation Authors Bingzhi Zhang, Peng Xu, Xiaohui Chen, Quntao Zhuang Published: 11.06.2024 Updated: 01.16.2025 Summary Randomness is a cornerstone of science, underpinning fields such as statistics, information theory, dynamical systems, and thermodynamics. In quantum science, quantum randomness, especially random pure states, plays a pivotal role in fundamental questions like black hole physics and quantum complexity, as well as in practical applications such as quantum device benchmarking and quantum advantage certification. The conventional approach for generating genuine random states, called `deep thermalization’, faces significant challenges, including scalability issues due to the need for a large ancilla system and susceptibility to attacks, as demonstrated in this work. We introduce holographic deep thermalization, a secure and hardware-efficient quantum random state generator. By adopting a sequential application of a scrambling-measure-reset process, it continuously trades space with time, and substantially reduces the required ancilla size to as small as a system-size independent constant; At the same time, it guarantees security by removing quantum correlation between the data system and attackers. Thanks to the resource reduction, our circuit-based implementation on IBM Quantum devices achieves genuine $5$-qubit random state generation utilizing only a total of $8$ qubits. Source arXiv: 2411.03587v2
Integrated lithium niobate photonic computing circuit based on efficient and high-speed electro-optic conversion Authors Yaowen Hu, Yunxiang Song, Xinrui Zhu, Xiangwen Guo, Shengyuan Lu, Qihang Zhang, Lingyan He, C. A. A. Franken, Keith Powell, Hana Warner, Daniel Assumpcao, Dylan Renaud, Ying Wang, Letícia Magalhães, Victoria Rosborough, Amirhassan Shams-Ansari, Xudong Li, Rebecca Cheng, Kevin Luke, Kiyoul Yang, George Barbastathis, Mian Zhang, Di Zhu, Leif Johansson, Andreas Beling, Neil Sinclair, Marko Loncar Published: 11.05.2024 Updated: 11.05.2024 Summary Here we show a photonic computing accelerator utilizing a system-level thin-film lithium niobate circuit which overcomes this limitation. Leveraging the strong electro-optic (Pockels) effect and the scalability of this platform, we demonstrate photonic computation at speeds up to 1.36 TOPS while consuming 0.057 pJ/OP. Our system features more than 100 thin-film lithium niobate high-performance components working synergistically, surpassing state-of-the-art systems on this platform. We further demonstrate binary-classification, handwritten-digit classification, and image classification with remarkable accuracy, showcasing our system’s capability of executing real algorithms. Finally, we investigate the opportunities offered by combining our system with a hybrid-integrated distributed feedback laser source and a heterogeneous-integrated modified uni-traveling carrier photodiode. Our results illustrate the promise of thin-film lithium niobate as a computational platform, addressing current bottlenecks in both electronic and photonic computation. Its unique properties of high-performance electro-optic weight encoding and conversion, wafer-scale scalability, and compatibility with integrated lasers and detectors, position thin-film lithium niobate photonics as a valuable complement to silicon photonics, with extensions to applications in ultrafast and power-efficient signal processing and ranging. Source arXiv: 2411.02734v1
Genuine non-Gaussian entanglement: quantum correlations beyond Hong-Ou-Mandel Authors Xiaobin Zhao, Pengcheng Liao, Quntao Zhuang Published: 11.03.2024 Updated: 11.03.2024 Summary Hong-Ou-Mandel effect is an important demonstration of particle indistinguishability, when identical single photons interfere at a beamsplitter to generate the two-photon entangled NOON state. On the other hand, NOON states with $Nge3$ photons have long been conjectured beyond the deterministic generation of photon interference. To characterize the separation, we introduce the notion of genuine non-Gaussian entanglement (NGE), which cannot be generated via a generalized Hong-Ou-Mandel experiment, with Gaussian protocols extending the beamsplitter and separable input states replacing the single photons. We establish a resource theory to characterize such quantum correlations beyond Hong-Ou-Mandel and prove that NOON states with $Nge 3$ are indeed among the NGE class. With the generalized Hong-Ou-Mandel protocol as free operations, we introduce two monotones to characterize genuine non-Gaussian entanglement: one derived from the entanglement entropy and the other from the minimal extension size required to convert a state into a free state. Finally, we demonstrate that the tomography process of pure free states can be performed efficiently, while all learning protocols of states with genuine non-Gaussian entanglement require exponential overheads connected to the monotone. This implies that states generated in Boson sampling are efficiently learnable despite its measurement statistics being hard to sample from. Source arXiv: 2411.01609v1
Practical hybrid PQC-QKD protocols with enhanced security and performance Authors Pei Zeng, Debayan Bandyopadhyay, José A. Méndez Méndez, Nolan Bitner, Alexander Kolar, Michael T. Solomon, Ziyu Ye, Filip Rozpȩdek, Tian Zhong, F. Joseph Heremans, David D. Awschalom, Liang Jiang, Junyu Liu Published: 11.02.2024 Updated: 11.05.2024 Summary Quantum resistance is vital for emerging cryptographic systems as quantum technologies continue to advance towards large-scale, fault-tolerant quantum computers. Resistance may be offered by quantum key distribution (QKD), which provides information-theoretic security using quantum states of photons, but may be limited by transmission loss at long distances. An alternative approach uses classical means and is conjectured to be resistant to quantum attacks, so-called post-quantum cryptography (PQC), but it is yet to be rigorously proven, and its current implementations are computationally expensive. To overcome the security and performance challenges present in each, here we develop hybrid protocols by which QKD and PQC inter-operate within a joint quantum-classical network. In particular, we consider different hybrid designs that may offer enhanced speed and/or security over the individual performance of either approach. Furthermore, we present a method for analyzing the security of hybrid protocols in key distribution networks. Our hybrid approach paves the way for joint quantum-classical communication networks, which leverage the advantages of both QKD and PQC and can be tailored to the requirements of various practical networks. Source arXiv: 2411.01086v2
Practical hybrid PQC-QKD protocols with enhanced security and performance Authors Pei Zeng, Debayan Bandyopadhyay, José A. Méndez Méndez, Nolan Bitner, Alexander Kolar, Michael T. Solomon, Ziyu Ye, Filip Rozpędek, Tian Zhong, F. Joseph Heremans, David D. Awschalom, Liang Jiang, Junyu Liu Published: 11.02.2024 Updated: 11.07.2024 Summary Quantum resistance is vital for emerging cryptographic systems as quantum technologies continue to advance towards large-scale, fault-tolerant quantum computers. Resistance may be offered by quantum key distribution (QKD), which provides information-theoretic security using quantum states of photons, but may be limited by transmission loss at long distances. An alternative approach uses classical means and is conjectured to be resistant to quantum attacks, so-called post-quantum cryptography (PQC), but it is yet to be rigorously proven, and its current implementations are computationally expensive. To overcome the security and performance challenges present in each, here we develop hybrid protocols by which QKD and PQC inter-operate within a joint quantum-classical network. In particular, we consider different hybrid designs that may offer enhanced speed and/or security over the individual performance of either approach. Furthermore, we present a method for analyzing the security of hybrid protocols in key distribution networks. Our hybrid approach paves the way for joint quantum-classical communication networks, which leverage the advantages of both QKD and PQC and can be tailored to the requirements of various practical networks. Source arXiv: 2411.01086v3
Practical hybrid PQC-QKD protocols with enhanced security and performance Authors Pei Zeng, Debayan Bandyopadhyay, José A. Méndez Méndez, Nolan Bitner, Alexander Kolar, Michael T. Solomon, Filip Rozpedek, Tian Zhong, F. Joseph Heremans, David D. Awschalom, Liang Jiang, Junyu Liu Published: 11.02.2024 Updated: 11.02.2024 Summary Quantum resistance is vital for emerging cryptographic systems as quantum technologies continue to advance towards large-scale, fault-tolerant quantum computers. Resistance may be offered by quantum key distribution (QKD), which provides information-theoretic security using quantum states of photons, but may be limited by transmission loss at long distances. An alternative approach uses classical means and is conjectured to be resistant to quantum attacks, so-called post-quantum cryptography (PQC), but it is yet to be rigorously proven, and its current implementations are computationally expensive. To overcome the security and performance challenges present in each, here we develop hybrid protocols by which QKD and PQC inter-operate within a joint quantum-classical network. In particular, we consider different hybrid designs that may offer enhanced speed and/or security over the individual performance of either approach. Furthermore, we present a method for analyzing the security of hybrid protocols in key distribution networks. Our hybrid approach paves the way for joint quantum-classical communication networks, which leverage the advantages of both QKD and PQC and can be tailored to the requirements of various practical networks. Source arXiv: 2411.01086v1
Towards efficient and secure quantum-classical communication networks Authors Pei Zeng, Debayan Bandyopadhyay, José A. Méndez Méndez, Nolan Bitner, Alexander Kolar, Michael T. Solomon, F. Joseph Heremans, David D. Awschalom, Liang Jiang, Junyu Liu Published: 11.01.2024 Updated: 11.05.2024 Summary The rapid advancement of quantum technologies calls for the design and deployment of quantum-safe cryptographic protocols and communication networks. There are two primary approaches to achieving quantum-resistant security: quantum key distribution (QKD) and post-quantum cryptography (PQC). While each offers unique advantages, both have drawbacks in practical implementation. In this work, we introduce the pros and cons of these protocols and explore how they can be combined to achieve a higher level of security and/or improved performance in key distribution. We hope our discussion inspires further research into the design of hybrid cryptographic protocols for quantum-classical communication networks. Source arXiv: 2411.01081v2
Towards efficient and secure quantum-classical communication networks Authors Pei Zeng, Debayan Bandyopadhyay, Jose A. Mendez, Nolan Bitner, Alexander Kolar, Michael T. Solomon, F. Joseph Heremans, David D. Awschalom, Liang Jiang, Junyu Liu Published: 11.01.2024 Updated: 11.01.2024 Summary The rapid advancement of quantum technologies calls for the design and deployment of quantum-safe cryptographic protocols and communication networks. There are two primary approaches to achieving quantum-resistant security: quantum key distribution (QKD) and post-quantum cryptography (PQC). While each offers unique advantages, both have drawbacks in practical implementation. In this work, we introduce the pros and cons of these protocols and explore how they can be combined to achieve a higher level of security and/or improved performance in key distribution. We hope our discussion inspires further research into the design of hybrid cryptographic protocols for quantum-classical communication networks. Source arXiv: 2411.01081v1
Quantum random access memory with transmon-controlled phonon routing Authors Zhaoyou Wang, Hong Qiao, Andrew N. Cleland, Liang Jiang Published: 11.01.2024 Updated: 11.01.2024 Summary Quantum random access memory (QRAM) promises simultaneous data queries at multiple memory locations, with data retrieved in coherent superpositions, essential for achieving quantum speedup in many quantum algorithms. We introduce a transmon-controlled phonon router and propose a QRAM implementation by connecting these routers in a tree-like architecture. The router controls the motion of itinerant surface acoustic wave phonons based on the state of the control transmon, implementing the core functionality of conditional routing for QRAM. Our QRAM design is compact, supports fast routing operations, and avoids frequency crowding. Additionally, we propose a hybrid dual-rail encoding method to detect dominant loss errors without additional hardware, a versatile approach applicable to other QRAM platforms. Our estimates indicate that the proposed QRAM platform can achieve high heralding rates using current device parameters, with heralding fidelity primarily limited by transmon dephasing. Source arXiv: 2411.00719v1
Optimality Condition for the Petz Map Authors Bikun Li, Zhaoyou Wang, Guo Zheng, Yat Wong, Liang Jiang Published: 10.31.2024 Updated: 03.16.2025 Summary In quantum error correction, the Petz map serves as a perfect recovery map when the Knill-Laflamme conditions are satisfied. Notably, while perfect recovery is generally infeasible for most quantum channels of finite dimension, the Petz map remains a versatile tool with near-optimal performance in recovering quantum states. This work introduces and proves, for the first time, the necessary and sufficient conditions for the optimality of the Petz in terms of entanglement fidelity. In some special cases, the violation of this condition can be easily characterized by a simple commutator that can be efficiently computed. We provide multiple examples that substantiate our new findings. Source arXiv: 2410.23622v3
Optimality Condition for the Transpose Channel Authors Bikun Li, Zhaoyou Wang, Guo Zheng, Liang Jiang Published: 10.31.2024 Updated: 11.04.2024 Summary In quantum error correction, the Petz transpose channel serves as a perfect recovery map when the Knill-Laflamme conditions are satisfied. Notably, while perfect recovery is generally infeasible for most quantum channels of finite dimension, the transpose channel remains a versatile tool with near-optimal performance in recovering quantum states. This work introduces and proves, for the first time, the necessary and sufficient conditions for the strict optimality of the transpose channel in terms of channel fidelity. The violation of this condition can be easily characterized by a simple commutator that can be efficiently computed. We provide multiple examples that substantiate our new findings. Source arXiv: 2410.23622v2
Optimality Condition for the Transpose Channel Authors Bikun Li, Zhaoyou Wang, Guo Zheng, Liang Jiang Published: 10.31.2024 Updated: 10.31.2024 Summary In quantum error correction, the Petz transpose channel serves as a perfect recovery map when the Knill-Laflamme conditions are satisfied. Notably, while perfect recovery is generally infeasible for most quantum channels of finite dimension, the transpose channel remains a versatile tool with near-optimal performance in recovering quantum states. This work introduces and proves, for the first time, the necessary and sufficient conditions for the strict optimality of the transpose channel in terms of channel fidelity. The violation of this condition can be easily characterized by a simple commutator that can be efficiently computed. We provide multiple examples that substantiate our new findings. Source arXiv: 2410.23622v1
Outcomes from a Workshop on a National Center for Quantum Education Authors Edwin Barnes, Michael B. Bennett, Alexandra Boltasseva, Victoria Borish, Bennett Brown, Lincoln D. Carr, Russell R. Ceballos, Faith Dukes, Emily W. Easton, Sophia E. Economou, E. E. Edwards, Noah D. Finkelstein, C. Fracchiolla, Diana Franklin, J. K. Freericks, Valerie Goss, Mark Hannum, Nancy Holincheck, Angela M. Kelly, Olivia Lanes, H. J. Lewandowski, Karen Jo Matsler, Emily Mercurio, Inès Montaño, Maajida Murdock, Kiera Peltz, Justin K. Perron, Christopher J. K. Richardson, Jessica L. Rosenberg, Richard S. Ross, Minjung Ryu, Raymond E. Samuel, Nicole Schrode, Susan Schwamberger, Thomas A. Searles, Chandralekha Singh, Alexandra Tingle, Benjamin M. Zwickl Published: 10.30.2024 Updated: 10.30.2024 Summary In response to numerous programs seeking to advance quantum education and workforce development in the United States, experts from academia, industry, government, and professional societies convened for a National Science Foundation-sponsored workshop in February 2024 to explore the benefits and challenges of establishing a national center for quantum education. Broadly, such a center would foster collaboration and build the infrastructure required to develop a diverse and quantum-ready workforce. The workshop discussions centered around how a center could uniquely address gaps in public, K-12, and undergraduate quantum information science and engineering (QISE) education. Specifically, the community identified activities that, through a center, could lead to an increase in student awareness of quantum careers, boost the number of educators trained in quantum-related subjects, strengthen pathways into quantum careers, enhance the understanding of the U.S. quantum workforce, and elevate public engagement with QISE. Core proposed activities for the center include professional development for educators, coordinated curriculum development and curation, expanded access to educational laboratory equipment, robust evaluation and assessment practices, network building, and enhanced public engagement with quantum science. Source arXiv: 2410.23460v1
Graphene calorimetric single-photon detector Authors Bevin Huang, Ethan G. Arnault, Woochan Jung, Caleb Fried, B. Jordan Russell, Kenji Watanabe, Takashi Taniguchi, Erik A. Henriksen, Dirk Englund, Gil-Ho Lee, Kin Chun Fong Published: 10.29.2024 Updated: 10.29.2024 Summary Single photon detectors (SPDs) are essential technology in quantum science, quantum network, biology, and advanced imaging. To detect the small quantum of energy carried in a photon, conventional SPDs rely on energy excitation across either a semiconductor bandgap or superconducting gap. While the energy gap suppresses the false-positive error, it also sets an energy scale that can limit the detection efficiency of lower energy photons and spectral bandwidth of the SPD. Here, we demonstrate an orthogonal approach to detect single near-infrared photons using graphene calorimeters. By exploiting the extremely low heat capacity of the pseudo-relativistic electrons in graphene near its charge neutrality point, we observe an electron temperature rise up to ~2 K using a hybrid Josephson junction. In this proof-of-principle experiment, we achieve an intrinsic quantum efficiency of 87% (75%) with dark count < 1 per second (per hour) at operation temperatures as high as 1.2 K. Our results highlight the potential of electron calorimetric SPDs for detecting lower-energy photons from the mid-IR to microwave regimes, opening pathways to study space science in far-infrared regime, to search for dark matter axions, and to advance quantum technologies across a broader electromagnetic spectrum. Source arXiv: 2410.22433v1
Low-Dimensional Solid-State Single-Photon Emitters Authors Jinli Chen, Chaohan Cui, Ben Lawrie, Yongzhou Xue, Saikat Guha, Matt Eichenfield, Huan Zhao, Xiaodong Yan Published: 10.29.2024 Updated: 10.29.2024 Summary Solid-state single-photon emitters (SPEs) are attracting significant attention as fundamental components in quantum computing, communication, and sensing. Low-dimensional materials-based SPEs (LD-SPEs) have drawn particular interest due to their high photon extraction efficiency, ease of integration with photonic circuits, and strong coupling with external fields. The accessible surfaces of LD materials allow for deterministic control over quantum light emission, while enhanced quantum confinement and light-matter interactions improve photon emissive properties. This review examines recent progress in LDSPEs across four key materials: zero-dimensional (0D) semiconductor quantum dots, one-dimensional (1D) nanotubes, two-dimensional (2D) materials, including hexagonal boron nitride (hBN) and transition metal dichalcogenides (TMDCs). We explore their structural and photophysical properties, along with techniques such as spectral tuning and cavity coupling that enhance SPE performance. Finally, we address future challenges and suggest strategies for optimizing LD-SPEs for practical quantum applications. Source arXiv: 2410.22106v1
Long Sequence Modeling with Attention Tensorization: From Sequence to Tensor Learning Authors Aosong Feng, Rex Ying, Leandros Tassiulas Published: 10.28.2024 Updated: 10.28.2024 Summary As the demand for processing extended textual data grows, the ability to handle long-range dependencies and maintain computational efficiency is more critical than ever. One of the key issues for long-sequence modeling using attention-based model is the mismatch between the limited-range modeling power of full attention and the long-range token dependency in the input sequence. In this work, we propose to scale up the attention receptive field by tensorizing long input sequences into compact tensor representations followed by attention on each transformed dimension. The resulting Tensorized Attention can be adopted as efficient transformer backbones to extend input context length with improved memory and time efficiency. We show that the proposed attention tensorization encodes token dependencies as a multi-hop attention process, and is equivalent to Kronecker decomposition of full attention. Extensive experiments show that tensorized attention can be used to adapt pretrained LLMs with improved efficiency. Notably, Llama-8B with tensorization is trained under 32,768 context length and can steadily extrapolate to 128k length during inference with $11times$ speedup, compared to full attention with FlashAttention-2. Source arXiv: 2410.20926v1
