Building the Quantum Internet

CQN is developing the entire technology stack to reliably carry quantum data across the globe, serving diverse applications across many user groups simultaneously... spurring new technology industries and a competitive marketplace of quantum service providers and application developers.

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Research Thrusts

Thrust 1

Thrust 1: Quantum Network Architecture

Thrust 2

Thrust 2: Quantum Subsystem Technologies

Thrust 3

Thrust 3: Quantum Materials

Thrust 4

Thrust 4: Societal Impacts of the Quantum Internet

Building the Quantum Internet

News

CQN open house featured in Optics.org article

On Monday, September 30 2024, the 4th floor of the Grand Challenges Research Building at the University of Arizona, hosted an open house. The goal was to create a community around the quantum research happening at the University of Arizona. In attendance was Ford Burkhart who wrote a lovely piece on the event and work […]

Save the Date for 2025 Winter School

We’re pleased to release the dates for our 2025 Winter School on Quantum Networks. Keep an eye out for the registration to open soon! All courses will be held via Zoom, co-taught by CQN faculty, postdocs and students.

World Quantum Day Panel – April 12

Join us for a World Quantum Day panel organized jointly by the Perimeter Institute and Quantum Ethics Project and sponsored by CQN. Our discussion will feature Raymond LaFlamme (Institute for Quantum Computing), Zeki Seskir (Karlsruhe Institute of Technology (KIT)) Jean Olemou (Leap Quantik) Taqi Raza (Center for Quantum Networks) and Joan Arrow (Quantum Ethics Project, Center for Quantum Networks). The panel will discuss how […]

Faculty Profile: Narayanan Rengaswamy

Narayanan Rengaswamy is a an assistant professor in the Electrical and Computer Engineering program at the University of Arizona.He also works at the NSF Engineering Research Center for Quantum Networks (CQN) in the university. He discusses his research focuses on quantum error correction and fault tolerance.

CQN Faculty Tapped to Lead New Journal

Optica Quantum is a new online-only journal dedicated to high-impact results in quantum information science and technology (QIST), as enabled by optics and photonics. Optica Quantum will publish its first issue in September 2023. Its scope will encompass theoretical and experimental research as well as technological advances in and applications of quantum optics. In addition, the Journal will […]

CQN Welcomes New DCI Director

We are pleased to announce the appointment of Julie Des Jardins as the new Director for Diversity and Culture of Inclusion (DCI) within CQN. Dr. Des Jardins is a cultural historian, educator, and DEI practitioner who examines gender, race, and intersectional identity in American culture, particularly in academia, athletics, politics, and STEM. She has also […]

CQN Video Featured at APS 2023

A short video highlighting CQN’s work in building the quantum Internet was featured at the American Physical Society (APS) meeting in Las Vegas in March 2023. The six-minute video features laboratory footage from multiple CQN campuses and interviews with director Saikat Guha, as well as investigators Linran Fan, Dirk Englund, Jane Bambauer, Don Towsley, and […]

CQN Releases Winter School on Quantum Networks Recordings

All nine courses can be found on our YouTube channel in the CQN Winter School for Quantum Networks playlist. Slides associated with the courses can be found here.

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Check out additional stories and events from the Center for Quantum Networks.

Research Feed

arXiv 2411.08767v1

SANDWICH: Towards an Offline, Differentiable, Fully-Trainable Wireless Neural Ray-Tracing Surrogate

  • Yifei Jin
  • Ali Maatouk
  • Sarunas Girdzijauskas
  • Shugong Xu
  • Leandros Tassiulas
  • Rex Ying
  • cs.NI
  • cs.AI

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.

arXiv 2411.08616v1

Multiplexed bi-layered realization of fault-tolerant quantum computation over optically networked trapped-ion modules

  • Nitish K. Chandra
  • Saikat Guha
  • Kaushik P. Seshadreesan
  • quant-ph
  • cs.DC

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.

arXiv 2411.04980v1

Quantum limited imaging of a nanomechanical resonator with a spatial mode sorter

  • Morgan Choi
  • Christian Pluchar
  • Wenhua He
  • Saikat Guha
  • Dalziel Wilson
  • quant-ph
  • cond-mat.mes-hall
  • physics.app-ph
  • physics.optics

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.

arXiv 2411.04395v1

Integrated electro-optic digital-to-analog link for efficient computing and arbitrary waveform generation

  • 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

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.

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