Quantum network protocols
This paper talks about quantum network protocols.
quantum cryptography networks key exchange↗
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Proposal for superconducting quantum networks using multioctave transduction to lower frequencies
We propose networking superconducting quantum circuits by transducing their excitations (typically 4–8 GHz) to 200–500 MHz photons for transmission via superconducting cryogenic coaxial cables. This frequency down-conversion reduces transmission losses and, counterintuitively, reduces noise. We introduce a multioctave asymmetrically threaded superconducting quantum interference device circuit capable of the required efficient, high-rate transduction. For a 100-meter cable with 𝑄 𝑖 = 10 5 at 10 mK, we theoretically show that our approach achieves single-photon fidelities of 0.962 at 200 MHz versus 0.772 at 8 GHz, and triples the lower bound on quantum channel capacity. In conclusion, this method enables highly efficient networking of superconducting qubits while maintaining high fidelities, combining improved performance with the practical advantages of flexible, compact coaxial cables.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Infinite neural network quantum states: entanglement and training dynamics
We study infinite limits of neural network quantum states (∞-NNQS), which exhibit representation power through ensemble statistics, and also tractable gradient descent dynamics. Ensemble averages of entanglement entropies are expressed in terms of neural network correlators, and architectures that exhibit volume-law entanglement are presented. The analytic calculations of entanglement entropy bound are tractable because the ensemble statistics are simplified in the Gaussian process limit. A general framework is developed for studying the gradient descent dynamics of neural network quantum states (NNQS), using a quantum state neural tangent kernel (QS-NTK). For ∞-NNQS the training dynamics is simplified, since the QS-NTK becomes deterministic and constant. An analytic solution is derived for quantum state supervised learning, which allows an ∞-NNQS to recover any target wavefunction. Numerical experiments on finite and infinite NNQS in the transverse field Ising model and Fermi Hubbard model demonstrate excellent agreement with theory. ∞-NNQS opens up new opportunities for studying entanglement and training dynamics in other physics applications, such as in finding ground states.
quantum state supervised learning↗
Quantum Network Repeater Simulation Package (QNPack) v1.0.0
Existing quantum network testbeds and prototypes are typically implemented in laboratory experiments with limited functionality and operate in a tightly coupled manner. These characteristics make it difficult to evaluate the behavior of emerging quantum platforms and protocols beyond local resource limitations. The QNPack software enables full-stack modeling of quantum repeater networks that allows researchers to simulate new approaches, and understand emergent behaviors, from local to national scales. Novel capabilities include: (1) performant and accurate quantum models that can be executed as independent simulations, which will allow users to characterize specific analog quantum processes, quantum devices, and protocols, (2) a modular and extensible approach to the simulation architecture to accommodate new quantum technologies, protocols, and topologies as they are developed across the quantum repeater generations under evaluation, and (3) a focus on managing the interactions between the simulation framework sub-components so that they may be re-used and composed in flexible ways.
Kissel, Ezra [Lawrence Berkeley National Laborator↗
Space-based quantum networking in the presence of a nuclear disturbed environment
Space-based quantum networks provide a means for near-term long-distance transmission of quantum information. Here this article analyzed the performance of a downlink quantum network between a low-Earth-orbit satellite and an observatory operating in less-than-ideal atmospheric conditions. The effects from fog, haze, and a nuclear disturbed environment on the long-range distribution of quantum states were investigated. A density matrix that estimates the quantum state by capturing the effects from increased signal loss and elevated background noise to estimate the state fidelity of the transmitted quantum state was developed. It was found that the nuclear disturbed environment and other atmospheric effects have a degrading effect on the quantum state. These environments impede the ability to perform quantum communications for the duration of the effects. In the case of the nuclear disturbed environment, the nuclear effects subside quickly, and network performance should return to normal by the next satellite pass.
42 ENGINEERING↗
Sample-Efficient Adaptive Calibration of Quantum Networks Using Bayesian Optimization
All physical systems employed for quantum information tasks must act as unbiased carriers of encoded quantum states. Ensuring such indistinguishability of information carriers is a major challenge in many quantum information applications, including advanced quantum communication protocols. For photons, the workhorses of quantum communication networks, it is difficult to obtain and maintain their indistinguishability because of environment-induced transformations and loss imparted by communication channels, especially in noisy scenarios. Conventional strategies to mitigate these transformations often require hardware or software overhead that is restrictive (e.g., adding noise), infeasible (e.g., on a satellite), or time-consuming for deployed networks. In this work we propose and develop resource-efficient Bayesian optimization techniques to rapidly and adaptively calibrate the indistinguishability of individual photons for quantum networks using only information derived from their measurement. To experimentally validate our approach, we demonstrate the optimization of Hong-Ou-Mandel interference between two photons-a central task in quantum networking- finding rapid, efficient, and reliable convergence towards maximal photon indistinguishability in the presence of high loss and shot noise. We expect our resource-optimized and experimentally friendly methodology will allow fast and reliable calibration of indistinguishable quanta, a necessary task in distributed quantum computing, communications, and sensing, as well as for fundamental investigations.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Entanglement Purification and Protection in a Superconducting Quantum Network
High-fidelity quantum entanglement is a key resource for quantum communication and distributed quantum computing, enabling quantum state teleportation, dense coding, and quantum encryption. Any sources of decoherence in the communication channel, however, degrade entanglement fidelity, thereby increasing the error rates of entangled state protocols. Entanglement purification provides a method to alleviate these nonidealities by distilling impure states into higher-fidelity entangled states. In this work, we demonstrate the entanglement purification of Bell pairs shared between two remote superconducting quantum nodes connected by a moderately lossy, 1-meter long superconducting communication cable. We use a purification process to correct the dominant amplitude damping errors caused by transmission through the cable, with fractional increases in fidelity as large as 25%, achieved for higher damping errors. The best final fidelity the purification achieves is 94.09 ± 0.98%. In addition, we use both dynamical decoupling and Rabi driving to protect the entangled states from local noise, increasing the effective qubit dephasing time by a factor of 4, from 3 to 12 μs. These methods demonstrate the potential for the generation and preservation of very high-fidelity entanglement in a superconducting quantum communication network.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Inferring Quantum Network Topology Using Local Measurements
Statistical correlations that can be generated across the nodes in a quantum network depend crucially on its topology. However, this topological information might not be known a priori, or it may need to be verified. In this paper, we propose an efficient protocol for distinguishing and inferring the topology of a quantum network. We leverage entropic quantities-namely, the von Neumann entropy and the measured mutual information-as well as measurement covariance to uniquely characterize the topology. We show that the entropic quantities are sufficient to distinguish two networks that prepare GHZ states. Moreover, if qubit measurements are available, both entropic quantities and covariance can be used to infer the network topology without state-preparation assumptions. We show that the protocol can be entirely robust to noise and can be implemented via quantum variational optimization. Numerical experiments on both classical simulators and quantum hardware show that covariance is generally more reliable for accurately and efficiently inferring the topology, whereas entropy-based methods are often better at identifying the absence of entanglement in the low-shot regime.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
High-rate multiplexed entanglement source based on time-bin qubits for advanced quantum networks
Entanglement distribution based on time-bin qubits is an attractive option for emerging quantum networks. We demonstrate a 4.09-GHz repetition rate source of photon pairs entangled across early and late time bins separated by 80 ps. Simultaneous high rates and high visibilities are achieved through frequency multiplexing the spontaneous parametric down conversion output into eight time-bin entangled channel pairs. We demonstrate entanglement visibilities as high as 99.4%, total entanglement rates up to 3.55×10 6 coincidences/s, and predict a straightforward path towards achieving up to an order of magnitude improvement in rates without compromising visibility. Finally, we resolve the density matrices of the entangled states for each multiplexed channel and express distillable entanglement rates in ebit/s, thereby quantifying the trade-off between visibility and coincidence rates that contributes to useful entanglement distribution. This source is a fundamental building block for high-rate entanglement-based quantum key distribution systems or advanced quantum networks.
Mueller, Andrew (ORCID:0000000265989732)↗
Automatic protection switching in an entanglement-based quantum network
We demonstrate multihop two-qubit entanglement distribution in a reconfigurable quantum network over deployed fiber. Using quantum-compatible software-defined networking, we distribute entanglement across six nodes in three buildings, with adaptive link recovery mitigating transmission disruptions.
Alshowkan, Muneer [ORNL] (ORCID:0000000264293450)↗
Quantum Networking and Communications at Oak Ridge National Laboratory
In this article we review recent and ongoing research in quantum communications and networking within the Quantum Information Science Section at Oak Ridge National Laboratory. Our research spans applications such as quantum key distribution as well as more fundamental aspects needed to develop scalable quantum networks including quantum repeaters and space-based quantum communications platforms.
Peters, Nicholas↗
Quantum Instrumentation and Control Kit (QICK) for Quantum Networks
We report the first demonstration of using the Quantum Instrumentation and Control Kit (QICK) system on RFSoC FPGA technology to drive an entangled photon pair source and to detect the photon signals. With the QICK system, we achieve high levels of performance metrics including coincidence-to-accidental ratio exceeding 150, and entanglement visibility exceeding 95%, consistent with performance metrics achieved using conventional waveform generators. We also demonstrate simultaneous detector readout using the digitization functional of QICK, achieving internal system synchronization time resolution of 3.2 ps. The work reported in this paper represents an explicit demonstration of the feasibility for replacing commercial waveform generators and time taggers with RFSoC-FPGA technology in the operation of a quantum network, representing a cost reduction of more than an order of magnitude.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Hybrid Quantum Networks with Discrete Polarizations and Continuous Quadrature Variables
Final Scientific/Technical Report for DOE Project DE-SC0022069. Quantum communication and computation systems have evolved along two largely independent paradigms: discrete-variable (DV) systems that encode information in qubits such as photon polarizations or photon-number states, and continuous-variable (CV) systems that encode information in optical field quadratures. Each approach offers distinct advantages—DVs provide low error rates and compatibility with single-photon platforms, while CVs support deterministic operations and efficient quantum state manipulation. A fundamental challenge for building a scalable Quantum Internet lies in interfacing these two regimes into a unified hybrid architecture that can coherently distribute and process quantum information across heterogeneous quantum nodes. This project aims to develop and demonstrate a hybrid optical quantum network that seamlessly integrates DV and CV systems. Specifically, we investigate a new class of hybrid entanglement between the discrete polarizations of single photons and the continuous quadrature variables of optical cat states, overcoming incompatibilities in existing DV–CV demonstrations. Using this new entanglement resource, the team investigates a multi-node hybrid quantum local area network (Q-LAN) testbed capable of DV–CV entanglement generation, swapping, and distribution across fiber links.
74 ATOMIC AND MOLECULAR PHYSICS↗
Distilling the Essential Elements of Nuclear Binding via Neural-Network Quantum States
To distill the essential elements of nuclear binding, we seek the simplest Hamiltonian capable of modeling atomic nuclei with percent-level accuracy. A critical aspect of this endeavor consists of accurately solving the quantum many-body problem without incurring an exponential computing cost with the number of nucleons. Furthermore, we address this challenge by leveraging a variational Monte Carlo method based on a highly expressive neural-network quantum state ansatz. In addition to computing binding energies and charge radii of nuclei with up to 𝐴 = 20 nucleons, by evaluating their magnetic moments, we demonstrate that neural-network quantum states are able to correctly capture the self-emerging nuclear shell structure. To this end, we introduce a novel computational protocol based on adding an external magnetic field to the nuclear Hamiltonian, which allows the neural network to learn the preferred polarization of the nucleus within the given magnetic field.
Binding energy & masses↗
Adaptive bandwidth management for entanglement distribution in quantum networks
Flexible grid wavelength division multiplexing is a powerful tool in lightwave communications to maximize spectral efficiency. In the emerging field of quantum networking, the need for effective resource provisioning is particularly acute, given the generally lower power levels, higher sensitivity to loss, and inapplicability of optical detection and retransmission. In this letter, we leverage flex grid technology to demonstrate reconfigurable distribution of quantum entanglement in a four-user tabletop network. By adaptively partitioning bandwidth with a single wavelength-selective switch, we successfully equalize two-party coincidence rates that initially differ by over two orders of magnitude. Our scalable approach introduces loss that is fixed with the number of users, offering a practical path for the establishment and management of quality-of-service guarantees in large quantum networks.
42 ENGINEERING↗
Theory for Equivariant Quantum Neural Networks
Quantum neural network architectures that have little to no inductive biases are known to face trainability and generalization issues. Inspired by a similar problem, recent breakthroughs in machine learning address this challenge by creating models encoding the symmetries of the learning task. This is materialized through the usage of equivariant neural networks the action of which commutes with that of the symmetry. In this work, we import these ideas to the quantum realm by presenting a comprehensive theoretical framework to design equivariant quantum neural networks (EQNNs) for essentially any relevant symmetry group. We develop multiple methods to construct equivariant layers for EQNNs and analyze their advantages and drawbacks. Our methods can find unitary or general equivariant quantum channels efficiently even when the symmetry group is exponentially large or continuous. As a special implementation, we show how standard quantum convolutional neural networks (QCNNs) can be generalized to group-equivariant QCNNs where both the convolution and pooling layers are equivariant to the symmetry group. We then numerically demonstrate the effectiveness of a S U ( 2 ) -equivariant QCNN over symmetry-agnostic QCNN on a classification task of phases of matter in the bond-alternating Heisenberg model. Our framework can be readily applied to virtually all areas of quantum machine learning. Lastly, we discuss about how symmetry-informed models such as EQNNs provide hopes to alleviate central challenges such as barren plateaus, poor local minima, and sample complexity. Published by the American Physical Society 2024
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
A phononic interface between a superconducting quantum processor and quantum networked spin memories
We introduce a method for high-fidelity quantum state transduction between a superconducting microwave qubit and the ground state spin system of a solid-state artificial atom, mediated via an acoustic bus connected by piezoelectric transducers. Applied to present-day experimental parameters for superconducting circuit qubits and diamond silicon-vacancy centers in an optimized phononic cavity, we estimate quantum state transduction with fidelity exceeding 99% at a MHz-scale bandwidth. By combining the complementary strengths of superconducting circuit quantum computing and artificial atoms, the hybrid architecture provides high-fidelity qubit gates with long-lived quantum memory, high-fidelity measurement, large qubit number, reconfigurable qubit connectivity, and high-fidelity state and gate teleportation through optical quantum networks.
47 OTHER INSTRUMENTATION↗
Tensor Network Quantum Virtual Machine for Simulating Quantum Circuits at Exascale
The numerical simulation of quantum circuits is an indispensable tool for development, verification, and validation of hybrid quantum-classical algorithms intended for near-term quantum co-processors. The emergence of exascale high-performance computing (HPC) platforms presents new opportunities for pushing the boundaries of quantum circuit simulation. Here, we present a modernized version of the Tensor Network Quantum Virtual Machine (TNQVM) that serves as the quantum circuit simulation backend in the eXtreme-scale ACCelerator (XACC) framework. The new version is based on the scalable tensor network processing library ExaTN (Exascale Tensor Networks). It provides multiple configurable quantum circuit simulators that perform either an exact quantum circuit simulation via the full tensor network contraction or an approximate simulation via a suitably chosen tensor factorization scheme. Upon necessity, stochastic noise modeling from real quantum processors is incorporated into the simulations by modeling quantum channels with Kraus tensors. By combining the portable XACC quantum programming frontend and the scalable ExaTN numerical processing backend, we introduce an end-to-end virtual quantum development environment that can scale from laptops to future exascale platforms. We report initial benchmarks of our framework, which include a demonstration of the distributed execution, incorporation of quantum decoherence models, and simulation of the random quantum circuits used for the certification of quantum supremacy on Google’s Sycamore superconducting architecture.
Nguyen, Thien↗