Measurement-Informed Safe Reinforcement Learning for Quantum Battery Charging via Harmonic-Syndrome Diagnostics and BMS Constraints

Abstract: Quantum batteries promise ultrafast energy storage but are highly sensitive to noise, drift, and hardware constraints, making safe high-performance charging a central challenge for noisy intermediate-scale quantum devices. We propose a measurement-informed safe control framework that couples harmonic-spectrum-based syndrome diagnostics—H2/H1, H3/H1, and frequency drift—with a battery management system (BMS)-constrained curriculum reinforcement learning (RL) policy. […]

Orthogonal Frequency-Division Multiplexing Continuous-Variable Terahertz QKD for Large-Scale Wireless Quantum Communication

Abstract: In this article, we introduce a continuous-variable quantum key distribution (CVQKD) protocol that combines orthogonal frequency-division multiplexing with terahertz (THz) carriers to deliver high-throughput and hardware-compatible quantum communication. By distributing quantum states across multiple subcarriers, our approach achieves a noticeable increase in spectral efficiency while mitigating dispersion and atmospheric losses that limit the performance […]

Encoder Circuit Optimization for Nonbinary Quantum Error Correction Codes in Prime Dimensions: An Algorithmic Framework

Abstract: Quantum computers are a revolutionary class of computational platforms with applications in combinatorial and global optimization, machine learning, and other domains involving computationally hard problems. While these machines typically operate on qubits—quantum information elements that can occupy superpositions of the basis |0⟩ and |1⟩ states—recent advances have demonstrated the practical implementation of higher dimensional […]

Parameter Analysis and Optimization of Layer Fidelity for Quantum Processor Benchmarking at Scale

Abstract: With the continued scaling of quantum processors, holistic benchmarks are essential for extensively evaluating device performance. Layer fidelity is a benchmark well-suited to assessing processor performance at scale. Key advantages of this benchmark include its natural alignment with randomized benchmarking (RB) procedures, crosstalk awareness, fast measurements over large numbers of qubits, high signal-to-noise ratio, […]

A Low Noise Signal Read-Out Circuit for Integrated Quantum Diamond Magnetometers

Abstract: A customized low-noise signal read-out circuit, which is designed for the implementation of the integrated low power consumption quantum magnetometers based on nitrogen-vacancy centers in diamond, is reported in this article. As the circuit has a 3.7 pA/Hz1/2 low-input noise which is superior to the latest studies, the integrated quantum diamond magnetometer can achieve […]

Accelerating the Max-Cut problems via distributed Ising machine solvers

Abstract: The Ising machine, as a quantum-inspired computing system, can be used to efficiently solve combinatorial optimization problems. Ongoing studies have positioned it to potentially surpass the performance limitations of traditional computers. However, such Ising machines also suffer from scalability as the solution quality becomes sub-optimal when the problem size increases. In this work, we […]

Differential Phase Encoded Plug-and-Play Measurement-Device-Independent Quantum Key Distribution

Abstract: Measurement-device-independent quantum key distribution (MDI-QKD) enhances security by removing vulnerabilities associated with detector side channels. Real-world implementations ofMDI-QKD face practical challenges, such as channel asymmetry and physical imperfections, which degrade the visibility of Hong–Ou–Mandel interference, an essential factor in determining the secure key rate. In this work, we evaluate the performance of differential phase […]

Explaining Robust Quantum Metrology by Counting Codewords

Abstract: Quantum sensing holds great promise for high-precision magnetic field measurements. However, its performance is significantly limited by noise. The investigation of active quantum error correction to address this noise led to the Hamiltonian-not-in-Lindblad-span (HNLS) condition. This states that the Heisenberg scaling is achievable if and only if the signal Hamiltonian is orthogonal to the […]

Parallel Variational Quantum Algorithms With Gradient-Informed Restart to Speed Up Optimization in the Presence of Barren Plateaus

Abstract: Inspired by the Fleming–Viot stochastic process, we propose a parallel implementation with restart of variational quantum algorithms, with the aim of reducing the time spent by the algorithm in barren plateaus where the optimization direction is unclear. In the Fleming–Viot tradition, parallel searches are called particles. In the proposed approach, the search by a […]