Selected work

Representative Papers

Quantum Maxwell Erasure Decoder for qLDPC codes

Jan 15, 2026

This work addresses the challenge of efficient and reliable decoding of CSS-type quantum low-density parity-check (qLDPC) codes over erasure channels by proposing a Quantum Maxwell Erasure Decoder. The method integrates a bounded-guess peeling algorithm, symbolic guess tracking, and constraint-aware check elimination to effectively eliminate erroneous guesses. By introducing an adjustable guess budget mechanism, it achieves a flexible trade-off between decoding complexity and performance: under an unbounded budget, it attains maximum-likelihood performance, while with a constant budget, it enables linear-time decoding that closely approaches optimal performance. Theoretical analysis establishes asymptotic performance guarantees, and experiments on bivariate bicycle codes and quantum Tanner codes demonstrate superior decoding efficacy.

1 citationsRead paper

Examining QRMI as a Unified Interface for Quantum-HPC Integration

Jul 21, 2026

This work addresses the lack of a unified mechanism for efficiently integrating and scheduling quantum computing resources within heterogeneous high-performance computing (HPC) environments. To bridge this gap, the authors propose QRMI, a lightweight, vendor-agnostic middleware that abstracts quantum resources as schedulable units and enables their co-management alongside classical CPU and GPU resources. QRMI seamlessly interoperates with diverse job schedulers—including PBS, LSF, Grid Engine, Kubernetes, and Flux—through a standardized API and modular architecture. Without requiring deep modifications to existing schedulers, QRMI achieves consistent, cross-platform access to and efficient scheduling of quantum resources for the first time. Experimental validation demonstrates its generality and practicality across both on-premises and cloud-based heterogeneous infrastructures.

0 citationsRead paper

Log-concavity and tunneling: adiabatic quantum optimization for convex functions (with a spike)

Jun 22, 2026

This work investigates the acceleration mechanism of quantum tunneling in adiabatic quantum optimization for spike-shaped convex potentials. By introducing the discrete log-concavity of the ground state into the analysis of one-dimensional discrete Schrödinger operators, the study establishes a theoretical framework applicable to nonsmooth potentials. It extends the classical Brascamp–Lieb inequality from the continuous to the discrete setting and generalizes the Hidden Weighted Subset (HWS) problem from linear to quadratic potentials. Combining spectral theory, the adiabatic theorem, and perturbation analysis, the authors derive a more general lower bound on the spectral gap, demonstrating that quantum tunneling retains its computational advantage even in the presence of spike-shaped convex barriers. This provides new theoretical support for quantum optimization in scenarios involving non-analytic potential landscapes.

0 citationsRead paper

Quantum-HPC Software Stacks and the openQSE Reference Architecture: A Survey

Apr 21, 2026

This work addresses the challenges hindering the integration of quantum and high-performance computing (QHPC), including fragmented software stack interfaces, proprietary implementations, and poor ecosystem interoperability. Through a systematic survey of nine prominent QHPC software stacks, the study identifies common design patterns and core requirements, leading to the first proposal of openQSE—an open reference architecture. By explicitly defining key inter-layer interfaces for runtime abstraction, resource management, interconnect semantics, and observability, openQSE ensures deployment flexibility and backward compatibility while enabling a smooth evolution from Noisy Intermediate-Scale Quantum (NISQ) to Fault-Tolerant Quantum Computing (FTQC). This architecture establishes a standardized foundation for building a unified and scalable QHPC software ecosystem.

0 citationsRead paper

Experimental differentiation and extremization with analog quantum circuits

Oct 23, 2025

Classical numerical methods for solving differential equations and optimizing function extrema incur high computational overhead, while fault-tolerant digital quantum hardware remains immature. Method: We propose a closed-loop framework integrating differentiable quantum circuits (DQCs) with quantum extremum learning (QEL), enabling direct search for extrema of implicitly defined functions—partially circumventing explicit differential equation solving. Contribution/Results: This framework is the first to be end-to-end experimentally validated on a commercially available neutral-atom analog quantum simulator, eliminating reliance on gate-based digital hardware. By synergistically combining variational optimization and machine-learning surrogate models, we successfully solve differential equations and locate extrema. Evaluations on synthetic benchmarks demonstrate robust convergence and stability, establishing a viable pathway for analog quantum simulation in scientific computing and highlighting its practical potential for real-world applications.

0 citationsRead paper

Recent publications

Latest Papers

Examining QRMI as a Unified Interface for Quantum-HPC Integration

Jul 21, 2026

This work addresses the lack of a unified mechanism for efficiently integrating and scheduling quantum computing resources within heterogeneous high-performance computing (HPC) environments. To bridge this gap, the authors propose QRMI, a lightweight, vendor-agnostic middleware that abstracts quantum resources as schedulable units and enables their co-management alongside classical CPU and GPU resources. QRMI seamlessly interoperates with diverse job schedulers—including PBS, LSF, Grid Engine, Kubernetes, and Flux—through a standardized API and modular architecture. Without requiring deep modifications to existing schedulers, QRMI achieves consistent, cross-platform access to and efficient scheduling of quantum resources for the first time. Experimental validation demonstrates its generality and practicality across both on-premises and cloud-based heterogeneous infrastructures.

0 citationsRead paper

Log-concavity and tunneling: adiabatic quantum optimization for convex functions (with a spike)

Jun 22, 2026

This work investigates the acceleration mechanism of quantum tunneling in adiabatic quantum optimization for spike-shaped convex potentials. By introducing the discrete log-concavity of the ground state into the analysis of one-dimensional discrete Schrödinger operators, the study establishes a theoretical framework applicable to nonsmooth potentials. It extends the classical Brascamp–Lieb inequality from the continuous to the discrete setting and generalizes the Hidden Weighted Subset (HWS) problem from linear to quadratic potentials. Combining spectral theory, the adiabatic theorem, and perturbation analysis, the authors derive a more general lower bound on the spectral gap, demonstrating that quantum tunneling retains its computational advantage even in the presence of spike-shaped convex barriers. This provides new theoretical support for quantum optimization in scenarios involving non-analytic potential landscapes.

0 citationsRead paper

Quantum-HPC Software Stacks and the openQSE Reference Architecture: A Survey

Apr 21, 2026

This work addresses the challenges hindering the integration of quantum and high-performance computing (QHPC), including fragmented software stack interfaces, proprietary implementations, and poor ecosystem interoperability. Through a systematic survey of nine prominent QHPC software stacks, the study identifies common design patterns and core requirements, leading to the first proposal of openQSE—an open reference architecture. By explicitly defining key inter-layer interfaces for runtime abstraction, resource management, interconnect semantics, and observability, openQSE ensures deployment flexibility and backward compatibility while enabling a smooth evolution from Noisy Intermediate-Scale Quantum (NISQ) to Fault-Tolerant Quantum Computing (FTQC). This architecture establishes a standardized foundation for building a unified and scalable QHPC software ecosystem.

0 citationsRead paper

Quantum Maxwell Erasure Decoder for qLDPC codes

Jan 15, 2026

This work addresses the challenge of efficient and reliable decoding of CSS-type quantum low-density parity-check (qLDPC) codes over erasure channels by proposing a Quantum Maxwell Erasure Decoder. The method integrates a bounded-guess peeling algorithm, symbolic guess tracking, and constraint-aware check elimination to effectively eliminate erroneous guesses. By introducing an adjustable guess budget mechanism, it achieves a flexible trade-off between decoding complexity and performance: under an unbounded budget, it attains maximum-likelihood performance, while with a constant budget, it enables linear-time decoding that closely approaches optimal performance. Theoretical analysis establishes asymptotic performance guarantees, and experiments on bivariate bicycle codes and quantum Tanner codes demonstrate superior decoding efficacy.

1 citationsRead paper

Experimental differentiation and extremization with analog quantum circuits

Oct 23, 2025

Classical numerical methods for solving differential equations and optimizing function extrema incur high computational overhead, while fault-tolerant digital quantum hardware remains immature. Method: We propose a closed-loop framework integrating differentiable quantum circuits (DQCs) with quantum extremum learning (QEL), enabling direct search for extrema of implicitly defined functions—partially circumventing explicit differential equation solving. Contribution/Results: This framework is the first to be end-to-end experimentally validated on a commercially available neutral-atom analog quantum simulator, eliminating reliance on gate-based digital hardware. By synergistically combining variational optimization and machine-learning surrogate models, we successfully solve differential equations and locate extrema. Evaluations on synthetic benchmarks demonstrate robust convergence and stability, establishing a viable pathway for analog quantum simulation in scientific computing and highlighting its practical potential for real-world applications.

0 citationsRead paper