This paper establishes log-concavity of the ground state for a large family of discrete, 1-dimensional Schrödinger operators, extending the analysis of the Hamming weight with a spike problem to more…

This paper introduces DQAOA-GPT, a hybrid framework that integrates DQAOA and GPT-based quantum circuit generation for solving combinatorial optimization problems, reducing computational cost and main…

This paper presents two quantum algorithms for solving linear systems with normalized solution $|x angle$ to accuracy $ε$, independent of the condition number $κ$.

The paper introduces QADR, a novel hybrid quantum-classical framework that efficiently trains variational quantum circuits by localizing entanglement reduction, thereby overcoming the exponential memo…

This paper proposes an economic model to optimize the trade-off between entanglement distribution latency and decoherence time in distributed quantum computing.

This paper proposes a method to explore the design space of quantum-classical applications using a formalization of an architectural style, enabling dynamic selection of the most suitable configuratio…

This paper shows that shallow circuits cannot prepare near-optimal states for random quantum $p$-spin glasses, and proves depth lower bounds for such preparations.

This paper proposes QCOEM, a quantum cloud orchestration framework using evolutionary algorithms for multi-objective optimization of quantum task scheduling, achieving zero rescheduling and 30% higher…

This paper shows that larger gradient-based parameterized quantum circuits can exhibit improved performance on unseen data, contrasting the traditional view.

The paper reformulates nonreversible perturbations of Fokker--Planck dynamics as gauge fields, providing a unified operator viewpoint to analyze relaxation processes and develop methods for learning o…

The paper establishes conditions for QUBO formulations of combinatorial optimization problems that guarantee valid binary and feasible local minimizers using gradient-based methods.

The paper introduces a unified framework for Quantum Fully Homomorphic Encryption (QFHE) that achieves exponential efficiency improvements by integrating a novel modular arithmetic program (MAP) tailo…