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quant-ph2025
A Lyapunov Framework for Quantum Algorithm Design in Combinatorial Optimization with Approximation Ratio Guarantees
Shengminjie Chen, Ziyang Li, Hongyi Zhou +3
In this work, we develop a framework aiming at designing quantum algorithms for combinatorial optimization problems while providing theoretical guarantees on their approximation ra…
quant-ph2025
Practical Homodyne Shadow Estimation
Ruyu Yang, Xiaoming Sun, Hongyi Zhou
Shadow estimation provides an efficient framework for estimating observable expectation values using randomized measurements. While originally developed for discrete-variable syste…
quant-ph2025
Stochastic Quantum Hamiltonian Descent
Sirui Peng, Shengminjie Chen, Xiaoming Sun +1
Stochastic Gradient Descent (SGD) and its variants underpin modern machine learning by enabling efficient optimization of large-scale models. However, their local search nature lim…