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Main Authors: Fan, Yun-Zhuo, Wu, Yu-Xia, Zhang, Dan-Bo
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2506.15466
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author Fan, Yun-Zhuo
Wu, Yu-Xia
Zhang, Dan-Bo
author_facet Fan, Yun-Zhuo
Wu, Yu-Xia
Zhang, Dan-Bo
contents Randomized compilation protocols have recently attracted attention as alternatives to traditional deterministic Trotter-Suzuki methods, potentially reducing circuit depth and resource overhead. These protocols determine gate application probabilities based on the strengths of Hamiltonian terms, as measured by the trace norm. However, relying solely on the trace norm to define sampling distributions may not be optimal, especially for continuous-variable and hybrid-variable systems involving unbounded operators, where quantifying Hamiltonian strengths is challenging. In this work, we propose an adaptive randomized compilation algorithm that dynamically updates sampling weights via low-order moment measurements of Hamiltonian terms, assigning higher probabilities to terms with greater uncertainty. This approach improves accuracy without significantly increasing gate counts and extends randomized compilation to continuous-variable and hybrid-variable systems by addressing the difficulties in characterizing the strengths of unbounded Hamiltonian terms. Numerical simulations demonstrate the effectiveness of our method.
format Preprint
id arxiv_https___arxiv_org_abs_2506_15466
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Adaptive random compiler for Hamiltonian simulation
Fan, Yun-Zhuo
Wu, Yu-Xia
Zhang, Dan-Bo
Quantum Physics
Randomized compilation protocols have recently attracted attention as alternatives to traditional deterministic Trotter-Suzuki methods, potentially reducing circuit depth and resource overhead. These protocols determine gate application probabilities based on the strengths of Hamiltonian terms, as measured by the trace norm. However, relying solely on the trace norm to define sampling distributions may not be optimal, especially for continuous-variable and hybrid-variable systems involving unbounded operators, where quantifying Hamiltonian strengths is challenging. In this work, we propose an adaptive randomized compilation algorithm that dynamically updates sampling weights via low-order moment measurements of Hamiltonian terms, assigning higher probabilities to terms with greater uncertainty. This approach improves accuracy without significantly increasing gate counts and extends randomized compilation to continuous-variable and hybrid-variable systems by addressing the difficulties in characterizing the strengths of unbounded Hamiltonian terms. Numerical simulations demonstrate the effectiveness of our method.
title Adaptive random compiler for Hamiltonian simulation
topic Quantum Physics
url https://arxiv.org/abs/2506.15466