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Main Authors: Abe, Yoshihiko, Nagai, Ryo
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.28624
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author Abe, Yoshihiko
Nagai, Ryo
author_facet Abe, Yoshihiko
Nagai, Ryo
contents We propose Quantum Riemannian Hamiltonian Descent (QRHD), a quantum algorithm for continuous optimization on Riemannian manifolds that extends Quantum Hamiltonian Descent (QHD) by incorporating geometric structure of the parameter space via a position-dependent metric in the kinetic term. We formulate QRHD at both operator and path integral formalisms and derive the corresponding quantum equations of motion, showing that quantum corrections appear in the action integral but they are suppressed at late times by the time-dependent dissipation factor. This implies that convergence near optimal points is controlled by the classical potential while quantum effects influence early-time dynamics. By analyzing the semiclassical equation, we estimate a lower bound on the convergence time and numerically demonstrate whether QRHD work as a quantum optimization algorithm in some examples. A quantum circuit implementation based on time-dependent Hamiltonian simulation is also discussed and the query complexity is estimated.
format Preprint
id arxiv_https___arxiv_org_abs_2603_28624
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Quantum Riemannian Hamiltonian Descent
Abe, Yoshihiko
Nagai, Ryo
Quantum Physics
High Energy Physics - Theory
We propose Quantum Riemannian Hamiltonian Descent (QRHD), a quantum algorithm for continuous optimization on Riemannian manifolds that extends Quantum Hamiltonian Descent (QHD) by incorporating geometric structure of the parameter space via a position-dependent metric in the kinetic term. We formulate QRHD at both operator and path integral formalisms and derive the corresponding quantum equations of motion, showing that quantum corrections appear in the action integral but they are suppressed at late times by the time-dependent dissipation factor. This implies that convergence near optimal points is controlled by the classical potential while quantum effects influence early-time dynamics. By analyzing the semiclassical equation, we estimate a lower bound on the convergence time and numerically demonstrate whether QRHD work as a quantum optimization algorithm in some examples. A quantum circuit implementation based on time-dependent Hamiltonian simulation is also discussed and the query complexity is estimated.
title Quantum Riemannian Hamiltonian Descent
topic Quantum Physics
High Energy Physics - Theory
url https://arxiv.org/abs/2603.28624