Full- and low-rank exponential midpoint schemes for forward and adjoint Lindblad equations

Fuente: arXiv
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Main Authors: Chen, Hao, Borzi, Alfio
Format: Preprint
Published: 2025
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author Chen, Hao
Borzi, Alfio
author_facet Chen, Hao
Borzi, Alfio
contents The Lindblad equation is a widely used quantum master equation to model the dynamical evolution of open quantum systems whose states are described by density matrices. This equation is also a fundamental building block to design optimal control functions. In this paper we develop full- and low-rank exponential midpoint integrators for solving both the forward and adjoint Lindblad equations. These schemes are applicable to optimize-then-discretize approaches for optimal control of open quantum systems. We show that the proposed schemes preserve positivity and trace unconditionally. Furthermore, convergence of these numerical schemes is proved theoretically and verified numerically.
format Preprint
id arxiv_https___arxiv_org_abs_2506_00346
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Full- and low-rank exponential midpoint schemes for forward and adjoint Lindblad equations
Chen, Hao
Borzi, Alfio
Quantum Physics
Numerical Analysis
Optimization and Control
The Lindblad equation is a widely used quantum master equation to model the dynamical evolution of open quantum systems whose states are described by density matrices. This equation is also a fundamental building block to design optimal control functions. In this paper we develop full- and low-rank exponential midpoint integrators for solving both the forward and adjoint Lindblad equations. These schemes are applicable to optimize-then-discretize approaches for optimal control of open quantum systems. We show that the proposed schemes preserve positivity and trace unconditionally. Furthermore, convergence of these numerical schemes is proved theoretically and verified numerically.
title Full- and low-rank exponential midpoint schemes for forward and adjoint Lindblad equations
topic Quantum Physics
Numerical Analysis
Optimization and Control
url https://arxiv.org/abs/2506.00346