4.7 Article

Algorithms for perturbative analysis and simulation of quantum dynamics

期刊

JOURNAL OF COMPUTATIONAL PHYSICS
卷 489, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcp.2023.112262

关键词

Quantum; Perturbation; Control; Simulation; Dyson; Magnus

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We develop general purpose algorithms for computing and utilizing both the Dyson series and Magnus expansion, with the goal of facilitating numerical perturbative studies of quantum dynamics. These algorithms are implemented in the open source software package Qiskit Dynamics, which utilizes the JAX array library to enable just-in-time compilation, automatic differentiation, and GPU execution of all computations. The Dyson and Magnus-based solvers provide a speedup over traditional ODE solvers when simulating a two-transmon entangling gate on a GPU.
We develop general purpose algorithms for computing and utilizing both the Dyson series and Magnus expansion, with the goal of facilitating numerical perturbative studies of quantum dynamics. To enable broad applications to models with multiple parameters, we phrase our algorithms in terms of multivariable sensitivity analysis, for either the solution or the time-averaged generator of the evolution over a fixed time-interval. These tools simultaneously compute a collection of terms up to arbitrary order, and are general in the sense that the model can depend on the parameters in an arbitrary time -dependent way. We implement the algorithms in the open source software package Qiskit Dynamics, utilizing the JAX array library to enable just-in-time compilation, automatic differentiation, and GPU execution of all computations. Using a model of a single transmon, we demonstrate how to use these tools to approximate fidelity in a region of model parameter space, as well as construct perturbative robust control objectives. We also derive and implement Dyson and Magnus-based variations of the recently introduced Dysolve algorithm [Shillito et al., Physical Review Research, 3(3):033266] for simulating linear matrix differential equations. We show how the pre-computation step can be phrased as a multivariable expansion computation problem with fewer terms than in the original method. When simulating a two-transmon entangling gate on a GPU, we find the Dyson and Magnus-based solvers provide a speedup over traditional ODE solvers, ranging from roughly 2x to 4x for a solution and 10x to 60x for a gradient, depending on solution accuracy.& COPY; 2023 Elsevier Inc. All rights reserved.

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