Dynamical low-rank approximation for the semiclassical Schrodinger equation with uncertainties
Liu Liu, Limin Xu, Zhenyi Zhu

TL;DR
This paper introduces a dynamical low-rank approximation method for efficiently solving the semiclassical Schrödinger equation with uncertainties, capturing quantum dynamics with fewer basis functions despite complex oscillations.
Contribution
The paper extends two robust integrators to the semiclassical regime and demonstrates their efficiency and accuracy in capturing low-rank structures in uncertain quantum systems.
Findings
DLR method is more efficient than stochastic Galerkin methods.
Wave functions remain in low-rank subspaces despite oscillations.
High fidelity achieved with small, robust numerical ranks.
Abstract
In this paper, we propose a dynamical low-rank (DLR) approximation framework for solving the semiclassical Schrodinger equation with uncertainties. The primary numerical challenges arise from the dual nature of the oscillations: the spatial oscillations inherent in the semiclassical limit and the high-frequency oscillations in the random space induced by uncertainties. We extend two robust integrators -- the projector-splitting integrator and the unconventional integrator -- to the semiclassical regime to evolve the solution on a low-rank manifold. Through extensive numerical experiments, we demonstrate that the DLR method is significantly more computationally efficient than the standard stochastic Galerkin method, as it captures the essential quantum dynamics using a much smaller number of basis functions. Our findings reveal that despite the complex oscillatory patterns of the wave…
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Taxonomy
TopicsProbabilistic and Robust Engineering Design · Tensor decomposition and applications · Stochastic Gradient Optimization Techniques
