AI & ML
Dynamical Tensor Train Approximation for Wigner--Fokker--Planck Equation with Applications to Open Quantum Systems
arXiv cs.NA0 views
arXiv:2610.36257v1 Announce Type: new Abstract: We develop a dynamical tensor-train method for the Wigner--Fokker--Planck equation arising in continuous-variable open quantum systems. The Wigner function is evolved directly in tensor-train form using a projector-splitting integrator, while the nonlocal Wigner pseudo-differential operator is treated through low-rank representations of the potential difference and matrix-free exponential actions. The resulting method avoids full tensor-product computations in high-dimensional phase space. Numerical experiments in one, two, and three spatial dimensions demonstrate the accuracy and scalability of the method, including simulations in a six-dimensional phase space.
Source：https://arxiv.org/abs/2610.36257PreviousGradient-Free Neural Hamilton-Jacobi Reachability for Scalable Safety-Critical ControlNextMonte Carlo Power Iteration Algorithms: Convergence, Analysis and Application to Reactor Criticality Calculations
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