The Random Batch Method for $N$-Body Quantum Dynamics

TL;DR

This paper introduces a random batch method to efficiently simulate large quantum systems by reducing interaction computations from quadratic to linear complexity, with proven convergence guarantees.

Contribution

The paper proposes a novel random batch approach for quantum dynamics that significantly reduces computational cost while providing uniform convergence estimates.

Findings

Reduces interaction computation from O(N^2) to O(N)

Provides convergence estimates uniform in N and independent of Planck's constant

Demonstrates effectiveness for large quantum systems

Abstract

This paper discusses a numerical method for computing the evolution of large interacting system of quantum particles. The idea of the random batch method is to replace the total interaction of each particle with the $N-1$ other particles by the interaction with $p<N$ particles chosen at random at each time step, multiplied by $(N-1)/p$. This reduces the computational cost of computing the interaction partial per time step from $O(N^2)$ to $O(N)$. For simplicity, we consider only in this work the case $p=1$. In other words, we assume that $N$ is even, and that at each time step, the $N$ particles are organized in $N/2$ pairs, with a random reshuffling of the pairs at the beginning of each time step. We obtain a convergence estimate for the Wigner transform of the single-particle reduced density matrix of the particle system at time $t$ that is uniform in $N>1$ and independent of the Planck constant $\hbar$.