Variational simulation of stochastic plasma dynamics*

Quantum computing holds the potential to accelerate simulations of physical systems, in particular in the field of plasma physics. However, current accessibility of public quantum computers is limited to a low number of qubits and shallow circuit depths.

Variational quantum algorithms have emerged as a promising approach for near-term quantum computers, in general presenting shorter circuit depths compared to fault-tolerant Hamiltonian simulation, and the ability to reconstruct the wavefunction at each time-step (allowing post-processing of the data). These have recently been applied to stochastic differential equations [1,2], an example of which being the Fokker-Planck equation. This class of equations has applications in many plasma physics problems, namely in the stochastic radiation reaction of charged particles in intense laser fields, and in dynamics of collisional plasmas, where phase-space volume is not necessarily conserved.

In this work, we explore the applicability of this method to the evolution of a 1D electron distribution function in several scenarios, discussing the different steps of the simulation: wavefunction ansatz, depth of the single time-step evolution, and extraction of observables.