Quantum computation of stopping power for inertial fusion target design

TL;DR

This paper proposes a quantum computing protocol to accurately calculate stopping power in inertial fusion targets, addressing classical computational challenges in modeling warm-dense matter conditions.

Contribution

It introduces a fault-tolerant quantum algorithm for first-principles stopping power calculations, optimizing electronic structure methods for non-equilibrium, finite-temperature systems.

Findings

Estimated logical qubit requirements for relevant calculations.

Projected Toffoli gate costs comparable to complex molecular simulations.

Demonstrated potential to perform classically intractable stopping power computations.

Abstract

Stopping power is the rate at which a material absorbs the kinetic energy of a charged particle passing through it -- one of many properties needed over a wide range of thermodynamic conditions in modeling inertial fusion implosions. First-principles stopping calculations are classically challenging because they involve the dynamics of large electronic systems far from equilibrium, with accuracies that are particularly difficult to constrain and assess in the warm-dense conditions preceding ignition. Here, we describe a protocol for using a fault-tolerant quantum computer to calculate stopping power from a first-quantized representation of the electrons and projectile. Our approach builds upon the electronic structure block encodings of Su et al. [PRX Quantum 2, 040332 2021], adapting and optimizing those algorithms to estimate observables of interest from the non-Born-Oppenheimer dynamics of multiple particle species at finite temperature. Ultimately, we report logical qubit requirements and leading-order Toffoli costs for computing the stopping power of various projectile/target combinations relevant to interpreting and designing inertial fusion experiments. We estimate that scientifically interesting and classically intractable stopping power calculations can be quantum simulated with roughly the same number of logical qubits and about one hundred times more Toffoli gates than is required for state-of-the-art quantum simulations of industrially relevant molecules such as FeMoCo or P450.