A quantum algorithm for solving open system dynamics on quantum computers using noise

TL;DR

This paper introduces a quantum algorithm that leverages noise as a resource to compute operator averages in open quantum systems, enabling simulations of complex models like the spin-boson at finite temperature.

Contribution

The paper presents a novel quantum algorithm that uses intrinsic qubit noise to simulate open system dynamics, with tunable bath spectral functions and robustness to high gate errors.

Findings

Algorithm performs well with gate errors up to 1%

Effective for systems with decomposable system-bath interactions

Feasible for simulating the spin-boson model at finite temperature

Abstract

In this paper we present a quantum algorithm that uses noise as a resource. The goal of our quantum algorithm is the calculation of operator averages of an open quantum system evolving in time. Selected low-noise system qubits and noisy bath qubits represent the system and the bath of the open quantum system. All incoherent qubit noise can be mapped to bath spectral functions. The form of the spectral functions can be tuned digitally, allowing for the time evolution of a wide range of open-system models at finite temperature. We study the feasibility of this approach with a focus on the solution of the spin-boson model and assume intrinsic qubit noise that is dominated by damping and dephasing. We find that classes of open quantum systems exist where our algorithm performs very well, even with gate errors as high as 1%. In general the presented algorithm performs best if the system-bath interactions can be decomposed into native gates.