An analytical error model for quantum computer simulation

TL;DR

This paper introduces an analytical error model for quantum computer simulation that constructs a probability error tree, enabling faster fidelity calculations compared to traditional Monte Carlo methods, especially for small problem sizes.

Contribution

The paper presents a novel analytical error model that significantly speeds up quantum error simulation by directly calculating fidelity, reducing computation time from days to hours.

Findings

Achieves approximately 1,000X speedup over Monte Carlo models

Provides accurate fidelity estimates for small quantum programs

Evaluates the scalability of the analytical error model

Abstract

Quantum computers (QCs) must implement quantum error correcting codes (QECCs) to protect their logical qubits from errors, and modeling the effectiveness of QECCs on QCs is an important problem for evaluating the QC architecture. The previously developed Monte Carlo (MC) error models may take days or weeks of execution to produce an accurate result due to their random sampling approach. We present an alternative analytical error model that generates, over the course of executing the quantum program, a probability tree of the QC's error states. By calculating the fidelity of the quantum program directly, this error model has the potential for enormous speedups over the MC model when applied to small yet useful problem sizes. We observe a speedup on the order of 1,000X when accuracy is required, and we evaluate the scaling properties of this new analytical error model.