ArsoNISQ: Analyzing Quantum Algorithms on Near-Term Architectures

TL;DR

The paper introduces the ArsoNISQ framework to evaluate the error tolerance and success probability of quantum algorithms on NISQ devices, highlighting the importance of error rates and circuit size for quantum computing feasibility.

Contribution

It presents a novel simulation-based framework for analyzing quantum algorithm robustness on NISQ hardware, providing insights into error tolerance limits and guiding platform selection.

Findings

No intrinsic robustness found in evaluated algorithms

Circuit size bounds error tolerance levels

Error rates must decrease or error correction needed for quantum advantage

Abstract

While scalable, fully error corrected quantum computing is years or even decades away, there is considerable interest in noisy intermediate-scale quantum computing (NISQ). In this paper, we introduce the ArsoNISQ framework that determines the tolerable error rate of a given quantum algorithm computation, i.e. quantum circuits, and the success probability of the computation given a success criterion and a NISQ computer. ArsoNISQ is based on simulations of quantum circuits subject to errors according to the Pauli error model. ArsoNISQ was evaluated on a set of quantum algorithms that can incur a quantum speedup or are otherwise relevant to NISQ computing. Despite optimistic expectations in recent literature, we did not observe quantum algorithms with intrinsic robustness, i.e. algorithms that tolerate one error on average, in this evaluation. The evaluation demonstrated, however, that the quantum circuit size sets an upper bound for its tolerable error rate and quantified the difference in tolerate error rates for quantum circuits of similar sizes. Thus, the framework can assist quantum algorithm developers in improving their implementation and selecting a suitable NISQ computing platform. Extrapolating the results into the quantum advantage regime suggests that the error rate of larger quantum computers must decrease substantially or active quantum error correction will need to be deployed for most of the evaluated algorithms.