Error Mitigation in Quantum Computers through Instruction Scheduling

TL;DR

This paper introduces TimeStitch, a compilation framework that optimizes the scheduling of existing quantum gates to mitigate errors in NISQ devices without increasing circuit duration.

Contribution

It presents a novel scheduling method that exploits circuit slack for error mitigation, inspired by spin-echo techniques, without adding extra gates or extending runtime.

Findings

Improves quantum circuit success rates on real hardware

Effectively mitigates decoherence and noise in NISQ devices

Operates as a compilation pass leveraging circuit reversibility

Abstract

Quantum systems have potential to demonstrate significant computational advantage, but current quantum devices suffer from the rapid accumulation of error that prevents the storage of quantum information over extended periods. The unintentional coupling of qubits to their environment and each other adds significant noise to computation, and improved methods to combat decoherence are required to boost the performance of quantum algorithms on real machines. While many existing techniques for mitigating error rely on adding extra gates to the circuit, calibrating new gates, or extending a circuit's runtime, this paper's primary contribution leverages the gates already present in a quantum program without extending circuit duration. We exploit circuit slack for single-qubit gates that occur in idle windows, scheduling the gates such that their timing can counteract some errors. Spin-echo corrections that mitigate decoherence on idling qubits act as inspiration for this work. Theoretical models, however, fail to capture all sources of noise in NISQ devices, making practical solutions necessary that better minimize the impact of unpredictable errors in quantum machines. This paper presents TimeStitch: a novel framework that pinpoints the optimum execution schedules for single-qubit gates within quantum circuits. TimeStitch, implemented as a compilation pass, leverages the reversible nature of quantum computation to boost the success of circuits on real quantum machines.