Considering Decoherence Errors in the Simulation of Quantum Circuits Using Decision Diagrams

TL;DR

This paper enhances quantum circuit simulation by integrating decoherence errors into decision diagram-based methods, significantly improving simulation efficiency and accuracy for real quantum devices.

Contribution

It introduces a novel approach to incorporate decoherence errors into decision diagram-based quantum circuit simulators, addressing a key gap in existing methods.

Findings

Decoherence error consideration improves simulation performance by several orders of magnitude.

Proposed solutions effectively mitigate negative effects of decoherence errors.

Experiments demonstrate practical benefits for simulating real quantum hardware.

Abstract

By using quantum mechanical effects, quantum computers promise significant speedups in solving problems intractable for conventional computers. However, despite recent progress they remain limited in scaling and availability-making quantum software and hardware development heavily reliant on quantum simulators running on conventional hardware. However, most of those simulators mimic perfect quantum computers and, hence, ignore the fragile nature of quantum mechanical effects which frequently yield to decoherence errors in real quantum devices. Considering those errors during the simulation is complex, but necessary in order to tailor quantum algorithms for specific devices. Thus far, most state-of-the-art simulators considering decoherence errors rely on (exponentially) large array representations. As an alternative, simulators based on decision diagrams have been shown very promising for simulation of quantum circuits in general, but have not supported decoherence errors yet. In this work, we are closing this gap. We investigate how the consideration of decoherence errors affects the simulation performance of approaches based on decision diagrams and propose advanced solutions to mitigate negative effects. Experiments confirm that this yields improvements of several orders of magnitudes compared to a naive consideration of errors.