Revisiting the Mapping of Quantum Circuits: Entering the Multi-Core Era

TL;DR

This paper introduces the Hungarian Qubit Assignment (HQA) algorithm for quantum circuit mapping in multi-core architectures, significantly reducing inter-core communication and execution time, thus advancing scalable quantum computing.

Contribution

The paper presents the HQA algorithm, a novel method for optimizing qubit-to-core assignments to minimize non-local communications in multi-core quantum systems.

Findings

HQA achieves 4.9x faster execution times

HQA reduces non-local communications by 1.6x

Theoretical bounds on non-local communications are derived

Abstract

Quantum computing represents a paradigm shift in computation, offering the potential to solve complex problems intractable for classical computers. Although current quantum processors already consist of a few hundred of qubits, their scalability remains a significant challenge. Modular quantum computing architectures have emerged as a promising approach to scale up quantum computing systems. This paper delves into the critical aspects of distributed multi-core quantum computing, focusing on quantum circuit mapping, a fundamental task to successfully execute quantum algorithms across cores while minimizing inter-core communications. We derive the theoretical bounds on the number of non-local communications needed for random quantum circuits and introduce the Hungarian Qubit Assignment (HQA) algorithm, a multi-core mapping algorithm designed to optimize qubit assignments to cores with the aim of reducing inter-core communications. Our exhaustive evaluation of HQA against state-of-the-art circuit mapping algorithms for modular architectures reveals a $4.9\times$ and $1.6\times$ improvement in terms of execution time and non-local communications, respectively, compared to the best performing algorithm. HQA emerges as a very promising scalable approach for mapping quantum circuits into multi-core architectures, positioning it as a valuable tool for harnessing the potential of quantum computing at scale.