Mapping quantum algorithms to multi-core quantum computing architectures

TL;DR

This paper discusses the challenges and solutions for mapping quantum algorithms onto multi-core quantum architectures, focusing on reducing inter-core communication and analyzing scalability.

Contribution

It introduces a detailed discussion of the quantum circuit mapping problem for multi-core architectures and evaluates a partitioning-based mapping method.

Findings

Partitioning over time graph approach improves mapping efficiency.

Scalability analysis highlights potential for larger multi-core quantum systems.

Mapping reduces inter-core communication costs.

Abstract

Current monolithic quantum computer architectures have limited scalability. One promising approach for scaling them up is to use a modular or multi-core architecture, in which different quantum processors (cores) are connected via quantum and classical links. This new architectural design poses new challenges such as the expensive inter-core communication. To reduce these movements when executing a quantum algorithm, an efficient mapping technique is required. In this paper, a detailed critical discussion of the quantum circuit mapping problem for multi-core quantum computing architectures is provided. In addition, we further explore the performance of a mapping method, which is formulated as a partitioning over time graph problem, by performing an architectural scalability analysis.