# A Beam Search Framework for Quantum Circuit Mapping

## TL;DR

This paper introduces a beam search framework to optimize quantum circuit mapping, reducing the number of SWAP gates needed for execution on quantum devices.

## Contribution

The novel contribution is a beam search framework that effectively reduces SWAP gates in quantum circuit mapping for NISQ devices.

## Key findings

- The proposed beam search framework reduces SWAP gates by an average of 44% compared to baseline methods.
- The method is effective for medium to large quantum circuits and works across various sizes and complexities.

## Abstract

In the era of noisy intermediate-scale quantum (NISQ) computing, the limited connectivity between qubits is one of the common physical limitations faced by current quantum computing devices. Quantum circuit mapping methods transform quantum circuits into equivalent circuits that satisfy physical connectivity constraints by remapping logical qubits, making them executable. The optimization problem of quantum circuit mapping has NP-hard computational complexity, and existing heuristic mapping algorithms still have significant potential for optimization in terms of the number of quantum gates generated. To reduce the number of SWAP gates inserted during mapping, the solution space of the mapping problem is represented as a tree structure, and the mapping process is equivalent to traversing this tree structure. To effectively and efficiently complete the search process, a beam search framework (BSF) is proposed for solving quantum circuit mapping. By iteratively selecting, expanding, and making decisions, high-quality target circuits are generated. Experimental results show that this method can significantly reduce the number of inserted SWAP gates on medium to large circuits, achieving an average reduction of 44% compared to baseline methods, and is applicable to circuits of various sizes and complexities.