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Quantum Machine Learning Quantum Optimization Quantum Circuit Design Gate Engineering Quantum Compilation Routing Architecture

Divide-et-impera Heuristic-based Randomized Search for the Qubit Routing Problem

arXiv
Authors: Marco Baioletti, Fabrizio Fagiolo, Angelo Oddi, Riccardo Rasconi

Year

2025

Paper ID

16968

Status

Preprint

Abstract Read

~2 min

Abstract Words

98

Citations

N/A

Abstract

This paper introduces the DIRSH algorithm for the Qubit Routing Problem (QRP), using a heuristic-guided randomized divide-and-conquer strategy. The method splits the circuit into chunks and optimizes each one with a stochastic selection of gates and swaps. It balances global search, via restarts and adaptive tuning of bandit parameters with depth-sensitive local pruning. Tested on RevLib benchmarks mapped to the 20-qubit IBMQ Tokyo topology, DIRSH outperformed three LightSABRE variants across different time budgets, achieving shorter depths and fewer swaps. These results confirm that combining chunk-based decomposition with bandit-driven heuristics is effective for routing quantum circuits on NISQ devices.

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  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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  • This paper introduces the DIRSH algorithm for the Qubit Routing Problem (QRP), using a heuristic-guided randomized divide-and-conquer strategy.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2511.14644 [2] arXiv https://arxiv.org/abs/2511.14644 [3] Publisher https://arxiv.org/abs/2511.14644

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