To run an algorithm on a quantum computer, one must choose an assignment from logical qubits in a circuit to physical qubits on quantum hardware. This task of initial qubit placement, or qubit allocation, is especially important on present-day quantum computers which have a limited number of qubits, connectivity constraints, and varying gate fidelities. In this work we formulate and implement the qubit placement problem as a quadratic, unconstrained binary optimization (QUBO) problem and solve it using simulated annealing to obtain a spectrum of initial placements. Compared to contemporary allocation methods available in t|ket⟩ and Qiskit, the QUBO method yields allocations with improved circuit depth for >50% of a large set of benchmark circuits, with many also requiring fewer CX gates.
@article{arxiv.2009.00140,
title = {A QUBO Formulation for Qubit Allocation},
author = {Bryan Dury and Olivia Di Matteo},
journal= {arXiv preprint arXiv:2009.00140},
year = {2020}
}
Comments
17 pages, 15 figures; updated some figures for clarity