Powerful Quantum Circuit Resizing with Resource Efficient Synthesis

TL;DR

This paper presents two resource-efficient quantum circuit resizing algorithms that significantly reduce qubit counts by leveraging mid-circuit measurement and reset operations, improving quantum circuit optimization in the NISQ era.

Contribution

It introduces novel algorithms for quantum circuit resizing that utilize dependency rules and synthesis techniques to optimize qubit usage, including resizing previously unresizable circuits.

Findings

First algorithm reduces qubits by 61.6%.

Second algorithm achieves 20.7% average qubit reduction on unresizable circuits.

Resizing enhances quantum circuit efficiency in the NISQ era.

Abstract

In the noisy intermediate-scale quantum era, mid-circuit measurement and reset operations facilitate novel circuit optimization strategies by reducing a circuit's qubit count in a method called resizing. This paper introduces two such algorithms. The first one leverages gate-dependency rules to reduce qubit count by 61.6% or 45.3% when optimizing depth as well. Based on numerical instantiation and synthesis, the second algorithm finds resizing opportunities in previously unresizable circuits via dependency rules and other state-of-the-art tools. This resizing algorithm reduces qubit count by 20.7% on average for these previously impossible-to-resize circuits.