Benchmarking Quantum Circuit Transformation with QKNOB Circuits

TL;DR

This paper introduces QKNOB, a benchmark for quantum circuit transformation that provides near-optimal transformations, enabling fair evaluation of algorithms like SABRE on real quantum hardware.

Contribution

The paper presents QKNOB, a novel benchmark construction method with near-optimal transformations, for unbiased evaluation of quantum circuit transformation algorithms.

Findings

SABRE performs best among tested algorithms on IBM Q Rochester and Google Sycamore.

QKNOB circuits have near-optimal SWAP count and depth overhead.

Significant performance gaps exist between current algorithms and near-optimal transformations.

Abstract

Current superconducting quantum devices impose strict connectivity constraints on quantum circuit execution, necessitating circuit transformation before executing quantum circuits on physical hardware. Numerous quantum circuit transformation (QCT) algorithms have been proposed. To enable faithful evaluation of state-of-the-art QCT algorithms, this paper introduces QKNOB (Qubit mapping Benchmark with Known Near-Optimality), a novel benchmark construction method for QCT. QKNOB circuits have built-in transformations with near-optimal (close to the theoretical optimum) SWAP count and depth overhead. QKNOB provides general and unbiased evaluation of QCT algorithms. Using QKNOB, we demonstrate that SABRE, the default Qiskit compiler, consistently achieves the best performance on the 53-qubit IBM Q Rochester and Google Sycamore devices for both SWAP count and depth objectives. Our results also reveal significant performance gaps relative to the near-optimal transformation costs of QKNOB. Our construction algorithm and benchmarks are open-source.