Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz
Ge Yan, Mengfei Ran, Ruocheng Wang, Kaisen Pan, Junchi Yan
Abstract
With the arrival of the Noisy Intermediate-Scale Quantum (NISQ) era, Variational Quantum Algorithms (VQAs) have emerged to obtain possible quantum advantage. In particular, how to effectively incorporate hard constraints in VQAs remains a critical and open question. In this paper, we manage to combine the Hamming Weight Preserving ansatz with a topological-aware parity check on physical qubits to enforce error mitigation and further hard constraints. We demonstrate the combination significantly outperforms peer VQA methods on both quantum chemistry problems and constrained combinatorial optimization problems e.g. Quadratic Assignment Problem. Intensive experimental results on both simulators and superconducting quantum processors are provided to verify that the combination of HWP ansatz with parity check is among the most promising candidates to demonstrate quantum advantages in the NISQ era to solve more realistic problems.
BibTeX
@inproceedings{
yan2024rethinking,
title={Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz},
author={Ge Yan and Mengfei Ran and Ruocheng Wang and Kaisen Pan and Junchi Yan},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=aIuByRyHhV}
}