QAOA performance improved by error detection for better optimization results
Toward Fault-Tolerant Variational Optimization: QAOA under [[4,2,2]] Error Detection
Emerging Technologies
Summary
Quantum computers need to handle errors to work well. This paper shows how using a special error-detecting code can improve a quantum algorithm called QAOA, which tries to solve optimization problems. The authors designed a new way for parts of the computer to talk while checking for errors. Their tests suggest this error-detection method can help get better answers more often, making quantum optimization more reliable in the near future.
What this means in practice
- •For quantum algorithm developers: Integrate partial error detection into QAOA circuits to increase the success rate of sampling optimal solutions under realistic noise conditions.
- •For quantum hardware engineers: Implement ancilla-mediated logical gates between error-detected blocks to enhance error resilience in near-term quantum processors running optimization tasks.
Authors
Matteo Robert Child, Emanuele Dri, Giacomo Vitali, Chiara Vercellino, Alberto Leporati
Abstract
We present a partially fault-tolerant implementation of QAOA based on the $[[4,2,2]]$ error-detection code, targeting the Max-Cut problem on a square graph. Our main contribution is a novel ancilla-mediated logical $R_{ZZ}$ gate enabling interactions between qubits in different $[[4,2,2]]$ blocks. We evaluate unencoded and encoded circuits under five noise models, with both all-to-all and grid-routed connectivity, using the Cirq and qsimcirq frameworks with parallel CPU execution. Post-selection on stabilizer measurements consistently improves the probability of sampling optimal bitstrings, with five measurements providing the strongest benefit. These results support error-detection as a practical near-term strategy for improving the quality of variational quantum algorithms.