Fault-tolerant quantum algorithm improves Max-Cut solution accuracy
Toward Fault-Tolerant Variational Optimization: QAOA under [[4,2,2]] Error Detection
Emerging Technologies
Summary
Quantum computers can solve tricky problems like Max-Cut by using special algorithms, but errors in their calculations often cause mistakes. The authors studied a way to reduce these errors by protecting quantum bits using a method called error detection, specifically the [[4,2,2]] code. They created a new technique to link protected quantum bits and tested it under various conditions, finding that checking for errors five times helped find better solutions. This approach shows that detecting errors can make quantum algorithms work more reliably in near-term devices.
Quantum computingQAOAMax-Cut problemError detection code[[4,2,2]] codeFault toleranceAncilla qubitLogical gatePost-selectionVariational algorithms
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.