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Quantum Error Correction Fault Tolerance Quantum Machine Learning Variational Hybrid Quantum Algorithms

Learning Better Error Correction Codes with Hybrid Quantum-Assisted Machine Learning

arXiv
Authors: Yariv Yanay

Year

2026

Paper ID

3927

Status

Preprint

Abstract Read

~2 min

Abstract Words

102

Citations

N/A

Abstract

Quantum error correction is one of the fundamental building blocks of digital quantum computation. The Quantum Lego formalism has introduced a systematic way of constructing new stabilizer codes out of basic lego-like building blocks, which in previous work we have used to generate improved error correcting codes via an automated reinforcement learning process. Here, we take this a step further and show the use of a hybrid classical-quantum algorithm. We combine classical reinforcement learning with calls to two commercial quantum devices to search for a stabilizer code to correct errors specific to the device, as well as an induced photon loss error.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • Quantum error correction is one of the fundamental building blocks of digital quantum computation.

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