---
title: "Reinforcement learning control of quantum error correction"
url: https://daily.dev/posts/reinforcement-learning-control-of-quantum-error-correction-ba4i1ryvs
source_url: https://www.nature.com/articles/s41586-026-10759-2
type: article
source: "Nature"
published: 2026-07-08T15:32:51.958Z
updated: 2026-07-09T08:21:43.523Z
tags: ["quantum-computing", "reinforcement-learning"]
reading_time: 32
upvotes: 1
comments: 0
language: en
---

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# Reinforcement learning control of quantum error correction

**[Nature](https://daily.dev/sources/nature)** · 32 min read · 1 upvotes · 0 comments

## Summary

Google Quantum AI demonstrates a framework that unifies quantum error correction (QEC) with real-time calibration using reinforcement learning (RL). Instead of halting computation for recalibration, the RL agent repurposes error-detection events as a learning signal to continuously steer over 1,000 control parameters on the Willow superconducting processor. This achieves a 3.5-fold improvement in logical error rate stability against injected drift and sets record logical error rates: 7.72×10⁻⁴ for the distance-7 surface code and 8.19×10⁻³ for the distance-5 colour code. Numerical simulations confirm scalability to distance-15 codes with ~40,000 parameters, with convergence rate independent of system size, enabling a quantum computer that learns from its errors without interrupting computation.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.nature.com/articles/s41586-026-10759-2>

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---

Tags: [#quantum-computing](https://daily.dev/tags/quantum-computing), [#reinforcement-learning](https://daily.dev/tags/reinforcement-learning)

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