keyword

surface codes

Surface codes are a class of topological quantum error-correcting codes that protect fragile quantum information by distributing it across a two-dimensional lattice of physical qubits. In these systems, data qubits and measurement qubits are arranged on a planar grid, where quantum errors are detected through localized stabilizer measurements involving only neighboring qubits. By relying solely on nearest-neighbor physical interactions and exhibiting a relatively high error tolerance threshold, surface codes minimize hardware complexity and provide a leading practical framework for building scalable, fault-tolerant quantum computers.

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Designing Quantum Error Correcting Codes to fit decoders via Reinforcement Learning

Omer S. Sella, Robert Pinsler, Thomas Heinis

OrganizationsImperial College LondonMicrosoft

Why you should read this

Develops a reinforcement learning framework using Proximal Policy Optimization to generate Bivariate Bicycle quantum error-correcting codes tailored specifically to maximize the performance of chosen decoder architectures.

We present a reinforcement learning (RL) approach to the co-design of stabilizer sets of Quantum Error Correcting Codes (QECCs) and decoders. We show how to produce a generative model that produces Bivariate Bicycle (BB) codes based on the choice of decoder. Specifically, we fix a decoder architecture and use Proximal Policy Optimisation (PPO) to train an agent over BB codes to maximise decoder performance under a depolarising channel noise model.

Source

https://arxiv.org/pdf/2608.15754.pdf

Added

2026-09-30