Snowflake: A Distributed Streaming Decoder

TL;DR

Snowflake is a distributed, streaming quantum error correction decoder for surface codes that improves accuracy and runtime efficiency over previous methods by eliminating processing overhead and enabling local, scalable implementation.

Contribution

It introduces a novel streaming decoding method for quantum error correction that reduces processing overhead and enhances accuracy and scalability.

Findings

25% more accurate than Union-Find decoder

Subquadratic runtime scaling in code distance

Distributed and local implementation

Abstract

We design Snowflake, a quantum error correction decoder that, for the surface code under circuit-level noise, is roughly 25% more accurate than the Union-Find decoder, with a better mean runtime scaling: subquadratic as opposed to cubic in the code distance. Our decoder runs in a streaming fashion and has a distributed, local implementation. In designing Snowflake, we propose a new method for general stream decoding that eliminates the processing overhead due to window overlap in existing windowing methods.