English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Quantum error correction (QEC) is required in quantum computers to mitigate the effect of errors on physical qubits. When adopting a QEC scheme based on surface codes, error decoding is the most computationally expensive task in the classical electronic back-end. Decoders employing neural networks (NN) are well-suited for this task but their hardware implementation has not been presented yet. This work presents a space exploration of fully connected feed-forward NN decoders for small distance surface codes. The goal is to optimize the NN for the high-decoding performance, while keeping a minimalistic hardware implementation. This is needed to meet the tight delay constraints of real-time surface code decoding. We demonstrate that hardware-based NN-decoders can achieve the high-decoding performance comparable to other state-of-the-art decoding algorithms whilst being well below the tight delay requirements <inline-formula><tex-math notation="LaTeX">$(\approx 440\ \text{ns})$</tex-math></inline-formula> of current solid-state qubit technologies for both application-specific integrated circuit designs <inline-formula><tex-math notation="LaTeX">$(< \!30\ \text{ns})$</tex-math></inline-formula> and field-programmable gate array implementations <inline-formula><tex-math notation="LaTeX">$(<\! 90\ \text{ns})$</tex-math></inline-formula>. These results indicate that NN-decoders are viable candidates for further exploration of an integrated hardware implementation in future large-scale quantum computers.

Neural-Network Decoders for Quantum Error Correction Using Surface Codes: A Space Exploration of the Hardware Cost-Performance Tradeoffs