Promatch: Extending the Reach of Real-Time Quantum Error Correction with Adaptive Predecoding
Narges Alavisamani, Suhas Vittal, Ramin Ayanzadeh, Poulami Das,, Moinuddin Qureshi

TL;DR
Promatch introduces an adaptive predecoding framework that significantly extends the reach of real-time quantum error correction, enabling decoding of surface codes up to distance 13 with high accuracy.
Contribution
This work presents Promatch, a novel real-time adaptive predecoder that improves the decoding of larger surface codes by converting high Hamming weight syndromes into manageable low-weight syndromes.
Findings
First real-time decoding of surface codes of distances 11 and 13.
Achieves an LER of 2.6×10^{-14} for distance 13.
Concurrent use with Astrea-G matches MWPM accuracy for distance 13.
Abstract
Fault-tolerant quantum computing relies on Quantum Error Correction, which encodes logical qubits into data and parity qubits. Error decoding is the process of translating the measured parity bits into types and locations of errors. To prevent a backlog of errors, error decoding must be performed in real-time. Minimum Weight Perfect Matching (MWPM) is an accurate decoding algorithm for surface code, and recent research has demonstrated real-time implementations of MWPM (RT-MWPM) for a distance of up to 9. Unfortunately, beyond d=9, the number of flipped parity bits in the syndrome, referred to as the Hamming weight of the syndrome, exceeds the capabilities of existing RT-MWPM decoders. In this work, our goal is to enable larger distance RT-MWPM decoders by using adaptive predecoding that converts high Hamming weight syndromes into low Hamming weight syndromes, which are accurately…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Computational Physics and Python Applications
