Neural decoders for quantum error correction on the 3D Toric code. Includes implementation of TheEND decoder for 2D toric code corrections.
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Updated
Jun 13, 2025 - Python
Neural decoders for quantum error correction on the 3D Toric code. Includes implementation of TheEND decoder for 2D toric code corrections.
Biased Pauli noise (weighted matching) and heralded erasure (from-scratch peeling decoder) on the toric code: reproducing the 0.5 erasure threshold and contrasting noise profiles.
A Python simulation toolkit for toric-code decoding with minimum-weight perfect matching under perfect and noisy syndrome measurements.
Experiments with the Toric code: Circuit-level noise simulations and Equivariant Neural Decoder implementation.
Simulation study: how much does imperfect erasure-flag efficiency cost matching decoding of the toric code, does recalibrating the unflagged prior help, and how does a flag-aware neural decoder compare? L=3-7, 3 seeds.
Simulation study of how many stabiliser measurements and syndrome-extraction CNOTs erasure recovery needs when only checks touching erased qubits are measured, on toric and bivariate bicycle codes (n=32-144), with noisy-readout sweep.
Code & data for "CHSH-Form Values Above 2 for Standard Fibonacci Anyons, and the Non-Topological Origin of Finite-Size Sector–CHSH Mutual Information in Z2 Lattice Gauge Theory."
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