Routed tile codes on a 2D nearest-neighbor grid achieve circuit-level thresholds of 0.11%-0.13% under SI1000 noise and become more qubit-efficient than the surface code below a physical error rate of 0.08%.
arXiv preprint arXiv:2503.10988 , year=
13 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
abstract
Tesseract is a Most-Likely Error decoder designed for low-density-parity-check quantum error-correcting codes. Tesseract conducts a search through a graph on the set of all subsets of errors to find the lowest cost subset of errors consistent with the input syndrome. Although this graph is exponentially large, the search can be made efficient in practice for random errors using $A^*$ search technique along with a few pruning heuristics. We show through benchmark circuits for surface, color, and bivariate-bicycle codes that Tesseract is significantly faster than integer programming-based decoders while retaining comparable accuracy at moderate physical error rates. We also find that Tesseract can decode transversal CNOT protocols for surface codes on neutral atom quantum computers. Finally, we compare surface code and bivariate bicycle code circuits, finding that the [[144,12,12]] bivariate bicycle code is $14\times$ to $19\times$ more efficient than surface codes using our most-likely error decoding, whereas using correlated matching and BP+OSD decoders would have implied only a $10\times$ improvement. Assuming instead that long-range couplers are $10\times$ noisier, the improvement drops to around $4\times$ using Tesseract or $2\times$ using correlated matching and BP+OSD.
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quant-ph 13years
2026 13roles
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Neural decoder for quantum LDPC codes achieves ~10^{-10} logical error at 0.1% physical error with 17x improvement and high throughput, enabling practical fault tolerance at modest code sizes.
Plaquette compiles realistic quantum hardware noise models into multiple sampler representations, showing that Pauli-twirled approximations can misestimate logical error rates by an order of magnitude compared to leakage-aware and near-Clifford methods.
The Frontier decoder approximates optimal quantum LDPC decoding via narrow-frontier dynamic programming, achieving near-optimal thresholds for surface and color codes plus state-of-the-art circuit-level performance with small retained lists.
Estimating DEM probabilities from experimental syndromes improves logical error rates by 5-10% in surface-code memory experiments on Google Willow and IBM ibm_miami without additional circuits or supervised fitting.
A forced-gap post-selection strategy using repeated Relay-BP decoder runs improves logical error rates by over 4x on 72- and 144-qubit bivariate bicycle codes at fixed post-selection rate.
Sparse Mamba Decoder processes only active defects in surface code syndromes using a 13-feature representation and Mamba backbone for O(k) complexity, reporting speedups and accuracy gains over dense decoders.
FTPrimitiveBench is a new benchmark suite for testing surface-code logical primitives under Pauli-biased, measurement-biased, and spatially non-uniform noise models, revealing that noise structure interacts distinctly with each primitive and decoder.
A resource-reusing FPGA architecture for GARI-structured message-passing decoding of quantum LDPC codes with correlated errors achieves 596 ns average latency and 6x lower resource use than prior GARI hardware on a VCU19P device.
New structural conditions on affine permutation matrices yield ultra-high-rate quantum LDPC codes (rate >1/2) with near-teraquop logical error rates under circuit-level noise on reconfigurable atom arrays.
A new 2D signal-rule local decoder for the toric code achieves exponential logical error suppression below a threshold under phenomenological noise with data and measurement errors.
Biased-noise ancillas (phase flips only) in bicycle bivariate and cyclic hypergraph product QLDPC codes increase effective fault distance, reduce short loops, and improve logical error rate by nearly 10x at 2e-3 circuit noise when bit flips are 50x rarer.
citing papers explorer
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Strictly Local Tile-Code Architectures on Two-Dimensional Planar Lattices
Routed tile codes on a 2D nearest-neighbor grid achieve circuit-level thresholds of 0.11%-0.13% under SI1000 noise and become more qubit-efficient than the surface code below a physical error rate of 0.08%.
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Scalable Neural Decoders for Practical Fault-Tolerant Quantum Computation
Neural decoder for quantum LDPC codes achieves ~10^{-10} logical error at 0.1% physical error with 17x improvement and high throughput, enabling practical fault tolerance at modest code sizes.
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Logical error estimation from syndrome data of surface-code experiments
Estimating DEM probabilities from experimental syndromes improves logical error rates by 5-10% in surface-code memory experiments on Google Willow and IBM ibm_miami without additional circuits or supervised fitting.
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Forced Gap Post-Selection for Quantum LDPC Codes and their Operations
A forced-gap post-selection strategy using repeated Relay-BP decoder runs improves logical error rates by over 4x on 72- and 144-qubit bivariate bicycle codes at fixed post-selection rate.
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Sparse Mamba Decoder for Quantum Error Correction: Efficient Defect-Centric Processing of Surface Code Syndromes
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FTPrimitiveBench: A Benchmark Suite For Logical Computation Under Hardware-Motivated and Biased Noise Models
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