Vine codes generalize directional codes to open planar boundaries, delivering up to 28% fewer data/measure qubits at circuit distance 7 and better simulated performance than the surface code at 10^{-3} noise while using fewer total qubits.
arXiv preprint arXiv:2406.14527 (2024)
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Subsystem bivariate bicycle codes achieve high-rate BB logical qubits with local four-qubit gauge checks, yielding examples such as [[108,12,6]] that outperform surface-code alternatives.
An algorithm converts topological data of 2D bulk stabilizer codes into 1D boundary subsystem codes via operator algebra and normal forms, enabling automatic generation of boundaries and defects demonstrated on toric, color, and other codes.
Degeneracy in quantum LDPC codes equals classical code shortening at the decoder, enabling impulse decoding that beats BP+OSD plus a residual-error follow-up step.
MBBP-LD creates multiple cycle-free subtree decompositions of the Tanner graph to run parallel BP decodings on quantum LDPC codes, cutting error rates by up to 30% versus BP-OSD and 20% versus BPGD on tested bivariate bicycle codes with fewer total iterations.
Edge-coloring eliminates automorphisms in low-weight stabilizer subgraphs of generalized bicycle codes, enabling improved anisotropic min-sum decoding.
Local syndrome-based preprocessing accelerates BP decoders for quantum LDPC codes, delivering up to 10x speedup on the [[144,12,12]] code while maintaining or improving logical error rates.
A collaborative BP decoder for QLDPC codes uses check node removal and information measurements to mitigate trapping sets via increased qubit separation.
A two-level decoder scheduling framework reduces classical processing requirements for quantum error correction by 10-40% on fault-tolerant benchmarks by managing bursty workloads as shared resources.
citing papers explorer
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Vine Codes: Low-Overhead Quantum LDPC Codes on a Planar Square Grid
Vine codes generalize directional codes to open planar boundaries, delivering up to 28% fewer data/measure qubits at circuit distance 7 and better simulated performance than the surface code at 10^{-3} noise while using fewer total qubits.
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Topological subsystem bivariate bicycle codes with four-qubit check operators
Subsystem bivariate bicycle codes achieve high-rate BB logical qubits with local four-qubit gauge checks, yielding examples such as [[108,12,6]] that outperform surface-code alternatives.
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Operator algebra and algorithmic construction of boundaries and defects in (2+1)D topological Pauli stabilizer codes
An algorithm converts topological data of 2D bulk stabilizer codes into 1D boundary subsystem codes via operator algebra and normal forms, enabling automatic generation of boundaries and defects demonstrated on toric, color, and other codes.
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Impulse Decoding of Quantum LDPC Codes: Equivalence of Degeneracy and Code-Shortening
Degeneracy in quantum LDPC codes equals classical code shortening at the decoder, enabling impulse decoding that beats BP+OSD plus a residual-error follow-up step.
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Multiple-Bases Belief Propagation List Decoding for Quantum LDPC Codes
MBBP-LD creates multiple cycle-free subtree decompositions of the Tanner graph to run parallel BP decodings on quantum LDPC codes, cutting error rates by up to 30% versus BP-OSD and 20% versus BPGD on tested bivariate bicycle codes with fewer total iterations.
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Edge-Based Anisotropic Decoding for Generalized Bicycle Codes
Edge-coloring eliminates automorphisms in low-weight stabilizer subgraphs of generalized bicycle codes, enabling improved anisotropic min-sum decoding.
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Accelerating BP-based decoders for QLDPC Codes with Local Syndrome-Based Preprocessing
Local syndrome-based preprocessing accelerates BP decoders for quantum LDPC codes, delivering up to 10x speedup on the [[144,12,12]] code while maintaining or improving logical error rates.
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Decoding Quantum LDPC Codes using Collaborative Check Node Removal
A collaborative BP decoder for QLDPC codes uses check node removal and information measurements to mitigate trapping sets via increased qubit separation.
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Managing Classical Processing Requirements for Quantum Error Correction
A two-level decoder scheduling framework reduces classical processing requirements for quantum error correction by 10-40% on fault-tolerant benchmarks by managing bursty workloads as shared resources.