Scalable surface code decoders with parallelization in time

• URL: http://arxiv.org/abs/2209.09219v2
• Date: Thu, 29 Sep 2022 21:11:40 GMT
• Title: Scalable surface code decoders with parallelization in time
• Authors: Xinyu Tan, Fang Zhang, Rui Chao, Yaoyun Shi, Jianxin Chen
• Abstract summary: We introduce a sliding-window decoding scheme that provides fast classical processing for the surface code through parallelism. Our scheme divides the syndromes in spacetime into overlapping windows along the time direction, which can be decoded in parallel with any inner decoder.
• Score: 8.28402656078529
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Fast classical processing is essential for most quantum fault-tolerance architectures. We introduce a sliding-window decoding scheme that provides fast classical processing for the surface code through parallelism. Our scheme divides the syndromes in spacetime into overlapping windows along the time direction, which can be decoded in parallel with any inner decoder. With this parallelism, our scheme can solve the decoding throughput problem as the code scales up, even if the inner decoder is slow. When using min-weight perfect matching and union-find as the inner decoders, we observe circuit-level thresholds of $0.68\%$ and $0.55\%$, respectively, which are almost identical to $0.70\%$ and $0.55\%$ for the batch decoding.

Related papers

• Decoding across transversal Clifford gates in the surface code [0.7100520098029438]
  We show how one can decode across an arbitrary sequence of window gates for the unrotated surface code.<n>Our work highlights the complexity and interest in efficient decoding of fast logic for the surface code.
  arXiv  Detail & Related papers  (2025-05-19T18:00:02Z)
• Fast correlated decoding of transversal logical algorithms [67.01652927671279]
  Quantum error correction (QEC) is required for large-scale computation, but incurs a significant resource overhead.<n>Recent advances have shown that by jointly decoding logical qubits in algorithms composed of logical gates, the number of syndrome extraction rounds can be reduced.<n>Here, we reform the problem of decoding circuits by directly decoding relevant logical operator products as they propagate through the circuit.
  arXiv  Detail & Related papers  (2025-05-19T18:00:00Z)
• Predictive Window Decoding for Fault-Tolerant Quantum Programs [5.258081366634739]
  Real-time decoding is a key ingredient in future fault-tolerant quantum systems. Windowed decoding schemes require that some decoding tasks be delayed until others have completed. We introduce a speculative window decoding scheme, taking inspiration from branch prediction in classical computer architecture. We find that speculation reduces application runtimes by 40% on average compared to prior parallel window decoders.
  arXiv  Detail & Related papers  (2024-12-06T15:17:18Z)
• Quantum error correction below the surface code threshold [107.92016014248976]
  Quantum error correction provides a path to reach practical quantum computing by combining multiple physical qubits into a logical qubit. We present two surface code memories operating below a critical threshold: a distance-7 code and a distance-5 code integrated with a real-time decoder. Our results present device performance that, if scaled, could realize the operational requirements of large scale fault-tolerant quantum algorithms.
  arXiv  Detail & Related papers  (2024-08-24T23:08:50Z)
• Spatially parallel decoding for multi-qubit lattice surgery [0.10713888959520208]
  Running quantum algorithms protected by quantum error correction requires a real time, classical decoder. Most prior work on real time decoding has focused on an isolated logical qubit encoded in the surface code. For surface code, quantum programs of utility will require multi-qubit interactions performed via lattice surgery. A large merged patch can arise during lattice surgery -- possibly as large as the entire device.
  arXiv  Detail & Related papers  (2024-03-03T00:17:13Z)
• Progressive-Proximity Bit-Flipping for Decoding Surface Codes [8.971989179518214]
  Topological quantum codes, such as toric and surface codes, are excellent candidates for hardware implementation. Existing decoders often fall short of meeting requirements such as having low computational complexity. We propose a novel bit-flipping (BF) decoder tailored for toric and surface codes.
  arXiv  Detail & Related papers  (2024-02-24T22:38:05Z)
• Break the Sequential Dependency of LLM Inference Using Lookahead Decoding [27.87483106859749]
  Lookahead decoding is an exact, parallel decoding algorithm for large language models (LLMs) Our implementation can speed up autoregressive decoding by up to 1.8x on MT-bench and 4x with strong scaling on multiple GPUs in code completion tasks.
  arXiv  Detail & Related papers  (2024-02-03T06:37:50Z)
• Fast Chain-of-Thought: A Glance of Future from Parallel Decoding Leads to Answers Faster [61.83949316226113]
  FastCoT is a model-agnostic framework based on parallel decoding. We show that FastCoT saves inference time by nearly 20% with only a negligible performance drop compared to the regular approach.
  arXiv  Detail & Related papers  (2023-11-14T15:56:18Z)
• Belief propagation as a partial decoder [0.0]
  We present a new two-stage decoder that accelerates the decoding cycle and boosts accuracy. In the first stage, a partial decoder based on belief propagation is used to correct errors that occurred with high probability. In the second stage, a conventional decoder corrects any remaining errors.
  arXiv  Detail & Related papers  (2023-06-29T17:44:20Z)
• Scalable Quantum Error Correction for Surface Codes using FPGA [67.74017895815125]
  A fault-tolerant quantum computer must decode and correct errors faster than they appear. We report a distributed version of the Union-Find decoder that exploits parallel computing resources for further speedup. The implementation employs a scalable architecture called Helios that organizes parallel computing resources into a hybrid tree-grid structure.
  arXiv  Detail & Related papers  (2023-01-20T04:23:00Z)
• Parallel window decoding enables scalable fault tolerant quantum computation [2.624902795082451]
  We present a methodology that parallelizes the decoding problem and achieves almost arbitrary syndrome processing speed. Our parallelization requires some classical feedback decisions to be delayed, leading to a slow-down of the logical clock speed. Using known auto-teleportation gadgets the slow-down can be eliminated altogether in exchange for increased qubit overhead.
  arXiv  Detail & Related papers  (2022-09-18T12:37:57Z)
• Graph Neural Networks for Channel Decoding [71.15576353630667]
  We showcase competitive decoding performance for various coding schemes, such as low-density parity-check (LDPC) and BCH codes. The idea is to let a neural network (NN) learn a generalized message passing algorithm over a given graph. We benchmark our proposed decoder against state-of-the-art in conventional channel decoding as well as against recent deep learning-based results.
  arXiv  Detail & Related papers  (2022-07-29T15:29:18Z)
• Rapid Person Re-Identification via Sub-space Consistency Regularization [51.76876061721556]
  Person Re-Identification (ReID) matches pedestrians across disjoint cameras. Existing ReID methods adopting real-value feature descriptors have achieved high accuracy, but they are low in efficiency due to the slow Euclidean distance computation. We propose a novel Sub-space Consistency Regularization (SCR) algorithm that can speed up the ReID procedure by 0.25$ times.
  arXiv  Detail & Related papers  (2022-07-13T02:44:05Z)
• Fast Interleaved Bidirectional Sequence Generation [90.58793284654692]
  We introduce a decoder that generates target words from the left-to-right and right-to-left directions simultaneously. We show that we can easily convert a standard architecture for unidirectional decoding into a bidirectional decoder. Our interleaved bidirectional decoder (IBDecoder) retains the model simplicity and training efficiency of the standard Transformer.
  arXiv  Detail & Related papers  (2020-10-27T17:38:51Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.