Near-optimal decoding algorithm for color codes using Population Annealing

• URL: http://arxiv.org/abs/2405.03776v1
• Date: Mon, 6 May 2024 18:17:42 GMT
• Title: Near-optimal decoding algorithm for color codes using Population Annealing
• Authors: Fernando Martínez-García, Francisco Revson F. Pereira, Pedro Parrado-Rodríguez,
• Abstract summary: We implement a decoder that finds the recovery operation with the highest success probability. We study the decoder performance on a 4.8.8 color code lattice under different noise models.
• Score: 44.99833362998488
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The development and use of large-scale quantum computers relies on integrating quantum error-correcting (QEC) schemes into the quantum computing pipeline. A fundamental part of the QEC protocol is the decoding of the syndrome to identify a recovery operation with a high success rate. In this work, we implement a decoder that finds the recovery operation with the highest success probability by mapping the decoding problem to a spin system and using Population Annealing to estimate the free energy of the different error classes. We study the decoder performance on a 4.8.8 color code lattice under different noise models, including code capacity with bit-flip and depolarizing noise, and phenomenological noise, which considers noisy measurements, with performance reaching near-optimal thresholds. This decoding algorithm can be applied to a wide variety of stabilizer codes, including surface codes and quantum low-density parity-check (qLDPC) codes.

Related papers

• Breadth-first graph traversal union-find decoder [0.0]
  We develop variants of the union-find decoder that simplify its implementation and provide potential decoding speed advantages. We show how these methods can be adapted to decode non-topological quantum low-density-parity-check codes.
  arXiv  Detail & Related papers  (2024-07-22T18:54:45Z)
• Testing the Accuracy of Surface Code Decoders [55.616364225463066]
  Large-scale, fault-tolerant quantum computations will be enabled by quantum error-correcting codes (QECC) This work presents the first systematic technique to test the accuracy and effectiveness of different QECC decoding schemes.
  arXiv  Detail & Related papers  (2023-11-21T10:22:08Z)
• The END: An Equivariant Neural Decoder for Quantum Error Correction [73.4384623973809]
  We introduce a data efficient neural decoder that exploits the symmetries of the problem. We propose a novel equivariant architecture that achieves state of the art accuracy compared to previous neural decoders.
  arXiv  Detail & Related papers  (2023-04-14T19:46:39Z)
• Deep Quantum Error Correction [73.54643419792453]
  Quantum error correction codes (QECC) are a key component for realizing the potential of quantum computing. In this work, we efficiently train novel emphend-to-end deep quantum error decoders. The proposed method demonstrates the power of neural decoders for QECC by achieving state-of-the-art accuracy.
  arXiv  Detail & Related papers  (2023-01-27T08:16:26Z)
• Neural Belief Propagation Decoding of Quantum LDPC Codes Using Overcomplete Check Matrices [60.02503434201552]
  We propose to decode QLDPC codes based on a check matrix with redundant rows, generated from linear combinations of the rows in the original check matrix. This approach yields a significant improvement in decoding performance with the additional advantage of very low decoding latency.
  arXiv  Detail & Related papers  (2022-12-20T13:41:27Z)
• Quantum Error Correction via Noise Guessing Decoding [0.0]
  Quantum error correction codes (QECCs) play a central role in both quantum communications and quantum computation. This paper shows that it is possible to both construct and decode QECCs that can attain the maximum performance of the finite blocklength regime.
  arXiv  Detail & Related papers  (2022-08-04T16:18:20Z)
• Improved decoding of circuit noise and fragile boundaries of tailored surface codes [61.411482146110984]
  We introduce decoders that are both fast and accurate, and can be used with a wide class of quantum error correction codes. Our decoders, named belief-matching and belief-find, exploit all noise information and thereby unlock higher accuracy demonstrations of QEC. We find that the decoders led to a much higher threshold and lower qubit overhead in the tailored surface code with respect to the standard, square surface code.
  arXiv  Detail & Related papers  (2022-03-09T18:48:54Z)
• Efficient Concatenated Bosonic Code for Additive Gaussian Noise [0.0]
  Bosonic codes offer noise resilience for quantum information processing. We propose using a Gottesman-Kitaev-Preskill code to detect discard error-prone qubits and a quantum parity code to handle residual errors. Our work may have applications in a wide range of quantum computation and communication scenarios.
  arXiv  Detail & Related papers  (2021-02-02T08:01:30Z)

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.