Improved decoding of circuit noise and fragile boundaries of tailored surface codes

• URL: http://arxiv.org/abs/2203.04948v5
• Date: Tue, 4 Jul 2023 15:26:28 GMT
• Title: Improved decoding of circuit noise and fragile boundaries of tailored surface codes
• Authors: Oscar Higgott, Thomas C. Bohdanowicz, Aleksander Kubica, Steven T. Flammia, Earl T. Campbell
• Abstract summary: 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.
• Score: 61.411482146110984
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Realizing the full potential of quantum computation requires quantum error correction (QEC), with most recent breakthrough demonstrations of QEC using the surface code. QEC codes use multiple noisy physical qubits to encode information in fewer logical qubits, enabling the identification of errors through a decoding process. This process increases the logical fidelity (or accuracy) making the computation more reliable. However, most fast (efficient runtime) decoders neglect important noise characteristics, thereby reducing their accuracy. In this work, we introduce decoders that are both fast and accurate, and can be used with a wide class of QEC codes including the surface code. Our decoders, named belief-matching and belief-find, exploit all noise information and thereby unlock higher accuracy demonstrations of QEC. Using the surface code threshold as a performance metric, we observe a threshold at 0.94\% error probability for our decoders, outperforming the 0.82\% threshold for a standard minimum-weight perfect matching decoder. We also tested our belief-matching decoders in a theoretical case study of codes tailored to a biased noise model. 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. Surprisingly, in the well-below threshold regime, the rectangular surface code becomes more resource-efficient than the tailored surface code, due to a previously unnoticed phenomenon that we call "fragile boundaries". Our decoders outperform all other fast decoders in terms of threshold and accuracy, enabling better results in current quantum error correction experiments and opening up new areas for theoretical case studies.

Related papers

• Local Clustering Decoder: a fast and adaptive hardware decoder for the surface code [0.0]
  We introduce the Local Clustering Decoder as a solution that simultaneously achieves the accuracy and speed requirements of a real-time decoding system. Our decoder is implemented on FPGAs and exploits hardware parallelism to keep pace with the fastest qubit types. It enables one million error-free quantum operations with 4x fewer physical qubits when compared to standard non-adaptive decoding.
  arXiv  Detail & Related papers  (2024-11-15T16:43:59Z)
• Accelerating Error Correction Code Transformers [56.75773430667148]
  We introduce a novel acceleration method for transformer-based decoders. We achieve a 90% compression ratio and reduce arithmetic operation energy consumption by at least 224 times on modern hardware.
  arXiv  Detail & Related papers  (2024-10-08T11:07:55Z)
• 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)
• 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)
• 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)
• A Practical and Scalable Decoder for Topological Quantum Error Correction with Digital Annealer [0.5658123802733283]
  We propose an efficient and scalable decoder for quantum error correction using Fujitsu Digital Annealer (DA) In particular, we implement the proposed DA decoder for the surface code and perform detailed numerical experiments for various code to see its performance and scalability. It is also shown that the DA decoder has advantages over the Union-Find (UF) decoder from a variety of perspectives including hardware implementation.
  arXiv  Detail & Related papers  (2022-03-29T07:48:51Z)
• Scalable Neural Decoder for Topological Surface Codes [0.0]
  We present a neural network based decoder for a family of stabilizer codes subject to noise and syndrome measurement errors. The key innovation is to autodecode error syndromes on small scales by shifting a preprocessing window over the underlying code. We show that such a preprocessing step allows to effectively reduce the error rate by up to two orders of magnitude in practical applications.
  arXiv  Detail & Related papers  (2021-01-18T19:02:09Z)
• Cellular automaton decoders for topological quantum codes with noisy measurements and beyond [68.8204255655161]
  We propose an error correction procedure based on a cellular automaton, the sweep rule, which is applicable to a broad range of codes beyond topological quantum codes. For simplicity, we focus on the three-dimensional (3D) toric code on the rhombic dodecahedral lattice with boundaries and prove that the resulting local decoder has a non-zero error threshold. We find that this error correction procedure is remarkably robust against measurement errors and is also essentially insensitive to the details of the lattice and noise model.
  arXiv  Detail & Related papers  (2020-04-15T18:00:01Z)

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.