Conservation laws and quantum error correction: towards a generalised
matching decoder
- URL: http://arxiv.org/abs/2207.06428v2
- Date: Wed, 28 Feb 2024 03:39:23 GMT
- Title: Conservation laws and quantum error correction: towards a generalised
matching decoder
- Authors: Benjamin J. Brown
- Abstract summary: We explore decoding algorithms for the surface code, a prototypical quantum low-density parity-check code.
The decoder works by exploiting underlying structure that arises due to materialised symmetries among surface-code stabilizer elements.
We propose a systematic way of constructing a minimum-weight perfect-matching decoder for codes with certain characteristic properties.
- Score: 2.1756081703276
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Decoding algorithms are essential to fault-tolerant quantum-computing
architectures. In this perspective we explore decoding algorithms for the
surface code; a prototypical quantum low-density parity-check code that
underlies many of the leading efforts to demonstrate scalable quantum
computing. Central to our discussion is the minimum-weight perfect-matching
decoder. The decoder works by exploiting underlying structure that arises due
to materialised symmetries among surface-code stabilizer elements. By
concentrating on these symmetries, we begin to address the question of how a
minimum-weight perfect-matching decoder might be generalised for other families
of codes. We approach this question first by investigating examples of matching
decoders for other codes. These include decoding algorithms that have been
specialised to correct for noise models that demonstrate a particular structure
or bias with respect to certain codes. In addition to this, we propose a
systematic way of constructing a minimum-weight perfect-matching decoder for
codes with certain characteristic properties. The properties we make use of are
common among topological codes. We discuss the broader applicability of the
proposal, and we suggest some questions we can address that may show us how to
design a generalised matching decoder for arbitrary stabilizer codes.
Related papers
- Generalizing the matching decoder for the Chamon code [1.8416014644193066]
We implement a matching decoder for a three-dimensional, non-CSS, low-density parity check code known as the Chamon code.
We find that a generalized matching decoder that is augmented by a belief-propagation step prior to matching gives a threshold of 10.5% for depolarising noise.
arXiv Detail & Related papers (2024-11-05T19:00:12Z) - 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) - Learning Linear Block Error Correction Codes [62.25533750469467]
We propose for the first time a unified encoder-decoder training of binary linear block codes.
We also propose a novel Transformer model in which the self-attention masking is performed in a differentiable fashion for the efficient backpropagation of the code gradient.
arXiv Detail & Related papers (2024-05-07T06:47:12Z) - 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) - 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) - Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes [59.55193427277134]
Reed-Muller (RM) codes achieve the capacity of general binary-input memoryless symmetric channels.
RM codes only admit limited sets of rates.
Efficient decoders are available for RM codes at finite lengths.
arXiv Detail & Related papers (2023-01-16T04:11:14Z) - Adversarial Neural Networks for Error Correcting Codes [76.70040964453638]
We introduce a general framework to boost the performance and applicability of machine learning (ML) models.
We propose to combine ML decoders with a competing discriminator network that tries to distinguish between codewords and noisy words.
Our framework is game-theoretic, motivated by generative adversarial networks (GANs)
arXiv Detail & Related papers (2021-12-21T19:14:44Z) - Dense Coding with Locality Restriction for Decoder: Quantum Encoders vs.
Super-Quantum Encoders [67.12391801199688]
We investigate dense coding by imposing various locality restrictions to our decoder.
In this task, the sender Alice and the receiver Bob share an entangled state.
arXiv Detail & Related papers (2021-09-26T07:29:54Z) - Trellis Decoding For Qudit Stabilizer Codes And Its Application To Qubit
Topological Codes [3.9962751777898955]
We show that trellis decoders have strong structure, extend the results using classical coding theory as a guide, and demonstrate a canonical form from which the structural properties of the decoding graph may be computed.
The modified decoder works for any stabilizer code $S$ and separates into two parts: a one-time, offline which builds a compact, graphical representation of the normalizer of the code, $Sperp$, and a quick, parallel, online computation using the Viterbi algorithm.
arXiv Detail & Related papers (2021-06-15T16:01:42Z) - Correcting spanning errors with a fractal code [7.6146285961466]
We propose an efficient decoder for the Fibonacci code'; a two-dimensional classical code that mimics the fractal nature of the cubic code.
We perform numerical experiments that show our decoder is robust to one-dimensional, correlated errors.
arXiv Detail & Related papers (2020-02-26T19:00:06Z)
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.