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Topological quantum computing has recently proven itself to be a powerful computational model when constructing viable architectures for large scale computation. The topological model is constructed from the foundation of a error correction…

Quantum Physics · Physics 2013-06-24 Simon J. Devitt , Kae Nemoto

In this paper, we consider a simplified error-correcting problem: for a fixed encoding process, to find a cascade connected quantum channel such that the worst fidelity between the input and the output becomes maximum. With the use of the…

Quantum Physics · Physics 2007-05-23 Naoki Yamamoto , Shinji Hara , Koji Tsumura

For realizing a quantum memory we suggest to first encode quantum information via a quantum error correcting code and then concatenate combined decoding and re-encoding operations. This requires that the encoding and the decoding operation…

Quantum Physics · Physics 2007-05-23 Dirk Schlingemann

Quantum error correction and the use of quantum error correction codes is likely to be essential for the realisation of practical quantum computing. Because the error models of quantum devices vary widely, quantum codes which are tailored…

Quantum Physics · Physics 2024-09-23 Mark Webster , Dan Browne

The realization of fault-tolerant quantum computers hinges on the construction of high-speed, high-accuracy, real-time decoding systems. The persistent challenge lies in the fundamental trade-off between speed and accuracy: efforts to…

Quantum Physics · Physics 2025-10-30 Riki Toshio , Kaito Kishi , Jun Fujisaki , Hirotaka Oshima , Shintaro Sato , Keisuke Fujii

Different choices of quantum error-correcting codes can reduce the demands on the physical hardware needed to build a quantum computer. To achieve the full potential of a code, we must develop practical decoding algorithms that can correct…

Quantum Physics · Physics 2025-06-18 Zohar Schwartzman-Nowik , Benjamin J. Brown

Large-scale quantum computers have the potential to hold computational capabilities beyond conventional computers for certain problems. However, the physical qubits within a quantum computer are prone to noise and decoherence, which must be…

Quantum Physics · Physics 2024-06-06 Luka Skoric , Dan E. Browne , Kenton M. Barnes , Neil I. Gillespie , Earl T. Campbell

Major obstacles remain to the implementation of macroscopic quantum computing: hardware problems of noise, decoherence, and scaling; software problems of error correction; and, most important, algorithm construction. Finding truly quantum…

Quantum Physics · Physics 2020-07-17 Nathan Thompson , James Steck , Elizabeth Behrman

Noise is one of the central obstacles to building useful quantum computers, and quantum error correction (QEC) provides the framework for protecting quantum information against it. Unlike classical error correction, QEC must preserve…

Surface code error correction offers a highly promising pathway to achieve scalable fault-tolerant quantum computing. When operated as stabilizer codes, surface code computations consist of a syndrome decoding step where measured stabilizer…

Quantum Physics · Physics 2023-07-14 Spiro Gicev , Lloyd C. L. Hollenberg , Muhammad Usman

In the NISQ era, one of the most important bottlenecks for the realization of universal quantum computation is error correction. Stabiliser code is the most recognizable type of quantum error correction code. A scalable efficient decoder is…

Quantum Physics · Physics 2025-10-28 Wei-Wei Zhang , Zhuo Xia , Wei Zhao , Wei Pan , Haobin Shi

Surface codes are among the best candidates to ensure the fault-tolerance of a quantum computer. In order to avoid the accumulation of errors during a computation, it is crucial to have at our disposal a fast decoding algorithm to quickly…

Quantum Physics · Physics 2020-07-15 Nicolas Delfosse , Gilles Zémor

A fault-tolerant quantum computer will be supported by a classical decoding system interfacing with quantum hardware to perform quantum error correction. It is important that the decoder can keep pace with the quantum clock speed, within…

Quantum Physics · Physics 2023-03-17 Samuel C. Smith , Benjamin J. Brown , Stephen D. Bartlett

Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern machine learning tools, which are versatile and easy to use, have the potential to significantly improve…

Neurons and Cognition · Quantitative Biology 2020-07-06 Joshua I. Glaser , Ari S. Benjamin , Raeed H. Chowdhury , Matthew G. Perich , Lee E. Miller , Konrad P. Kording

Quantum computers are highly vulnerable to noise, necessitating the use of error-correcting codes to protect stored data. Errors must be continuously corrected over time to counteract decoherence using appropriate decoders. Therefore, fast…

Quantum Physics · Physics 2025-04-03 Diego Forlivesi , Lorenzo Valentini , Marco Chiani

The most common error models for quantum computers assume the independence of errors on different qubits. However, most noise mechanisms have some correlations in space. We show how to improve quantum information processing for few-qubit…

Quantum Physics · Physics 2018-12-19 Vickram N. Premakumar , Robert Joynt

Recent work on approximate quantum error correction (QEC) has opened up the possibility of constructing subspace codes that protect information with high fidelity in scenarios where perfect error correction is impossible. Motivated by this,…

Quantum Physics · Physics 2012-07-31 Prabha Mandayam , Hui Khoon Ng

Quantum error correction (QEC) is critical for scalable fault-tolerant quantum computing. Topological codes, such as the toric code, offer hardware-efficient architectures but their Tanner graphs contain many girth-4 cycles that degrade the…

Quantum Physics · Physics 2026-03-24 Luca Menti , Francisco Lázaro

Real-time decoding of quantum error correction (QEC) is essential for enabling fault-tolerant quantum computation. A practical decoder must operate with high accuracy at low latency, while remaining robust to spatial and temporal variations…

Quantum Physics · Physics 2026-01-23 Samuel Stein , Shuwen Kan , Chenxu Liu , Adrian Harkness , Sean Garner , Zefan Du , Yufei Ding , Ying Mao , Ang Li

Surface codes reach high error thresholds when decoded with known algorithms, but the decoding time will likely exceed the available time budget, especially for near-term implementations. To decrease the decoding time, we reduce the…

Quantum Physics · Physics 2019-02-07 Savvas Varsamopoulos , Ben Criger , Koen Bertels
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