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Variable length codes exhibit de-synchronization problems when transmitted over noisy channels. Trellis decoding techniques based on Maximum A Posteriori (MAP) estimators are often used to minimize the error rate on the estimated sequence.…

Networking and Internet Architecture · Computer Science 2016-08-16 Simon Malinowski , Hervé Jégou , Christine Guillemot

Some new results are derived concerning random coding error exponents and expurgated exponents for list decoding with a deterministic list size $L$. Two asymptotic regimes are considered, the fixed list-size regime, where $L$ is fixed…

Information Theory · Computer Science 2016-11-17 Neri Merhav

Quantum error correction requires decoders that are both accurate and efficient. To this end, union-find decoding has emerged as a promising candidate for error correction on the surface code. In this work, we benchmark a weighted variant…

Quantum Physics · Physics 2020-07-22 Shilin Huang , Michael Newman , Kenneth R. Brown

Low complexity error correction code is a key enabler for next generation ultra-reliable low-latency communications (xURLLC) in six generation (6G). Against this background, this paper proposes a decoding scheme for linear block code by…

Signal Processing · Electrical Eng. & Systems 2025-12-11 Di Zhang , Yinglei Yang , Zilong Liu , Shaobo Jia , Kyungchun Lee , Zhirong Zhang

Fracton models provide examples of novel gapped quantum phases of matter that host intrinsically immobile excitations and therefore lie beyond the conventional notion of topological order. Here, we calculate optimal error thresholds for…

Quantum Physics · Physics 2022-12-06 Hao Song , Janik Schönmeier-Kromer , Ke Liu , Oscar Viyuela , Lode Pollet , M. A. Martin-Delgado

Split learning is a privacy-preserving distributed learning paradigm in which an ML model (e.g., a neural network) is split into two parts (i.e., an encoder and a decoder). The encoder shares so-called latent representation, rather than raw…

Machine Learning · Computer Science 2023-09-07 Omar Alhussein , Moshi Wei , Arashmid Akhavain

In this paper, we use reinforcement learning to find effective decoding strategies for binary linear codes. We start by reviewing several iterative decoding algorithms that involve a decision-making process at each step, including…

Information Theory · Computer Science 2019-12-10 Fabrizio Carpi , Christian Häger , Marco Martalò , Riccardo Raheli , Henry D. Pfister

Learning-based lossy image compression usually involves the joint optimization of rate-distortion performance. Most existing methods adopt spatially invariant bit length allocation and incorporate discrete entropy approximation to constrain…

Computer Vision and Pattern Recognition · Computer Science 2019-04-02 Mu Li , Wangmeng Zuo , Shuhang Gu , Jane You , David Zhang

The surface code is one of the leading quantum error correction codes for realizing large-scale fault-tolerant quantum computing (FTQC). One major challenge in realizing surface-code-based FTQC is the extremely large number of qubits…

Quantum Physics · Physics 2026-05-19 Kohei Fujiu , Shota Nagayama , Shin Nishio , Hideaki Kawaguchi , Takahiko Satoh

The simulation of high-rate deformation and failure of metals is has traditionally been performed using Lagrangian finite element methods or Eulerian hydrocodes. Lagrangian mesh-based methods are limited by issues involving mesh…

Computational Physics · Physics 2012-01-13 Biswajit Banerjee , James E. Guilkey , Todd B. Harman , John A. Schmidt , Patrick A. McMurtry

Complexity in quantum physics measures how difficult a state can be reached from a reference state and more precisely it is the number of fundamental unitary gates we have to operate to transform the reference state to the state we are…

High Energy Physics - Theory · Physics 2020-06-05 Hao Geng

Locally decodable channel codes form a special class of error-correcting codes with the property that the decoder is able to reconstruct any bit of the input message from querying only a few bits of a noisy codeword. It is well known that…

Information Theory · Computer Science 2013-08-28 Ali Makhdoumi , Shao-Lun Huang , Muriel Medard , Yury Polyanskiy

Quantum error correction offers a promising path for performing quantum computations with low errors. Although a fully fault-tolerant execution of a quantum algorithm remains unrealized, recent experimental developments, along with…

Quantum computers hold the promise of solving computational problems which are intractable using conventional methods. For fault-tolerant operation quantum computers must correct errors occurring due to unavoidable decoherence and limited…

This letter introduces two fast maximum-likelihood (ML) detection methods for 4*4 quasi-orthogonal space-time block code (QOSTBC). The first algorithm with a relatively simple design exploits structure of quadrature amplitude modulation…

Information Theory · Computer Science 2017-06-14 Adel Ahmadi , Siamak Talebi

Monte Carlo simulations have been used to study the Z6 ferromagnet in a random field on simple cubic lattices, which is a simple model for randomly pinned charge-density waves. The random field is chosen to have infinite strength on a…

Condensed Matter · Physics 2009-10-28 Ronald Fisch

The surface code is a promising candidate for fault-tolerant quantum computation, achieving a high threshold error rate with nearest-neighbor gates in two spatial dimensions. Here, through a series of numerical simulations, we investigate…

Quantum Physics · Physics 2014-02-18 Ashley M. Stephens

Polar codes are of great interest since they are the first provably capacity-achieving forward error correction codes. To improve throughput and to reduce decoding latency of polar decoders, maximum likelihood (ML) decoding units are used…

Information Theory · Computer Science 2015-10-27 Chenrong Xiong , Jun Lin , Zhiyuan Yan

Monitored quantum circuits host a rich variety of exotic non-equilibrium phases. Among the most representative examples are measurement-induced phase transitions between distinct area-law entangled states. However, because these transitions…

Quantum Physics · Physics 2026-04-07 Hui Yu , Jiangping Hu , Shi-Xin Zhang

Data encoding plays a fundamental and distinctive role in Quantum Machine Learning (QML). While classical approaches process data directly as vectors, QML may require transforming classical data into quantum states through encoding…

Quantum Physics · Physics 2025-12-11 Orlane Zang , Grégoire Barrué , Tony Quertier
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