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Hypergraph product codes are a class of constant-rate quantum low-density parity-check (LDPC) codes equipped with a linear-time decoder called small-set-flip (SSF). This decoder displays sub-optimal performance in practice and requires very…

Quantum Physics · Physics 2021-04-21 Antoine Grospellier , Lucien Grouès , Anirudh Krishna , Anthony Leverrier

We derive two families of EA-QC quantum LDPC (EA-QC-QLDPC) codes by tiling permutation matrices of prime and composite orders. The unassisted portion of the Tanner graphs corresponding to these codes, constructed from two distinct classical…

Information Theory · Computer Science 2025-11-04 Pavan Kumar , Abhi Kumar Sharma , Shayan Srinivasa Garani

In this paper, we study the integrality gap of the Knapsack linear program in the Sherali- Adams and Lasserre hierarchies. First, we show that an integrality gap of 2 - {\epsilon} persists up to a linear number of rounds of Sherali-Adams,…

Computational Complexity · Computer Science 2010-07-09 Anna R. Karlin , Claire Mathieu , C. Thach Nguyen

We analyze the finite-length performance of spatially coupled low-density parity-check (SC-LDPC) codes under window decoding over the binary erasure channel. In particular, we propose a refinement of the scaling law by Olmos and Urbanke for…

Information Theory · Computer Science 2020-08-26 Roman Sokolovskii , Alexandre Graell i Amat , Fredrik Brännström

This paper proposes two approaches for reducing the impact of the error floor phenomenon when decoding quantum low-density parity-check codes with belief propagation based algorithms. First, a low-complexity syndrome-based linear…

Information Theory · Computer Science 2024-01-22 Sana Javed , Francisco Garcia-Herrero , Bane Vasic , Mark F. Flanagan

We give new rounding schemes for SDP relaxations for the problems of maximizing cubic polynomials over the unit sphere and the $n$-dimensional hypercube. In both cases, the resulting algorithms yield a $O(\sqrt{n/k})$ multiplicative…

Data Structures and Algorithms · Computer Science 2023-10-03 Jun-Ting Hsieh , Pravesh K. Kothari , Lucas Pesenti , Luca Trevisan

Long polar codes can achieve the capacity of arbitrary binary-input discrete memoryless channels under a low complexity successive cancelation (SC) decoding algorithm. But for polar codes with short and moderate code length, the decoding…

Information Theory · Computer Science 2016-11-18 Jun Lin , Chenrong Xiong , Zhiyuan Yan

We consider linear-programming (LP) decoding of low-density parity-check (LDPC) codes. While it is clear that one can use any general-purpose LP solver to solve the LP that appears in the decoding problem, we argue in this paper that the LP…

Information Theory · Computer Science 2007-07-16 Pascal O. Vontobel , Ralf Koetter

Linear Programming (LP) is an important decoding technique for binary linear codes. However, the advantages of LP decoding, such as low error floor and strong theoretical guarantee, etc., come at the cost of high computational complexity…

Signal Processing · Electrical Eng. & Systems 2020-06-16 Yi Wei , Ming-Min Zhao , Min-Jian Zhao , Ming Lei

Efficient and high-performance quantum error correction is essential for achieving fault-tolerant quantum computing. Low-depth random circuits offer a promising approach to identifying effective and practical encoding strategies. In this…

Quantum Physics · Physics 2026-03-02 Guoding Liu , Zhenyu Du , Zi-Wen Liu , Xiongfeng Ma

For a large class of optimization problems, namely those that can be expressed as finite-valued constraint satisfaction problems (VCSPs), we establish a dichotomy on the number of levels of the Lasserre hierarchy of semi-definite programs…

Logic in Computer Science · Computer Science 2016-09-27 Anuj Dawar , Pengming Wang

In this paper, we develop efficient decoders for non-binary low-density parity-check (LDPC) codes using the alternating direction method of multipliers (ADMM). We apply ADMM to two decoding problems. The first problem is linear programming…

Information Theory · Computer Science 2015-07-29 Xishuo Liu , Stark C. Draper

Maximum Likelihood (ML) decoding is the optimal decoding algorithm for arbitrary linear block codes and can be written as an Integer Programming (IP) problem. Feldman et al. relaxed this IP problem and presented Linear Programming (LP)…

Information Theory · Computer Science 2008-12-16 Akin Tanatmis , Stefan Ruzika , Horst W. Hamacher , Mayur Punekar , Frank Kienle , Norbert Wehn

We investigate iterative low-resolution message-passing algorithms for quasi-cyclic LDPC codes with horizontal and vertical layered schedules. Coarse quantization and layered scheduling are highly relevant for hardware implementations to…

Information Theory · Computer Science 2022-12-19 Philipp Mohr , Gerhard Bauch

The concept of the smoothing parameter plays a crucial role in both lattice-based and code-based cryptography, primarily due to its effectiveness in achieving nearly uniform distributions through the addition of noise. Recent research by…

Information Theory · Computer Science 2024-05-17 Hao Yan , Cong Ling

We consider a special family of SC-LDPC codes, that is, time-invariant LDPCC codes, which are known in the literature for a long time. Codes of this kind are usually designed by starting from QC block codes, and applying suitable unwrapping…

Information Theory · Computer Science 2016-05-19 Marco Baldi , Massimo Battaglioni , Franco Chiaraluce , Giovanni Cancellieri

Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover, a type of integer programming (IP) problem. A lattice-gas model on the Erd\"os-R\'enyi random graphs of $\alpha$-uniform…

Disordered Systems and Neural Networks · Physics 2016-06-01 Satoshi Takabe , Koji Hukushima

A Bounded-Degree Low-Rank Parity-Check (BD-LRPC) code is a rank-metric code that admits a parity-check matrix whose support is generated by a set of powers of an element. This specific structure of the parity-check matrix was employed to…

Information Theory · Computer Science 2025-09-17 Hermann Tchatchiem Kamche

In this paper, we investigate the probabilistic set covering problem (PSCP) in which the right-hand side is a binary random vector and the covering constraint is required to be satisfied with a prespecified probability. We consider the case…

Optimization and Control · Mathematics 2026-03-24 Wei Lv , Wei-Kun Chen , Yi-Long Chen , Yu-Hong Dai

Maximum a posteriori (MAP) inference is a fundamental computational paradigm for statistical inference. In the setting of graphical models, MAP inference entails solving a combinatorial optimization problem to find the most likely…

Machine Learning · Computer Science 2020-03-03 Jonathan N. Lee , Aldo Pacchiano , Michael I. Jordan
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