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We introduce a new protocol for a lossy data compression algorithm which is based on constraint satisfaction gates. We show that the theoretical capacity of algorithms built from standard parity-check gates converges exponentially fast to…

Disordered Systems and Neural Networks · Physics 2009-11-11 S. Ciliberti , M. Mezard , R. Zecchina

We consider the problem of compressing memoryless binary data with or without side information at the decoder. We review the parity- and the syndrome-based approaches and discuss their theoretical limits, assuming that there exists a…

Information Theory · Computer Science 2010-08-03 Lorenzo Cappellari , Andrea De Giusti

The use of parity-check gates in information theory has proved to be very efficient. In particular, error correcting codes based on parity checks over low-density graphs show excellent performances. Another basic issue of information…

Disordered Systems and Neural Networks · Physics 2007-05-23 S. Ciliberti , M. Mezard , R. Zecchina

As conventional communication systems based on classic information theory have closely approached the limits of Shannon channel capacity, semantic communication has been recognized as a key enabling technology for the further improvement of…

Information Theory · Computer Science 2023-06-06 Jiancheng Tang , Qianqian Yang , Zhaoyang Zhang

Let $W$ be a binary-input memoryless symmetric (BMS) channel with Shannon capacity $I(W)$ and fix any $\alpha > 0$. We construct, for any sufficiently small $\delta > 0$, binary linear codes of block length $O(1/\delta^{2+\alpha})$ and rate…

Information Theory · Computer Science 2022-01-25 Venkatesan Guruswami , Andrii Riazanov , Min Ye

Much progress has been made on decoding algorithms for error-correcting codes in the last decade. In this article, we give an introduction to some fundamental results on iterative, message-passing algorithms for low-density parity check…

Information Theory · Computer Science 2007-07-16 Venkatesan Guruswami

We investigate the performance of parity check codes using the mapping onto Ising spin systems proposed by Sourlas. We study codes where each parity check comprises products of K bits selected from the original digital message with exactly…

Disordered Systems and Neural Networks · Physics 2009-10-31 Renato Vicente , David Saad , Yoshiyuki Kabashima

We show how universal codes can be used for solving some of the most important statistical problems for time series. By definition, a universal code (or a universal lossless data compressor) can compress any sequence generated by a…

Information Theory · Computer Science 2008-09-09 Boris Ryabko

We study the problem of efficient compression of a stochastic source of probability distributions. It can be viewed as a generalization of Shannon's source coding problem. It has relation to the theory of common randomness, as well as to…

Quantum Physics · Physics 2016-09-08 Andreas Winter

Quantum Shannon theory is loosely defined as a collection of coding theorems, such as classical and quantum source compression, noisy channel coding theorems, entanglement distillation, etc., which characterize asymptotic properties of…

Quantum Physics · Physics 2008-10-03 I. Devetak , A. W. Harrow , A. Winter

The information spectrum approach gives general formulae for optimal rates of various information theoretic protocols, under minimal assumptions on the nature of the sources, channels and entanglement resources involved. This paper…

Quantum Physics · Physics 2007-05-23 Garry Bowen , Nilanjana Datta

The paper introduces new bounds on the asymptotic density of parity-check matrices and the achievable rates under ML decoding of binary linear block codes transmitted over memoryless binary-input output-symmetric channels. The lower bounds…

Information Theory · Computer Science 2007-07-13 Gil Wiechman , Igal Sason

This paper considers lossy source coding of $n$-dimensional memoryless sources and shows an explicit approximation to the minimum source coding rate required to sustain the probability of exceeding distortion $d$ no greater than $\epsilon$,…

Information Theory · Computer Science 2017-02-28 Victoria Kostina

Using a mild variant of polar codes we design linear compression schemes compressing Hidden Markov sources (where the source is a Markov chain, but whose state is not necessarily observable from its output), and to decode from Hidden Markov…

Information Theory · Computer Science 2018-10-05 Venkatesan Guruswami , Preetum Nakkiran , Madhu Sudan

We prove that, for all binary-input symmetric memoryless channels, polar codes enable reliable communication at rates within $\epsilon > 0$ of the Shannon capacity with a block length, construction complexity, and decoding complexity all…

Information Theory · Computer Science 2013-11-19 Venkatesan Guruswami , Patrick Xia

The generalization of Shannon's theory to include messages with given autocorrelations is presented. The analytical calculation of the channel capacity is based on the transfer matrix method of the effective 1D Hamiltonian. This bridge…

Statistical Mechanics · Physics 2007-05-23 Ido Kanter , Hanan Rosemarin

We study source compression with a helper in the fully quantum regime, extending our earlier result on classical source compression with a quantum helper [arXiv:1501.04366, 2015]. We characterise the quantum resources involved in this…

Quantum Physics · Physics 2017-01-12 Min-Hsiu Hsieh , Shun Watanabe

Typical performance of low-density parity-check (LDPC) codes over a general binary-input output-symmetric memoryless channel is investigated using methods of statistical mechanics. Theoretical framework for dealing with general symmetric…

Disordered Systems and Neural Networks · Physics 2009-11-07 Toshiyuki Tanaka , David Saad

In this thesis we present several results in coding theory, concerning error-correcting codes and the Shannon capacity. 1. We give a general symmetry reduction of matrices occuring in semidefinite programs in coding theory. 2. We apply the…

Combinatorics · Mathematics 2020-05-07 Sven Polak

Assessing whether two datasets are distributionally consistent is central to modern scientific analysis, particularly as generative artificial intelligence produces synthetic data whose fidelity must be validated against real observations…

Information Theory · Computer Science 2026-03-24 Cristiano Fanelli
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