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In an earlier work, the statistical physics associated with finite--temperature decoding of code ensembles, along with the relation to their random coding error exponents, were explored in a framework that is analogous to Derrida's random…

Information Theory · Computer Science 2016-11-15 Neri Merhav

We present herein a scheme by which to accurately evaluate the error exponents of a lossy data compression problem, which characterize average probabilities over a code ensemble of compression failure and success above or below a critical…

Statistical Mechanics · Physics 2007-05-23 Tadaaki Hosaka , Yoshiyuki Kabashima

The performance of ``typical set (pairs) decoding'' for ensembles of Gallager's linear code is investigated using statistical physics. In this decoding, error happens when the information transmission is corrupted by an untypical noise or…

Disordered Systems and Neural Networks · Physics 2009-11-07 Yoshiyuki Kabashima , Kazutaka Nakamura , Jort van Mourik

We solve the random energy model when the energies of the configurations take only integer values. In the thermodynamic limit, the average overlaps remain size dependent and oscillate as the system size increases. While the extensive part…

Disordered Systems and Neural Networks · Physics 2022-06-22 Bernard Derrida , Peter Mottishaw

Code Division Multiple Access (CDMA) in which the spreading code assignment to users contains a random element has recently become a cornerstone of CDMA research. The random element in the construction is particular attractive as it…

Disordered Systems and Neural Networks · Physics 2015-05-13 Jack Raymond , David Saad

Variable selection is a problem of statistics that aims to find the subset of the $N$-dimensional possible explanatory variables that are truly related to the generation process of the response variable. In high-dimensional setups, where…

Statistics Theory · Mathematics 2025-02-27 Takashi Takahashi

We explore the relation between the techniques of statistical mechanics and information theory for assessing the performance of channel coding. We base our study on a framework developed by Gallager in {\em IEEE Trans. Inform. Theory} {\bf…

Information Theory · Computer Science 2009-11-13 Yoshiyuki Kabashima

In this work, we study the percolation transition and large deviation properties of generalized canonical network ensembles. This new type of random networks might have a very rich complex structure, including high heterogeneous degree…

Statistical Mechanics · Physics 2009-05-15 Serena Bradde , Ginestra Bianconi

A variation of Gallager error-correcting codes is investigated using statistical mechanics. In codes of this type, a given message is encoded into a codeword which comprises Boolean sums of message bits selected by two randomly constructed…

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

Using tools developed in a recent work by Shen and the second author, in this paper we carry out an in-depth study on the average decoding error probability of the random matrix ensemble over the erasure channel under three decoding…

Information Theory · Computer Science 2024-04-23 Chin Hei Chan , Fang-Wei Fu , Maosheng Xiong

A quantum error-correcting code with a nonzero error threshold undergoes a mixed-state phase transition when the error rate reaches that threshold. We explore this phase transition for Haar-random quantum codes, in which the logical…

Ensemble methods are among the state-of-the-art predictive modeling approaches. Applied to modern big data, these methods often require a large number of sub-learners, where the complexity of each learner typically grows with the size of…

Machine Learning · Computer Science 2018-10-29 Amichai Painsky , Saharon Rosset

Compression of integer sets and sequences has been extensively studied for settings where elements follow a uniform probability distribution. In addition, methods exist that exploit clustering of elements in order to achieve higher…

Information Theory · Computer Science 2014-02-11 N. Jesper Larsson

We propose a universal ensemble for random selection of rate-distortion codes, which is asymptotically optimal in a sample-wise sense. According to this ensemble, each reproduction vector, $\hbx$, is selected independently at random under…

Information Theory · Computer Science 2022-12-26 Neri Merhav

The state-of-the-art error correcting codes are based on large random constructions (random graphs, random permutations, ...) and are decoded by linear-time iterative algorithms. Because of these features, they are remarkable examples of…

Disordered Systems and Neural Networks · Physics 2016-08-31 Silvio Franz , Michele Leone , Andrea Montanari , Federico Ricci-Tersenghi

We consider a monitoring application where sensors periodically report data to a common receiver in a time division multiplex fashion. The sensors are constrained by the limited and unpredictable energy availability provided by Energy…

Information Theory · Computer Science 2017-06-29 Chiara Pielli , Cedomir Stefanovic , Petar Popovski , Michele Zorzi

Assuming the validity of random matrices for describing the statistics of a closed chaotic quantum system, we study analytically some statistical properties of the S-matrix characterizing scattering in its open counterpart. In the first…

Mesoscale and Nanoscale Physics · Physics 2016-08-31 Yan. V. Fyodorov , H. -J. Sommers

Randomness extraction is an essential post-processing step in practical quantum cryptography systems. When statistical fluctuations are taken into consideration, the requirement of large input data size could heavily penalise the speed and…

Quantum Physics · Physics 2024-04-09 Hong Jie Ng , Wen Yu Kon , Ignatius William Primaatmaja , Chao Wang , Charles Lim

In biology, stochastic branching processes with a two-stage, hierarchical structure arise in the study of population dynamics, gene expression, and phylogenetic inference. These models have been commonly analyzed using generating functions,…

Molecular Networks · Quantitative Biology 2023-02-13 Ximo Pechuan-Jorge , Raymond S. Puzio , Cameron Smith

I present here some results on the statistical behaviour of large random matrices in an ensemble where the probability distribution is not a function of the eigenvalues only. The perturbative expansion can be cast in a closed form and the…

Disordered Systems and Neural Networks · Physics 2008-02-03 Giorgio Parisi
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