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We lay a comprehensive foundation for the study of redundant information storage in decoherence processes. Redundancy has been proposed as a prerequisite for objectivity, the defining property of classical objects. We consider two ensembles…

Quantum Physics · Physics 2009-11-11 Robin Blume-Kohout , W. H. Zurek

We examine the coordinated and universal rate-efficient sampling of a subset of correlated discrete memoryless sources followed by lossy compression of the sampled sources. The goal is to reconstruct a predesignated subset of sources within…

Information Theory · Computer Science 2017-06-23 Vinay Praneeth Boda , Prakash Narayan

This paper proposes a novel entropy encoding technique for lossless data compression. Representing a message string by its lexicographic index in the permutations of its symbols results in a compressed version matching Shannon entropy of…

Information Theory · Computer Science 2017-03-24 Abu Bakar Siddique

We introduce new definitions of universal and superuniversal computable codes, which are based on a code's ability to approximate Kolmogorov complexity within the prescribed margin for all individual sequences from a given set. Such sets of…

Machine Learning · Statistics 2009-04-10 Łukasz Dębowski

In this paper we consider the class of anti-uniform Huffman codes and derive tight lower and upper bounds on the average length, entropy, and redundancy of such codes in terms of the alphabet size of the source. The Fibonacci distributions…

Information Theory · Computer Science 2012-07-27 Soheil Mohajer , Ali Kakhbod

The entropy rate of printed English is famously estimated to be about one bit per character, a benchmark that modern large language models (LLMs) have only recently approached. This entropy rate implies that English contains nearly 80…

Computation and Language · Computer Science 2026-02-19 Weishun Zhong , Doron Sivan , Tankut Can , Mikhail Katkov , Misha Tsodyks

Packets originated from an information source in the network can be highly correlated. These packets are often routed through different paths, and compressing them requires to process them individually. Traditional universal compression…

Information Theory · Computer Science 2019-01-14 Ahmad Beirami , Faramarz Fekri

Measurements can be viewed as interactions between a measured system and a pointer system that imprint information about the system on the pointer. For so-called unbiased interactions, the measurement statistics--the information…

Quantum Physics · Physics 2025-03-31 Tiago Debarba , Marcus Huber , Nicolai Friis

Universal source coding at short blocklengths is considered for an exponential family of distributions. The \emph{Type Size} code has previously been shown to be optimal up to the third-order rate for universal compression of all memoryless…

Information Theory · Computer Science 2016-12-21 Nematollah Iri , Oliver Kosut

A classic result in algorithmic information theory is that every infinite binary sequence is computable from a Martin-Loef random infinite binary sequence. Proved independently by Kucera and Gacs, this result answered a question by Charles…

Computational Complexity · Computer Science 2017-06-13 George Barmpalias , Andrew Lewis-Pye

Given a probability distribution P, what is the minimum amount of bits needed to store a value x sampled according to P, such that x can later be recovered (except with some small probability)? Or, what is the maximum amount of uniform…

Information Theory · Computer Science 2007-07-13 Thomas Holenstein , Renato Renner

We consider universal variable-to-fixed length compression of memoryless sources with a fidelity criterion. We design a dictionary codebook over the reproduction alphabet which is used to parse the source stream. Once a source subsequence…

Information Theory · Computer Science 2022-11-24 Nematollah Iri

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

We propose a compression-based version of the empirical entropy of a finite string over a finite alphabet. Whereas previously one considers the naked entropy of (possibly higher order) Markov processes, we consider the sum of the…

Information Theory · Computer Science 2011-04-05 Paul M. B. Vitányi

This thesis concerns sequential-access data compression, i.e., by algorithms that read the input one or more times from beginning to end. In one chapter we consider adaptive prefix coding, for which we must read the input character by…

Information Theory · Computer Science 2009-02-03 Travis Gagie

The trapping redundancy of a linear code is the number of rows of a smallest parity-check matrix such that no submatrix forms an $(a,b)$-trapping set. This concept was first introduced in the context of low-density parity-check (LDPC) codes…

Information Theory · Computer Science 2016-11-15 Yu Tsunoda , Yuichiro Fujiwara

This paper is concerned with the lossy compression of general random variables, specifically with rate-distortion theory and quantization of random variables taking values in general measurable spaces such as, e.g., manifolds and fractal…

Probability · Mathematics 2023-06-05 Erwin Riegler , Helmut Bölcskei , Günther Koliander

Memorization in large language models poses critical risks for privacy and fairness as these systems scale to billions of parameters. While previous studies established correlations between memorization and factors like token frequency and…

Machine Learning · Computer Science 2025-09-01 Jie Zhang , Qinghua Zhao , Chi-ho Lin , Zhongfeng Kang , Lei Li

The concepts of pseudocodeword and pseudoweight play a fundamental role in the finite-length analysis of LDPC codes. The pseudoredundancy of a binary linear code is defined as the minimum number of rows in a parity-check matrix such that…

Information Theory · Computer Science 2014-10-08 Zihui Liu , Jens Zumbrägel , Marcus Greferath , Xin-Wen Wu

A novel, non-trivial, probabilistic upper bound on the entropy of an unknown one-dimensional distribution, given the support of the distribution and a sample from that distribution, is presented. No knowledge beyond the support of the…

Information Theory · Computer Science 2007-07-13 Joseph DeStefano , Erik Learned-Miller