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The entropy accumulation theorem, and its subsequent generalized version, is a powerful tool in the security analysis of many device-dependent and device-independent cryptography protocols. However, it has the drawback that the finite-size…

Quantum Physics · Physics 2025-12-22 Amir Arqand , Thomas A. Hahn , Ernest Y. -Z. Tan

Obtaining a non-trivial (super-linear) lower bound for computation of the Fourier transform in the linear circuit model has been a long standing open problem. All lower bounds so far have made strong restrictions on the computational model.…

Computational Complexity · Computer Science 2013-05-22 Nir Ailon

In adaptive data analysis, a mechanism gets $n$ i.i.d. samples from an unknown distribution $D$, and is required to provide accurate estimations to a sequence of adaptively chosen statistical queries with respect to $D$. Hardt and Ullman…

Machine Learning · Computer Science 2023-11-07 Kobbi Nissim , Uri Stemmer , Eliad Tsfadia

In this paper, we study the problem of lossless universal source coding for stationary memoryless sources on countably infinite alphabets. This task is generally not achievable without restricting the class of sources over which…

Information Theory · Computer Science 2015-04-20 Boucheron Stephane , Elisabeth Gassiat , Mesrob I. Ohannessian

Several applications in communication, control, and learning require approximating target distributions to within small informational divergence (I-divergence). The additional requirement of invertibility usually leads to using encoders…

Information Theory · Computer Science 2020-10-22 Patrick Schulte , Rana Ali Amjad , Thomas Wiegart , Gerhard Kramer

We construct a system of nonequilibrium entropy limiters for the lattice Boltzmann methods (LBM). These limiters erase spurious oscillations without blurring of shocks, and do not affect smooth solutions. In general, they do the same work…

Statistical Mechanics · Physics 2007-11-19 R. A. Brownlee , A. N. Gorban , J. Levesley

We consider estimating the Shannon entropy of a discrete distribution $P$ from $n$ i.i.d. samples. Recently, Jiao, Venkat, Han, and Weissman, and Wu and Yang constructed approximation theoretic estimators that achieve the minimax $L_2$…

Information Theory · Computer Science 2019-01-03 Yanjun Han , Jiantao Jiao , Tsachy Weissman

We give new explicit constructions of several fundamental objects in linear-algebraic pseudorandomness and combinatorics, including lossless rank extractors, weak subspace designs, and strong $s$-blocking sets over finite fields. Our focus…

Information Theory · Computer Science 2026-04-16 Zeyu Guo , Roshan Raj , Chong Shangguan , Zihan Zhang

We model (interactive) resources that provide Alice with a string $X$ and a guarantee that any Eve interacting with her interface of the resource obtains a (quantum) system $E$ such that the conditional (smooth) min-entropy of $X$ given $E$…

Quantum Physics · Physics 2017-05-31 Christopher Portmann

The entropy accumulation theorem states that the smooth min-entropy of an $n$-partite system $A = (A_1, \ldots, A_n)$ is lower-bounded by the sum of the von Neumann entropies of suitably chosen conditional states up to corrections that are…

Quantum Physics · Physics 2019-07-23 Frédéric Dupuis , Omar Fawzi

In classical and quantum information theory, operational quantities such as the amount of randomness that can be extracted from a given source or the amount of space needed to store given data are normally characterized by one of two…

Quantum Physics · Physics 2011-03-18 Marco Tomamichel , Roger Colbeck , Renato Renner

The problem of sampling according to the probability distribution minimizing a given free energy, using interacting particles unadjusted kinetic Langevin Monte Carlo, is addressed. In this setting, three sources of error arise, related to…

Probability · Mathematics 2024-12-05 Pierre Monmarché , Katharina Schuh

Recent masked diffusion models (MDMs) have shown competitive performance compared to autoregressive models (ARMs) for language modeling. While most literature has focused on performance enhancing sampling procedures, efficient sampling from…

Machine Learning · Computer Science 2025-06-02 Heli Ben-Hamu , Itai Gat , Daniel Severo , Niklas Nolte , Brian Karrer

In this paper, we consider the generation and utilization of helper data for physical unclonable functions (PUFs) that provide real-valued readout symbols. Compared to classical binary PUFs, more entropy can be extracted from each basic…

Information Theory · Computer Science 2024-03-01 Robert F. H. Fischer

Normalizing flows are a promising tool for modeling probability distributions in physical systems. While state-of-the-art flows accurately approximate distributions and energies, applications in physics additionally require smooth energies…

Machine Learning · Statistics 2021-12-01 Jonas Köhler , Andreas Krämer , Frank Noé

Flow and diffusion models are typically pre-trained on limited available data (e.g., molecular samples), covering only a fraction of the valid design space (e.g., the full molecular space). As a consequence, they tend to generate samples…

Machine Learning · Computer Science 2026-02-19 Riccardo De Santi , Kimon Protopapas , Ya-Ping Hsieh , Andreas Krause

Min-entropy sampling gives a bound on the min-entropy of a randomly chosen subset of a string, given a bound on the min-entropy of the whole string. K\"onig and Renner showed a min-entropy sampling theorem that holds relative to quantum…

Quantum Physics · Physics 2011-07-18 Jürg Wullschleger

The problem of secure multiterminal source coding with side information at the eavesdropper is investigated. This scenario consists of a main encoder (referred to as Alice) that wishes to compress a single source but simultaneously…

Information Theory · Computer Science 2013-11-11 Joffrey Villard , Pablo Piantanida

Markov Chain Monte Carlo (MCMC) methods sample from unnormalized probability distributions and offer guarantees of exact sampling. However, in the continuous case, unfavorable geometry of the target distribution can greatly limit the…

Machine Learning · Statistics 2020-10-09 Zengyi Li , Yubei Chen , Friedrich T. Sommer

The extraction of randomness from weakly random seeds is a problem of central importance with multiple applications. In the device-independent setting, this problem of quantum randomness amplification has been mainly restricted to specific…

Quantum Physics · Physics 2023-04-20 Ravishankar Ramanathan
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