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Zero-range processes with decreasing jump rates exhibit a condensation transition, where a positive fraction of all particles condenses on a single lattice site when the total density exceeds a critical value. We study the onset of…

Probability · Mathematics 2013-06-07 Inés Armendáriz , Stefan Grosskinsky , Michail Loulakis

The entropy of network ensembles characterizes the amount of information encoded in the network structure, and can be used to quantify network complexity, and the relevance of given structural properties observed in real network datasets…

Disordered Systems and Neural Networks · Physics 2014-06-18 Kartik Anand , Dimitri Krioukov , Ginestra Bianconi

It is always some constraint that yields any nontrivial structure from statistical averages. As epitomized by the Boltzmann distribution, the energy conservation is often the principal constraint acting on mechanical systems. Here, we…

Statistics Theory · Mathematics 2016-07-06 Naoki Sato , Zensho Yoshida

Shannon entropy in position ($S_{\rvec}$) and momentum ($S_{\pvec}$) spaces, along with their sum ($S_t$) are presented for unit-normalized densities of He, Li$^+$ and Be$^{2+}$ ions, spatially confined at the center of an impenetrable…

Quantum Physics · Physics 2021-03-01 Sangita Majumdar , Amlan K. Roy

We study quantum phase transitions out of the fracton ordered phase of the $\mathbb{Z}_N$ X-cube model. These phase transitions occur when various types of sub-dimensional excitations and their composites are condensed. The condensed phases…

Strongly Correlated Electrons · Physics 2021-11-18 Ethan Lake , Michael Hermele

We study the behavior of a nonlinear semiclassical system using Shannon entropy and two approaches to statistical complexity. These systems involve the interaction between classical variables (representing the environment) and quantum ones.…

Quantum Physics · Physics 2024-11-22 Gaspar Gonzalez , Andrés M. Kowalski

Reliable data-driven estimation of Shannon entropy from small data sets, where the number of examples is potentially smaller than the number of possible outcomes, is a critical matter in several applications. In this paper, we introduce a…

Machine Learning · Computer Science 2025-12-12 Gabriel F. A. Bastos , Jugurta Montalvão

We study the Shannon entropy of the probability distribution resulting from the ground-state wave function of a one-dimensional quantum model. This entropy is related to the entanglement entropy of a Rokhsar-Kivelson-type wave function…

Strongly Correlated Electrons · Physics 2009-11-25 Jean-Marie Stéphan , Shunsuke Furukawa , Grégoire Misguich , Vincent Pasquier

The pattern of isentropes in the vicinity of a first-order phase transition is proposed as a key for a sub-classification. While the confinement--deconfinement transition, conjectured to set in beyond a critical end point in the QCD phase…

High Energy Physics - Phenomenology · Physics 2016-05-25 Falk Wunderlich , Roman Yaresko , Burkhard Kampfer

Discrete-element simulations are used to monitor several micro-scale characteristics within a granular material, demonstrating their convergence during loading toward the critical state, their stationarity at the critical state, and the…

Soft Condensed Matter · Physics 2018-12-20 Matthew R. Kuhn

Entropy estimation is of practical importance in information theory and statistical science. Many existing entropy estimators suffer from fast growing estimation bias with respect to dimensionality, rendering them unsuitable for…

Information Theory · Computer Science 2023-08-22 Ziqiao Ao , Jinglai Li

When liquids are cooled sufficiently rapidly below their melting temperature, they may bypass crystalization and, instead, enter a long-lived metastable supercooled state that has long been the focus of intense research. Although they…

Statistical Mechanics · Physics 2023-12-05 Zohar Nussinov

We give numerical evidence that the location of the first order phase transition between the low and the high density phases of the one dimensional asymmetric simple exclusion process with open boundaries becomes sample dependent when…

Other Condensed Matter · Physics 2009-11-10 C. Enaud , B. Derrida

We present estimators for entropy and other functions of a discrete probability distribution when the data is a finite sample drawn from that probability distribution. In particular, for the case when the probability distribution is a joint…

comp-gas · Physics 2008-02-03 David H. Wolpert , David R. Wolf

Shannon entropy is widely used to quantify the uncertainty of discrete random variables. But when normalized to the unit interval, as is often done in practice, it no longer conveys the alphabet sizes of the random variables being studied.…

Information Theory · Computer Science 2022-07-26 John Çamkıran

We consider the Constrained-degree percolation model in random environment on the square lattice. In this model, each vertex $v$ has an independent random constraint ${\kappa}_v$ which takes the value $j\in \{0,1,2,3\}$ with probability…

Probability · Mathematics 2021-11-02 Rémy Sanchis , Diogo C. dos Santos , Roger W. C. Silva

We perform extensive simulations of $10^4$ Lennard-Jones particles to study the effect of particle size dispersity on the thermodynamic stability of two-dimensional solids. We find a novel phase diagram in the dispersity-density parameter…

Materials Science · Physics 2009-10-30 M. Reza Sadr-Lahijany , Purusattam Ray , H. Eugene Stanley

We identify a phase transition between two kinds of volume-law entangled phases in non-local but few-body unitary dynamics with local projective measurements. In one phase, a finite fraction of the system belongs to a fully-entangled state,…

Quantum Physics · Physics 2020-05-08 Sagar Vijay

We study the problem of overcoming exponential sample complexity in differential entropy estimation under Gaussian convolutions. Specifically, we consider the estimation of the differential entropy $h(X+Z)$ via $n$ independently and…

Information Theory · Computer Science 2023-05-12 Kristjan Greenewald , Brian Kingsbury , Yuancheng Yu

We present a detailed derivation of some estimators of Shannon entropy for discrete distributions. They hold for finite samples of N points distributed into M "boxes", with N and M -> oo, but N/M < oo. In the high sampling regime (<< 1…

Data Analysis, Statistics and Probability · Physics 2011-11-09 P. Grassberger