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# Statistical Physics - Science topic

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Publications related to Statistical Physics (10,000)

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The theme of this textbook revolves around how machine learning (ML) can help civil and environmental engineers transform their domain. This textbook hopes to deliver the knowledge and information necessary to educate engineering students and practitioners on the principles of ML and how to integrate these into our field. This textbook is about nav...

Hyperuniformity is the study of stationary point processes with a sub-Poisson variance in a large window. In other words, counting the points of a hyperuniform point process that fall in a given large region yields a small-variance Monte Carlo estimation of the volume. Hyperuniform point processes have received a lot of attention in statistical phy...

Background:
Microbiome dynamics are both crucial indicators and potential drivers of human health, agricultural output, and industrial bio-applications. However, predicting microbiome dynamics is notoriously difficult because communities often show abrupt structural changes, such as "dysbiosis" in human microbiomes.
Methods:
We integrated theore...

We consider the information transmission problem in neurons and its possible implications for learning in neural networks. Our approach is based on recent developments in statistical physics and complexity science. We also develop a method to try and select significant neural responses from the background activity and consider its wider application...

The Liouville theorem is a fundamental concept in understanding the properties of systems that adhere to Hamilton's equations. However, the traditional notion of the theorem may not always apply. Specifically, when the entropy gradient in phase space fails to reach equilibrium, the phase-space density may not have a zero time derivative, i.e., $\fr...

A central role in shaping the experience of users online is played by recommendation algorithms. On the one hand they help retrieving content that best suits users taste, but on the other hand they may give rise to the so called "filter bubble" effect, favoring the rise of polarization. In the present paper we study how a user-user collaborative-fi...

Models for spin systems known from statistical physics are applied by analogy in econometrics in the form of agent-based models. Researchers suggest that the state variable temperature T corresponds to volatility σ in capital market theory problems. To the best of our knowledge, this has not yet been theoretically derived, for example, for an ideal...

Klaus Hasselmann's revolutionary intuition was to take advantage of the stochasticity associated with fast weather processes to probe the slow dynamics of the climate system. This has led to fundamentally new ways to study the response of climate models to perturbations, and to perform detection and attribution for climate change signals. Hasselman...

The site percolation problem is one of the core topics in statistical physics. Evaluation of the percolation threshold, which separates two phases (sometimes described as conducting and isolating), is useful for a lot of problems ranging from core condensed matter to interdisciplinary application of statistical physics in epidemiology or any other...

The Fermi-Pasta-Ulam-Tsingou (FPUT) problem addresses fundamental questions in statistical physics, and attempts to understand the origin of recurrences in the system have led to many great advances in nonlinear dynamics and mathematical physics. In this work we revisit the problem and study the cause of quasiperiodic recurrences in the weakly nonl...

The stochastic block model (SBM) is widely studied as a benchmark for graph clustering aka community detection. In practice, graph data often come with node attributes that bear additional information about the communities. Previous works modeled such data by considering that the node attributes are generated from the node community memberships. In...

Plain Language Summary
Knowledge of the permeability of fractured rocks is critical for many geo‐engineering applications (such as deep geological disposal of radioactive wastes, mining and dam engineering) and environmental problems (such as ground water and pollutant transport). The influence of fracture attributes (e.g., orientations, sizes, and...

The important recent book by Schurz (2019) appreciates that the no-free-lunch theorems (NFL) have major implications for the problem of (meta) induction. Here I review the NFL theorems, emphasizing that they do not only concern the case where there is a uniform prior—they prove that there are “as many priors” (loosely speaking) for which any induct...

The lattice Boltzmann method (LBM) is a new powerful numerical method used to simulate various flows in complex geometries. This method is based on the mesoscopic description of the particles constituting the representative elementary volume (REV) resulting from the theory of the kinetics of gases (statistical physics).
The LBM has been widely appl...

The Central Limit Theorem stands as a milestone in probability theory and statistical physics, as the privileged, if not the unique, universal route to normal distributions. This article addresses and describes several other alternative routes to Gaussianity, stemming from physical interactions, related to particle-particle and radiative particle–p...

Transfer entropy (TE) has proven to be an effective tool for determining the causal connection between two processes. For example, TE has been used to classify leader and follower agents in collective dynamics in the Vicsek model (VM). However, previous results have limited interaction radii, which are precisely the same among all agents, which is...

High concentrations of fluoride (F−) in drinking water represent a public health threat, and consequently, effective and sustainable methods are required to improve the water quality, mainly in developing and low-income countries. This study focused on the thermodynamics of fluoride adsorption on bone char regenerated with NaOH for water defluorida...

Transport coefficients, such as the mobility, thermal conductivity and shear viscosity, are quantities of prime interest in statistical physics. At the macroscopic level, transport coefficients relate an external forcing of magnitude $\eta$, with $\eta \ll 1$, acting on the system to an average response expressed through some steady-state flux. In...

We perform extensive simulations and systematic statistical analyses of the structural dynamics of amorphous silicon. The simulations follow the dynamics introduced by Wooten, Winer and Weaire: the energy is obtained with the Keating potential, and the dynamics consists of bond transpositions proposed at random locations and accepted with the Metro...

The $K$-core of a graph is the unique maximum subgraph within which each vertex connects to at least $K$ other vertices. The $K$-core optimal attack problem asks to construct a minimum-sized set of vertices whose removal results in the complete collapse of the $K$-core. In this paper, we construct a hierarchical cycle-tree packing model which conve...

The interplay among differential geometry, statistical physics, and quantum information science has been increasingly gaining theoretical interest in recent years. In this paper, we present an explicit analysis of the Bures and Sjoqvist metrics over the manifolds of thermal states for specific spin qubit and the superconducting flux qubit Hamiltoni...

Human behavior, and in particular vaccine hesitancy, is a critical factor for the control of childhood infectious disease. Here we propose a spatio-temporal behavioral epidemiology model where the vaccine propensity depends on information that is non-local in space and in time. The properties of the proposed model are analysed under different hypot...

Air transportation is a complex system characterized by a plethora of interactions at multiple temporal and spatial scales; as a consequence, even simple dynamics like sequencing aircraft for landing can lead to the appearance of emergent behaviors, which are both difficult to control and detrimental to operational efficiency. We propose a model, b...

Physical mechanisms of phase separation in living systems play key physiological roles and have recently been the focus of intensive studies. The strongly heterogeneous nature of such phenomena poses difficult modeling challenges that require going beyond mean-field approaches based on postulating a free energy landscape. The pathway we take here i...

Apis cerana cerana counted on its sensitive olfactory system to make survival activities in the surrounding environment and the olfactory receptors can be considered as a primary requirement of odorant detection, recognition and coding. Indeed, the exploitation of the olfactory system of insects in particular the Asian honeybee "Apis cerana cerana"...

The quantitative description of the scientific conference MECO (Middle European Cooperation in Statistical Physics) based on bibliographic records is presented in the paper. Statistics of contributions and participants, co-authorship patterns at the levels of authors and countries, typical proportions of newcomers and permanent participants as well...

This Thesis explores how tools from Statistical Physics and Information Theory can help us describe and understand complex systems. In the first part, we study the interplay between internal interactions, environmental changes, and effective representations of complex stochastic systems. We model the environment as an unobserved stochastic process...

We analyze the performance of the least absolute shrinkage and selection operator (Lasso) for the linear model when the number of regressors $N$ grows larger keeping the true support size $d$ finite, i.e., the ultra-sparse case. The result is based on a novel treatment of the non-rigorous replica method in statistical physics, which has been applie...

I have proposed Negentropy Maximization Principle (NMP) as a variational principle for the evolution of conscious experience. Mathematically, NMP is very similar to the second law although it states something completely opposite. Second law follows from statistical physics and is not an independent physical law. Is the situation the same with the N...

In this paper, we reconsider the spin model suggested recently to understand some features of collective decision making among higher organisms [A.T. Hartnett et al., Phys. Rev. Lett. 116 (2016) 038701]. Within the model, the state of an agent $i$ is described by the pair of variables corresponding to its opinion $S_i=\pm 1$ and a bias $\omega_i$ t...

New statistics of a low-parameter distribution of the sech (ε, µ) type are presented, which reproduce the results of plasma simulation by the method of dynamics of many particles (DMP) with high accuracy. The distribution is based on a conceptual model of a two-component plasma — virtual quasiparticles of negative energy (exciton phase ε<0); the sc...

Based on algorithms of solving directly MHD partial differential equation algorithm (e.g., ATHENA [1], NIRVANA [2], ZEUS [3], FLASH [4], PIC [5-8], HPIC [9-11]), conventional simulation methods cannot attain the extreme range of scale for 3D turbulence fine-structure (Geometry and Physics) in flare-CME phenomena, especially for nanoflare heating pr...

The vaccination game is a social dilemma that refers to the conundrum individuals face (to get immunized or not) when the population is exposed to an infectious disease. The model has recently gained much traction due to the COVID-19 pandemic since the public perception of vaccines plays a significant role in disease dynamics. This paper studies th...

Glauber dynamics are a natural model of dynamics of dependent systems. While originally introduced in statistical physics, they have found important applications in the study of social networks, computer vision and other domains. In this work, we introduce a model of corrupted Glauber dynamics whereby instead of updating according to the prescribed...

Economic analysis has approached the problem of the neutrality of money through methods of supply-demand equilibrium in which changes in aggregate demand due to monetary or fiscal policy are equivalent to changes in the denomination of the monetary standard. We reexamine this question using statistical equilibrium methods adapted from statistical p...

This paper is divided into two parts. The first part is devoted to the study of a class of Approximate Message Passing (AMP) algorithms which are widely used in the fields of statistical physics, machine learning, or communication theory. The AMP algorithms studied in this part are those where the measurement matrix has independent elements, up to...

We propose a new approach to identifying geographical clustering and hotspots of inequality from decadal census data. We use diffusion mapping to study the 181,408 Output Areas in England and Wales, which allows us to decompose the feature structures of countries in the census data space. Additionally, we develop a new localization metric inspired...

Modern technology has brought novel types of wealth. In contrast to hard cash, digital currency does not have a physical form. It exists in electronic forms only. To date, it has not been clear what impacts its ongoing growth will have, if any, on wealth distribution. Here, we propose to identify all forms of contemporary wealth into two classes: '...

In two-dimensional statistical physics, correlation functions of the O(N) and Potts models may be written as sums over configurations of non-intersecting loops. We define sums associated to a large class of combinatorial maps (also known as ribbon graphs). We allow disconnected maps, but not maps that include monogons. Given a map with n vertices,...

Generative Autoregressive Neural Networks (ARNN) have recently demonstrated exceptional results in image and language generation tasks, contributing to the growing popularity of generative models in both scientific and commercial applications. This work presents a physical interpretation of the ARNNs by reformulating the Boltzmann distribution of b...

Ecosystems that consist in a large number of species are often modelled as Lotka-Volterra dynamical systems built around a large random interaction matrix. Under some known conditions, global equilibria exist for such dynamical systems. This paper is devoted towards studying rigorously the asymptotic behavior of the distribution of the elements of...

The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians...

The Burgers-type equations are noticed in plasma astrophysics, ocean dynamics, atmospheric science, computational fluid mechanics, cosmology, condensed matter physics, statistical physics, nonlinear acoustics, vehicular traffic, electronic transport, etc. This prompts us to examine an extended (2 + 1)-dimensional coupled Burgers system in fluid mec...

Spin glasses are disordered magnets with random interactions that are, generally, in conflict with each other. Finding the ground states of spin glasses is not only essential for understanding the nature of disordered magnets and many other physical systems, but also useful to solve a broad array of hard combinatorial optimization problems across m...

We develop new tools in the theory of nonlinear random matrices and apply them to study the performance of the Sum of Squares (SoS) hierarchy on average-case problems. The SoS hierarchy is a powerful optimization technique that has achieved tremendous success for various problems in combinatorial optimization, robust statistics and machine learning...

The spread of seizures across brain networks is the main impairing factor, often leading to loss-of-consciousness, in people with epilepsy. Despite advances in recording and modeling brain activity, uncovering the nature of seizure spreading dynamics remains an important challenge to understanding and treating pharmacologically resistant epilepsy....

The availability of training data remains a significant obstacle for the implementation of machine learning in scientific applications. In particular, estimating how a system might respond to external forcings or perturbations requires specialized labeled data or targeted simulations, which may be computationally intensive to generate at scale. In...

Grammatical forms are said to evolve via two main mechanisms. These are, respectively, the `descent' mechanism, where current forms can be seen to have descended (albeit with occasional modifications) from their roots in ancient languages, and the `contact' mechanism, where evolution in a given language occurs via borrowing from other languages wit...

The time dependent Ginzburg Landau equation (TGLE) is a prototype model of non-equilibrium statistical physics and critical phenomena. This brief report points out that, applying TGLE to the chaotic dynamics of interacting fields hints to unexpected solutions to the challenges confronting high-energy theory.

Constitutive relations are fundamental and essential to characterize physical systems. By utilizing the κ-deformed functions, some constitutive relations are generalized. We here show some applications of the Kaniadakis distributions, based on the inverse hyperbolic sine function, to some topics belonging to the realm of statistical physics and nat...

Greece is one of Europe’s most seismically active areas. Seismic activity in Greece has been characterized by a series of strong earthquakes with magnitudes up to Mw = 7.0 over the last five years. In this article we focus on these strong events, namely the Mw6.0 Arkalochori (27 September 2021), the Mw6.3 Elassona (3 March 2021), the Mw7.0 Samos (3...

Electron temperature is reconsidered for weakly-ionized oxygen and nitrogen plasmas with its discharge pressure of a few hundred Pa, with its electron density of the order of 10^{17}m^{-3} and in a state of non-equilibrium, based on thermodynamics and statistical physics. The relationship between entropy and electron mean energy is focused on based...

The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stored in a recurrent network of neurons, given its synaptic connectivity matrix. Here, we address this...

Studying independent sets of maximum size is equivalent to considering the hard-core model with the fugacity parameter $$\lambda $$ λ tending to infinity. Finding the independence ratio of random d -regular graphs for some fixed degree d has received much attention both in random graph theory and in statistical physics. For $$d \ge 20$$ d ≥ 20 the...

The adsorption of As(V), Pb(II), Cd(II), and Cr(III) ions from aqueous solutions on natural and modified chabazite was studied. The functionalization of chabazite was performed via a protonation and calcination with the aim of generating Lewis acid sites to improve its anion exchange properties. The surface and physicochemical properties of both ad...

The critical brain hypothesis posits that neural circuits may operate close to critical points of a phase transition, which has been argued to have functional benefits for neural computation. Theoretical and computational studies arguing for or against criticality in neural dynamics largely rely on establishing power laws or scaling functions of st...

In this paper we present a new Monte Carlo Search (MCS) algorithm for finding the ground state energy of proteins in the HP-model. We also compare it briefly to other MCS algorithms not usually used on the HP-model and provide an overview of the algorithms used on HP-model. The algorithm presented in this paper does not beat state of the art algori...

p>Brain Inspired Computing (BIC) is an emerging research field that aims to build fundamental theories, models, hardware architectures, and application systems toward more general Artificial Intelligence (AI) by learning from the information processing mechanisms or structures/functions of biological nervous systems. It is regarded as one of the mo...

Since the 1990s, as we know, comparability and incomparability graphs find use in experimental sciences, particularly in chemistry and physical chemistry as well as in statistical physics, to characterize molecular properties, order isomers or specify the topology of certain structures such as chemical structures. In this mostly historical article,...

Natural populations are virtually never observed in equilibrium, yet equilibrium approximations comprise the majority of our understanding of population genetics. Using standard tools from statistical physics, a formalism is presented that re-expresses the stochastic equations describing allelic evolution as a partition functional over all possible...

Oceans at a depth ranging from ~100 to ~1000-m (defined as the intermediate water here), though poorly understood compared to the sea surface, is a critical layer of the Earth system where many important oceanographic processes take place. Advances in ocean observation and computer technology have allowed ocean science to enter the era of big data...

The dependence of elastomers' behavior on loading conditions, e.g., strain rate or temperature, has been the subject of interest in recent decades, and numerous phenomenological models have captured it successfully. However, given the complexity of the compound property relation, so far, a few physics-based models can take into account the micromec...

Conflicting interests between individuals and groups are always emphasized in collective actions towards goals such as resource sustainability and environmental protection. These social dilemmas can be modeled by public goods games and collective risk dilemmas. However, the reality is that multiple generations share a common pool of resources, whic...

These pages include the book cover, Preface, Contents, chapter abstracts, contributors, index, bookback of the book ALL ABOUT SCIENCE: PHILOSOPHY, HISTORY, SOCIOLOGY & COMMUNICATION, M. Burguete & L. Lam (eds.) (World Scientific, 2014). The importance of science goes without saying. Yet there is a lot of confusion and misconception concerning Scien...

The partial theta function is the sum of the series \medskip\centerline{$\displaystyle\theta (q,x):=\sum\nolimits _{j=0}^{\infty}q^{j(j+1)/2}x^j$,}\medskip\noi where $q$is a real or complex parameter ($|q|<1$). Its name is due to similaritieswith the formula for the Jacobi theta function$\Theta (q,x):=\sum _{j=-\infty}^{\infty}q^{j^2}x^j$. The func...

The derivations of the most probable distribution are not self-consistent in most statistical physics textbooks since the Stirling’s approximation adopted in the derivations is not valid for systems with very few particles. Any improvement by taking more higher terms of the Stirling series is insufficient due to erroneous divergence for small numbe...

This paper proposes to build a bridge between microscopic descriptions of matter with internal energy, composed of many fast interacting particles inside an environment, and their port-Hamiltonian (PH) descriptions at macroscopic scale. The environment, assumed to be slow, is modeled through experimental constraints on macroscopic quantities (e.g....

Bio-polymer networks are ubiquitous in nature and fulfil unique mechanical and biological functionalities that sensitively rely on the mesoscopic structure of the network. Understanding how these structures are encoded for by the bio-macromolecular building blocks would open up a powerful means to design novel soft materials, but remains hampered b...

This is part II of a review relating to the three classes of random non-Hermitian Gaussian matrices introduced by Ginibre in 1965. While part I restricted attention to the GinUE (Ginibre unitary ensemble) case of complex elements, in this part the cases of real elements (GinOE, denoting Ginibre orthogonal ensemble) and quaternion elements represent...

Computation of entropy in liquids and liquid crystal phases is a big challenge in statistical physics. In this work, we extend the two-phase thermodynamic model (2PT) to shape anisotropic soft repulsive spherocylinders (SRSs) and report the absolute values of entropy for different liquid crystal (LC) phases for a range of aspect ratios L/D = 2-5. W...

This is a non-standard exposition of main notions of quantum mechanics and quantum field theory that also includes some recent results. It is based on algebraic approach where the starting point is an associative algebra with involution and states are defined as positive linear functionals on this algebra and on geometric approach where the startin...

Exclusion processes in one dimension first appeared in the 70s and have since dragged much attention from communities in different domains: stochastic processes, out-of-equilibriums statistical physics, and more recently integrable systems. While the state of the art for a single species totally asymmetric simple exclusion process (TASEP) can be de...

Regression models usually tend to recover a noisy signal in the form of a combination of regressors, also called features in machine learning, themselves being the result of a learning process. The alignment of the prior covariance feature matrix with the signal is known to play a key role in the generalization properties of the model, i.e. its abi...

The Slutsky equation, central in consumer choice theory, is derived from the usual hypotheses underlying most standard models in Economics, such as full rationality, homogeneity, and absence of interactions. We present a statistical physics framework that allows us to relax such assumptions. We first derive a general \textit{fluctuation-response} f...

This Special Issue is a subsequent edition of a previous collection that focused on the notion of distance in two major fields: Distance in Information and Statistical Physics Volume 2 [...]

In this research, the solid–liquid adsorption systems for MSAC (PbFe2O4 spinel-activated carbon)-phenol and pristine activated carbon-phenol were scrutinized from the thermodynamics and statistical physics (sta-phy) viewpoints. Experimental results indicated that MSAC composite outperformed pristine AC for the uptake of phenol from waste streams. B...