arXiv subjects

Sergio Davis

Publications and source records attributed to Sergio Davis.

At least 37 records · Page 2Linked to original sources

arXiv2023

Prediction and Retrodiction in Statistical Mechanics from the Principle of Maximum Caliber

A statistical, path-dependent framework to describe time-dependent macroscopic theories using the Principle of Maximum Caliber is presented. By means of this procedure, it is possible to infer predictive non-equilibrium statistical mechanical models from a variational principle, provided that the adequate time-dependent constraints and the state of the system at some specific times are given. The approach is exemplified by obtaining the description of a time-dependent Brownian particle from kinetic restrictions. We relate the predictive nature of a model to the structure of the prior distribution that represents the state of knowledge about the system before the dynamical constraints are considered. Non-predictive models are shown to be possible in the presented framework and as an example, retrodictive dynamics are obtained from the same kinetic constraints.

cond-mat.stat-mech↗

arXiv2022

Configurational density of states and melting of simple solids

We analyze the behavior of the microcanonical and canonical caloric curves for a piecewise model of the configurational density of states of simple solids, in the context of melting from the superheated state, as realized numerically in the Z-method via atomistic molecular dynamics. A first-order phase transition with metastable regions is reproduced by the model, being therefore useful to describe aspects of the melting transition. Within this model, transcendental equations connecting the superheating limit, the melting point, and the specific heat of each phase are presented and numerically solved. Our results suggest that the essential elements of the microcanonical Z curves can be extracted from simple modeling of the configurational density of states.

cond-mat.stat-mech↗

arXiv2022

A classification of nonequilibrium steady states based on temperature correlations

Although generalized ensembles have now been in use in statistical mechanics for decades, including frameworks such as Tsallis' nonextensive statistics and superstatistics, a classification of these generalized ensembles outlining the boundaries of validity of different families of models, is still lacking. In this work, such a classification is proposed in terms of supercanonical and subcanonical ensembles, according to a newly defined parameter, the inverse temperature covariance parameter $\mathcal{U}$. This parameter is non-negative in superstatistics (and is equal to the variance of the inverse temperature) but can be negative for other families of statistical ensembles, adquiring then a broader meaning. It is shown that $\mathcal{U}$ is equal for every region of a composite system in a steady state, and examples are given of supercanonical and subcanonical states.

cond-mat.stat-mech↗

arXiv2022

Temperature fluctuations in finite systems: Application to the one-dimensional Ising chain

The theory of superstatistics, originally proposed for the study of complex nonequilibrium systems, has recently been extended to studies of small systems interacting with a finite environment, because such systems display interestingly similar statistical behavior. In both situations there are several applicable definitions of inverse temperature, either intrinsic or dependent of the statistical ensemble. In this work we develop these concepts focusing our attention on a region of an isolated, one-dimensional Ising chain as an example of a subsystem that does not follow the canonical Gibbs distribution. For this example, we explicitly show that superstatistics cannot describe the behavior of the subsystem, and verify a recently reported relation between the fundamental and microcanonical inverse temperatures. Our results hint at a new framework for dealing with regions of microcanonical systems with positive heat capacity, which should be described by some new class of statistical ensembles outside superstatistics but still preserving the notion of temperature fluctuations.

cond-mat.stat-mech↗

arXiv2022

The $q$-canonical ensemble as a consequence of Bayesian superstatistics

Superstatistics is a generalization of equilibrium statistical mechanics that describes systems in nonequilibrium steady states. Among the possible superstatistical distributions, the $q$-canonical ensemble (also known as Tsallis' statistics, and in plasma physics as Kappa distributions) is probably the most widely used, however the current explanations of its origin are not completely consistent. In this work it is shown that, under a Bayesian interpretation of superstatistics, the origin of the $q$-canonical ensemble can be explained as the superstatistical distribution with maximum Shannon-Jaynes entropy under noninformative constraints. The $q$-canonical distributions are singled out by the mathematical structure of superstatistics itself, and thus no assumptions about the physics of the systems of interest, or regarding their complexity or range of interactions, are needed. These results support the thesis that the success of the $q$-canonical ensemble is information-theoretical in nature, and explainable in terms of the original maximum entropy principle by Jaynes.

cond-mat.stat-mech↗

arXiv2021

A portable and flexible implementation of the Wang--Landau algorithm in order to determine the Density of States

In this work we develop an implementation of the Wang--Landau algorithm [Phys. Rev. Lett. \textbf{86}, 2050-2053 (2001)]. This algorithm allows us to find the density of states (DOS), a function that, for a given system, describes the proportion of states that have a certain energy. The implementation uses the Python language for the algorithm itself, and it can take advantage of any library, such as the powerful LAMMPS library, for the computation of energy. Therefore, the resulting implementation is simple and flexible without sacrificing efficiency. This implementation also considers recent developments in the parallelization of the code for faster computation. We establish the soundness and effectiveness of our implementation by studying well-known systems such as the Ising model, the Lennard--Jones and EAM solids. We have found that our implementation can find the DOS with very good precision in a reasonable amount of time. Therefore, we are equipped with a very powerful and flexible implementation that can be easily used in order to study more realistic models of matter.

cond-mat.stat-mech↗

arXiv2021

A novel Bayesian approach to the computation of the configurational density of states

In this work we develop and implement a novel Bayesian method for computing the DOS of a system. This method is based on the use of a test function with adjustable parameters and we use Bayes theorem to find the best parameters given a certain number of measurements done on the system. This measurements can be done in any ensemble defined by a distribution function. We found that the algorithm can find the DOS in a reasonable amount of time, and that if the test function is suitable enough, the DOS found by the algorithm is very close to the true DOS.

cond-mat.stat-mech↗

arXiv2021

Fluctuating temperature outside superstatistics: thermodynamics of small systems

The existence of fluctuations of temperature has been a somewhat controversial topic in thermodynamics but nowadays it is recognized that they must be taken into account in small, finite systems. Although for nonequilibrium steady states superstatistics is becoming the \textit{de facto} framework for expressing such temperature fluctuations, some recent results put into question the idea of temperature as a phase space observable. In this work we present and explore the statistics that describes a part of an isolated system, small enough to have well-defined uncertainties in energy and temperature, but lacking a superstatistical description. These results motivate the use of the so-called fundamental temperature as an observable and may be relevant for the statistical description of small systems in physical chemistry.

cond-mat.stat-mech↗

arXiv2020

Multiple metastable states in an off-lattice Potts model

The interactions between a group of components are commonly studied in several areas of science (social science, biology, material science, complex dynamical systems, among others) using the methods of thermodynamics and statistical mechanics. In this work we study the properties of the recently proposed off-lattice, two-dimensional Potts model [Eur. Phys. J. B 87, 78 (2014)], originally motivated by the dynamics of agent opinions, and which is described by a Hamiltonian obtained by a maximum entropy inference procedure. We performed microcanonical and canonical Monte Carlo simulations of the first-order phase transition in the model, revealing a caloric curve with metastable regions. Furthermore, we report a "switching" behavior between multiple metastable states. We also note that the thermodynamics of the model has striking similarities with systems having long-range interactions, even though the interactions are short-ranged.

cond-mat.stat-mech↗

arXiv2020

Superheated solid state induced by a single collision event

High-energy incident particles from both pulsed and continuous radiation sources can induce significant damage to the structure of a material by creating vacancy-interstitial pairs and other more complex defects, and this leads typically to localized melting. In this work, we present evidence via molecular dynamics simulations of a superheated solid state in BCC tungsten induced by single PKA events of $\sim$ 1.5 keV of energy. Despite the striking difference between this highly inhomogeneous energy injection and homogeneous melting, the lifetime of the obtained superheated solid state, reaching up to 200 ps, is described through a waiting time distribution in agreement with previous studies on superheating in the Z-method methodology.

cond-mat.mtrl-sci↗

arXiv2020

Conditional maximum entropy and Superstatistics

Superstatistics describes nonequilibrium steady states as superpositions of canonical ensembles with a probability distribution of temperatures. Rather than assume a certain distribution of temperature, recently [J. Phys. A: Math. Theor. 53, 045004 (2020)] we have discussed general conditions under which a system in contact with a finite environment can be described by superstatistics together with a physically interpretable, microscopic definition of temperature. In this work, we present a new interpretation of this result in terms of the standard maximum entropy principle (MaxEnt) using conditional expectation constraints, and provide an example model where this framework can be tested.

cond-mat.stat-mech↗

arXiv2020

Computational Statistical Mechanics of a confined, three-dimensional Coulomb gas

The thermodynamic properties of systems with long-range interactions is still an ongoing challenge, both from the point of view of theory as well as computer simulation. In this work we study a model system, a Coulomb gas confined inside a sphere, by using the Wang-Landau algorithm. We have computed the configurational density of states (CDOS), the thermodynamic entropy and the caloric curve, and compared with microcanonical Metropolis simulations, while showing how concepts such as the configurational inverse temperature can be used to understand some aspects of thermodynamic behavior. A dynamical multistability behavior is seen at low energies in microcanonical Monte Carlo simulations, suggesting that flat-histogram methods are in fact superior alternatives to traditional simulation in complex systems.

cond-mat.stat-mech↗

arXiv2020

Solving equations of motion by using Monte Carlo Metropolis: Novel method via Random Paths and Maximum Caliber Principle

A permanent challenge in physics and other disciplines is to solve partial differential equations, thereby a beneficial investigation is to continue searching for new procedures to do it. In this Letter, a novel Monte-Carlo Metropolis framework is presented for solving the equations of motion in Lagrangian systems. The implementation lies in sampling the paths space with a probability functional obtained by using the maximum caliber principle. The methodology was applied to the free particle and the harmonic oscillator problems, where the numerically-averaged path obtained from the Monte-Carlo simulation converges to the analytical solution from classical mechanics, in an analogous way with a canonical system where energy is minimized by sampling the state space and computing the average state for each system. Thus, we expect that this procedure can be general enough to solve other differential equations in physics and to be a useful tool to calculate the time-dependent properties of dynamical systems in order to understand the non-equilibrium behavior of statistical mechanical systems.

physics.comp-ph↗

arXiv2019

A general statistical model for waiting times until collapse of a system

The distribution of waiting times until the occurrence of a critical event is a crucial statistical problem across several disciplines in Science. In this work we present a statistical model in which a relevant quantity X accumulates until overcoming a threshold X*, which defines the collapse. The obtained waiting time distribution is a mixture of gamma distributions, which in turn can be approximated as an effective gamma distribution.

stat.AP↗

arXiv2019

Fluctuation theorems in nonextensive statistics

Nonextensive statistics is a formalism of statistical mechanics that describes the ocurrence of power-law distributions in complex systems, particularly the so-called $q$ exponential family of distributions. In this work we present the use of fluctuation theorems for $q$-canonical ensembles as a powerful tool to readily obtain statistical properties. In particular, we have obtained strong conditions for the possible values of $q$ depending on the density of states of the system.

cond-mat.stat-mech↗

arXiv2019

On the possible distributions of temperature in nonequilibrium steady states

Superstatistics is a framework in nonequilibrium statistical mechanics that successfully describes a wide variety of complex systems, including hydrodynamic turbulence, weakly-collisional plasmas, cosmic rays, power grid fluctuations, among several others. In this work we analyze the class of nonequilibrium steady-state systems consisting of a subsystem and its environment, and where the subsystem is described by the superstatistical framework. In this case we provide an answer to the mechanism by which a broad distribution of temperature arises, namely due to correlation between subsystem and environment. We prove that there is a unique microscopic definition $\mathcal{B}$ of inverse temperature compatible with superstatistics, in the sense that all moments of $\mathcal{B}$ and $β=1/(k_B T)$ coincide. The function $\mathcal{B}$ however, cannot depend on the degrees of freedom of the system itself, only on the environment, in full agreement with our previous impossibility theorem [Physica A \textbf{505}, 864-870 (2018)]. The present results also constrain the possible joint ensembles of system and environment compatible with superstatistics.

cond-mat.stat-mech↗

arXiv2019

Single-particle velocity distributions of collisionless, steady-state plasmas must follow Superstatistics

The correct modelling of velocity distribution functions for particles in steady-state plasmas is a central element in the study of nuclear fusion and also in the description of space plasmas. In this work, a statistical mechanical formalism for the description of collisionless plasmas in a steady state is presented, based solely on the application of the rules of probability and not relying on the concept of entropy. Beck and Cohen's superstatistical framework is recovered as a limiting case, and a "microscopic" definition of inverse temperature $β$ is given. Non-extensivity is not invoked a priori but enters the picture only through the analysis of correlations between parts of the system.

cond-mat.stat-mech↗

arXiv2019

Extended correlations in the critical superheated solid

Metastable states in first-order phase transitions reveal interesting behavior about a wide range of systems in statistical mechanics, including spin systems, cellular automata and condensed matter systems. These metastable states are often observed in a microcanonical setting, where they manifest long-range correlations due to collective effects. In this work we show the existence of long-range potential energy correlations between atoms in a microcanonical superheated Lennard-Jones crystal prior to homogeneous melting. Our results suggest that the cooperative motion made possible by the presence of vacancy-interstitial pairs above the melting temperature induces effective long-range interatomic forces even beyond the fourth neighboring layer.

cond-mat.stat-mech↗