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Gonzalo Gutiérrez

Publications and source records attributed to Gonzalo Gutiérrez.

12 recordsLinked to original sources

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↗

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↗

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↗

Emergence of Tsallis statistics as a consequence of invariance

For non-equilibrium systems in a steady state we present two necessary and sufficient conditions for the emergence of $q$-canonical ensembles, also known as Tsallis statistics. These conditions are invariance requirements over the definition of subsystem and environment, and over the joint rescaling of temperature and energy. Our approach is independent of, but complementary to, the notions of Tsallis non-extensive statistics and Superstatistics.

cond-mat.stat-mech↗

Origin of the anomalous semiconducting behaviour in dense lithium

Experimentally, it is known that lithium undergoes a metal to semiconductor transition at about 80 GPA and a reentrant semiconductor to metal transition near 120 GPA. This unusual behaviour has been attributed to the formation of high-pressure electrides in the Li-\textit{Aba}2 phase. Using the accurate wave function based quantum Monte Carlo (DMC) method, we show that the valence charge distribution of the Li-\textit{Aba}2 phase is incompatible with an insulating or semiconducting ground state. At DMC level, the most stable phase at 100 GPA is an orthorhombic oP24 structure with Pbca symmetry whose valence charge density shows an electride paired distribution, in correspondence with the theoretical predictions of Neaton and Ashcroft [Nature 00, 141 (1999)]. Here, we propose the electride pairing in the oP24-(Pbca) phase as the origin of the semiconducting behaviour observed in diamond anvil cell experiments.

cond-mat.mtrl-sci↗

Microcanonical Monte Carlo approach for computing melting curves by atomistic simulations

We report microcanonical Monte Carlo simulations of melting and superheating of a generic, Lennard-Jones system starting from the crystalline phase. The isochoric curve, the melting temperature $T_m$ and the critical superheating temperature $T_{LS}$ obtained are in close agreement (well within the microcanonical temperature fluctuations) with standard molecular dynamics one-phase and two-phase methods. These results validate the use of microcanonical Monte Carlo to compute melting points, a method which has the advantage of only requiring the configurational degrees of freedom. Our findings show that the strict preservation of the Hamiltonian dynamics does not constitute a necessary condition to produce a realistic estimate of $T_{LS}$ and the melting point, which brings new insight on the nature of the melting transition. These results widen the use and applicability of the recently developed Z method for the determination of the melting points of materials.

cond-mat.stat-mech↗

Temperature is not an observable in superstatistics

Superstatistics (Physica A 322, 267-275, 2003) is a formalism that attempts to explain the presence of distributions other than the Boltzmann-Gibbs distributions in Nature, typically power-law behavior, for systems out of equilibrium such as fluids under turbulence, plasmas and gravitational systems. Superstatistics postulates that those systems are found in a superposition of canonical ensembles at different temperatures. The usual interpretation is one of local thermal equilibrium (LTE) in the sense of an inhomogeneous temperature distribution in different regions of space or instants of time. Here we show that, in order for superstatistics to be internally consistent, it is impossible to define a phase-space function or observable $B(p, q)$ corresponding one-to-one to the local value of $β=1/k_B T$. Temperature then belongs to a different class of observables than the energy, which has as a phase-space function the Hamiltonian $\mathcal{H}(p, q)$. An important consequence of our proof is that, in Superstatistics, the identification of temperature with the kinetic energy is limited to the expectation of $β$ and cannot be used to measure the different temperatures in LTE or its fluctuations.

cond-mat.stat-mech↗

Applications of the divergence theorem in Bayesian inference and MaxEnt

Given a probability density $P({\bf x}|{\boldsymbol λ})$, where $\bf x$ represents continuous degrees of freedom and $λ$ a set of parameters, it is possible to construct a general identity relating expectations of observable quantities, which is a generalization of the equipartition theorem in Thermodynamics. In this work we explore some of the consequences of this relation, both in the context of sampling distributions and Bayesian posteriors, and how it can be used to extract some information without the need for explicit calculation of the partition function (or the Bayesian evidence, in the case of posterior expectations). Together with the general family of fluctuation theorems it constitutes a powerful tool for Bayesian/MaxEnt problems.

cond-mat.stat-mech↗

Slipping on an Arbitrary Surface with Friction

The motion of a block slipping on a surface is a well studied problem for flat and circular surfaces, but the necessary conditions for the block to leave (or not) the surface deserve a detailed treatment. In this article, using basic differential geometry, we generalize this problem to an arbitrary surface, including the effects of friction, providing a general expression to determine under which conditions the particle leaves the surface. An explicit integral form for the velocity is given, which is analytically integrable for some cases, and we find general criteria to determine the critical velocity at which the particle immediately leaves the surface. Five curves, a circle, ellipse, parabola, catenary and cycloid, are analyzed in detail. Several interesting features appear, for instance, in the absense of friction, a particle moving on a catenary leaves the surface just before touching the floor, and in the case of the parabola, the particle never leaves the surface, regardless of the friction. A phase diagram that separates the conditions that lead to a particle stopping in the surface to those that lead to a particle departuring from the surface is also discussed.

cond-mat.soft↗

A Bayesian interpretation of abrupt phase transitions

The formalism used in describing the thermodynamics of abrupt (or first-order) phase transitions is reviewed as an application of maximum entropy inference. In this treatment, we show that the concepts of transition temperature, latent heat and entropy difference between phases will inevitably have an equivalent in any problem of inferring the result of a yes/no question, given information in the form of expectation values.

cond-mat.stat-mech↗

A maximum entropy model for opinions in social groups

We study how the opinions of a group of individuals determine their spatial distribution and connectivity, through an agent-based model. The interaction between agents is described by a Potts-like Hamiltonian in which agents are allowed to move freely without an underlying lattice (the average network topology connecting them is determined from the parameters). This kind of model was derived using maximum entropy statistical inference under fixed expectation values of certain probabilities that (we propose) are relevant to social organization. Control parameters emerge as Lagrange multipliers of the maximum entropy problem, and they can be associated with the level of consequence between the personal beliefs and external opinions, and the tendency to socialize with peers of similar or opposing views. These parameters define a phase diagram for the social system, which we studied using Monte Carlo Metropolis simulations. Our model presents both first and second-order phase transitions, depending on the ratio between the internal consequence and the interaction with others. We have found a critical value for the level of internal consequence, below which the personal beliefs of the agents seem to be irrelevant.

physics.soc-ph↗

Newtonian Dynamics from the principle of Maximum Caliber

The foundations of Statistical Mechanics can be recovered almost in their entirety from the Principle of Maximum Entropy. In this work we show that its non-equilibrium generalization, the Principle of Maximum Caliber (Jaynes, 1980), when applied to the unknown trajectory followed by a particle, leads to Newton's second law under two quite intuitive assumptions (the expected square displacement in one step and the spatial probability distribution of the particle are known at all times). Our derivation explicitly highlights the role of mass as an emergent measure of the fluctuations in velocity (inertia) and the origin of potential energy as a manifestation of spatial correlations. According to our findings, the application of Newton's equations is not limited to mechanical systems, and therefore could be used in modelling ecological, financial and biological systems, among others.

physics.data-an↗