Equilibrium fluctuation theorems compatible with anomalous response

Previously, we have derived a generalization of the canonical fluctuation relation between heat capacity and energy fluctuations $C=\beta^{2}<\delta U^{2}>$, which is able to describe the existence of macrostates with negative heat capacities $C<0$. In this work, we extend our previous results for an equilibrium situation with several control parameters to account for the existence of states with anomalous values in other response functions. Our analysis leads to the derivation of three different equilibrium fluctuation theorems: the \textit{fundamental and the complementary fluctuation theorems}, which represent the generalization of two fluctuation identities already obtained in previous works, and the \textit{associated fluctuation theorem}, a result that has no counterpart in the framework of Boltzmann-Gibbs distributions. These results are applied to study the anomalous susceptibility of a ferromagnetic system, in particular, the case of 2D Ising model.Comment: Extended version of the paper published in JSTA

Extending canonical Monte Carlo methods II

Previously, we have presented a methodology to extend canonical Monte Carlo methods inspired on a suitable extension of the canonical fluctuation relation $C=\beta^{2}$ compatible with negative heat capacities $C<0$. Now, we improve this methodology by introducing a better treatment of finite size effects affecting the precision of a direct determination of the microcanonical caloric curve $\beta (E) =\partial S(E) /\partial E$, as well as a better implementation of MC schemes. We shall show that despite the modifications considered, the extended canonical MC methods possibility an impressive overcome of the so-called \textit{super-critical slowing down} observed close to the region of a temperature driven first-order phase transition. In this case, the dependence of the decorrelation time $\tau$ with the system size $N$ is reduced from an exponential growth to a weak power-law behavior $\tau(N)\propto N^{\alpha}$, which is shown in the particular case of the 2D seven-state Potts model where the exponent $\alpha=0.14-0.18$.Comment: Version submitted to JSTA

Geometrical aspects and connections of the energy-temperature fluctuation relation

Recently, we have derived a generalization of the known canonical fluctuation relation $k_{B}C=\beta^{2}$ between heat capacity $C$ and energy fluctuations, which can account for the existence of macrostates with negative heat capacities $C<0$. In this work, we presented a panoramic overview of direct implications and connections of this fluctuation theorem with other developments of statistical mechanics, such as the extension of canonical Monte Carlo methods, the geometric formulations of fluctuation theory and the relevance of a geometric extension of the Gibbs canonical ensemble that has been recently proposed in the literature.Comment: Version accepted for publication in J. Phys. A: Math and The

Classification of life by the mechanism of genome size evolution

The classification of life should be based upon the fundamental mechanism in the evolution of life. We found that the global relationships among species should be circular phylogeny, which is quite different from the common sense based upon phylogenetic trees. The genealogical circles can be observed clearly according to the analysis of protein length distributions of contemporary species. Thus, we suggest that domains can be defined by distinguished phylogenetic circles, which are global and stable characteristics of living systems. The mechanism in genome size evolution has been clarified; hence main component questions on C-value enigma can be explained. According to the correlations and quasi-periodicity of protein length distributions, we can also classify life into three domains.Comment: 53 pages, 9 figures, 2 table

Thermodynamic fluctuation relation for temperature and energy

The present work extends the well-known thermodynamic relation $C=\beta ^{2}< \delta {E^{2}}>$ for the canonical ensemble. We start from the general situation of the thermodynamic equilibrium between a large but finite system of interest and a generalized thermostat, which we define in the course of the paper. The resulting identity $=1+< \delta {E^{2}}> \partial ^{2}S(E) /\partial {E^{2}}$ can account for thermodynamic states with a negative heat capacity $C<0$; at the same time, it represents a thermodynamic fluctuation relation that imposes some restrictions on the determination of the microcanonical caloric curve $\beta (E) =\partial S(E) /\partial E$. Finally, we comment briefly on the implications of the present result for the development of new Monte Carlo methods and an apparent analogy with quantum mechanics.Comment: Version accepted for publication in J. Phys. A: Math and The

Fluctuation geometry: A counterpart approach of inference geometry

Starting from an axiomatic perspective, \emph{fluctuation geometry} is developed as a counterpart approach of inference geometry. This approach is inspired on the existence of a notable analogy between the general theorems of \emph{inference theory} and the the \emph{general fluctuation theorems} associated with a parametric family of distribution functions $dp(I|\theta)=\rho(I|\theta)dI$, which describes the behavior of a set of \emph{continuous stochastic variables} driven by a set of control parameters $\theta$. In this approach, statistical properties are rephrased as purely geometric notions derived from the \emph{Riemannian structure} on the manifold $\mathcal{M}_{\theta}$ of stochastic variables $I$. Consequently, this theory arises as an alternative framework for applying the powerful methods of differential geometry for the statistical analysis. Fluctuation geometry has direct implications on statistics and physics. This geometric approach inspires a Riemannian reformulation of Einstein fluctuation theory as well as a geometric redefinition of the information entropy for a continuous distribution.Comment: Version submitted to J. Phys. A. 26 pages + 2 eps figure

Proper motions of the HH1 jet

We describe a new method for determining proper motions of extended objects, and a pipeline developed for the application of this method. We then apply this method to an analysis of four epochs of [S~II] HST images of the HH~1 jet (covering a period of $\sim 20$~yr). We determine the proper motions of the knots along the jet, and make a reconstruction of the past ejection velocity time-variability (assuming ballistic knot motions). This reconstruction shows an "acceleration" of the ejection velocities of the jet knots, with higher velocities at more recent times. This acceleration will result in an eventual merging of the knots in $\sim 450$~yr and at a distance of $\sim 80"$ from the outflow source, close to the present-day position of HH~1.Comment: 12 pages, 8 figure

A computationally efficient reduced order model to generate multi-parameter fluid-thermal databases

A reduced order model (ROM) is proposed to generate multi-parameter databases of some fluid-thermal problems, using a combination of proper orthogonal decomposition, a gradient-like method, and a continuation method. The resulting ROM greatly reduces the CPU time required by slower methods based on genetic algorithm formulations. As a byproduct, the number of required snapshots is also reduced, which yields an additional improvement of the computational efficiency. The work presented in this article aims to facilitate the use of ROMs in industrial environments, in which time is a very important asset. The methodology is illustrated with the non-isothermal flow past a backward-facing step in the laminar regime, which is a representative problem, related to the engineering design of micro-heat sinks