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T. J. P. Penna

Publications and source records attributed to T. J. P. Penna.

At least 19 recordsLinked to original sources
arXiv2024

Benchmarking symbolic regression constant optimization schemes

Symbolic regression is a machine learning technique, and it has seen many advancements in recent years, especially in genetic programming approaches (GPSR). Furthermore, it has been known for many years that constant optimization of parameters, during the evolutionary search, greatly increases GPSR performance However, different authors approach such tasks differently and no consensus exists regarding which methods perform best. In this work, we evaluate eight different parameter optimization methods, applied during evolutionary search, over ten known benchmark problems, in two different scenarios. We also propose using an under-explored metric called Tree Edit Distance (TED), aiming to identify symbolic accuracy. In conjunction with classical error measures, we develop a combined analysis of model performance in symbolic regression. We then show that different constant optimization methods perform better in certain scenarios and that there is no overall best choice for every problem. Finally, we discuss how common metric decisions may be biased and appear to generate better models in comparison.

cs.LG↗
arXiv2016

Fingerprint of Tsallis statistics in cosmic ray showers

We investigate the impact of the Tsallis non extensive statistics introduced by intrinsic temperature fluctuations in p-Air ultra high energy interactions on observables of cosmic ray showers, such as the slant depth of the maximum Xmax and the muon number on the ground $n_μ$. The results show that these observables are significantly affected by temperature fluctuations and agree qualitatively with the Heitler model predictions.

hep-ph↗
arXiv2016

A Langevin model for complex cardiological time series

There has been considerable efforts to understand the underlying complex dynamics in physiological time series. Methods originated from statistical physics revealed a non-Gaussian statistics and long range correlations in those signals. This suggests that the regulatory system operates out of equilibrium. Herein the complex fluctuations in blood pressure time series were successful described by physiological motivated Langevin equation under a sigmoid restoring force with multiplicative noise.

q-bio.NC↗
arXiv2012

Dynamical behavior of the Niedermayer algorithm applied to Potts models

In this work we make a numerical study of the dynamic universality class of the Niedermayer algorithm applied to the two-dimensional Potts model with 2, 3, and 4 states. This algorithm updates clusters of spins and has a free parameter, $E_0$, which controls the size of these clusters, such that $E_0=1$ is the Metropolis algorithm and $E_0=0$ regains the Wolff algorithm, for the Potts model. For $-1 0$, spins in different states may be added to the cluster but the dynamic behavior is less efficient than for the Wolff algorithm ($E_0=0$). Therefore, our results show that the Wolff algorithm is the best choice for Potts models, when compared to the Niedermayer's generalization.

cond-mat.stat-mech↗
arXiv2010

Love kills: Simulations in Penna Ageing Model

The standard Penna ageing model with sexual reproduction is enlarged by adding additional bit-strings for love: Marriage happens only if the male love strings are sufficiently different from the female ones. We simulate at what level of required difference the population dies out.

q-bio.PE↗
arXiv2009

Detrended Fluctuation Analysis of Systolic Blood Pressure Control Loop

We use detrended fluctuation analysis (DFA) to study the dynamics of blood pressure oscillations and its feedback control in rats by analyzing systolic pressure time series before and after a surgical procedure that interrupts its control loop. We found, for each situation, a crossover between two scaling regions characterized by exponents that reflect the nature of the feedback control and its range of operation. In addition, we found evidences of adaptation in the dynamics of blood pressure regulation a few days after surgical disruption of its main feedback circuit. Based on the paradigm of antagonistic, bipartite (vagal and sympathetic) action of the central nerve system, we propose a simple model for pressure homeostasis as the balance between two nonlinear opposing forces, successfully reproducing the crossover observed in the DFA of actual pressure signals.

physics.bio-ph↗
arXiv2005

A Harris-Todaro Agent-Based Model to Rural-Urban Migration

The Harris-Todaro model of the rural-urban migration process is revisited under an agent-based approach. The migration of the workers is interpreted as a process of social learning by imitation, formalized by a computational model. By simulating this model, we observe a transitional dynamics with continuous growth of the urban fraction of overall population toward an equilibrium. Such an equilibrium is characterized by stabilization of rural-urban expected wages differential (generalized Harris-Todaro equilibrium condition), urban concentration and urban unemployment. These classic results obtained originally by Harris and Todaro are emergent properties of our model.

physics.soc-ph↗
arXiv2005

Rural-urban migration in d-dimensional lattices

The rural-urban migration phenomenon is analyzed by using an agent-based computational model. Agents are placed on lattices which dimensions varying from d=2 up to d=7. The localization of the agents in the lattice define their social neighborhood (rural or urban) not being related to their spatial distribution. The effect of the dimension of lattice is studied by analyzing the variation of the main parameters that characterizes the migratory process. The dynamics displays strong effects even for around one million of sites, in higher dimensions (d=6, 7).

physics.comp-ph↗
arXiv2005

An agent-based model to rural-urban migration analysis

In this paper we analyze the rural-urban migration phenomena as it is usually observed in economies which are in the early stages of industrialization. The analysis is conducted by means of a statistical mechanics approach which builds a computational agent-based model. Agents are placed on a lattice and the connections among them are described via an Ising like model. Simulations on this computational model show some emergent properties that are common in developing economies, such as a transitional dynamics characterized by continuous growth of urban population, followed by the equalization of expected wages between rural and urban sectors (Harris-Todaro equilibrium condition), urban concentration and increasing of per capita income.

physics.comp-ph↗
arXiv2001

Dynamic Drop Models

We follow the dynamic evolution of a cluster of Ising spins pointing up surrounded by other spins pointing down, on a lattice. The cluster represents a liquid drop. Under a microscopic point of view, the short range ferromagnetic coupling between these spins plays the role of the van der Waals attraction. Alternatively, under a macroscopic point of view, the same ferromagnetic coupling gives rise to the surface tension along the drop boundary. This naive model is applied to the study of different systems, out of thermodynamic equilibrium. For each such a system, other interaction terms can be included, for instance an external magnetic field with a downwards uniform gradient, representing Earth's gravity. Also, for each system, proper dynamic rules and boundary conditions are adopted. The behaviour of such a drop is monitored as a function of time, through computer simulations. Many quantities of interest, in particular those related to drop fragmentation, were measured and the results were compared with available experimental data. The real systems we have in mind are exemplified by water drops falling from a leaky faucet, nuclear multifragmentation, mercury drops falling on the ground, magnetic hysteresis curves, and interface roughness.

cond-mat↗
arXiv2000

Computer Simulations for Biological Ageing and Sexual Reproduction

The sexual version of the Penna model of biological ageing, simulated since 1996, is compared here with alternative forms of reproduction as well as with models not involving ageing. In particular we want to check how sexual forms of life could have evolved and won over earlier asexual forms hundreds of million years ago. This computer model is based on the mutation-accumulation theory of ageing, using bits-strings to represent the genome. Its population dynamics is studied by Monte Carlo methods.

cond-mat.stat-mech↗
arXiv2000

First-order transition in small-world networks

The small-world transition is a first-order transition at zero density $p$ of shortcuts, whereby the normalized shortest-path distance undergoes a discontinuity in the thermodynamic limit. On finite systems the apparent transition is shifted by $Δp \sim L^{-d}$. Equivalently a ``persistence size'' $L^* \sim p^{-1/d}$ can be defined in connection with finite-size effects. Assuming $L^* \sim p^{-τ}$, simple rescaling arguments imply that $τ=1/d$. We confirm this result by extensive numerical simulation in one to four dimensions, and argue that $τ=1/d$ implies that this transition is first-order.

cond-mat.dis-nn↗
arXiv2000

A comparison between broad histogram and multicanonical methods

We discuss the conceptual differences between the Broad Histogram (BHM) and reweighting methods in general, and particularly the so-called Multicanonical (MUCA) approaches. The main difference is that BHM is based on microcanonical, fixed-energy averages which depends only on the good statistics taken {\bf inside} each energy level. The detailed distribution of visits among different energy levels, determined by the particular dynamic rule one adopts, is irrelevant. Contrary to MUCA, where the results are extracted from the dynamic rule itself, within BHM any microcanonical dynamics could be adopted. As a numerical test, we have used both BHM and MUCA in order to obtain the spectral energy degeneracy of the Ising model in $4 \times 4 \times 4$ and $32 \times 32$ lattices, for which exact results are known. We discuss why BHM gives more accurate results than MUCA, even using {\bf the same} Markovian sequence of states. In addition, such advantage increases for larger systems.

cond-mat.stat-mech↗
arXiv1999

Broad Histogram Method for Multiparametric Hamiltonians

We extended the Broad Histogram Method in order to obtain spectral degeneracies for systems with multiparametric Hamiltonians. As examples we obtained the critical lines for the square lattice Ising model with nearest and next-nearest neighbor interactions and the antiferromagnetic Ising model in an external field. For each system, the entire critical line is obtained using data from a single computer run. We also discuss the accuracy and efficiency of our method.

cond-mat.stat-mech↗
arXiv1999

Sliding blocks with random friction and absorbing random walks

With the purpose of explaining recent experimental findings, we study the distribution $A(λ)$ of distances $λ$ traversed by a block that slides on an inclined plane and stops due to friction. A simple model in which the friction coefficient $μ$ is a random function of position is considered. The problem of finding $A(λ)$ is equivalent to a First-Passage-Time problem for a one-dimensional random walk with nonzero drift, whose exact solution is well-known. From the exact solution of this problem we conclude that: a) for inclination angles $θ$ less than $θ_c=\tan(\avμ)$ the average traversed distance $\avλ$ is finite, and diverges when $θ\to θ_c^{-}$ as $\avλ \sim (θ_c-θ)^{-1}$; b) at the critical angle a power-law distribution of slidings is obtained: $A(λ) \sim λ^{-3/2}$. Our analytical results are confirmed by numerical simulation, and are in partial agreement with the reported experimental results. We discuss the possible reasons for the remaining discrepancies.

cond-mat.stat-mech↗
arXiv1999

Monte Carlo Simulation of Magnetic System in the Tsallis Statistics

We apply the Broad Histogram Method to an Ising system in the context of the recently reformulated Generalized Thermostatistics, and we claim it to be a very efficient simulation tool for this non-extensive statistics. Results are obtained for the nearest-neighbour version of the Ising model for a range of values of the $q$ parameter of Generalized Thermostatistics. We found an evidence that the 2D-Ising model does not undergo phase transitions at finite temperatures except for the extensive case $q=1$.

cond-mat.stat-mech↗
arXiv1998

Tsallis statistics with normalized q-expectation values is thermodynamically stable: illustrations

We present a study of both the ``Iterative Procedure'' and the ``$β\to β'$ transformation'', proposed by Tsallis et al (Physica A261, 534) to find the probabilities $p_i$ of a system to be in a state with energy $ε_i$, within the framework of a generalized statistical mechanics. Using stability and convexity arguments, we argue that the iterative procedure does not always provide the right temperature dependence of thermodynamic observables. In addition, we show how to get the correct answers from the ``$β\to β'$ transformation''. Our results provide an evidence that the Tsallis statistics with normalized q-expectation values is stable for all ranges of temperatures. We also show that the cut-off in the computation of probabilities is required to achieve the stable solutions.

cond-mat.stat-mech↗