Thermal dependence of the zero-bias conductance through a nanostructure

We show that the conductance of a quantum wire side-coupled to a quantum dot, with a gate potential favoring the formation of a dot magnetic moment, is a universal function of the temperature. Universality prevails even if the currents through the dot and the wire interfere. We apply this result to the experimental data of Sato et al.[Phys. Rev. Lett. 95, 066801 (2005)].Comment: 6 pages, 3 figures. More detailed presentation, and updated references. Final version

Collapse of Primordial Clouds

We present here studies of collapse of purely baryonic Population III objects with masses ranging from $10M_\odot$ to $10^6M_\odot$. A spherical Lagrangian hydrodynamic code has been written to study the formation and evolution of the primordial clouds, from the beginning of the recombination era ($z_{rec} \sim 1500$) until the redshift when the collapse occurs. All the relevant processes are included in the calculations, as well as, the expansion of the Universe. As initial condition we take different values for the Hubble constant and for the baryonic density parameter (considering however a purely baryonic Universe), as well as different density perturbation spectra, in order to see their influence on the behavior of the Population III objects evolution. We find, for example, that the first mass that collapses is $8.5\times10^4M_\odot$ for $h=1$, $\Omega=0.1$ and $\delta_i={\delta\rho / \rho}=(M / M_o)^{-1/3}(1+z_{rec})^{-1}$ with the mass scale $M_o=10^{15}M_\odot$. For $M_o=4\times10^{17}M_\odot$ we obtain $4.4\times10^{4}M_\odot$ for the first mass that collapses. The cooling-heating and photon drag processes have a key role in the collapse of the clouds and in their thermal history. Our results show, for example, that when we disregard the Compton cooling-heating, the collapse of the objects with masses $>8.5\times10^4M_\odot$ occurs earlier. On the other hand, disregarding the photon drag process, the collapse occurs at a higher redshift.Comment: 10 pages, MN plain TeX macros v1.6 file, 9 PS figures. Also available at http://www.iagusp.usp.br/~oswaldo (click "OPTIONS" and then "ARTICLES"). MNRAS in pres

Collapse of Primordial Clouds II. The Role of Dark Matter

In this article we extend the study performed in our previous article on the collapse of primordial objects. We here analyze the behavior of the physical parameters for clouds ranging from $10^7M_\odot$ to $10^{15}M_\odot$. We studied the dynamical evolution of these clouds in two ways: purely baryonic clouds and clouds with non-baryonic dark matter included. We start the calculations at the beginning of the recombination era, following the evolution of the structure until the collapse (that we defined as the time when the density contrast of the baryonic matter is greater than $10^4$). We analyze the behavior of the several physical parameters of the clouds (as, e.g., the density contrast and the velocities of the baryonic matter and the dark matter) as a function of time and radial position in the cloud. In this study all physical processes that are relevant to the dynamical evolution of the primordial clouds, as for example photon-drag (due to the cosmic background radiation), hydrogen molecular production, besides the expansion of the Universe, are included in the calculations. In particular we find that the clouds, with dark matter, collapse at higher redshift when we compare the results with the purely baryonic models. As a general result we find that the distribution of the non-baryonic dark matter is more concentrated than the baryonic one. It is important to stress that we do not take into account the putative virialization of the non-baryonic dark matter, we just follow the time and spatial evolution of the cloud solving its hydrodynamical equations. We studied also the role of the cooling-heating processes in the purely baryonic clouds.Comment: 8 pages, MN plain TeX macros v1.6 file, 13 PS figures. Also available at http://www.iagusp.usp.br/~oswaldo (click "OPTIONS" and then "ARTICLES"). MNRAS in pres

Numerical simulation study of the dynamical behavior of the Niedermayer algorithm

We calculate the dynamic critical exponent for the Niedermayer algorithm applied to the two-dimensional Ising and XY models, for various values of the free parameter $E_0$. For $E_0=-1$ we regain the Metropolis algorithm and for $E_0=1$ we regain the Wolff algorithm. For $-1<E_0<1$, we show that the mean size of the clusters of (possibly) turned spins initially grows with the linear size of the lattice, $L$, but eventually saturates at a given lattice size $\widetilde{L}$, which depends on $E_0$. For $L>\widetilde{L}$, the Niedermayer algorithm is equivalent to the Metropolis one, i.e, they have the same dynamic exponent. For $E_0>1$, the autocorrelation time is always greater than for $E_0=1$ (Wolff) and, more important, it also grows faster than a power of $L$. Therefore, we show that the best choice of cluster algorithm is the Wolff one, when compared to the Nierdermayer generalization. We also obtain the dynamic behavior of the Wolff algorithm: although not conclusive, we propose a scaling law for the dependence of the autocorrelation time on $L$.Comment: Accepted for publication in Journal of Statistical Mechanics: Theory and Experimen

Forest growth dynamics of managed forests in the Southwestern Brazilian Amazon.

The objective of this work was to present the growth forest dynamics results obtained in two sites located in Acre and Amazonas states in the southwestern Brazilian Amazon.Abstracts of the XXV IUFRO World Congress

Optimizing Connectivity through Network Gradients for the Restricted Boltzmann Machine

Leveraging sparse networks to connect successive layers in deep neural networks has recently been shown to provide benefits to large scale state-of-the-art models. However, network connectivity also plays a significant role on the learning performance of shallow networks, such as the classic Restricted Boltzmann Machines (RBM). Efficiently finding sparse connectivity patterns that improve the learning performance of shallow networks is a fundamental problem. While recent principled approaches explicitly include network connections as model parameters that must be optimized, they often rely on explicit penalization or have network sparsity as a hyperparameter. This work presents a method to find optimal connectivity patterns for RBMs based on the idea of network gradients (NCG): computing the gradient of every possible connection, given a specific connection pattern, and using the gradient to drive a continuous connection strength parameter that in turn is used to determine the connection pattern. Thus, learning RBM parameters and learning network connections is truly jointly performed, albeit with different learning rates, and without changes to the objective function. The method is applied to the MNIST and other datasets showing that better RBM models are found for the benchmark tasks of sample generation and input classification. Results also show that NCG is robust to network initialization, both adding and removing network connections while learning

Manejo e exploração sustentável de florestas naturais tropicais: opções, restrições e alternativas.

Introdução; Conceito e manejo florestal e sustentabilidade; Características das florestas naturais tropicais; Formas de manejo florestal; Manejo de produtos não-madeireiros; Manejo de uso múltiplo; Manejo florestal em área com população; Modelo geral para pequena propriedade; condições gerais para o manejo florestal; Condições imediatas para implantação do manejo florestal.bitstream/CNPF-2009-09/40472/1/doc110.pd

Projected single-spin flip dynamics in the Ising Model

We study transition matrices for projected dynamics in the energy-magnetization space, magnetization space and energy space. Several single spin flip dynamics are considered such as the Glauber and Metropolis canonical ensemble dynamics and the Metropolis dynamics for three multicanonical ensembles: the flat energy-magnetization histogram, the flat energy histogram and the flat magnetization histogram. From the numerical diagonalization of the matrices for the projected dynamics we obtain the sub-dominant eigenvalue and the largest relaxation times for systems of varying size. Although, the projected dynamics is an approximation to the full state space dynamics comparison with some available results, obtained by other authors, shows that projection in the magnetization space is a reasonably accurate method to study the scaling of relaxation times with system size. The transition matrices for arbitrary single-spin flip dynamics are obtained from a single Monte-Carlo estimate of the infinite temperature transition-matrix, for each system size, which makes the method an efficient tool to evaluate the relative performance of any arbitrary local spin-flip dynamics. We also present new results for appropriately defined average tunnelling times of magnetization and compute their finite-size scaling exponents that we compare with results of energy tunnelling exponents available for the flat energy histogram multicanonical ensemble.Comment: 23 pages and 6 figure

Irreversible Opinion Spreading on Scale-Free Networks

We study the dynamical and critical behavior of a model for irreversible opinion spreading on Barab\'asi-Albert (BA) scale-free networks by performing extensive Monte Carlo simulations. The opinion spreading within an inhomogeneous society is investigated by means of the magnetic Eden model, a nonequilibrium kinetic model for the growth of binary mixtures in contact with a thermal bath. The deposition dynamics, which is studied as a function of the degree of the occupied sites, shows evidence for the leading role played by hubs in the growth process. Systems of finite size grow either ordered or disordered, depending on the temperature. By means of standard finite-size scaling procedures, the effective order-disorder phase transitions are found to persist in the thermodynamic limit. This critical behavior, however, is absent in related equilibrium spin systems such as the Ising model on BA scale-free networks, which in the thermodynamic limit only displays a ferromagnetic phase. The dependence of these results on the degree exponent is also discussed for the case of uncorrelated scale-free networks.Comment: 9 pages, 10 figures; added results and discussion on uncorrelated scale-free networks; added references. To appear in PR

Modeling and simulation of micro direct methanol Fuel Cells

Fuel cells have unique technological attributes: efficiency, absence of moving parts and low emissions. The Direct Methanol Fuel Cell (DMFC) has attracted much attention due to its potential applications as a power source for transportation and portable electronic devices. With the advance of micromachining technologies, miniaturization of power sources became one of the trends of evolution of research in this area. Based on the advantages of the scaling laws, miniaturization promises higher efficiency and performance of power generating devices, so, MicroDMFC is an emergent technology. Models play an important role in fuel cell development since they facilitate a better understanding of parameters affecting the performance of fuel cells. In this work, a steady state, one-dimensional model accounting for coupled heat and mass transfer, along with the electrochemical reactions occurring in a fuel cell, already developed and validated for DMFC in [1-3], is used to predict Micro DMFC performance. The model takes in account all relevant phenomena occurring in a DMFC. Polarization curves predicted by the model are compared with experimental data existing in literature and the model shows good agreement, mainly for lower current densities. The model is used to predict some important parameters to analyze fuel cell performance, such as water transport coefficient and leakage current density. This easily to implement simplified model is suitable for use in real-time MicroDMFC simulations