PRODUÇÃO CIENTÍFICA BRASILEIRA EM ADMINISTRAÇÃO NA DÉCADA DE 2000

Presentation at the forum: scientific production in Business Administration in the period 2000-2010 with reflections and ideas in the area. Presentation at the forum: scientific production in Business Administration in the period 2000-2010 with reflections and ideas in the area

A p-Spin Interaction Ashkin-Teller Spin-Glass Model

A p-spin interaction Ashkin-Teller spin glass, with three independent Gaussian probability distributions for the exchange interactions, is studied by means of the replica method. A simple phase diagram is obtained within the replica-symmetric approximation, presenting an instability of the paramagnetic solution at low temperatures. The replica-symmetry-breaking procedure is implemented and a rich phase diagram is obtained; besides the paramagnetic phase, three distinct spin-glass phases appear. Three first-order critical frontiers are found and they all meet at a triple point; among such lines, two of them present discontinuities in the order parameters, but no latent heat, whereas the other one exhibits both discontinuities in the order parameters and a finite latent heat.Comment: 17 pages, 2 figures, submitted to Physica

Degeneracy Algorithm for Random Magnets

It has been known for a long time that the ground state problem of random magnets, e.g. random field Ising model (RFIM), can be mapped onto the max-flow/min-cut problem of transportation networks. I build on this approach, relying on the concept of residual graph, and design an algorithm that I prove to be exact for finding all the minimum cuts, i.e. the ground state degeneracy of these systems. I demonstrate that this algorithm is also relevant for the study of the ground state properties of the dilute Ising antiferromagnet in a constant field (DAFF) and interfaces in random bond magnets.Comment: 17 pages(Revtex), 8 Postscript figures(5color) to appear in Phys. Rev. E 58, December 1st (1998

Spinodal Decomposition in a Binary Polymer Mixture: Dynamic Self Consistent Field Theory and Monte Carlo Simulations

We investigate how the dynamics of a single chain influences the kinetics of early stage phase separation in a symmetric binary polymer mixture. We consider quenches from the disordered phase into the region of spinodal instability. On a mean field level we approach this problem with two methods: a dynamical extension of the self consistent field theory for Gaussian chains, with the density variables evolving in time, and the method of the external potential dynamics where the effective external fields are propagated in time. Different wave vector dependencies of the kinetic coefficient are taken into account. These early stages of spinodal decomposition are also studied through Monte Carlo simulations employing the bond fluctuation model that maps the chains -- in our case with 64 effective segments -- on a coarse grained lattice. The results obtained through self consistent field calculations and Monte Carlo simulations can be compared because the time, length, and temperature scales are mapped onto each other through the diffusion constant, the chain extension, and the energy of mixing. The quantitative comparison of the relaxation rate of the global structure factor shows that a kinetic coefficient according to the Rouse model gives a much better agreement than a local, i.e. wave vector independent, kinetic factor. Including fluctuations in the self consistent field calculations leads to a shorter time span of spinodal behaviour and a reduction of the relaxation rate for smaller wave vectors and prevents the relaxation rate from becoming negative for larger values of the wave vector. This is also in agreement with the simulation results.Comment: Phys.Rev.E in prin

Self-adapting method for the localization of quantum critical points using Quantum Monte Carlo techniques

A generalization to the quantum case of a recently introduced algorithm (Y. Tomita and Y. Okabe, Phys. Rev. Lett. {\bf 86}, 572 (2001)) for the determination of the critical temperature of classical spin models is proposed. We describe a simple method to automatically locate critical points in (Quantum) Monte Carlo simulations. The algorithm assumes the existence of a finite correlation length in at least one of the two phases surrounding the quantum critical point. We illustrate these ideas on the example of the critical inter-chain coupling for which coupled antiferromagnetic S=1 spin chains order at T=0. Finite-size scaling relations are used to determine the exponents, $\nu=0.72(2)$ and $\eta=0.038(3)$ in agreement with previous estimates.Comment: 5 pages, 3 figures, published versio

Critical Phenomena with Linked Cluster Expansions in a Finite Volume

Linked cluster expansions are generalized from an infinite to a finite volume. They are performed to 20th order in the expansion parameter to approach the critical region from the symmetric phase. A new criterion is proposed to distinguish 1st from 2nd order transitions within a finite size scaling analysis. The criterion applies also to other methods for investigating the phase structure such as Monte Carlo simulations. Our computational tools are illustrated at the example of scalar O(N) models with four and six-point couplings for $N=1$ and $N=4$ in three dimensions. It is shown how to localize the tricritical line in these models. We indicate some further applications of our methods to the electroweak transition as well as to models for superconductivity.Comment: 36 pages, latex2e, 7 eps figures included, uuencoded, gzipped and tarred tex file hdth9607.te

Electron Glass in Ultrathin Granular Al Films at Low Temperatures

Quench-condensed granular Al films, with normal-state sheet resistance close to 10 k$\Omega/\Box$, display strong hysteresis and ultraslow, non-exponential relaxation in the resistance when temperature is varied below 300 mK. The hysteresis is nonlinear and can be suppressed by a dc bias voltage. The relaxation time does not obey the Arrhenius form, indicating the existence of a broad distribution of low energy barriers. Furthermore, large resistance fluctuations, having a 1/f-type power spectrum with a low-frequency cut-off, are observed at low temperatures. With decreasing temperature, the amplitude of the fluctuation increases and the cut-off frequency decreases. These observations combine to provide a coherent picture that there exists a new glassy electron state in ultrathin granular Al films, with a growing correlation length at low temperatures.Comment: RevTeX 3.1, 4 pages, 4 figures (EPS files) (Minor Additions

The genotype-phenotype relationship in multicellular pattern-generating models - the neglected role of pattern descriptors

Background: A deep understanding of what causes the phenotypic variation arising from biological patterning processes, cannot be claimed before we are able to recreate this variation by mathematical models capable of generating genotype-phenotype maps in a causally cohesive way. However, the concept of pattern in a multicellular context implies that what matters is not the state of every single cell, but certain emergent qualities of the total cell aggregate. Thus, in order to set up a genotype-phenotype map in such a spatiotemporal pattern setting one is actually forced to establish new pattern descriptors and derive their relations to parameters of the original model. A pattern descriptor is a variable that describes and quantifies a certain qualitative feature of the pattern, for example the degree to which certain macroscopic structures are present. There is today no general procedure for how to relate a set of patterns and their characteristic features to the functional relationships, parameter values and initial values of an original pattern-generating model. Here we present a new, generic approach for explorative analysis of complex patterning models which focuses on the essential pattern features and their relations to the model parameters. The approach is illustrated on an existing model for Delta-Notch lateral inhibition over a two-dimensional lattice. Results: By combining computer simulations according to a succession of statistical experimental designs, computer graphics, automatic image analysis, human sensory descriptive analysis and multivariate data modelling, we derive a pattern descriptor model of those macroscopic, emergent aspects of the patterns that we consider of interest. The pattern descriptor model relates the values of the new, dedicated pattern descriptors to the parameter values of the original model, for example by predicting the parameter values leading to particular patterns, and provides insights that would have been hard to obtain by traditional methods. Conclusion: The results suggest that our approach may qualify as a general procedure for how to discover and relate relevant features and characteristics of emergent patterns to the functional relationships, parameter values and initial values of an underlying pattern-generating mathematical model

Unconventional ferromagnetic and spin-glass states of the reentrant spin glass Fe0.7Al0.3

Spin excitations of single crystal Fe0.7Al0.3 were investigated over a wide range in energy and reciprocal space with inelastic neutron scattering. In the ferromagnetic phase, propagating spin wave modes become paramagnon-like diffusive modes beyond a critical wave vector q0, indicating substantial disorder in the long-range ordered state. In the spin glass phase, spin dynamics is strongly q-dependent, suggesting remnant short-range spin correlations. Quantitative model for S(energy,q) in the ``ferromagnetic'' phase is determined.Comment: 4 pages, 5 figure

Loop algorithms for quantum simulations of fermion models on lattices

Two cluster algorithms, based on constructing and flipping loops, are presented for worldline quantum Monte Carlo simulations of fermions and are tested on the one-dimensional repulsive Hubbard model. We call these algorithms the loop-flip and loop-exchange algorithms. For these two algorithms and the standard worldline algorithm, we calculated the autocorrelation times for various physical quantities and found that the ordinary worldline algorithm, which uses only local moves, suffers from very long correlation times that makes not only the estimate of the error difficult but also the estimate of the average values themselves difficult. These difficulties are especially severe in the low-temperature, large-$U$ regime. In contrast, we find that new algorithms, when used alone or in combinations with themselves and the standard algorithm, can have significantly smaller autocorrelation times, in some cases being smaller by three orders of magnitude. The new algorithms, which use non-local moves, are discussed from the point of view of a general prescription for developing cluster algorithms. The loop-flip algorithm is also shown to be ergodic and to belong to the grand canonical ensemble. Extensions to other models and higher dimensions is briefly discussed.Comment: 36 pages, RevTex ver.