Long term ordering kinetics of the two dimensional q-state Potts model

We studied the non-equilibrium dynamics of the q-state Potts model in the square lattice, after a quench to sub-critical temperatures. By means of a continuous time Monte Carlo algorithm (non-conserved order parameter dynamics) we analyzed the long term behavior of the energy and relaxation time for a wide range of quench temperatures and system sizes. For q>4 we found the existence of different dynamical regimes, according to quench temperature range. At low (but finite) temperatures and very long times the Lifshitz-Allen-Cahn domain growth behavior is interrupted with finite probability when the system stuck in highly symmetric non-equilibrium metastable states, which induce activation in the domain growth, in agreement with early predictions of Lifshitz [JETP 42, 1354 (1962)]. Moreover, if the temperature is very low, the system always gets stuck at short times in a highly disordered metastable states with finite life time, which have been recently identified as glassy states. The finite size scaling properties of the different relaxation times involved, as well as their temperature dependency are analyzed in detail.Comment: 10 pages, 17 figure

Registration-based model reduction of parameterized two-dimensional conservation laws

We propose a nonlinear registration-based model reduction procedure for rapid and reliable solution of parameterized two-dimensional steady conservation laws. This class of problems is challenging for model reduction techniques due to the presence of nonlinear terms in the equations and also due to the presence of parameter-dependent discontinuities that cannot be adequately represented through linear approximation spaces. Our approach builds on a general (i.e., independent of the underlying equation) registration procedure for the computation of a mapping Φ that tracks moving features of the solution field and on an hyper-reduced least-squares Petrov-Galerkin reduced-order model for the rapid and reliable computation of the solution coefficients. The contributions of this work are twofold. First, we investigate the application of registration-based methods to two-dimensional hyperbolic systems. Second, we propose a multi-fidelity approach to reduce the offline costs associated with the construction of the parameterized mapping and the reduced-order model. We discuss the application to an inviscid supersonic flow past a parameterized bump, to illustrate the many features of our method and to demonstrate its effectiveness

REYNOLDS STRESS CORRECTION BY MACHINE LEARNING METHODS WITH PHYSICAL CONSTRAINTS

For the past three decade, Reynolds Average Navier-Stokes models have been widely used in the industry to simulate complex flows. However, these models suffer from limitations. Indeed there are still large discrepancies in the Reynolds stresses between the RANS model and high-fidelity data provided by DNS or experiments. This paper presents a strategy to correct the Menter SST model using an explicit algebraic model and two different neural networks: An multilayer perceptron (MLP) and a generative adversarial network (GAN). Moreover, in order to preserve the physical properties of the Reynolds stress tensor, we introduce a penalisation term in the loss of the GAN

Advanced simulation code for alpha spectrometry

A Monte Carlo code, known as AASI, is developed for simulating energy spectra in alpha spectrometry. The code documented here is a comprehensive package where all the major processes affecting the spectrum are included. A unique feature of the code is its ability to take into account coincidences between the particles emitted from the source. Simulations and measurements highlight the importance of coincidences in high-resolution alpha spectrometry. To show the validity of the simulated results, comparisons with measurements and other simulation codes are presented.Comment: 21 pages, 4 figures, to be published in Nucl. Instr. and Meth.

Multivariate p-dic L-function

We construct multivariate p-adic L-function in the p-adic number fild by using Washington method.Comment: 9 page

Orthogonal Polynomial Representation of Imaginary-Time Green's Functions

We study the expansion of single-particle and two-particle imaginary-time Matsubara Green's functions of quantum impurity models in the basis of Legendre orthogonal polynomials. We discuss various applications within the dynamical mean-field theory (DMFT) framework. The method provides a more compact representation of the Green's functions than standard Matsubara frequencies and therefore significantly reduces the memory-storage size of these quantities. Moreover, it can be used as an efficient noise filter for various physical quantities within the continuous-time quantum Monte Carlo impurity solvers recently developed for DMFT and its extensions. In particular, we show how to use it for the computation of energies in the context of realistic DMFT calculations in combination with the local density approximation to the density functional theory (LDA+DMFT) and for the calculation of lattice susceptibilities from the local irreducible vertex function.Comment: 14 pages, 11 figure

IL-1R and inflammasomes mediate early pulmonary protective mechanisms in respiratory brucella abortus infection

Brucella spp. infection is frequently acquired through contaminated aerosols. The role of interleukin-1 beta (IL-1β) in the early pulmonary response to respiratory Brucella infection is unknown. As shown here, IL-1β levels in lung homogenates and bronchoalveolar lavage fluid (BALF) of mice intratracheally inoculated with B. abortus were increased at 3 and 7 days p.i. At 7 days p.i., pulmonary CFU numbers were higher in IL-1 receptor (IL-1R) knockout (KO) mice than in wild type (WT) mice. At different times p.i. CFU in lungs and BALF were higher in mice lacking some inflammasome components (caspase-1, AIM2, NLRP3) than in WT mice. At 2 days p.i. pulmonary levels of IL-1b and CXCL1 (neutrophils chemoattractant) were lower in caspase-1/11 KO mice. At day 3 p.i., neutrophils counts in BALF were lower in caspase-1/11 KO mice than in WT mice. During in vitro infections, IL-1β secretion was lower in alveolar macrophages from caspase-1/11, NLRP3 or AIM2 KO mice than in WT controls. Similarly, IL-1β production by B. abortus-infected alveolar epithelial cells was reduced by pretreatment with a specific caspase-1 inhibitor. This study shows that IL-1R, probably through IL-1β action, and the NLRP3 and AIM2 inflammasomes are involved in pulmonary innate immune protective mechanisms against respiratory B. abortus infection.Fil: Hielpos, María Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica; ArgentinaFil: Fernandez, Andrea Giselle. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Falivene, Juliana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Alonso Paiva, Iván Mathias. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Muñoz González, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Ferrero, Mariana Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Campos, Priscila C.. Universidade Federal de Minas Gerais; BrasilFil: Vieira, Angelica T.. Universidade Federal de Minas Gerais; BrasilFil: Oliveira, Sergio Costa. Universidade Federal de Minas Gerais; BrasilFil: Baldi, Pablo Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; Argentin

Steady-State Diffusion in a Spatially Varying Porous Medium

Heterogeneous porous material represents a persistent challenge in the field of engineering. Microscale properties such as the porosity and microchannel torturosity significantly control the macroscale transport characteristics of homogeneous porous medium. Additional complexity is introduced when these small-scale features vary in space. Examples of heterogeneous porous systems include artificial body tissues, groundwater flow across different soil types, and asymmetric membrane filtration systems. While these processes are ubiquitous in engineering applications, modeling a fully resolved porous material larger than a few millimeters is restricted by the availability of computational resources. Upscaling techniques such as the method of volume averaging use information from a small portion of the porous medium to derive parameter values to describe transport over the original large-scale system. This research aims to extend the method of volume averaging to modeling heterogeneous systems that contain significant porosity gradients. In particular, a new model is developed that incorporates information relating to the center of mass of the system to the overall transport properties of the heterogeneous porous material. This model is used to model mass transport within a variety of periodic and disordered porous media. The accuracy of the model is compared to previously described MVA models and the limitations and advantages of each model are detailed

Anaphe - OO Libraries and Tools for Data Analysis

The Anaphe project is an ongoing effort to provide an Object Oriented software environment for data analysis in HENP experiments. A range of commercial and public domain libraries is used to cover basic functionalities; on top of these libraries a set of HENP-specific C++ class libraries for histogram management, fitting, plotting and ntuple-like data analysis has been developed. In order to comply with the user requirements for a command-line driven tool, we have chosen to use a scripting language (Python) as the front-end for a data analysis tool. The loose coupling provided by the consequent use of (AIDA compliant) Abstract Interfaces for each component in combination with the use of shared libraries for their implementation provides an easy integration of existing libraries into modern scripting languages thus allowing for rapid application development. This integration is simplified even further using a specialised toolkit (SWIG) to create "shadow classes" for the Python language, which map the definitions of the Abstract Interfaces almost at a one-to-one level. This paper will give an overview of the architecture and design choices and will present the current status and future developments of the project