CLUSTEREASY: A program for lattice simulations of scalar fields in an expanding universe on parallel computing clusters

We describe an MPI C++ program that we have written and made available for calculating the evolution of interacting scalar fields in an expanding universe on parallel clusters. The program is a parallel programming extension of the simulation program LATTICEEASY. The ability to run these simulations on parallel clusters, however, greatly extends the range of scales and times that can be simulated. The program is particularly useful for the study of reheating and thermalization after inflation. The program and its full documentation are available on the Web at http://www.science.smith.edu/departments/Physics/fstaff/gfelder/latticeeasy/. In this paper we provide a brief overview of what the program does and what it is useful for.

Program summary

Program title: CLUSTEREASYCatalogue identifier: AEBJ_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBJ_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 7469No. of bytes in distributed program, including test data, etc.: 613 334Distribution format: tar.gzProgramming language: C++/MPIComputer: Cluster. Must have the library FFTW installedOperating system: AnyRAM: Typically 4 MB to 1 GB per processorClassification: 1.9External routines: A single-precision version of the FFTW library (http://www.fftw.org/) must be available on the target machine.Nature of problem: After inflation the universe consisted of interacting fields in a high energy, nonthermal state [1]. The evolution of these fields cannot be described with standard approximation techniques such as linearization, kinetic theory, or Hartree expansion, and must thus be simulated numerically. Fortunately, the fields rapidly acquire large occupation numbers over a range of frequencies, so their evolution can be accurately modeled with classical field theory [2]. The specific fields and interactions relevant at these high energies are not known, so different models must be tested phenomenologically. In many cases, e.g., those involving symmetry breaking, the wide range of physical time and length scales in the problem requires parallel computing.Solution method: CLUSTEREASY solves the equations of motion for interacting scalar fields in an expanding universe. The user describes a particular theory by entering the field potential and its derivatives in a model file and the program then uses a staggered leapfrog method to evolve the field equations and Friedmann equation for the fields and the expansion of the universe. Different processors compute the evolution on subgrids defined by block decomposition, and the processors exchange edge data after each time step to allow for calculation of spatial derivatives.Restrictions: In its current form CLUSTEREASY only includes scalar fields and does not include metric perturbations. For 2D and 3D simulations the cluster must already have the (free) libraries FFTW installed.Additional comments: CLUSTEREASY is the parallel form of the program LATTICEEASY (AEAW_v1_0), Comp. Phys. Comm. 178 (2008) 929.Note: The default installation type for FFTW is double-precision so care must be taken to specify single-precision when running the “configure” file associated with the FFTW software package installation.Running time: The running time can range from minutes to weeks.References:[1] A.D. Linde, Particle Physics and Inflationary Cosmology, Harwood, Chur, Switzerland, 1990.[2] S. Khlebnikov, I. Tkachev, Phys. Rev. Lett. 77 (1996) 219, hep-ph/9603378.     

"Evaluation of child witnesses for confrontation by criminal defendants": Erratum.

Reports an error in the original article by M. A. Small and G. B. Melton (Professional Psychology: Research and Practice, 1994[August], Vol 25[3], 228–233). Footnote 1 incorrectly indicates that the Craig brief was written without the aid of private legal counsel. Though the brief in question was written with more APA member involvement than has been the case for other briefs, private legal counsel participated and was listed as a coauthor. (The following abstract of this article originally appeared in record 1994-43476-001.) States have passed legislation governing the procedures by which children may testify in cases of child abuse. In Maryland v. Craig (1990), the US Supreme Court reviewed the constitutionality of these procedures. As a result, psychologists may be asked to perform evaluations regarding the potential trauma a child faces in confronting a defendant in a criminal case. Specifically, opinions of psychologists may be sought as to the potential trauma a child may endure as a result of a face-to-face confrontation with a defendant. Research relevant to this assessment is reviewed, and it is suggested that psychologists may be of most help in preparing children to testify.… (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A rationale for the TEI recommendations for feature-structure markup

In this paper, we concentrate on justifying the decisions we made in developing the TEI recommendations for feature structure markup. The first four sections of this paper present the justification for the recommended treatment of feature structures, of features and their values, and of combinations of features or values and of alternations and negations of features and their values. Section 5 departs briefly from the linguistic focus to argue that the markup scheme developed for feature structures is in fact a general-purpose mechanism that can be used for a wide range of applications. Section 6 describes an auxiliary document called a feature system declaration that is used to document and validate a system of feature-structure markup. The seventh and final section illustrates the use of the recommended markup scheme with two examples, lexical tagging and interlinear text analysis.Terry Langendoen is Professor and Head of the Department of Linguistics at The University of Arizona. He was Chair of the TEI Committee on Analysis and Interpretation. He received his PhD in Linguistics from the Massachusetts Institute of Technology in 1964, and held teaching positions at The Ohio State University and the City University of New York (Brooklyn College and the Graduate Center) before moving to Arizona in 1988. He is author, co-author, or co-editor of six books in linguistics, and of numerous articles.Gary Simons is Director of the Academic Computing Department of the Summer Institute of Linguistics, Dallas, TX. He served on the TEI Committee on Analysis and Interpretation. He received his PhD in Linguistics (with minor emphasis in Computer Science) from Cornell University in 1979. Before taking up his current position in 1984, he spent five years in the Solomon Islands doing field work with SIL. He is author, co-author, or co-editor of eight books in the fields of linguistics and linguistic computing.The initial feature-structure recommendations were formulated by the Analysis and Interpretation Committee at a meeting in Tucson, Arizona in March 1990, following suggestions by Mitch Marcus and Beatrice Santorini. The authors received valuable help in the further revision and refinement of the recommendations from Steven Zepp.     

Exploring age and gender differences of computational thinkers in primary school: A developmental perspective

Over the past decade, the call to foster computational thinking (CT) in every child has received considerable attention. However, there is little understanding of whether children are developmentally ready to think computationally and what specific CT concepts and skills can be developed at various ages. This study explored the developmental and gender differences in CT skills of 197 Grade 4–6 students (aged 9–13) before being exposed to instruction and investigated the age–gender interaction effects on their CT acquisition in an intervention combining both programming and non-programming (unplugged) activities. Results show that students' CT skills followed a developmental progression before instruction. Gender difference across ages was insignificant in conditionals, logical operators, pattern recognition and generalization skills. Additionally, students of different ages developed CT differently during the intervention, and their CT acquisition was unaffected by gender. Implications for practice and research in CT education were discussed.     

Composite bending-dominated hollow nanolattices: A stiff,cyclable mechanical metamaterial

Manufacturing ultralight and mechanical reliable materials has been a long-time challenge. Ceramic-based mechanical metamaterials provide significant opportunities to reverse their brittle nature and unstable mechanical properties and have great potential as strong, ultralight, and ultrastiff materials. However, the failure of ceramics nanolattice and degradation of strength/modulus with decreasing density are caused by buckling of the struts and failure of the nodes within the nanolattices, especially during cyclic loading. Here, we explore a new class of 3D ceramic-based metamaterials with a high strength–density ratio, stiffness, recoverability, cyclability, and optimal scaling factor. Deformation mode of the fabricated nanolattices has been engineered through the unique material design and architecture tailoring. Bending-dominated hollow nanolattice (B-H-Lattice) structure is employed to take advantages of its flexibility, while a few nanometers of carbonized mussel-inspired bio-polymer (C-PDA) is coherently deposited on ceramics’ nanolayer to enable non-buckling struts and bendable nodes during deformation, resulting in reliable mechanical properties and outperforming the current bending-dominated lattices (B-Lattices) and carbon-based cellulose materials. Meanwhile, the structure has comparable stiffness to stretching-dominated lattices (S-Lattices) while with better cyclability and reliability. The B-H-Lattices exhibit high specific stiffness (>10⁶?Pa·kg^?1·m^?3), low-density (～30?kg/m³), buckling-free recovery at 55% strain, and stable cyclic loading behavior under up to 15% strain. As one of the B-Lattices, the modulus scaling factor reaches 1.27, which is lowest among current B-Lattices. This study suggests that non-buckling behavior and reliable nodes are the key factors that contribute to the outstanding mechanical performance of nanolattice materials. A new concept of engineering the internal deformation behavior of mechanical metamaterial is provided to optimize their mechanical properties in real service conditions.     

Linear,parameter-varying control of a supercavitating vehicle

A systematic approach to parameter-dependent control synthesis of a high-speed supercavitation vehicle (HSSV) is presented. The aim of the control design is to provide robust reference tracking across a large flight envelope, while directly accounting for the interaction of liquid and gas phases with the vehicle. A nonlinear dynamic HSSV model is presented and discussed relative to the actual vehicle. A linear, parameter-varying (LPV) controller is synthesized for angle rate tracking in the presence of model uncertainty. The control design takes advantage of coupling in the governing equations to achieve improved performance. Multiple LPV controllers synthesized for smaller overlapping regions of the parameter space are blended together, providing a single controller for the full flight envelope. Time-domain simulations implemented on high-fidelity simulations, provide insight into the performance and robustness of the proposed scheme.     

Optimization of silicon solar cell fabrication based on neural network and genetic programming modeling

This study describes techniques for the cascade modeling and the optimization that are required to conduct the simulator-based process optimization of solar cell fabrication. Two modeling approaches, neural networks and genetic programming, are employed to model the crucial relation for the consecutively connected two processes in solar cell fabrication. One model (Model 1) is used to map the five inputs (time, amount of nitrogen and DI water in surface texturing and temperature and time in emitter diffusion) to the two outputs (reflectance and sheet resistance) of the first process. The other model (Model 2) is used to connect the two inputs (reflectance and sheet resistance) to the one output (efficiency) of the second process. After modeling of the two processes, genetic algorithms and particle swarm optimization were applied to search for the optimal recipe. In the first optimization stage, we searched for the optimal reflectance and sheet resistance that can provide the best efficiency in the fabrication process. The optimized reflectance and sheet resistance found by the particle swarm optimization were better than those found by the genetic algorithm. In the second optimization stage, the five input parameters were searched by using the reflectance and sheet resistance values obtained in the first stage. The found five variables such as the texturing time, amount of nitrogen, DI water, diffusion time, and temperature are used as a recipe for the solar cell fabrication. The amount of nitrogen, DI water, and diffusion time in the optimized recipes showed considerable differences according to the modeling approaches. More importantly, repeated applications of particle swarm optimization yielded process conditions with smaller variations, implying greater consistency in recipe generation.     

Iteratively constrained selection of word alignment links using knowledge and statistics

Word alignment is a crucial component in applications that use bilingual resources. Statistical methods are widely used because they are portable and allow simple system building. However, pure statistical methods often incorrectly align functional words in the English–Korean language pair due to differences in the typology of the languages and a lack of knowledge. Knowledge is inevitably required to correct errors and to improve word alignment quality. In this paper, we introduce an effective method that uses an iterative process to incorporate knowledge into the word alignment system. The method achieved significant improvements in word alignment and its application: statistical machine translation.     

Failure mode and effects analysis using a group-based evidential reasoning approach

Failure mode and effects analysis (FMEA) is a methodology to evaluate a system, design, process or service for possible ways in which failures (problems, errors, risks and concerns) can occur. It is a group decision function and cannot be done on an individual basis. The FMEA team often demonstrates different opinions and knowledge from one team member to another and produces different types of assessment information such as complete and incomplete, precise and imprecise and known and unknown because of its cross-functional and multidisciplinary nature. These different types of information are very difficult to incorporate into the FMEA by the traditional risk priority number (RPN) model and fuzzy rule-based approximate reasoning methodologies. In this paper we present an FMEA using the evidential reasoning (ER) approach, a newly developed methodology for multiple attribute decision analysis. The proposed FMEA is then illustrated with an application to a fishing vessel. As is illustrated by the numerical example, the proposed FMEA can well capture FMEA team members’ diversity opinions and prioritize failure modes under different types of uncertainties.