HRMC_1.1: Hybrid Reverse Monte Carlo method with silicon and carbon potentials

The Hybrid Reverse Monte Carlo (HRMC) code models the atomic structure of materials via the use of a combination of constraints including experimental diffraction data and an empirical energy potential. This energy constraint is in the form of either the Environment Dependent Interatomic Potential (EDIP) for carbon and silicon and the original and modified Stillinger–Weber potentials applicable to silicon. In this version, an update is made to correct an error in the EDIP carbon energy calculation routine.

New version program summary

Program title: HRMC version 1.1Catalogue identifier: AEAO_v1_1Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAO_v1_1.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.: 36 991No. of bytes in distributed program, including test data, etc.: 907 800Distribution format: tar.gzProgramming language: FORTRAN 77Computer: Any computer capable of running executables produced by the g77 Fortran compiler.Operating system: Unix, WindowsRAM: Depends on the type of empirical potential use, number of atoms and which constraints are employed.Classification: 7.7Catalogue identifier of previous version: AEAO_v1_0Journal reference of previous version: Comput. Phys. Comm. 178 (2008) 777Does the new version supersede the previous version?: YesNature of problem: Atomic modelling using empirical potentials and experimental data.Solution method: Monte CarloReasons for new version: An error in a term associated with the calculation of energies using the EDIP carbon potential which results in incorrect energies.Summary of revisions: Fix to correct brackets in the two body part of the EDIP carbon potential routine.Additional comments: The code is not standard FORTRAN 77 but includes some additional features and therefore generates errors when compiled using the Nag95 compiler. It does compile successfully with the GNU g77 compiler (http://www.gnu.org/software/fortran/fortran.html).Running time: Depends on the type of empirical potential use, number of atoms and which constraints are employed. The test included in the distribution took 37 minutes on a DEC Alpha PC.     

Program package for multicanonical simulations of U(1) lattice gauge theory

We document our Fortran 77 code for multicanonical simulations of 4D U(1) lattice gauge theory in the neighborhood of its phase transition. This includes programs and routines for canonical simulations using biased Metropolis heatbath updating and overrelaxation, determination of multicanonical weights via a Wang-Landau recursion, and multicanonical simulations with fixed weights supplemented by overrelaxation sweeps. Measurements are performed for the action, Polyakov loops and some of their structure factors. Many features of the code transcend the particular application and are expected to be useful for other lattice gauge theory models as well as for systems in statistical physics.

Program summary

Program title: STMC_U1MUCACatalogue identifier: AEET_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEET_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.: 18 376No. of bytes in distributed program, including test data, etc.: 205 183Distribution format: tar.gzProgramming language: Fortran 77Computer: Any capable of compiling and executing Fortran codeOperating system: Any capable of compiling and executing Fortran codeClassification: 11.5Nature of problem: Efficient Markov chain Monte Carlo simulation of U(1) lattice gauge theory close to its phase transition. Measurements and analysis of the action per plaquette, the specific heat, Polyakov loops and their structure factors.Solution method: Multicanonical simulations with an initial Wang-Landau recursion to determine suitable weight factors. Reweighting to physical values using logarithmic coding and calculating jackknife error bars.Running time: The prepared tests runs took up to 74 minutes to execute on a 2 GHz PC.     

SMMP v. 3.0—Simulating proteins and protein interactions in Python and Fortran

We describe a revised and updated version of the program package SMMP. SMMP is an open-source FORTRAN package for molecular simulation of proteins within the standard geometry model. It is designed as a simple and inexpensive tool for researchers and students to become familiar with protein simulation techniques. SMMP 3.0 sports a revised API increasing its flexibility, an implementation of the Lund force field, multi-molecule simulations, a parallel implementation of the energy function, Python bindings, and more.

Program summary

Title of program:SMMPCatalogue identifier:ADOJ_v3_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADOJ_v3_0.htmlProgram obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandLicensing provisions:Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlProgramming language used:FORTRAN, PythonNo. of lines in distributed program, including test data, etc.:52 105No. of bytes in distributed program, including test data, etc.:599 150Distribution format:tar.gzComputer:Platform independentOperating system:OS independentRAM:2 MbytesClassification:3Does the new version supersede the previous version?:YesNature of problem:Molecular mechanics computations and Monte Carlo simulation of proteins.Solution method:Utilizes ECEPP2/3, FLEX, and Lund potentials. Includes Monte Carlo simulation algorithms for canonical, as well as for generalized ensembles.Reasons for new version:API changes and increased functionality.Summary of revisions:Added Lund potential; parameters used in subroutines are now passed as arguments; multi-molecule simulations; parallelized energy calculation for ECEPP; Python bindings.Restrictions:The consumed CPU time increases with the size of protein molecule.Running time:Depends on the size of the simulated molecule.     

JuNoLo - Jülich nonlocal code for parallel post-processing evaluation of vdW-DF correlation energy

Nowadays the state of the art Density Functional Theory (DFT) codes are based on local (LDA) or semilocal (GGA) energy functionals. Recently the theory of a truly nonlocal energy functional has been developed. It has been used mostly as a post-DFT calculation approach, i.e. by applying the functional to the charge density calculated using any standard DFT code, thus obtaining a new improved value for the total energy of the system. Nonlocal calculation is computationally quite expensive and scales as N² where N is the number of points in which the density is defined, and a massively parallel calculation is welcome for a wider applicability of the new approach. In this article we present a code which accomplishes this goal.

Program summary

Program title: JuNoLoCatalogue identifier: AEFM_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFM_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.: 176 980No. of bytes in distributed program, including test data, etc.: 2 126 072Distribution format: tar.gzProgramming language: Fortran 90Computer: any architecture with a Fortran 90 compilerOperating system: Linux, AIXHas the code been vectorised or parallelized?: Yes, from 1 to 65536 processors may be used.RAM: depends strongly on the problem's size.Classification: 7.3External routines:• FFTW (http://www.tw.org/)• MPI (http://www.mcs.anl.gov/research/projects/mpich2/ or http://www.lam-mpi.org/)Nature of problem: Obtaining the value of the nonlocal vdW-DF energy based on the charge density distribution obtained from some Density Functional Theory code.Solution method: Numerical calculation of the double sum is implemented in a parallel F90 code. Calculation of this sum yields the required nonlocal vdW-DF energy.Unusual features: Binds to virtually any DFT program.Additional comments: Excellent parallelization features.Running time: Depends strongly on the size of the problem and the number of CPUs used.     

MontePython: Implementing Quantum Monte Carlo using Python

We present a cross-language C++/Python program for simulations of quantum mechanical systems with the use of Quantum Monte Carlo (QMC) methods. We describe a system for which to apply QMC, the algorithms of variational Monte Carlo and diffusion Monte Carlo and we describe how to implement theses methods in pure C++ and C++/Python. Furthermore we check the efficiency of the implementations in serial and parallel cases to show that the overhead using Python can be negligible.

Program summary

Program title: MontePythonCatalogue identifier: ADZP_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZP_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.: 49 519No. of bytes in distributed program, including test data, etc.: 114 484Distribution format: tar.gzProgramming language: C++, PythonComputer: PC, IBM RS6000/320, HP, ALPHAOperating system: LINUXHas the code been vectorised or parallelized?: Yes, parallelized with MPINumber of processors used: 1-96RAM: Depends on physical system to be simulatedClassification: 7.6; 16.1Nature of problem: Investigating ab initio quantum mechanical systems, specifically Bose-Einstein condensation in dilute gases of ⁸⁷RbSolution method: Quantum Monte CarloRunning time: 225 min with 20 particles (with 4800 walkers moved in 1750 time steps) on 1 AMD Opteron^TM Processor 2218 processor; Production run for, e.g., 200 particles takes around 24 hours on 32 such processors.     

PETAG01: A program for the direct simulation of a pellet target

We describe a numerical model of an internal pellet target to study the beam dynamics in storage rings, where the nuclear experiments with such type of target are planned. In this model the Monte Carlo algorithm is applied to evaluate the particle coordinates and momentum deviation depending on time and parameters of the target. One has to mention that due to statistical character of the pellet distribution in the target the analytical techniques are not applicable. This is also true for the particle distribution in the stored beam, which is influenced by various effects (such as a cooling process, intra-beam scattering, betatron oscillation, space charge effect). In this case only the Monte Carlo technique to model energy straggling in combination with the pellet distribution in the target should be considered.

Program summary

Program title: PETAG01Catalogue identifier: ADZV_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZV_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.: 1068No. of bytes in distributed program, including test data, etc.: 11 314Distribution format: tar.gzProgramming language: Fortran 77, C/C++Computer: Platform independentOperating system: MS Windows 95/2000/XP, Linux (Unix)RAM: 128 MBClassification: 11.10Nature of problem: Particle beam dynamics with use of the pellet target.Solution method: Monte Carlo with analytical approximation.Running time: dozens of seconds     

A molecular dynamics implementation of the 3D Mercedes-Benz water model

The three-dimensional Mercedes-Benz model was recently introduced to account for the structural and thermodynamic properties of water. It treats water molecules as point-like particles with four dangling bonds in tetrahedral coordination, representing H-bonds of water. Its conceptual simplicity renders the model attractive in studies where complex behaviors emerge from H-bond interactions in water, e.g., the hydrophobic effect. A molecular dynamics (MD) implementation of the model is non-trivial and we outline here the mathematical framework of its force-field. Useful routines written in modern Fortran are also provided. This open source code is free and can easily be modified to account for different physical context. The provided code allows both serial and MPI-parallelized execution.Program summaryProgram title: CASHEW (Coarse Approach Simulator for Hydrogen-bonding Effects in Water)Catalogue identifier: AEKM_v1_0Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEKM_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.: 20 501No. of bytes in distributed program, including test data, etc.: 551 044Distribution format: tar.gzProgramming language: Fortran 90Computer: Program has been tested on desktop workstations and a Cray XT4/XT5 supercomputer.Operating system: Linux, Unix, OS XHas the code been vectorized or parallelized?: The code has been parallelized using MPI.RAM: Depends on size of system, about 5 MB for 1500 molecules.Classification: 7.7External routines: A random number generator, Mersenne Twister (http://www.math.sci.hiroshima-u.ac.jp/m-mat/MT/VERSIONS/FORTRAN/mt95.f90), is used. A copy of the code is included in the distribution.Nature of problem: Molecular dynamics simulation of a new geometric water model.Solution method: New force-field for water molecules, velocity–Verlet integration, representation of molecules as rigid particles with rotations described using quaternion algebra.Restrictions: Memory and cpu time limit the size of simulations.Additional comments: Software web site: https://gitorious.org/cashew/.Running time: Depends on the size of system. The sample tests provided only take a few seconds.     

BOKASUN: A fast and precise numerical program to calculate the Master Integrals of the two-loop sunrise diagrams

We present the program BOKASUN for fast and precise evaluation of the Master Integrals of the two-loop self-mass sunrise diagram for arbitrary values of the internal masses and the external four-momentum. We use a combination of two methods: a Bernoulli accelerated series expansion and a Runge-Kutta numerical solution of a system of linear differential equations.

Program summary

Program title: BOKASUNCatalogue identifier: AECG_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AECG_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.: 9404No. of bytes in distributed program, including test data, etc.: 104 123Distribution format: tar.gzProgramming language: FORTRAN77Computer: Any computer with a Fortran compiler accepting FORTRAN77 standard. Tested on various PC's with LINUXOperating system: LINUXRAM: 120 kbytesClassification: 4.4Nature of problem: Any integral arising in the evaluation of the two-loop sunrise Feynman diagram can be expressed in terms of a given set of Master Integrals, which should be calculated numerically. The program provides a fast and precise evaluation method of the Master Integrals for arbitrary (but not vanishing) masses and arbitrary value of the external momentum.Solution method: The integrals depend on three internal masses and the external momentum squared p². The method is a combination of an accelerated expansion in 1/p² in its (pretty large!) region of fast convergence and of a Runge-Kutta numerical solution of a system of linear differential equations.Running time: To obtain 4 Master Integrals on PC with 2 GHz processor it takes 3 μs for series expansion with pre-calculated coefficients, 80 μs for series expansion without pre-calculated coefficients, from a few seconds up to a few minutes for Runge-Kutta method (depending on the required accuracy and the values of the physical parameters).     

Solution of few-body problems with the stochastic variational method II: Two-dimensional systems

A computational approach is presented for efficient solution of two-dimensional few-body problems, such as quantum dots or excitonic complexes, using the stochastic variational method. The computer program can be used to calculate the energies and wave functions of various two-dimensional systems.

Program summary

Program title: svm-2dCatalogue identifier: AEBE_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBE_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.: 5091No. of bytes in distributed program, including test data, etc.: 130 963Distribution format: tar.gzProgramming language: Fortran 90Computer: The program should work on any system with a Fortran 90 compilerOperating system: The program should work on any system with a Fortran 90 compilerClassification: 7.3Nature of problem: Variational calculation of energies and wave functions using Correlated Gaussian basis.Solution method: Two-dimensional few-electron problems are solved by the variational method. The ground state wave function is expanded into Correlated Gaussian basis functions and the parameters of the basis states are optimized by a stochastic selection procedure. Accurate results can be obtained for 2-6 electron systems.Running time: A couple of hours for a typical system.     

SUSY Les Houches Accord 2 I/O made easy

A library for reading and writing data in the SUSY Les Houches Accord 2 format is presented. The implementation is in native Fortran 77. The data are contained in a single array conveniently indexed by preprocessor statements.

Program summary

Program title: SLHA2LibCatalogue identifier: AEDY_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDY_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.: 7550No. of bytes in distributed program, including test data, etc.: 160 123Distribution format: tar.gzProgramming language: FortranComputer: For the build process, a Fortran 77 compiler in a Unixish environment (make, shell) are requiredOperating system: Linux, Mac OS, Windows (Cygwin), Tru64 UnixRAM: The SLHA Record is currently 88 944 bytes longClassification: 4.14, 11.6Nature of problem: Exchange of SUSY parameters and decay information in an ASCII file format.Solution method: The SLHA2Lib provides routines for reading and writing files in the SUSY Les Houches Accord 2 format, a common interchange format for SUSY parameters and decay data.Restrictions: The fixed-sized array that holds the SLHA2 data necessarily limits the amount of decay data that can be stored. This limit can be enlarged by editing and re-running the SLHA2.m program.Unusual features: Data are transported in a single “double complex” array in Fortran, indexed through preprocessor macros. This is about the simplest conceivable container and needs neither dynamic memory allocation nor Fortran extension like structures.Running time: Both reading and writing a SLHA file are typically in the range of a few milliseconds.     

TiReX: Replica-exchange molecular dynamics using Tinker

We present a driver program for performing replica-exchange molecular dynamics simulations with the Tinker package. Parallelization is based on the Message Passing Interface, with every replica assigned to a separate process. The algorithm is not communication intensive, which makes the program suitable for running even on loosely coupled cluster systems. Particular attention is paid to the practical aspects of analyzing the program output.

Program summary

Program title: TiReXCatalogue identifier: AEEK_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEK_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.: 43 385No. of bytes in distributed program, including test data, etc.: 502 262Distribution format: tar.gzProgramming language: Fortran 90/95Computer: Most UNIX machinesOperating system: LinuxHas the code been vectorized or parallelized?: parallelized with MPIClassification: 16.13External routines: TINKER version 4.2 or 5.0, built as a libraryNature of problem: Replica-exchange molecular dynamics.Solution method: Each replica is assigned to a separate process; temperatures are swapped between replicas at regular time intervals.Running time: The sample run may take up to a few minutes.     

From data to probability densities without histograms

When one deals with data drawn from continuous variables, a histogram is often inadequate to display their probability density. It deals inefficiently with statistical noise, and binsizes are free parameters. In contrast to that, the empirical cumulative distribution function (obtained after sorting the data) is parameter free. But it is a step function, so that its differentiation does not give a smooth probability density. Based on Fourier series expansion and Kolmogorov tests, we introduce a simple method, which overcomes this problem. Error bars on the estimated probability density are calculated using a jackknife method. We give several examples and provide computer code reproducing them. You may want to look at the corresponding figures 4 to 9 first.

Program summary

Program title: cdf_to_pdCatalogue identifier: AEBC_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBC_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.: 2758No. of bytes in distributed program, including test data, etc.: 18 594Distribution format: tar.gzProgramming language: Fortran 77Computer: Any capable of compiling and executing Fortran codeOperating system: Any capable of compiling and executing Fortran codeClassification: 4.14, 9Nature of problem: When one deals with data drawn from continuous variables, a histogram is often inadequate to display the probability density. It deals inefficiently with statistical noise, and binsizes are free parameters. In contrast to that, the empirical cumulative distribution function (obtained after sorting the data) is parameter free. But it is a step function, so that its differentiation does not give a smooth probability density.Solution method: Based on Fourier series expansion and Kolmogorov tests, we introduce a simple method, which overcomes this problem. Error bars on the estimated probability density are calculated using a jackknife method. Several examples are included in the distribution file.Running time: The test runs provided take only a few seconds to execute.     

A completely open source based computing system for computer generation of Fourier holograms

Computer generated holograms are usually generated using commercial software like MATLAB, MATHCAD, Mathematica, etc. This work is an approach in doing the same using freely distributed open source packages and Operating System. A Fourier hologram is generated using this method and tested for simulated and optical reconstruction. The reconstructed images are in good agreement with the objects chosen. The significance of using such a system is also discussed.

Program summary

Program title: FHOLOCatalogue identifier: AEDS_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDS_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.: 176 336No. of bytes in distributed program, including test data, etc.: 4 294 872Distribution format: tar.gzProgramming language: C++Computer: any X86 micro computerOperating system: Linux (Debian Etch)RAM: 512 MBClassification: 18Nature of problem: To generate a Fourier Hologram in micro computer only by using open source operating system and packages.Running time: Depends on the matrix size. 10 sec for a matrix of size 256×256.     

REACH: A program for coarse-grained biomolecular simulation

REACH (Realistic Extension Algorithm viaCovariance Hessian) is a program package for residue-scale coarse-grained biomolecular simulation. The program calculates the force constants of a residue-scale elastic network model in single-domain proteins using the variance-covariance matrix obtained from atomistic molecular dynamics simulation. Secondary-structure dependence of the force constants is integrated. The method involves self-consistent, direct mapping of atomistic simulation results onto a coarse-grained force field in an efficient automated procedure without requiring iterative fits and avoiding system dependence.

Program summary

Program title: REACHCatalogue identifier: AEDA_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDA_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.: 42 244No. of bytes in distributed program, including test data, etc.: 3 682 118Distribution format: tar.gzProgramming language: FORTRAN 77Computer: x86 PCOperating system: GNU/Linux, SUSE and Red HatRAM: Depends on the system size to be calculatedWord size: 32 or 64 bitsClassification: 3External routines: LAPACK, BLASNature of problem: A direct calculation of force field for residue-scale coarse-grained biomolecular simulation derived from atomistic molecular dynamics trajectory.Solution method: A variance-covariance matrix and the associated Hessian (second-derivative) matrix are calculated from an atomistic molecular dynamics trajectory of single-domain protein internal motion and the off-diagonal Hessian matrix is fitted to that of a residue-scale elastic network model. The resulting force constants for the residue pair interactions are expressed as model functions as a function of pairwise distance.Running time: Depends on the system size and the number of MD trajectory frames used. The test run provided with the distribution takes only a few seconds to execute.     

Visual tool for estimating the fractal dimension of images

This work presents a new Visual Basic 6.0 application for estimating the fractal dimension of images, based on an optimized version of the box-counting algorithm. Following the attempt to separate the real information from “noise”, we considered also the family of all band-pass filters with the same band-width (specified as parameter). The fractal dimension can be thus represented as a function of the pixel color code. The program was used for the study of paintings cracks, as an additional tool which can help the critic to decide if an artistic work is original or not.

Program summary

Program title: Fractal Analysis v01Catalogue identifier: AEEG_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEG_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.: 29 690No. of bytes in distributed program, including test data, etc.: 4 967 319Distribution format: tar.gzProgramming language: MS Visual Basic 6.0Computer: PCOperating system: MS Windows 98 or laterRAM: 30MClassification: 14Nature of problem: Estimating the fractal dimension of images.Solution method: Optimized implementation of the box-counting algorithm. Use of a band-pass filter for separating the real information from “noise”. User friendly graphical interface.Restrictions: Although various file-types can be used, the application was mainly conceived for the 8-bit grayscale, windows bitmap file format.Running time: In a first approximation, the algorithm is linear.     

golem95: A numerical program to calculate one-loop tensor integrals with up to six external legs

We present a program for the numerical evaluation of form factors entering the calculation of one-loop amplitudes with up to six external legs. The program is written in Fortran95 and performs the reduction to a certain set of basis integrals numerically, using a formalism where inverse Gram determinants can be avoided. It can be used to calculate one-loop amplitudes with massless internal particles in a fast and numerically stable way.

Program summary

Program title: golem95_v1.0Catalogue identifier: AEEO_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEO_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.: 50 105No. of bytes in distributed program, including test data, etc.: 241 657Distribution format: tar.gzProgramming language: Fortran95Computer: Any computer with a Fortran95 compilerOperating system: Linux, UnixRAM: RAM used per form factor is insignificant, even for a rank six six-point form factorClassification: 4.4, 11.1External routines: Perl programming language (http://www.perl.com/)Nature of problem: Evaluation of one-loop multi-leg tensor integrals occurring in the calculation of next-to-leading order corrections to scattering amplitudes in elementary particle physics.Solution method: Tensor integrals are represented in terms of form factors and a set of basic building blocks (“basis integrals”). The reduction to the basis integrals is performed numerically, thus avoiding the generation of large algebraic expressions.Restrictions: The current version contains basis integrals for massless internal particles only. Basis integrals for massive internal particles will be included in a future version.Running time: Depends on the nature of the problem. A rank 6 six-point form factor at a randomly chosen kinematic point takes 0.13 seconds on an Intel Core 2 Q9450 2.66 GHz processor, without any optimisation. With compiler optimisation flag -O3 the same point takes 0.09 seconds. Timings for lower point form factors are: All form factors for five-point functions from rank 0 to rank 4: 0.04 s. All form factors for rank 5 five-point functions: 0.05 s. All form factors for four-point functions from rank 0 to rank 4: 0.01 s.     

GenMin: An enhanced genetic algorithm for global optimization

A new method that employs grammatical evolution and a stopping rule for finding the global minimum of a continuous multidimensional, multimodal function is considered. The genetic algorithm used is a hybrid genetic algorithm in conjunction with a local search procedure. We list results from numerical experiments with a series of test functions and we compare with other established global optimization methods. The accompanying software accepts objective functions coded either in Fortran 77 or in C++.

Program summary

Program title: GenMinCatalogue identifier: AEAR_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAR_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.: 35 810No. of bytes in distributed program, including test data, etc.: 436 613Distribution format: tar.gzProgramming language: GNU-C++, GNU-C, GNU Fortran 77Computer: The tool is designed to be portable in all systems running the GNU C++ compilerOperating system: The tool is designed to be portable in all systems running the GNU C++ compilerRAM: 200 KBWord size: 32 bitsClassification: 4.9Nature of problem: A multitude of problems in science and engineering are often reduced to minimizing a function of many variables. There are instances that a local optimum does not correspond to the desired physical solution and hence the search for a better solution is required. Local optimization techniques are frequently trapped in local minima. Global optimization is hence the appropriate tool. For example, solving a nonlinear system of equations via optimization, employing a least squares type of objective, one may encounter many local minima that do not correspond to solutions (i.e. they are far from zero).Solution method: Grammatical evolution and a stopping rule.Running time: Depending on the objective function. The test example given takes only a few seconds to run.     

Object-oriented design patterns in Fortran 90/95: mazev1, mazev2 and mazev3

This paper discusses the concept, application, and usefulness of software design patterns for scientific programming in Fortran 90/95. An example from the discipline of object-oriented design patterns, that of a game based on navigation through a maze, is used to describe how some important patterns can be implemented in Fortran 90/95 and how the progressive introduction of design patterns can usefully restructure Fortran software as it evolves. This example is complemented by a discussion of how design patterns have been used in a real-life simulation of Particle-in-Cell plasma physics. The following patterns are mentioned in this paper: Factory, Strategy, Template, Abstract Factory and Facade.

Program summary

Program title: mazev1, mazev2, mazev3Catalogue identifier: AEAI_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAI_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.: 1958No. of bytes in distributed program, including test data, etc.: 17 100Distribution format: tar.gzProgramming language: Fortran 95Computer: PC/MacOperating system: Unix/Linux/Mac (FreeBSD)/Windows (Cygwin)RAM: These are interactive programs with small (KB) memory requirementsClassification: 6.5, 20Nature of problem: A sequence of programs which demonstrate the use of object oriented design patterns for the restructuring of Fortran 90/95 software. The programs implement a simple maze game similar to that described in [1].Solution method: Restructuring uses versions of the Template, Strategy and Factory design patterns.Running time: Interactive.References:

[1] 

E. Gamma, R. Helm, R. Johnson, J. Vlissides, Design Patterns: Elements of Reusable Object Oriented Software, Addison-Wesley, 1995, ISBN 0201633612.