HypExp, a Mathematica package for expanding hypergeometric functions around integer-valued parameters

We present the Mathematica package HypExp which allows to expand hypergeometric functions around integer parameters to arbitrary order. At this, we apply two methods, the first one being based on an integral representation, the second one on the nested sums approach. The expansion works for both symbolic argument z and unit argument. We also implemented new classes of integrals that appear in the first method and that are, in part, yet unknown to Mathematica.

Program summary

Title of program:HypExpCatalogue identifier:ADXF_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXF_v1_0Program obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandLicence:noneComputers:Computers running Mathematica under Linux or WindowsOperating system:Linux, WindowsProgram language:MathematicaNo. of bytes in distributed program, including test data, etc.:739 410No. of lines in distributed program, including test data, etc.:89 747Distribution format:tar.gzOther package needed:the package HPL, included in the distributionExternal file required:noneNature of the physical problem:Expansion of hypergeometric functions around integer-valued parameters. These are needed in the context of dimensional regularization for loop and phase space integrals.Method of solution:Algebraic manipulation of nested sums and integral representation.Restrictions on complexity of the problem:Limited by the memory availableTypical running time:Strongly depending on the problem and the availability of libraries.     

Light Dialectica Program Extraction from a Classical Fibonacci Proof

We demonstrate program extraction by the Light Dialectica Interpretation (LDI) on a minimal logic proof of the classical existence of Fibonacci numbers. This semi-classical proof is available in MinLog's library of examples. The term of Gödel's T extracted by the LDI is, after strong normalization, exactly the usual recursive algorithm which defines the Fibonacci numbers (in pairs). This outcome of the Light Dialectica meta-algorithm is much better than the T-program extracted by means of the pure Gödel Dialectica Interpretation. It is also strictly less complex than the result obtained by means of the refined A-translation technique of Berger, Buchholz and Schwichtenberg on an artificially distorted variant of the input proof, but otherwise it is identical with the term yielded by Berger's Kripke-style refined A-translation. Although syntactically different, it also has the same computational complexity as the original program yielded by the refined A-translation from the undistorted input classical Fibonacci proof.     

GRACE/SUSY: Automatic generation of tree amplitudes in the minimal supersymmetric standard model

GRACE/SUSY is a program package for generating the tree-level amplitude and evaluating the corresponding cross section of processes of the minimal supersymmetric extension of the standard model (MSSM). The Higgs potential adopted in the system, however, is assumed to have a more general form indicated by the two-Higgs-doublet model. This system is an extension of GRACE for the standard model (SM) of the electroweak and strong interactions. For a given MSSM process the Feynman graphs and amplitudes at tree-level are automatically created. The Monte Carlo phase space integration by means of BASES gives the total and differential cross sections. When combined with SPRING, an event generator, the program package provides us with the simulation of the SUSY particle productions.     

A computer program for two-particle generalized coefficients of fractional parentage

We present a FORTRAN90 program GCFP for the calculation of the generalized coefficients of fractional parentage (generalized CFPs or GCFP). The approach is based on the observation that the multi-shell CFPs can be expressed in terms of single-shell CFPs, while the latter can be readily calculated employing a simple enumeration scheme of antisymmetric A-particle states and an efficient method of construction of the idempotent matrix eigenvectors. The program provides fast calculation of GCFPs for a given particle number and produces results possessing numerical uncertainties below the desired tolerance. A single j-shell is defined by four quantum numbers, (e,l,j,t).A supplemental C++ program parGCFP allows calculation to be done in batches and/or in parallel.

Program summary

Program title:GCFP, parGCFPCatalogue identifier: AEBI_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBI_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.: 17 199No. of bytes in distributed program, including test data, etc.: 88 658Distribution format: tar.gzProgramming language: FORTRAN 77/90 (GCFP), C++ (parGCFP)Computer: Any computer with suitable compilers. The program GCFP requires a FORTRAN 77/90 compiler. The auxiliary program parGCFP requires GNU-C++ compatible compiler, while its parallel version additionally requires MPI-1 standard librariesOperating system: Linux (Ubuntu, Scientific) (all programs), also checked on Windows XP (GCFP, serial version of parGCFP)RAM: The memory demand depends on the computation and output mode. If this mode is not 4, the program GCFP demands the following amounts of memory on a computer with Linux operating system. It requires around 2 MB of RAM for the A=12 system at Ex?2. Computation of the A=50 particle system requires around 60 MB of RAM at Ex=0 and ∼70 MB at Ex=2 (note, however, that the calculation of this system will take a very long time). If the computation and output mode is set to 4, the memory demands by GCFP are significantly larger. Calculation of GCFPs of A=12 system at Ex=1 requires 145 MB. The program parGCFP requires additional 2.5 and 4.5 MB of memory for the serial and parallel version, respectively.Classification: 17.18Nature of problem: The program GCFP generates a list of two-particle coefficients of fractional parentage for several j-shells with isospin.Solution method: The method is based on the observation that multishell coefficients of fractional parentage can be expressed in terms of single-shell CFPs [1]. The latter are calculated using the algorithm [2,3] for a spectral decomposition of an antisymmetrization operator matrix Y. The coefficients of fractional parentage are those eigenvectors of the antisymmetrization operator matrix Y that correspond to unit eigenvalues. A computer code for these coefficients is available [4]. The program GCFP offers computation of two-particle multishell coefficients of fractional parentage. The program parGCFP allows a batch calculation using one input file. Sets of GCFPs are independent and can be calculated in parallel.Restrictions:A<86 when Ex=0 (due to the memory constraints); small numbers of particles allow significantly higher excitations, though the shell with j?11/2 cannot get full (it is the implementation constraint).Unusual features: Using the program GCFP it is possible to determine allowed particle configurations without the GCFP computation. The GCFPs can be calculated either for all particle configurations at once or for a specified particle configuration. The values of GCFPs can be printed out with a complete specification in either one file or with the parent and daughter configurations printed in separate files. The latter output mode requires additional time and RAM memory. It is possible to restrict the (J,T) values of the considered particle configurations. (Here J is the total angular momentum and T is the total isospin of the system.) The program parGCFP produces several result files the number of which equals to the number of particle configurations. To work correctly, the program GCFP needs to be compiled to read parameters from the standard input (the default setting).Running time: It depends on the size of the problem. The minimum time is required, if the computation and output mode (CompMode) is not 4, but the resulting file is larger. A system with A=12 particles at Ex=0 (all 9411 GCFPs) took around 1 sec on a Pentium4 2.8 GHz processor with 1 MB L2 cache. The program required about 14 min to calculate all 1.3×¹⁰⁶ GCFPs of Ex=1. The time for all 5.5×¹⁰⁷ GCFPs of Ex=2 was about 53 hours. For this number of particles, the calculation time of both Ex=0 and Ex=1 with CompMode = 1 and 4 is nearly the same, when no other processes are running. The case of Ex=2 could not be calculated with CompMode = 4, because the RAM memory was insufficient. In general, the latter CompMode requires a longer computation time, although the resulting files are smaller in size. The program parGCFP puts virtually no time overhead. Its parallel version speeds-up the calculation. However, the results need to be collected from several files created for each configuration.References:[1] J. Levinsonas, Works of Lithuanian SSR Academy of Sciences 4 (1957) 17.[2] A. Deveikis, A. Bon?kus, R. Kalinauskas, Lithuanian Phys. J. 41 (2001) 3.[3] A. Deveikis, R.K. Kalinauskas, B.R. Barrett, Ann. Phys. 296 (2002) 287.[4] A. Deveikis, Comput. Phys. Comm. 173 (2005) 186. (CPC Catalogue ID. ADWI_v1_0)     

Top++: A program for the calculation of the top-pair cross-section at hadron colliders

We present the program Top++ for the numerical evaluation of the total inclusive cross-section for producing top quark pairs at hadron colliders. The program calculates the cross-section in (a) fixed order approach with exact next-to-next-to leading order (NNLO) accuracy and (b) by including soft-gluon resummation for the hadronic cross-section in Mellin space with full next-to-next-to-leading logarithmic (NNLL) accuracy. The program offers the user significant flexibility through the large number (29) of available options. Top++ is written in C++. It has a very simple to use interface that is intuitive and directly reflects the physics. The running of the program requires no programming experience from the user.     

FLY. A parallel tree N-body code for cosmological simulations

FLY is a parallel treecode which makes heavy use of the one-sided communication paradigm to handle the management of the tree structure. In its public version the code implements the equations for cosmological evolution, and can be run for different cosmological models.This reference guide describes the actual implementation of the algorithms of the public version of FLY, and suggests how to modify them to implement other types of equations (for instance, the Newtonian ones).

Program summary

Title of program:FLYCatalogue identifier: ADSCProgram summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSCProgram obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandComputer for which the program is designed and others on which it has been tested: Cray T3E, Sgi Origin 3000, IBM SPOperating systems or monitors under which the program has been tested: Unicos 2.0.5.40, Irix 6.5.14, Aix 4.3.3Programming language used: Fortran 90, CMemory required to execute with typical data: about 100 Mwords with 2 million-particlesNumber of bits in a word: 32Number of processors used: parallel program. The user can select the number of processors ?1Has the code been vectorized or parallelized?: parallelizedNumber of bytes in distributed program, including test data, etc.: 4 615 604Distribution format: tar gzip fileKeywords: Parallel tree N-body code for cosmological simulationsNature of physical problem:FLY is a parallel collisionless N-body code for the calculation of the gravitational force.Method of solution: It is based on the hierarchical oct-tree domain decomposition introduced by Barnes and Hut (1986).Restrictions on the complexity of the program: The program uses the leapfrog integrator schema, but could be changed by the user.Typical running time: 50 seconds for each time-step, running a 2-million-particles simulation on an Sgi Origin 3800 system with 8 processors having 512 Mbytes RAM for each processor.Unusual features of the program:FLY uses the one-side communications libraries: the SHMEM library on the Cray T3E system and Sgi Origin system, and the LAPI library on IBM SP system     

MC-TESTER: a universal tool for comparisons of Monte Carlo predictions for particle decays in high energy physics

Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be used for such tests of decays of intermediate states (particles or resonances) in a semi-automated way. Our test consists of two steps. Different Monte Carlo programs are run; events with decays of a chosen particle are searched, decay trees are analyzed and appropriate information is stored. Then, at the analysis step, a list of all found decay modes is defined and branching ratios are calculated for both runs. Histograms of all scalar Lorentz-invariant masses constructed from the decay products are plotted and compared for each decay mode found in both runs. For each plot a measure of the difference of the distributions is calculated and its maximal value over all histograms for each decay channel is printed in a summary table. As an example of MC-TESTER application, we include a test with the τ lepton decay Monte Carlo generators, TAUOLA and PYTHIA. The HEPEVT (or LUJETS) common block is used as exclusive source of information on the generated events.

Program summary

Title of the program:MC-TESTER, version 1.1Catalogue identifier: ADSMProgram summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSMProgram obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandComputer: PC, two Intel Xeon 2.0 GHz processors, 512MB RAMOperating system: Linux Red Hat 6.1, 7.2, and also 8.0Programming language used:C++, FORTRAN77: gcc 2.96 or 2.95.2 (also 3.2) compiler suite with g++ and g77Size of the package: 7.3 MB directory including example programs (2 MB compressed distribution archive), without ROOT libraries (additional 43 MB).No. of bytes in distributed program, including test data, etc.: 2 024 425Distribution format: tar gzip fileAdditional disk space required: Depends on the analyzed particle: 40 MB in the case of τ lepton decays (30 decay channels, 594 histograms, 82-pages booklet).Keywords: particle physics, decay simulation, Monte Carlo methods, invariant mass distributions, programs comparisonNature of the physical problem: The decays of individual particles are well defined modules of a typical Monte Carlo program chain in high energy physics. A fast, semi-automatic way of comparing results from different programs is often desirable, for the development of new programs, to check correctness of the installations or for discussion of uncertainties.Method of solution: A typical HEP Monte Carlo program stores the generated events in the event records such as HEPEVT or PYJETS. MC-TESTER scans, event by event, the contents of the record and searches for the decays of the particle under study. The list of the found decay modes is successively incremented and histograms of all invariant masses which can be calculated from the momenta of the particle decay products are defined and filled. The outputs from the two runs of distinct programs can be later compared. A booklet of comparisons is created: for every decay channel, all histograms present in the two outputs are plotted and parameter quantifying shape difference is calculated. Its maximum over every decay channel is printed in the summary table.Restrictions on the complexity of the problem: For a list of limitations see Section 6.Typical running time: Varies substantially with the analyzed decay particle. On a PC/Linux with 2.0 GHz processors MC-TESTER increases the run time of the τ-lepton Monte Carlo program TAUOLA by 4.0 seconds for every 100000 analyzed events (generation itself takes 26 seconds). The analysis step takes 13 seconds; processing takes additionally 10 seconds. Generation step runs may be executed simultaneously on multi-processor machines.Accessibility: web page: http://cern.ch/Piotr.Golonka/MC/MC-TESTER e-mails: Piotr.Golonka@CERN.CH, T.Pierzchala@friend.phys.us.edu.pl, Zbigniew.Was@CERN.CH.     

The tauola-photos-F environment for the TAUOLA and PHOTOS packages, release II

We present the system for maintaining the versions of two packages: the TAUOLA of τ-lepton decay and PHOTOS for radiative corrections in decays. The following features can be chosen in an automatic or semi-automatic way: (1) format of the common block HEPEVT; (2) version of the physics input (for TAUOLA): as published, as initialized by the CLEO collaboration, as initialized by the ALEPH collaboration (it is suggested to use this version only with the help of the collaboration advice), new optional parametrization of matrix elements in 4π decay channels; (3) type of application: stand-alone, universal interface based on the information stored in the HEPEVT common block including longitudinal spin effects in the elementary Z/γ^∗→τ⁺τ⁻ process, extended version of the standard universal interface including full spin effects in the H/A→τ⁺τ⁻ decay, interface for KKMC Monte Carlo, (4) random number generators; (5) compiler options. The last section of the paper contains documentation of the programs updates introduced over the last two years.

Program summary

Title of program:tauola-photos-F, release IICatalogue identifier:ADXO_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXO_v1_0Programs obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandComputer: PC running GNU/Linux operating systemProgramming languages and tools used:CPP: standard C-language preprocessor, GNU Make builder tool, also FORTRAN compilerNo. of lines in distributed program, including test data, etc.: 194 118No. of bytes in distributed program, including test data, etc.:2 481 234Distribution format: tar.gzCatalogue identifier:ADXO_v2_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXO_v2_0No. of lines in distributed program, including test data, etc.:308 235No. of bytes in distributed program, including test data, etc.:2 988 363Distribution format:tar.gzDoes the new version supersede the previous version:YesNature of the physical problem: The code of Monte Carlo generators often has to be tuned to the needs of large HEP Collaborations and experiments. Usually, these modifications do not introduce important changes in the algorithm, but rather modify the initialization and form of the hadronic current in τ decays. The format of the event record (HEPEVT common block) used to exchange information between building blocks of Monte Carlo systems often needs modification. Thus, there is a need to maintain various, slightly modified versions of the same code. The package presented here allows the production of ready-to-compile versions of TAUOLA [S. Jadach, Z. Wa?s, R. Decker, J.H. Kühn, Comput. Phys. Comm. 76 (1993) 361; A.E. Bondar, et al., Comput. Phys. Comm. 146 (2002) 139] and PHOTOS [E. Barberio, Z. Wa?s, Comput. Phys. Comm. 79 (1994) 291] Monte Carlo generators with appropriate demonstration programs. The new algorithm, universal interface of TAUOLA to work with the HEPEVT common block, is also documented here. Finally, minor technical improvements of TAUOLA and PHOTOS are also listed.Method of solution: The standard UNIX tool: the C-language preprocessor is used to produce a ready-to-distribute version of TAUOLA and PHOTOS code. The final FORTRAN code is produced from the library of ‘pre-code’ that is included in the package.Reasons for new version: The functionality of the version of TAUOLA and PHOTOS changed over the last two years. The changes, and their reasons, are documented in Section 9, and our new papers cited in this section.Additional comments: The updated version includes new features described in Section 9 of the paper. PHOTOS and TAUOLA were first submitted to the library as separate programs. Summary details of these previous programs are obtainable from the CPC Program Library.Typical running time: Depends on the speed of the computer used and the demonstration program chosen. Typically a few seconds.     

Automatized analytic continuation of Mellin-Barnes integrals

This paper describe a package written in MATHEMATICA that automatizes typical operations performed during evaluation of Feynman graphs with Mellin-Barnes (MB) techniques. The main procedure allows to analytically continue a MB integral in a given parameter without any intervention from the user and thus to resolve the singularity structure in this parameter. The package can also perform numerical integrations at specified kinematic points, as long as the integrands have satisfactory convergence properties. It is demonstrated that, at least in the case of massive graphs in the physical region, the convergence may turn out to be poor, making naïve numerical integration of MB integrals unusable. Possible solutions to this problem are presented, but full automatization in such cases may not be achievable.

Program summary

Title of program: MBProgram summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYG_v1_0Catalogue identifier: ADYG_v1_0Program obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandComputers: AllOperating systems: AllProgramming language used:MATHEMATICA, Fortran 77 for numerical evaluationMemory required to execute with typical data: Sufficient for a typical installation of MATHEMATICA.No. of lines in distributed program, including test data, etc.: 12 013No. of bytes in distributed program, including test data, etc.: 231 899Distribution format: tar.gzLibraries used:CUBA [T. Hahn, Comput. Phys. Commun. 168 (2005) 78] for numerical evaluation of multidimensional integrals and CERNlib [CERN Program Library, obtainable from: http://cernlib.web.cern.ch/cernlib/] for the implementation of Γ and ψ functions in Fortran.Nature of physical problem: Analytic continuation of Mellin-Barnes integrals in a parameter and subsequent numerical evaluation. This is necessary for evaluation of Feynman integrals from Mellin-Barnes representations.Method of solution: Recursive accumulation of residue terms occurring when singularities cross integration contours. Numerical integration of multidimensional integrals with the help of the CUBA library.Restrictions on the complexity of the problem: Limited by the size of the available storage space.Typical running time: Depending on the problem. Usually seconds for moderate dimensionality integrals.     

Practical Datatype Specializations with Phantom Types and Recursion Schemes

Datatype specialization is a form of subtyping that captures program invariants on data structures that are expressed using the convenient and intuitive datatype notation. Of particular interest are structural invariants such as well-formedness. We investigate the use of phantom types for describing datatype specializations. We show that it is possible to express statically-checked specializations within the type system of Standard ML. We also show that this can be done in a way that does not lose useful programming facilities such as pattern matching in case expressions.     

eHDECAY: An implementation of the Higgs effective Lagrangian into HDECAY

We present eHDECAY, a modified version of the program HDECAY which includes the full list of leading bosonic operators of the Higgs effective Lagrangian with a linear or non-linear realization of the electroweak symmetry and implements two benchmark composite Higgs models.     

HypExp 2, Expanding hypergeometric functions about half-integer parameters

In this article, we describe a new algorithm for the expansion of hypergeometric functions about half-integer parameters. The implementation of this algorithm for certain classes of hypergeometric functions in the already existing Mathematica package HypExp is described. Examples of applications in Feynman diagrams with up to four loops are given.

New version program summary

Program title:HypExp 2Catalogue identifier:ADXF_v2_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXF_v2_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.:106 401No. of bytes in distributed program, including test data, etc.:2 668 729Distribution format:tar.gzProgramming language:MathematicaComputer:Computers running MathematicaOperating system:Linux, Windows, MacRAM:Depending on the complexity of the problemSupplementary material:Library files which contain the expansion of certain hypergeometric functions around their parameters are availableClassification:4.7, 5Does the new version supersede the previous version?:YesNature of problem:Expansion of hypergeometric functions about parameters that are integer and/or half-integer valued.Solution method:New algorithm implemented in Mathematica.Reasons for new version:Expansion about half-integer parameters.Summary of revisions:Ability to expand about half-integer valued parameters added.Restrictions:The classes of hypergeometric functions with half-integer parameters that can be expanded are listed below.Additional comments:The package uses the package HPL included in the distribution.Running time:Depending on the expansion.     

Extended rate, more GFUN

We present a software package that guesses formulae for sequences of, for example, rational numbers or rational functions, given the first few terms. We implement an algorithm due to Bernhard Beckermann and George Labahn, together with some enhancements to render our package efficient. Thus we extend and complement Christian Krattenthaler’s program Rate.m, the parts concerned with guessing of Bruno Salvy and Paul Zimmermann’s GFUN, the univariate case of Manuel Kauers’ Guess.m and Manuel Kauers’ and Christoph Koutschan’s qGeneratingFunctions.m.     

TaylUR 3, a multivariate arbitrary-order automatic differentiation package for Fortran 95

This new version of TaylUR is based on a completely new core, which now is able to compute the numerical values of all of a complex-valued function's partial derivatives up to an arbitrary order, including mixed partial derivatives.

New version program summary

Program title: TaylURCatalogue identifier: ADXR_v3_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXR_v3_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: GPLv2No. of lines in distributed program, including test data, etc.: 6750No. of bytes in distributed program, including test data, etc.: 19 162Distribution format: tar.gzProgramming language: Fortran 95Computer: Any computer with a conforming Fortran 95 compilerOperating system: Any system with a conforming Fortran 95 compilerClassification: 4.12, 4.14Catalogue identifier of previous version: ADXR_v2_0Journal reference of previous version: Comput. Phys. Comm. 176 (2007) 710Does the new version supersede the previous version?: YesNature of problem: Problems that require potentially high orders of partial derivatives with respect to several variables or derivatives of complex-valued functions, such as e.g. momentum or mass expansions of Feynman diagrams in perturbative QFT, and which previous versions of this TaylUR [1,2] cannot handle due to their lack of support for mixed partial derivatives.Solution method: Arithmetic operators and Fortran intrinsics are overloaded to act correctly on objects of a defined type taylor, which encodes a function along with its first few partial derivatives with respect to the user-defined independent variables. Derivatives of products and composite functions are computed using multivariate forms [3] of Leibniz's rule where ν=(ν₁,…,νd), , , Dνf=^∂|ν|f/(ν₁^∂x₁?νd^∂xd), and μ<ν iff either |μ|<|ν| or |μ|=|ν|,μ₁=ν₁,…,μk=νk,μk+1<νk+1 for some k∈{0,…,d−1}, and of Fàa di Bruno's formula where the sum is over , . An indexed storage system is used to store the higher-order derivative tensors in a one-dimensional array. The relevant indices (k₁,…,ks;λ₁,…,λs) and the weights occurring in the sums in Leibniz's and Fàa di Bruno's formula are precomputed at startup and stored in static arrays for later use.Reasons for new version: The earlier version lacked support for mixed partial derivatives, but a number of projects of interest required them.Summary of revisions: The internal representation of a taylor object has changed to a one-dimensional array which contains the partial derivatives in ascending order, and in lexicographic order of the corresponding multiindex within the same order. The necessary mappings between multiindices and indices into the taylor objects' internal array are computed at startup. To support the change to a genuinely multivariate taylor type, the DERIVATIVE function is now implemented via an interface that accepts both the older format derivative(f,mu,n) and also a new format derivative(f,mu(:))=Dμf that allows access to mixed partial derivatives. Another related extension to the functionality of the module is the HESSIAN function that returns the Hessian matrix of second derivatives of its argument. Since the calculation of all mixed partial derivatives can be very costly, and in many cases only some subset is actually needed, a masking facility has been added. Calling the subroutine DEACTIVATE_DERIVATIVE with a multiindex as an argument will deactivate the calculation of the partial derivative belonging to that multiindex, and of all partial derivatives it can feed into. Similarly, calling the subroutine ACTIVATE_DERIVATIVE will activate the calculation of the partial derivative belonging to its argument, and of all partial derivatives that can feed into it. Moreover, it is possible to turn off the computation of mixed derivatives altogether by setting Diagonal_taylors to .TRUE.. It should be noted that any change of Diagonal_taylors or Taylor_order invalidates all existing taylor objects. To aid the better integration of TaylUR into the HPSrc library [4], routines SET_DERIVATIVE and SET_ALL_DERIVATIVES are provided as a means of manually constructing a taylor object with given derivatives.Restrictions: Memory and CPU time constraints may restrict the number of variables and Taylor expansion order that can be achieved. Loss of numerical accuracy due to cancellation may become an issue at very high orders.Unusual features: These are the same as in previous versions, but are enumerated again here for clarity. The complex conjugation operation assumes all independent variables to be real. The functions REAL and AIMAG do not convert to real type, but return a result of type taylor (with the real/imaginary part of each derivative taken) instead. The user-defined functions VALUE, REALVALUE and IMAGVALUE, which return the value of a taylor object as a complex number, and the real and imaginary part of this value, respectively, as a real number are also provided. Fortran 95 intrinsics that are defined only for arguments of real type (ACOS, AINT, ANINT, ASIN, ATAN, ATAN2, CEILING, DIM, FLOOR, INT, LOG10, MAX, MAXLOC, MAXVAL, MIN, MINLOC, MINVAL, MOD, MODULO, NINT, SIGN) will silently take the real part of taylor-valued arguments unless the module variable Real_args_warn is set to .TRUE., in which case they will return a quiet NaN value (if supported by the compiler) when called with a taylor argument whose imaginary part exceeds the module variable Real_args_tol. In those cases where the derivative of a function becomes undefined at certain points (as for ABS, AINT, ANINT, MAX, MIN, MOD, and MODULO), while the value is well defined, the derivative fields will be filled with quiet NaN values (if supported by the compiler).Additional comments: This version of TaylUR is released under the second version of the GNU General Public License (GPLv2). Therefore anyone is free to use or modify the code for their own calculations. As part of the licensing, it is requested that any publications including results from the use of TaylUR or any modification derived from it cite Refs. [1,2] as well as this paper. Finally, users are also requested to communicate to the author details of such publications, as well as of any bugs found or of required or useful modifications made or desired by them.Running time: The running time of TaylUR operations grows rapidly with both the number of variables and the Taylor expansion order. Judicious use of the masking facility to drop unneeded higher derivatives can lead to significant accelerations, as can activation of the Diagonal_taylors variable whenever mixed partial derivatives are not needed.Acknowledgments: The author thanks Alistair Hart for helpful comments and suggestions. This work is supported by the Deutsche Forschungsgemeinschaft in the SFB/TR 09.References:

[1]

G.M. von Hippel, TaylUR, an arbitrary-order diagonal automatic differentiation package for Fortran 95, Comput. Phys. Comm. 174 (2006) 569.

[2]

G.M. von Hippel, New version announcement for TaylUR, an arbitrary-order diagonal automatic differentiation package for Fortran 95, Comput. Phys. Comm. 176 (2007) 710.

[3]

G.M. Constantine, T.H. Savits, A multivariate Faa di Bruno formula with applications, Trans. Amer. Math. Soc. 348 (2) (1996) 503.

[4]

A. Hart, G.M. von Hippel, R.R. Horgan, E.H. Müller, Automated generation of lattice QCD Feynman rules, Comput. Phys. Comm. 180 (2009) 2698, doi:10.1016/j.cpc.2009.04.021, arXiv:0904.0375.

     

PLNoise: a package for exact numerical simulation of power-law noises

Many simulations of stochastic processes require colored noises: here I describe a small program library that generates samples with a tunable power-law spectral density: the algorithm can be modified to generate more general colored noises, and is exact for all time steps, even when they are unevenly spaced (as may often happen in the case of astronomical data, see e.g. [N.R. Lomb, Astrophys. Space Sci. 39 (1976) 447]. The method is exact in the sense that it reproduces a process that is theoretically guaranteed to produce a range-limited power-law spectrum 1/f1+β with −1<β?1. The algorithm has a well-behaved computational complexity, it produces a nearly perfect Gaussian noise, and its computational efficiency depends on the required degree of noise Gaussianity.

Program summary

Title of program: PLNoiseCatalogue identifier:ADXV_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXV_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandLicensing provisions: noneProgramming language used: ANSI CComputer: Any computer with an ANSI C compiler: the package has been tested with gcc version 3.2.3 on Red Hat Linux 3.2.3-52 and gcc version 4.0.0 and 4.0.1 on Apple Mac OS X-10.4Operating system: All operating systems capable of running an ANSI C compilerNo. of lines in distributed program, including test data, etc.:6238No. of bytes in distributed program, including test data, etc.:52 387Distribution format:tar.gzRAM: The code of the test program is very compact (about 50 Kbytes), but the program works with list management and allocates memory dynamically; in a typical run (like the one discussed in Section 4 in the long write-up) with average list length 2⋅¹⁰⁴, the RAM taken by the list is 200 Kbytes.External routines: The package needs external routines to generate uniform and exponential deviates. The implementation described here uses the random number generation library ranlib freely available from Netlib [B.W. Brown, J. Lovato, K. Russell, ranlib, available from Netlib, http://www.netlib.org/random/index.html, select the C version ranlib.c], but it has also been successfully tested with the random number routines in Numerical Recipes [W.H. Press, S.A. Teulkolsky, W.T. Vetterling, B.P. Flannery, Numerical Recipes in C: The Art of Scientific Computing, second ed., Cambridge Univ. Press, Cambridge, 1992, pp. 274-290]. Notice that ranlib requires a pair of routines from the linear algebra package LINPACK, and that the distribution of ranlib includes the C source of these routines, in case LINPACK is not installed on the target machine.Nature of problem: Exact generation of different types of Gaussian colored noise.Solution method: Random superposition of relaxation processes [E. Milotti, Phys. Rev. E 72 (2005) 056701].Unusual features: The algorithm is theoretically guaranteed to be exact, and unlike all other existing generators it can generate samples with uneven spacing.Additional comments: The program requires an initialization step; for some parameter sets this may become rather heavy.Running time: Running time varies widely with different input parameters, however in a test run like the one in Section 4 in this work, the generation routine took on average about 7 ms for each sample.     

Foam: A general-purpose cellular Monte Carlo event generator

A general-purpose, self-adapting Monte Carlo (MC) event generator (simulator) Foam is described. The high efficiency of the MC, that is small maximum weight or variance of the MC weight is achieved by means of dividing the integration domain into small cells. The cells can be n-dimensional simplices, hyperrectangles or a Cartesian product of them. The grid of cells, called “foam”, is produced in the process of the binary split of the cells. The choice of the next cell to be divided and the position/direction of the division hyperplane is driven by the algorithm which optimizes the ratio of the maximum weight to the average weight or (optionally) the total variance. The algorithm is able to deal, in principle, with an arbitrary pattern of the singularities in the distribution. As any MC generator, Foam can also be used for the MC integration. With the typical personal computer CPU, the program is able to perform adaptive integration/simulation of a relatively small number of dimensions (?16). With the continuing progress in CPU power, this limit will inevitably get shifted to ever higher dimensions. Foam program is aimed (and already tested) as a component of the MC event generators for the high energy physics experiments. A few simple examples of the related applications are presented. Foam code is written in fully object-oriented style, in the C++ language. Two other versions with a slightly limited functionality, are available in the Fortran77 language. The source codes are available from http://jadach.home.cern.ch/jadach/.     

Dynamic Event Generation for Runtime Checking using the JDI

Approaches to runtime checking have to track the execution of a software system and therefore have to deal with generating and processing execution events. Often these techniques are applied at the code level – either by inserting new source code prior to the compilation or by modifying the target code, e.g. Java byte code, before running the program.The jassda [4,3] framework and tool enable runtime checking of Java programs against a CSP-like specification. For generating events it uses the Java Debug Interface (JDI) and thus no modifications to the code are necessary. Another advantage is that events are generated on demand, i.e. dynamically at runtime it is determined which events to generate for the current debug run without modifying the program itself. This paper shows how this event generation is done by the jassda framework.