DPEMC: A Monte Carlo for double diffraction

We extend the POMWIG Monte Carlo generator developed by B. Cox and J. Forshaw, to include new models of central production through inclusive and exclusive double Pomeron exchange in proton-proton collisions. Double photon exchange processes are described as well, both in proton-proton and heavy-ion collisions. In all contexts, various models have been implemented, allowing for comparisons and uncertainty evaluation and enabling detailed experimental simulations.

Program summary

Title of the program:DPEMC, version 2.4Catalogue identifier: ADVFProgram summary URL:http://cpc.cs.qub.ac.uk/summaries/ADVFProgram obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandComputer: any computer with the FORTRAN 77 compiler under the UNIX or Linux operating systemsOperating system: UNIX; LinuxProgramming language used: FORTRAN 77High speed storage required:<25 MBNo. of lines in distributed program, including test data, etc.: 71 399No. of bytes in distributed program, including test data, etc.: 639 950Distribution format: tar.gzNature of the physical problem: Proton diffraction at hadron colliders can manifest itself in many forms, and a variety of models exist that attempt to describe it [A. Bialas, P.V. Landshoff, Phys. Lett. B 256 (1991) 540; A. Bialas, W. Szeremeta, Phys. Lett. B 296 (1992) 191; A. Bialas, R.A. Janik, Z. Phys. C 62 (1994) 487; M. Boonekamp, R. Peschanski, C. Royon, Phys. Rev. Lett. 87 (2001) 251806; Nucl. Phys. B 669 (2003) 277; R. Enberg, G. Ingelman, A. Kissavos, N. Timneanu, Phys. Rev. Lett. 89 (2002) 081801; R. Enberg, G. Ingelman, L. Motyka, Phys. Lett. B 524 (2002) 273; R. Enberg, G. Ingelman, N. Timneanu, Phys. Rev. D 67 (2003) 011301; B. Cox, J. Forshaw, Comput. Phys. Comm. 144 (2002) 104; B. Cox, J. Forshaw, B. Heinemann, Phys. Lett. B 540 (2002) 26; V. Khoze, A. Martin, M. Ryskin, Phys. Lett. B 401 (1997) 330; Eur. Phys. J. C 14 (2000) 525; Eur. Phys. J. C 19 (2001) 477; Erratum, Eur. Phys. J. C 20 (2001) 599; Eur. Phys. J. C 23 (2002) 311]. This program implements some of the more significant ones, enabling the simulation of central particle production through color singlet exchange between interacting protons or antiprotons.Method of solution: The Monte Carlo method is used to simulate all elementary 2→2 and 2→1 processes available in HERWIG. The color singlet exchanges implemented in DPEMC are implemented as functions reweighting the photon flux already present in HERWIG.Restriction on the complexity of the problem: The program relying extensively on HERWIG, the limitations are the same as in [G. Marchesini, B.R. Webber, G. Abbiendi, I.G. Knowles, M.H. Seymour, L. Stanco, Comput. Phys. Comm. 67 (1992) 465; G. Corcella, I.G. Knowles, G. Marchesini, S. Moretti, K. Odagiri, P. Richardson, M. Seymour, B. Webber, JHEP 0101 (2001) 010].Typical running time: Approximate times on a 800 MHz Pentium III: 5-20 min per 10 000 unweighted events, depending on the process under consideration.     

SPICE: Simulation Package for Including Flavor in Collider Events

We describe SPICE: Simulation Package for Including Flavor in Collider Events. SPICE takes as input two ingredients: a standard flavor-conserving supersymmetric spectrum and a set of flavor-violating slepton mass parameters, both of which are specified at some high “mediation” scale. SPICE then combines these two ingredients to form a flavor-violating model, determines the resulting low-energy spectrum and branching ratios, and outputs HERWIG and SUSY Les Houches files, which may be used to generate collider events. The flavor-conserving model may be any of the standard supersymmetric models, including minimal supergravity, minimal gauge-mediated supersymmetry breaking, and anomaly-mediated supersymmetry breaking supplemented by a universal scalar mass. The flavor-violating contributions may be specified in a number of ways, from specifying charges of fields under horizontal symmetries to completely specifying all flavor-violating parameters. SPICE is fully documented and publicly available, and is intended to be a user-friendly aid in the study of flavor at the Large Hadron Collider and other future colliders.

Program summary

Program title: SPICECatalogue identifier: AEFL_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFL_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.: 8153No. of bytes in distributed program, including test data, etc.: 67 291Distribution format: tar.gzProgramming language: C++Computer: Personal computerOperating system: Tested on Scientific Linux 4.xClassification: 11.1External routines: SOFTSUSY [1,2] and SUSYHIT [3]Nature of problem: Simulation programs are required to compare theoretical models in particle physics with present and future data at particle colliders. SPICE determines the masses and decay branching ratios of supersymmetric particles in theories with lepton flavor violation. The inputs are the parameters of any of several standard flavor-conserving supersymmetric models, supplemented by flavor-violating parameters determined, for example, by horizontal flavor symmetries. The output are files that may be used for detailed simulation of supersymmetric events at particle colliders.Solution method: Simpson's rule integrator, basic algebraic computation.Additional comments: SPICE interfaces with SOFTSUSY and SUSYHIT to produce the low energy sparticle spectrum. Flavor mixing for sleptons and sneutrinos is fully implemented; flavor mixing for squarks is not included.Running time: <1 minute. Running time is dominated by calculating the possible and relevant three-body flavor-violating decays of sleptons, which is usually 10-15 seconds per slepton.References:

[1]

B.C. Allanach, Comput. Phys. Commun. 143 (2002) 305, arXiv:hep-ph/0104145.

[2]

B.C. Allanach, M.A. Bernhardt, arXiv:0903.1805 [hep-ph].

[3]

A. Djouadi, M.M. Muhlleitner, M. Spira, Acta Phys. Pol. B 38 (2007) 635, arXiv:hep-ph/0609292.

     

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

In a recent paper I have introduced a package for the exact simulation of power-law noises and other colored noises [E. Milotti, Comput. Phys. Comm. 175 (2006) 212]: in particular, the algorithm generates 1/fα noises with 0<α?2. Here I extend the algorithm to generate 1/fα noises with 2<α?4 (black noises). The method is exact in the sense that it produces a sampled process with a theoretically guaranteed range-limited power-law spectrum for any arbitrary sequence of sampling intervals, i.e. the sampling times may be unevenly spaced.

Program summary

Title of program: PLNoiseCatalogue identifier:ADXV_v2_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXV_v2_0.htmlLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlProgram obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandProgramming 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 compilerRAM: The code of the test program is very compact (about 60 Kbytes), but the program works with list management and allocates memory dynamically; in a typical run with average list length 2⋅¹⁰⁴, the RAM taken by the list is 200 KbytesExternal 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.No. of lines in distributed program, including test data, etc.:2975No. of bytes in distributed program, including test data, etc.:194 588Distribution format:tar.gzCatalogue identifier of previous version: ADXV_v1_0Journal reference of previous version: Comput. Phys. Comm. 175 (2006) 212Does the new version supersede the previous version?: YesNature of problem: Exact generation of different types of colored noise.Solution method: Random superposition of relaxation processes [E. Milotti, Phys. Rev. E 72 (2005) 056701], possibly followed by an integration step to produce noise with spectral index >2.Reasons for the new version: Extension to 1/fα noises with spectral index 2<α?4: the new version generates both noises with spectral with spectral index 0<α?2 and with 2<α?4.Summary of revisions: Although the overall structure remains the same, one routine has been added and several changes have been made throughout the code to include the new integration step.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 3 in the long write-up, the generation routine took on average about 75 μs for each sample.     

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.     

Optimal Jet Finder (v1.0 C++)

We describe a C++ implementation of the Optimal Jet Definition for identification of jets in hadronic final states of particle collisions. We explain interface subroutines and provide a usage example. The source code is available from http://www.inr.ac.ru/~ftkachov/projects/jets/.

Program summary

Title of program: Optimal Jet Finder (v1.0 C++)Catalogue identifier: ADSB_v2_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSB_v2_0Program obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandComputer: any computer with a standard C++ compilerTested with:

(1)

GNU gcc 3.4.2, Linux Fedora Core 3, Intel i686;

(2)

Forte Developer 7 C++ 5.4, SunOS 5.9, UltraSPARC III+;

(3)

Microsoft Visual C++ Toolkit 2003 (compiler 13.10.3077, linker 7.10.30777, option /EHsc), Windows XP, Intel i686.

Programming language used: C++Memory required:∼1 MB (or more, depending on the settings)No. of lines in distributed program, including test data, etc.: 3047No. of bytes in distributed program, including test data, etc.: 17 884Distribution format: tar.gzNature of physical problem: Analysis of hadronic final states in high energy particle collision experiments often involves identification of hadronic jets. A large number of hadrons detected in the calorimeter is reduced to a few jets by means of a jet finding algorithm. The jets are used in further analysis which would be difficult or impossible when applied directly to the hadrons. Grigoriev et al. [D.Yu. Grigoriev, E. Jankowski, F.V. Tkachov, Phys. Rev. Lett. 91 (2003) 061801] provide brief introduction to the subject of jet finding algorithms and a general review of the physics of jets can be found in [R. Barlow, Rep. Prog. Phys. 36 (1993) 1067].Method of solution: The software we provide is an implementation of the so-called Optimal Jet Definition (OJD). The theory of OJD was developed in [F.V. Tkachov, Phys. Rev. Lett. 73 (1994) 2405; Erratum, Phys. Rev. Lett. 74 (1995) 2618; F.V. Tkachov, Int. J. Modern Phys. A 12 (1997) 5411; F.V. Tkachov, Int. J. Modern Phys. A 17 (2002) 2783]. The desired jet configuration is obtained as the one that minimizes Ω, a certain function of the input particles and jet configuration. A FORTRAN 77 implementation of OJD is described in [D.Yu. Grigoriev, E. Jankowski, F.V. Tkachov, Comput. Phys. Comm. 155 (2003) 42].Restrictions on the complexity of the program: Memory required by the program is proportional to the number of particles in the input × the number of jets in the output. For example, for 650 particles and 20 jets ∼300 KB memory is required.Typical running time: The running time (in the running mode with a fixed number of jets) is proportional to the number of particles in the input × the number of jets in the output × times the number of different random initial configurations tried (ntries). For example, for 65 particles in the input and 4 jets in the output, the running time is ∼4⋅¹⁰⁻³ s per try (Pentium 4 2.8 GHz).     

THERMUS—A thermal model package for ROOT

THERMUS is a package of C++ classes and functions allowing statistical-thermal model analyses of particle production in relativistic heavy-ion collisions to be performed within the ROOT framework of analysis. Calculations are possible within three statistical ensembles; a grand-canonical treatment of the conserved charges B, S and Q, a fully canonical treatment of the conserved charges, and a mixed-canonical ensemble combining a canonical treatment of strangeness with a grand-canonical treatment of baryon number and electric charge. THERMUS allows for the assignment of decay chains and detector efficiencies specific to each particle yield, which enables sensible fitting of model parameters to experimental data.

Program summary

Program title: THERMUS, version 2.1Catalogue identifier: AEBW_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBW_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 152No. of bytes in distributed program, including test data, etc.: 93 581Distribution format: tar.gzProgramming language: C++Computer: PC, Pentium 4, 1 GB RAM (not hardware dependent)Operating system: Linux: FEDORA, RedHat, etc.Classification: 17.7External routines: Numerical Recipes in C [1], ROOT [2]Nature of problem: Statistical-thermal model analyses of heavy-ion collision data require the calculation of both primordial particle densities and contributions from resonance decay. A set of thermal parameters (the number depending on the particular model imposed) and a set of thermalized particles, with their decays specified, is required as input to these models. The output is then a complete set of primordial thermal quantities for each particle, together with the contributions to the final particle yields from resonance decay. In many applications of statistical-thermal models it is required to fit experimental particle multiplicities or particle ratios. In such analyses, the input is a set of experimental yields and ratios, a set of particles comprising the assumed hadron resonance gas formed in the collision and the constraints to be placed on the system. The thermal model parameters consistent with the specified constraints leading to the best-fit to the experimental data are then output.Solution method: THERMUS is a package designed for incorporation into the ROOT [2] framework, used extensively by the heavy-ion community. As such, it utilizes a great deal of ROOT's functionality in its operation. ROOT features used in THERMUS include its containers, the wrapper TMinuit implementing the MINUIT fitting package, and the TMath class of mathematical functions and routines. Arguably the most useful feature is the utilization of CINT as the control language, which allows interactive access to the THERMUS objects. Three distinct statistical ensembles are included in THERMUS, while additional options to include quantum statistics, resonance width and excluded volume corrections are also available. THERMUS provides a default particle list including all mesons (up to the (2045)) and baryons (up to the Ω⁻) listed in the July 2002 Particle Physics Booklet [3]. For each typically unstable particle in this list, THERMUS includes a text-file listing its decays. With thermal parameters specified, THERMUS calculates primordial thermal densities either by performing numerical integrations or else, in the case of the Boltzmann approximation without resonance width in the grand-canonical ensemble, by evaluating Bessel functions. Particle decay chains are then used to evaluate experimental observables (i.e. particle yields following resonance decay). Additional detector efficiency factors allow fine-tuning of the model predictions to a specific detector arrangement. When parameters are required to be constrained, use is made of the ‘Numerical Recipes in C’ [1] function which applies the Broyden globally convergent secant method of solving nonlinear systems of equations. Since the NRC software is not freely-available, it has to be purchased by the user. THERMUS provides the means of imposing a large number of constraints on the chosen model (amongst others, THERMUS can fix the baryon-to-charge ratio of the system, the strangeness density of the system and the primordial energy per hadron). Fits to experimental data are accomplished in THERMUS by using the ROOT TMinuit class. In its default operation, the standard χ² function is minimized, yielding the set of best-fit thermal parameters. THERMUS allows the assignment of separate decay chains to each experimental input. In this way, the model is able to match the specific feed-down corrections of a particular data set.Running time: Depending on the analysis required, run-times vary from seconds (for the evaluation of particle multiplicities given a set of parameters) to several minutes (for fits to experimental data subject to constraints).References:

[1]

W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery, Numerical Recipes in C: The Art of Scientific Computing, Cambridge University Press, Cambridge, 2002.

[2]

R. Brun, F. Rademakers, Nucl. Inst. Meth. Phys. Res. A 389 (1997) 81. See also http://root.cern.ch/.

[3]

K. Hagiwara et al., Phys. Rev. D 66 (2002) 010001.

     

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.     

Maple procedures for the coupling of angular momenta. An up-date of the Racah module

An up-date of the Racah module is presented, adopted to Maple 11 and 12, which supports both, algebraic manipulations of expressions from Racah's algebra as well as numerical computations of many functions and symbols from the theory of angular momentum. The functions that are known to the program include the Wigner rotation matrices and n-j symbols, Clebsch-Gordan and Gaunt coefficients, spherical harmonics of various kinds as well as several others.

Program summary

Program title:RacahCatalogue identifier: ADFV_v10_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADFV_v10_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.: 30 436No. of bytes in distributed program, including test data, etc.: 544 866Distribution format: tar.gzProgramming language: Maple 11 and 12Computer: All computers with a license for the computer algebra package Maple [1]Operating system: Suse Linux 10.2+ and Ubuntu 8.10Classification: 4.1, 5Catalogue identifier of previous version: ADFV_v9_0Journal reference of previous version: Comput. Phys. Comm. 174 (2006) 616Does the new version supersede the previous version?: YesNature of problem: The theories of angular momentum and spherical tensor operators, sometimes known also as Racah's algebra, provide a powerful calculus for studying spin networks and (quantum) many-particle systems. For an efficient use of these theories, however, one requires not only a reliable handling of a large number of algebraic transformations and rules but, more often than not, also a fast access to their standard quantities, such as the Wigner n-j symbols, Clebsch-Gordan coefficients, spherical harmonics of various kinds, the rotation matrices, and many others.Solution method: A set of Maple procedures has been developed and maintained during the last decade which supports both, algebraic manipulations as well as fast computations of the standard expressions and symbols from the theory of angular momentum [2,3]. These procedures are based on a sizeable set of group-theoretical (and often rather sophisticated) relations which has been discussed and proven in the literature; see the monograph by Varshalovich et al. [4] for a comprehensive compilation. In particular the algebraic manipulation of complex (Racah) expressions may result in considerable simplifications, thus reducing the ‘numerical costs’, and often help obtain further insight into the behaviour of physical systems.Reasons for new version: A revision of the Racah module became necessary for mainly three reasons: (i) Since the last extension of the Racah procedures [5], which was developed within the framework of Maple 8, several updates of Maple were distributed by the vendors (currently Maple 13) and required a number of adaptations to the source code; (ii) the increasing size and program structure of the Racah module made it advisible to separate the (procedures for the treatment of the) atomic shell model from the manipulation and computation of Racah expressions. Therefore, the computation of angular coefficients for different coupling schemes, (grand) coefficients of fractional parentage as well as the matrix elements (of various irreducible tensors from the shell model) is to be maintained from now on independently within the Jucys module; (iii) a number of bugs and inconsistencies have been reported to us and corrected in the present version.Summary of revisions: In more detail, the following changes have been made:

1.

Since recent versions of Maple now support the automatic type checking of all incoming arguments and the definition of user-defined types; we have adapted most of the code to take advantage of these features, and especially those commands that are accessible by the user.

2.

In the computation of the Wigner n-j symbols and Clebsch-Gordan coefficients, we now return a ‘0’ in all cases in which the triangular rules are not fulfilled, for example, if δ(a,b,c)=0 for or . This change in the program saves the user making these tests on the quantum numbers explicitly everytime (in the summation over more complex expressions) that such a symbol or coefficient is invoked. The program still terminates with an error message if the (half-integer and integer) angular momentum quantum numbers appear in an inproper combination.

3.

While a recursive generation of the Wigner 3-j and 6-j symbols [6] may reduce the costs of some computations (and has thus been utilized in the past), it also makes the program rather sophisticated, especially if an algebraic evaluation or computations with a high number of Digits need to be supported by the same generic commands. The following procedures are therefore no longer supported by the Racah module:Racah_compute_w3j_jrange(), Racah_compute_w3j_mrange(),Racah_compute_w3j_recursive(), Racah_compute_w6j_range(), andRacah_compute_w6j_recursive().On most PCs, a sequential computation of all requested symbols is carried out within the same time basically.

4.

Because the module Jucys has grown to a size of about 35,000 lines of code and data, it appears helpful and necessary to maintain it independently. The procedures from the Jucys modules were designed to facilitate the computation of matrix elements of the unit tensors, the coefficients of fractional parentage (of various types) as well as transformation matrices between different coupling schemes [7] and are, thus, independent of the Racah module (although they typically require that the Racah code is available). The Jucys module is no longer distributed together with the present code.

5.

Apart from the Wigner n-j symbols (see above), some minor bugs have been reported and corrected in Racah_expand() and Racah_set().

6.

To facilitate the test of the installation and as a first tutorial on the module, we now provide the Maple worksheet Racah-tests-2009-maple12.mw in the Racah2009 root directory. This worksheet contains the examples and test cases from the previous versions. For the test of the installation, it is recommended that a ‘copy’ of this worksheet is saved and compared to the results from the re-run. It can be used also as a helpful source to define new examples in interactive work with the Racah module.

The Racah module is distributed in a tar file ADFV_v10_0.tar.gz from which the RACAH2009 root directory is (re-)generated by the command tar -zxvf ADFV_v10_0.tar.gz. This directory contains the source code libraries (tested for Maple 11 and 12), a Read.me for the installation of the program, the worksheet Racah-tests-2009-maple12.mw as well as the document Racah-commands-2009.pdf. This .pdf document serves as a Short Reference Manual and provides the definition of all the data structures of the Racah program together with an alphabetic list of all user relevant (and exported) commands. Although emphasis was placed on preserving the compatibility of the program with earlier releases of Maple, this cannot always be guaranteed due to changes in the Maple syntax. The Racah2009 root also contains an example of a .mapleinit file that can be modified and incorporated into the user's home directory to make the Racah module accessible like any other module of Maple. As mentioned above, the worksheet Racah-tests-2009-maple12.mw, help test the installation and may serve as a first tutorial.Restrictions: The (Racah) program is based on the concept of Racah expressions [cf. Fig. 1 in Ref. [4]] which, in principle, may contain any number of Wigner n-j symbols (n?9), Clebsch-Gordan coefficients, spherical harmonics and/or rotation matrices. In practise, of course, the required time and the success of an evaluation procedure depends on the complexity of the expressions and on the storage available, sometimes also on Maple's internal garbage treatment. In some cases, it is advisable to attempt first a simplification of the magnetic quantum numbers for a given expression before the summation over further 6-j and 9-j symbols should be taken into account. For all other quantities (that are compiled in Ref. [8], Tables 1 and 2, and explained in more detail in the Short Reference Manual, Racah-commands-2009.pdf), we currently just facilitate fast numerical computations by exploiting, as far as possible, Maple's hardware floating-point model. The program also supports simplifications on the Wigner rotation matrices. In integrals over the rotation matrices, products of up to three Wigner D-functions or reduced matrices (with the same angular arguments) are recognized; for the integration over a solid angle, however, the domain of integration must be specified explicitly for the Euler angles α and γ in order to force Maple to generate a constant of integration. In the course of the evaluation of Racah expressions, it is, in practice, often difficult to check internally whether all substructures of an expression are defined properly. Therefore, the user must ensure that all angular momenta (if given explicitly) must finally evaluate to integer and half-integer values and that they satisfy proper coupling conditions.Unusual features: The Racah program is designed for interactive use and for providing a quick and algebraic evaluation of (complex) expressions from Racah's algebra. In the evaluation, it exploits a large set of sum rules which are known from Racah's algebra and which may include (multiple) summations over dummy indices; see Varshalovich et al. [5] for a more detailed account of the theory. One strength of the program is that it recognizes automatically the symmetries of the symbols and functions, and that it applies also (some of) the graphical rules due to Yutsis and coworkers [9]. As before, the result of the evaluation process will be provided as Racah expressions, if a further simplification could be achieved, and may hence be used for further derivations and calculations within the given framework. In dealing with recoupling coefficients, these coefficients can be entered simply as a string of angular momenta (variables), separated by commas, and very similar to how they appear in mathematical texts. This is a crucial advantage of the program, compared with previous developments, for which the angular momenta and coupling coefficients had often to be given in a very detailed format. A Short Reference Manual to all procedures of the Racah program is provided by this distribution; it also contains the worksheet Racah-tests-2009-maple12.mw that contains the examples from all previous versions and may help test the installation. This worksheet can serve as a first tutorial to the Racah procedures. In the past, the Racah program has been utilized extensively in a number of applications including angular and polarization studies of heavy ions [10], angular distributions and correlation functions following photon-induced excitation processes [11], entanglement studies [12], in application of point-group symmetries and several others.Running time: The worksheet supplied with the distribution takes about 1 minute to run.References:

[1] Maple is a registered trademark of Waterloo Maple Inc.

[2] S. Fritzsche, Comp. Phys. Commun. 103 (1997) 51.

[3] S. Fritzsche, S. Varga, D. Geschke, B. Fricke, Comp. Phys. Commun. 111 (1998) 167;

T. Ingho, S. Fritzsche, B. Fricke, Comp. Phys. Commun. 139 (2001) 297;

S. Fritzsche, T. Ingho, T. Bastug, M. Tomaselli, Comp. Phys. Commun. 139 (2001) 314.

[4] D.A. Varshalovich, A.N. Moskalev, V.K. Khersonskii, Quantum Theory of Angular Momentum, World Scientific, Singapore a.o., 1988.

[5] J. Pagaran, S. Fritzsche, G. Gaigalas, Comp. Phys. Commun. 174 (2006) 616.

[6] K. Schulten, R.G. Gordon, Comp. Phys. Commun. 11 (1976) 269.

[7] G. Gaigalas, S. Fritzsche, B. Fricke, Comp. Phys. Commun. 135 (2001) 219;

G. Gaigalas, S. Fritzsche, Comp. Phys. Commun. 149 (2002) 39;

G. Gaigalas, O. Scharf, S. Fritzsche, Comp. Phys. Commun. 166 (2005) 141.

[8] S. Fritzsche, T. Ingho, M. Tomaselli, Comp. Phys. Commun. 153 (2003) 424.

[9] A.P. Yutsis, I.B. Levinson, V.V. Vanagas, The Theory of Angular Momentum, Israel Program for Scientific Translation, Jerusalem, 1962.

[10] S. Fritzsche, P. Indelicato, T. Stöhlker, J. Phys. B 38 (2005) S707.

[11] M. Kitajima, M. Okamoto, M. Hoshino, et al., J. Phys. B 35 (2002) 3327;

N.M. Kabachnik, S. Fritzsche, A.N. Grum-Grzhimailo, et al., Phys. Reports 451 (2007) 155;

S. Fritzsche, A.N. Grum-Grzhimailo, E.V. Gryzlova, N.M. Kabachnik, J. Phys. B 41 (2008) 165601;

T. Radtke, et al., Phys. Rev. A 77 (2008) 022507.

[12] T. Radtke, S. Fritzsche, Comp. Phys. Commun. 175 (2006) 145.

     

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)     

Programs for generating Clebsch-Gordan coefficients of SU(3) in SU(2) and SO(3) bases

Computer codes are developed to calculate Clebsch-Gordan coefficients of SU(3) in both SU(2)- and SO(3)-coupled bases. The efficiency of this code derives from the use of vector coherent state theory to evaluate the required coefficients directly without recursion relations. The approach extends to other compact semi-simple Lie groups. The codes are given in subroutine form so that users can incorporate the codes into other programs.

Program summary

Title of program: SU3CGVCSCatalogue identifier: ADTNProgram summary URL:http://cpc.cs.qub.ac.uk/summaries/ADTNProgram obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandLicensing provisions: Persons requesting the program must sign the standard CPC non-profit use licenseComputers for which the program is designed and others on which it is operable: SGI Origin 2000, HP Apollo 9000, Sun, IBM SP, PentiumOperating systems under which the program has been tested: IRIX 6.5, HP UX 10.01, SunOS, AIX, LinuxProgramming language used: FORTRAN 77Memory required to execute with typical data: On the HP system, it requires about 732 KBytes.Disk space used for output: 2100+2460 bytesNo. of bits in a word: 32 bit integer and 64 bit floating point numbers.No. of processors used: 1Has the code been vectorized: NoNo. of bytes in distributed program, including test data, etc.: 26 309No. of lines in distributed program, including test data, etc.: 3969Distribution format: tar gzip fileNature of physical problem: The group SU(3) and its Lie algebra have important applications, for example, in elementary particle physics, nuclear physics, and quantum optics [1-3]. The code presented is particularly relevant for the last two fields. Clebsch-Gordan (CG) coefficients are required whenever the symmetries of many-body systems are used for the evaluation of matrix elements of tensor operators. Moreover, the construction of CG coefficients for SU(3) serves as a nontrivial prototype for larger compact semi-simple Lie algebras and even for non semi-simple Lie algebras. It is the simplest Lie algebra to have multiplicity in its outer products and a non-canonical subalgebra, i.e., SO(3).Method of solution: Vector coherent state theory is first used to construct bases for the products of two irreducible representations (irreps) [4]. The bases are SU(2)-coupled so that SU(2)-reduced CG (or isoscalar factors) can be constructed naturally. The CG coefficients in the SO(3) bases are constructed subsequently from the overlaps between the SU(2) and SO(3) bases.Restriction on the complexity of the problem: The programs are limited by computer memory and the maximum size of variable arrays. As dimension overflow conditions are possible, they are flagged and can be fixed by following the directions given as part of the error message.Typical running time: The calculation time for a single SU(3) CG coefficient is very different for SU(2) and SO(3) bases. It varies between 7.3-54.1 ns in SGI Origin 2000, 0.81-5.48 ms in HP Apollo 9000, or 0.055-0.373 ms in Intel Pentium 4 for SU(2) bases while it is between 0.027-0.255 s in Intel Pentium 4 for SO(3) bases.Unusual features of the program: Intrinsic bit functions: and, or, and shift, called iand, ior, and ishft, respectively, in FORTRAN, are used for packing and unpacking the labels for the irreps. Intrinsic logical btest is used to test the bit for the phase factor.References:[1] Y. Ne'eman, Nucl. Phys. 26 (1961) 222;  M. Gell-Man, Y. Ne'eman, The Eightfold Way, Benjamin, New York, 1964.[2] J.P. Elliott, Proc. Roy. Soc. A 245 (1958) 128, 562.[3] M. Reck, A. Zeilinger, H.J. Bernstein, P. Bertani, Phys. Rev. Lett. 73 (1994) 58;  B.C. Sanders, H. de Guise, D.J. Rowe, A. Mann, J. Phys. A 32 (1999) 7111.[4] D.J. Rowe, C. Bahri, J. Math. Phys. 41 (2000) 6544.     

Heavy ion event generator HYDJET++ (HYDrodynamics plus JETs)

HYDJET++ is a Monte Carlo event generator for simulation of relativistic heavy ion AA collisions considered as a superposition of the soft, hydro-type state and the hard state resulting from multi-parton fragmentation. This model is the development and continuation of HYDJET event generator (Lokhtin and Snigirev, EPJC 45 (2006) 211). The main program is written in the object-oriented C++ language under the ROOT environment. The hard part of HYDJET++ is identical to the hard part of Fortran-written HYDJET and it is included in the generator structure as a separate directory. The soft part of HYDJET++ event is the “thermal” hadronic state generated on the chemical and thermal freeze-out hypersurfaces obtained from the parameterization of relativistic hydrodynamics with preset freeze-out conditions. It includes the longitudinal, radial and elliptic flow effects and the decays of hadronic resonances. The corresponding fast Monte Carlo simulation procedure, C++ code FAST MC (Amelin et al., PRC 74 (2006) 064901; PRC 77 (2008) 014903) is adapted to HYDJET++. It is designed for studying the multi-particle production in a wide energy range of heavy ion experimental facilities: from FAIR and NICA to RHIC and LHC.

Program summary

Program title: HYDJET++, version 2Catalogue identifier: AECR_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AECR_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.: 100 387No. of bytes in distributed program, including test data, etc.: 797 019Distribution format: tar.gzProgramming language: C++ (however there is a Fortran-written part which is included in the generator structure as a separate directory)Computer: Hardware independent (both C++ and Fortran compilers and ROOT environment [1] (http://root.cern.ch/) should be installed)Operating system: Linux (Scientific Linux, Red Hat Enterprise, FEDORA, etc.)RAM: 50 MBytes (determined by ROOT requirements)Classification: 11.2External routines: ROOT [1] (http://root.cern.ch/)Nature of problem: The experimental and phenomenological study of multi-particle production in relativistic heavy ion collisions is expected to provide valuable information on the dynamical behavior of strongly-interacting matter in the form of quark-gluon plasma (QGP) [2-4], as predicted by lattice Quantum Chromodynamics (QCD) calculations. Ongoing and future experimental studies in a wide range of heavy ion beam energies require the development of new Monte Carlo (MC) event generators and improvement of existing ones. Especially for experiments at the CERN Large Hadron Collider (LHC), implying very high parton and hadron multiplicities, one needs fast (but realistic) MC tools for heavy ion event simulations [5-7]. The main advantage of MC technique for the simulation of high-multiplicity hadroproduction is that it allows a visual comparison of theory and data, including if necessary the detailed detector acceptances, responses and resolutions. The realistic MC event generator has to include maximum possible number of observable physical effects, which are important to determine the event topology: from the bulk properties of soft hadroproduction (domain of low transverse momenta pT?1 GeV/c) such as collective flows, to hard multi-parton production in hot and dense QCD-matter, which reveals itself in the spectra of high-pT particles and hadronic jets. Moreover, the role of hard and semi-hard particle production at LHC can be significant even for the bulk properties of created matter, and hard probes of QGP became clearly observable in various new channels [8-11]. In the majority of the available MC heavy ion event generators, the simultaneous treatment of collective flow effects for soft hadroproduction and hard multi-parton in-medium production (medium-induced partonic rescattering and energy loss, so-called “jet quenching”) is lacking. Thus, in order to analyze existing data on low and high-pT hadron production, test the sensitivity of physical observables at the upcoming LHC experiments (and other future heavy ion facilities) to the QGP formation, and study the experimental capabilities of constructed detectors, the development of adequate and fast MC models for simultaneous collective flow and jet quenching simulations is necessary. HYDJET++ event generator includes detailed treatment of soft hadroproduction as well as hard multi-parton production, and takes into account known medium effects.Solution method: A heavy ion event in HYDJET++ is a superposition of the soft, hydro-type state and the hard state resulting from multi-parton fragmentation. Both states are treated independently. HYDJET++ is the development and continuation of HYDJET MC model [12]. The main program is written in the object-oriented C++ language under the ROOT environment [1]. The hard part of HYDJET++ is identical to the hard part of Fortran-written HYDJET [13] (version 1.5) and is included in the generator structure as a separate directory. The routine for generation of single hard NN collision, generator PYQUEN [12,14], modifies the “standard” jet event obtained with the generator PYTHIA 6.4 [15]. The event-by-event simulation procedure in PYQUEN includes

1.

generation of initial parton spectra with PYTHIA and production vertexes at given impact parameter;

2.

rescattering-by-rescattering simulation of the parton path in a dense zone and its radiative and collisional energy loss;

3.

final hadronization according to the Lund string model for hard partons and in-medium emitted gluons.

Then the PYQUEN multi-jets generated according to the binomial distribution are included in the hard part of the event. The mean number of jets produced in an AA event is the product of the number of binary NN subcollisions at a given impact parameter and the integral cross section of the hard process in NN collisions with the minimum transverse momentum transfer . In order to take into account the effect of nuclear shadowing on parton distribution functions, the impact parameter dependent parameterization obtained in the framework of Glauber-Gribov theory [16] is used. The soft part of HYDJET++ event is the “thermal” hadronic state generated on the chemical and thermal freeze-out hypersurfaces obtained from the parameterization of relativistic hydrodynamics with preset freeze-out conditions (the adapted C++ code FAST MC [17,18]). Hadron multiplicities are calculated using the effective thermal volume approximation and Poisson multiplicity distribution around its mean value, which is supposed to be proportional to the number of participating nucleons at a given impact parameter of AA collision. The fast soft hadron simulation procedure includes

1.

generation of the 4-momentum of a hadron in the rest frame of a liquid element in accordance with the equilibrium distribution function;

2.

generation of the spatial position of a liquid element and its local 4-velocity in accordance with phase space and the character of motion of the fluid;

3.

the standard von Neumann rejection/acceptance procedure to account for the difference between the true and generated probabilities;

4.

boost of the hadron 4-momentum in the center mass frame of the event;

5.

the two- and three-body decays of resonances with branching ratios taken from the SHARE particle decay table [19].

The high generation speed in HYDJET++ is achieved due to almost 100% generation efficiency of the “soft” part because of the nearly uniform residual invariant weights which appear in the freeze-out momentum and coordinate simulation. Although HYDJET++ is optimized for very high energies of RHIC and LHC colliders (c.m.s. energies of heavy ion beams and 5500 GeV per nucleon pair, respectively), in practice it can also be used for studying the particle production in a wider energy range down to per nucleon pair at other heavy ion experimental facilities. As one moves from very high to moderately high energies, the contribution of the hard part of the event becomes smaller, while the soft part turns into just a multi-parameter fit to the data.Restrictions: HYDJET++ is only applicable for symmetric AA collisions of heavy (A?40) ions at high energies (c.m.s. energy per nucleon pair). The results obtained for very peripheral collisions (with the impact parameter of the order of two nucleus radii, b∼2RA) and very forward rapidities may be not adequate.Additional comments: Accessibility http://cern.ch/lokhtin/hydjet++Running time: The generation of 100 central (0-5%) Au+Au events at (Pb+Pb events at ) with default input parameters takes about 7 (85) minutes on a PC 64 bit Intel Core Duo CPU @ 3 GHz with 8 GB of RAM memory under Red Hat Enterprise.References:[1] I.P. Lokhtin, A.M. Snigirev, Eur. Phys. J. C 46 (2006) 211.[2] N.S. Amelin, R. Lednicky, T.A. Pocheptsov, I.P. Lokhtin, L.V. Malinina, A.M. Snigirev, Iu.A. Karpenko, Yu.M. Sinyukov, Phys. Rev. C 74 (2006) 064901.[3] N.S. Amelin, I. Arsene, L. Bravina, Iu.A. Karpenko, R. Lednicky, I.P. Lokhtin, L.V. Malinina, A.M. Snigirev, Yu.M. Sinyukov, Phys. Rev. C 77 (2008) 014903.     

ExHuME 1.3: A Monte Carlo event generator for exclusive diffraction

We have written the Exclusive Hadronic Monte Carlo Event (ExHuME) generator. ExHuME is based around the perturbative QCD calculation of Khoze, Martin and Ryskin of the process pp→p+X+p, where X is a centrally produced colour singlet system.

Program summary

Title of program:ExHuMECatalogue identifier:ADYA_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYA_v1_0Program obtainable from:CPC Program Library, Queen's University of Belfast, N. IrelandLicensing provisions:NoneProgramming language used:C++, some FORTRANComputer:Any computer with UNIX capability. Users should refer to the README file distributed with the source code for further detailsOperating system:Linux, Mac OS XNo. of lines in distributed program, including test data, etc.:111 145No. of bytes in distributed program, including test data, etc.: 791 085Distribution format:tar.gzRAM:60 MBExternal routines/libraries:LHAPDF [http://durpdg.dur.ac.uk/lhapdf/], CLHEP v1.8 or v1.9 [L. Lönnblad, Comput. Phys. Comm. 84 (1994) 307; http://wwwinfo.cern.ch/asd/lhc++/clhep/]Subprograms used:Pythia [T. Sjostrand et al., Comput. Phys. Comm. 135 (2001) 238], HDECAY [A. Djouadi, J. Kalinowski, M. Spira, HDECAY: A program for Higgs boson decays in the standard model and its supersymmetric extension, Comput. Phys. Comm. 108 (1998) 56, hep-ph/9704448]. Both are distributed with the source codeNature of problem:Central exclusive production offers the opportunity to study particle production in a uniquely clean environment for a hadron collider. This program implements the KMR model [V.A. Khoze, A.D. Martin, M.G. Ryskin, Prospects for New Physics observations in diffractive processes at the LHC and Tevatron, Eur. Phys. J. C 23 (2002) 311, hep-ph/0111078], which is the only fully perturbative model of exclusive production.Solution method:Monte Carlo techniques are used to produce the central exclusive parton level system. Pythia routines are then used to develop a realistic hadronic system.Restrictions:The program is, at present, limited to Higgs, di-gluon and di-quark production. However, in principle it is not difficult to include more.Running time:Approximately 10 minutes for 10000 Higgs events on an Apple 1 GHz G4 PowerPC.     

Optimal Jet Finder

We describe a FORTRAN 77 implementation of the optimal jet definition for identification of jets in hadronic final states of particle collisions. We discuss details of the implementation, explain interface subroutines and provide a usage example. The source code is available from http://www.inr.ac.ru/~ftkachov/projects/jets/.

Program summary

Title of program: Optimal Jet Finder (OJF_014)Catalogue identifier: ADSBProgram Summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSBProgram obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandComputer: Any computer with the FORTRAN 77 compilerTested with: g77/Linux on Intel, Alpha and Sparc; Sun f77/Solaris (thwgs.cern.ch); xlf/AIX (rsplus.cern.ch); MS Fortran PowerStation 4.0/Win98Programming language used: FORTRAN 77Memory required: ∼1 MB (or more, depending on the settings)Number of bytes in distributed program, including examples and test data: 251 463Distribution format: tar gzip fileKeywords: Hadronic jets, jet finding algorithmsNature of physical problem: Analysis of hadronic final states in high energy particle collision experiments often involves identification of hadronic jets. A large number of hadrons detected in the calorimeter is reduced to a few jets by means of a jet finding algorithm. The jets are used in further analysis which would be difficult or impossible when applied directly to the hadrons. Grigoriev et al. [hep-ph/0301185] provide a brief introduction to the subject of jet finding algorithms and a general review of the physics of jets can be found in [Rep. Prog. Phys. 36 (1993) 1067].Method of solution: The software we provide is an implementation of the so-called optimal jet definition (OJD). The theory of OJD was developed by Tkachov [Phys. Rev. Lett. 73 (1994) 2405; 74 (1995) 2618; Int. J. Mod. Phys. A 12 (1997) 5411; 17 (2002) 2783]. The desired jet configuration is obtained as the one that minimizes , a certain function of the input particles and jet configuration.Restrictions on the complexity of the program: The size of the largest data structure the program uses is (maximal number of particles in the input) × (maximal number of jets in the output) × 8 bytes. (For the standard settings <1 MB). Therefore, there is no memory restriction for any conceivable application for which the program was designed.Typical running time: The running time depends strongly on the physical process being analyzed and the parameters used. For the benchmark process we studied, , with the average number of ∼80 particles in the input, the running time was <10−2s on a modest PC (per event with n_tries=1). For a fixed number of jets the complexity of the algorithm grows linearly with the number of particles (cells) in the input, in contrast with other known jet finding algorithms for which this dependence is cubic. The reader is referred to Grigoriev et al. [hep-ph/0301185] for a more detailed discussion of this issue.     

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.     

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.     

AutoDipole - Automated generation of dipole subtraction terms -

We present an automated generation of the subtraction terms for next-to-leading order QCD calculations in the Catani-Seymour dipole formalism. For a given scattering process with n external particles our Mathematica package generates all dipole terms, allowing for both massless and massive dipoles. The numerical evaluation of the subtraction terms proceeds with MadGraph, which provides Fortran code for the necessary scattering amplitudes. Checks of the numerical stability are discussed.

Program summary

Program title: AutoDipoleCatalogue identifier: AEGO_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGO_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.: 138 042No. of bytes in distributed program, including test data, etc.: 1 117 665Distribution format: tar.gzProgramming language: Mathematica and FortranComputer: Computers running Mathematica (version 7.0)Operating system: The package should work on every Linux system supported by Mathematica. Detailed tests have been performed on Scientific Linux as supported by DESY and CERN and on openSUSE and Debian.RAM: Depending on the complexity of the problem, recommended at least 128 MB RAMClassification: 11.5External routines: MadGraph (including HELAS library) available under http://madgraph.hep.uiuc.edu/ or http://madgraph.phys.ucl.ac.be/ or http://madgraph.roma2.infn.it/. A copy of the tar file, MG_ME_SA_V4.4.30, is included in the AutoDipole distribution package.Nature of problem: Computation of next-to-leading order QCD corrections to scattering cross sections, regularization of real emission contributions.Solution method: Catani-Seymour subtraction method for massless and massive partons [1,2]; Numerical evaluation of subtracted matrix elements interfaced to MadGraph [3-5] (stand-alone version) using helicity amplitudes and the HELAS library [6,7] (contained in MadGraph).Restrictions: Limitations of MadGraph are inherited.Running time: Dependent on the complexity of the problem with typical run times of the order of minutes.References:

[1]

S. Catani, M.H. Seymour, Nuclear Phys. B 485 (1997) 291, hep-ph/9605323.

[2]

S. Catani, et al., Nuclear Phys. B 627 (2002) 189, hep-ph/0201036.

[3]

T. Stelzer, W.F. Long, Comput. Phys. Comm. 81 (1994) 357, hep-ph/9401258.

[4]

F. Maltoni, T. Stelzer, JHEP 0302 (2003) 027, hep-ph/0208156.

[5]

J. Alwall, et al., JHEP 0709 (2007) 028, arXiv:0706.2334 [hep-ph].

[6]

K. Hagiwara, H. Murayama, I. Watanabe, Nuclear Phys. B 367 (1991) 257.

[7]

H. Murayama, I. Watanabe, K. Hagiwara, KEK-91-11.

     

f1: a code to compute Appell's F1 hypergeometric function

In this work we present the FORTRAN code to compute the hypergeometric function F₁(α,β₁,β₂,γ,x,y) of Appell. The program can compute the F₁ function for real values of the variables {x,y}, and complex values of the parameters {α,β₁,β₂,γ}. The code uses different strategies to calculate the function according to the ideas outlined in [F.D. Colavecchia et al., Comput. Phys. Comm. 138 (1) (2001) 29].

Program summary

Title of the program: f1Catalogue identifier: ADSJProgram summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSJProgram obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandLicensing provisions: noneComputers: PC compatibles, SGI Origin2∗Operating system under which the program has been tested: Linux, IRIXProgramming language used: Fortran 90Memory required to execute with typical data: 4 kbytesNo. of bits in a word: 32No. of bytes in distributed program, including test data, etc.: 52 325Distribution format: tar gzip fileExternal subprograms used: Numerical Recipes hypgeo [W.H. Press et al., Numerical Recipes in Fortran 77, Cambridge Univ. Press, 1996] or chyp routine of R.C. Forrey [J. Comput. Phys. 137 (1997) 79], rkf45 [L.F. Shampine and H.H. Watts, Rep. SAND76-0585, 1976].Keywords: Numerical methods, special functions, hypergeometric functions, Appell functions, Gauss functionNature of the physical problem: Computing the Appell F₁ function is relevant in atomic collisions and elementary particle physics. It is usually the result of multidimensional integrals involving Coulomb continuum states.Method of solution: The F₁ function has a convergent-series definition for |x|<1 and |y|<1, and several analytic continuations for other regions of the variable space. The code tests the values of the variables and selects one of the precedent cases. In the convergence region the program uses the series definition near the origin of coordinates, and a numerical integration of the third-order differential parametric equation for the F₁ function. Also detects several special cases according to the values of the parameters.Restrictions on the complexity of the problem: The code is restricted to real values of the variables {x,y}. Also, there are some parameter domains that are not covered. These usually imply differences between integer parameters that lead to negative integer arguments of Gamma functions.Typical running time: Depends basically on the variables. The computation of Table 4 of [F.D. Colavecchia et al., Comput. Phys. Comm. 138 (1) (2001) 29] (64 functions) requires approximately 0.33 s in a Athlon 900 MHz processor.