Multiplicity fluctuations in relativistic nuclear collisions: Statistical model versus experimental data

“…Recent applications of THERMUS include [2,10,11,12,13,14,15,16,17,18,19]. An on-going effort to extend the range of applications of THERMUS has led to several publications on fluctuations in statistical models [20,21,22].…”

Section: Introductionmentioning

confidence: 99%

THERMUS—A thermal model package for ROOT

Wheaton

Cleymans

Hauer

2009

Computer Physics Communications

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306

289

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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 mixedcanonical ensemble combining a canonical treatment of strangeness with a grandcanonical 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. 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 thermalised 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 utilises 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 utilisation of CINT as the control language, which allows interactive 2 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 K * 4 (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...

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“…Let us again first attend to fully phase space integrated multiplicity fluctuations discussed in Refs. [30,31]. The final state scaled variance increases in the GCE and CE compared to the primordial scaled variance.…”

Section: Final Statementioning

confidence: 94%

“…(54)- (56) are equivalent to the "acceptance scaling" approximation 4 used in Refs. [29][30][31]. For the correlation …”

Section: Extrapolating Fully Phase Space Integrated Quantities Tomentioning

confidence: 99%

Statistical ensembles with finite bath: A description for an event generator

Hauer

Wheaton

2009

Phys. Rev. C

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A Monte Carlo event generator has been developed assuming thermal production of hadrons. The system under consideration is sampled grand canonically in the Boltzmann approximation. A reweighting scheme is then introduced to account for conservation of charges (baryon number, strangeness, electric charge) and energy and momentum, effectively allowing for extrapolation of grand canonical results to the microcanonical limit. This method has two strong advantages compared to analytical approaches and standard microcanonical Monte Carlo techniques in that it is capable of handling resonance decays as well as (very) large system sizes.

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Multiplicity fluctuations in relativistic nuclear collisions: Statistical model versus experimental data

Cited by 78 publications

References 47 publications

Strongly intensive measures for multiplicity fluctuations

Strongly intensive measures for multiplicity fluctuations

THERMUS—A thermal model package for ROOT

Statistical ensembles with finite bath: A description for an event generator

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