The Horn and the Thermal Model

Cleymans, J.; Oeschler, H.; Redlich, K.; Wheaton, S.

doi:10.1088/1742-6596/50/1/058

Cited by 88 publications

(162 citation statements)

References 7 publications

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“…For very high energy collisions, µ B → 0 and the temperature extracted from a thermal analysis of the data (T ch ∼ 150 − 170 MeV) is found to be very close to the critical (crossover) temperature estimated in lattice QCD, T c ∈ (143, 171) MeV [8]. Despite these observations, the profound meaning of the freeze-out curve [7,9,10,11,12] remains unclear and several key questions remain unanswered:…”

Section: Introductionmentioning

confidence: 70%

Hadron yields and the phase diagram of strongly interacting matter

2014

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Section: Introductionmentioning

confidence: 70%

Hadron yields and the phase diagram of strongly interacting matter

2014

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“…This makes the model a unique tool in the attempt to quantify from the experimental side the features of the phase diagram of hadronic matter [17,18,19]. Recent analyses over a broad energy range [20,21] have contributed in the on-going efforts to understand the chemical freeze-out criteria [1,10,11,22,23,24] in the phase diagram. It has been pointed out within a thermal model analysis that scanning the energy one encounters a transition from baryon-to meson-dominated freeze-out [25], with its associated fingerprint on the characteristics of hadron yields, also evidenced earlier [26].…”

Section: Introductionmentioning

confidence: 99%

Hadron production in central nucleus–nucleus collisions at chemical freeze-out

2006

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We analyze the experimental hadron yield ratios for central nucleus-nucleus collisions in terms of thermal model calculations over a broad energy range, √ s N N =2.7-200 GeV. The fits of the experimental data with the model calculations provide the thermal parameters, temperature and baryo-chemical potential at chemical freezeout. We compare our results with the values obtained in other studies and also investigate more technical aspects such as a potential bias in the fits when fitting particle ratios or yields. Using parametrizations of the temperature and baryonic chemical potential as a function of energy, we compare the model calculations with data for a large variety of hadron yield ratios. We provide quantitative predictions for experiments at LHC energy, as well as for the low RHIC energy of 62.4 GeV. The relation of the determined parameters with the QCD phase boundary is discussed.

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“…The statistical-thermal model has proved extremely successful [1,2,3] in describing the hadron multiplicities observed in relativistic collisions of both heavy-ions and elementary particles. The methods used in calculating these yields have been extensively reviewed in recent years [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…This allows them to be fully integrated into the interactive ROOT environment, allowing all of the ROOT functionality in a statistical-thermal model analysis. 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

307

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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The Horn and the Thermal Model

Cited by 88 publications

References 7 publications

Hadron yields and the phase diagram of strongly interacting matter

Hadron yields and the phase diagram of strongly interacting matter

Hadron production in central nucleus–nucleus collisions at chemical freeze-out

THERMUS—A thermal model package for ROOT

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