THERMUS—A thermal model package for ROOT Wheaton, S.; Cleymans, J.; Hauer, M.
Computer physics communications,
2009, 2009-1-00, Letnik:
180, Številka:
1
Journal Article
Recenzirano
Odprti dostop
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 title: THERMUS, version 2.1
Catalogue identifier: AEBW_v1_0
Program summary URL:
http://cpc.cs.qub.ac.uk/summaries/AEBW_v1_0.html
Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland
Licensing provisions: Standard CPC licence,
http://cpc.cs.qub.ac.uk/licence/licence.html
No. of lines in distributed program, including test data, etc.: 17 152
No. of bytes in distributed program, including test data, etc.: 93 581
Distribution format: tar.gz
Programming language: C++
Computer: PC, Pentium 4, 1 GB RAM (not hardware dependent)
Operating system: Linux: FEDORA, RedHat, etc.
Classification: 17.7
External 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
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 (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
χ
2
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.
To date, projections of human migration induced by sea-level change (SLC) largely suggest large-scale displacement away from vulnerable coastlines. However, results from our model of Bangladesh ...suggest counterintuitively that people will continue to migrate toward the vulnerable coastline irrespective of the flooding amplified by future SLC under all emissions scenarios until the end of this century. We developed an empirically calibrated agent-based model of household migration decision-making that captures the multi-faceted push, pull and mooring influences on migration at a household scale. We then exposed ∼4800 000 simulated migrants to 871 scenarios of projected 21st-century coastal flooding under future emissions pathways. Our model does not predict flooding impacts great enough to drive populations away from coastlines in any of the scenarios. One reason is that while flooding does accelerate a transition from agricultural to non-agricultural income opportunities, livelihood alternatives are most abundant in coastal cities. At the same time, some coastal populations are unable to migrate, as flood losses accumulate and reduce the set of livelihood alternatives (so-called 'trapped' populations). However, even when we increased access to credit, a commonly-proposed policy lever for incentivizing migration in the face of climate risk, we found that the number of immobile agents actually rose. These findings imply that instead of a straightforward relationship between displacement and migration, projections need to consider the multiple constraints on, and preferences for, mobility. Our model demonstrates that decision-makers seeking to affect migration outcomes around SLC would do well to consider individual-level adaptive behaviors and motivations that evolve through time, as well as the potential for unintended behavioral responses.
This report provides a review of early and late effects of radiation in normal tissues and organs with respect to radiation protection. It was instigated following a recommendation in Publication 103 ...(ICRP, 2007), and it provides updated estimates of ‘practical’ threshold doses for tissue injury defined at the level of 1% incidence. Estimates are given for morbidity and mortality endpoints in all organ systems following acute, fractionated, or chronic exposure. The organ systems comprise the haematopoietic, immune, reproductive, circulatory, respiratory, musculoskeletal, endocrine, and nervous systems; the digestive and urinary tracts; the skin; and the eye.
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Radiotherapy of thoracic and chest wall tumors, if all or part of the heart was included in the radiation field, can lead to radiation-induced heart disease (RIHD), a late and potentially severe side ...effect. RIHD presents clinically several years after irradiation and manifestations include accelerated atherosclerosis, pericardial and myocardial fibrosis, conduction abnormalities, and injury to cardiac valves. The pathogenesis of RIHD is largely unknown, and a treatment is not available. Hence, ongoing pre-clinical studies aim to elucidate molecular and cellular mechanisms of RIHD. Here, an overview of recent pre-clinical studies is given, and based on the results of these studies, potential targets for intervention in RIHD are discussed.
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