Statistical signatures of critical behavior in small systems

Elliott, J. B.; Albergo, S.; Bieser, F.; Brady, F. P.; Caccia, Z.; Cebra, D.; Chacon, A. D.; Chance, J. L.; Choi, Y.; Costa, S.; Gilkes, M. L.; Hauger, J. A.; Hirsch, A.; Hjort, E.; Insolia, A.; Justice, M.; Keane, D.; Kintner, J. C.; Lindenstruth, V.; Lisa, M. A.; Matis, H. S.; McMahan, M. A.; McParland, C.; Müller, W. F. J.; Olson, D.; Partlan, M. D.; Porile, N.; Potenza, R.; Rai, G.; Rasmussen, J. O.; Ritter, H. G.; Romański, J.; Romero, J. L.; Russo, G.; Sann, H.; Scharenberg, R. P.; Scott, A.; Shao, Y.; Srivastava, B.; Symons, T. J. M.; Tincknell, M.; Tuvé, C.; Wang, S.; Warren, P.; Wieman, H.; Wienold, T.; Wolf, K.

doi:10.1103/physrevc.62.064603

Cited by 52 publications

(68 citation statements)

References 96 publications

(142 reference statements)

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“…, (n − 1). Our algorithm of random partitioning differs from that of the EOS one [35] in the sense that we considered the charge of the remnant part of the projectile nucleus as the charge of the fragmenting system, not the total charge of the projectile. Our technique rests on the random selection of total charge of the fragmenting system from a uniform distribution of (1, Z proj ), while EOS's technique relies on the random selection on (1, Z proj ) of multiplicity in which the incident projectile will disintegrate.…”

Section: Resultsmentioning

confidence: 99%

“…We started our analysis by formulating a 'toy model' of nuclear multi-fragmentation that is different from the EOS Collaboration [35] and is based on the following algorithm: first the total charge Q PF of a fragmenting system is determined randomly from 36 total system constituents which is the charge of the projectile for present investigation. The number of prompt protons emitted from a particular event is then considered as N prompt = 36 − Q PF .…”

Section: Resultsmentioning

confidence: 99%

“…It is also known that the most readily observed fluctuations in the cluster distribution are those in the size of the largest cluster [35,50,56]. In Fig.…”

Section: Fluctuations In Z Maxmentioning

confidence: 94%

“…Moreover, Elliott et al (EOS Collaboration) [35] have shown that out of several techniques adopted by different workers in estimating percolation exponents, only a few of these may serve as true sensitive tools to study the criticality. From a study of 1A GeV Au-C data and its comparison with two theoretical models, such as one that undergoes phase transition and the other that does not, they categorized the traditional signals of critical behavior into a number of insensitive and sensitive tools.…”

Section: Introductionmentioning

confidence: 99%

“…In an attempt to get the signatures of critical behavior in the case of break up of nuclei, several workers have analyzed their experimental data on various systems at different energies [2,[29][30][31][33][34][35][36][37][38][39][40][41]. The experimentally evaluated values of σ , β, τ and γ are then compared with the values obtained for different three-dimensional known systems exhibiting critical behavior.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Evidence of phase transition in the break up of Kr-projectile nuclei at 0.95A GeV

Bhattacharjee

Debnath

2009

Nuclear Physics A

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…It is also known that the most readily observed fluctuations in the cluster distribution are those in the size of the largest cluster [35,50,56]. In Fig.…”

Section: Fluctuations In Z Maxmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Evidence of phase transition in the break up of Kr-projectile nuclei at 0.95A GeV

Bhattacharjee

Debnath

2009

Nuclear Physics A

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Fluctuations of fragment observables

Gulminelli

D’Agostino

Dynamics and Thermodynamics With Nuclear Degrees of Freedom

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Abstract. This contribution presents a review of our present theoretical as well as experimental knowledge of different fluctuation observables relevant to nuclear multifragmentation. The possible connection between the presence of a fluctuation peak and the occurrence of a phase transition or a critical phenomenon is critically analyzed. Many different phenomena can lead both to the creation and to the suppression of a fluctuation peak. In particular, the role of constraints due to conservation laws and to data sorting is shown to be essential. From the experimental point of view, a comparison of the available fragmentation data reveals that there is a good agreement between different data sets of basic fluctuation observables, if the fragmenting source is of comparable size. This compatibility suggests that the fragmentation process is largely independent of the reaction mechanism (central versus peripheral collisions, symmetric versus asymmetric systems, light ions versus heavy ion induced reactions). Configurational energy fluctuations, that may give important information on the heat capacity of the fragmenting system at the freeze out stage, are not fully compatible among different data sets and require further analysis to properly account for Coulomb effects and secondary decays. Some basic theoretical questions, concerning the interplay between the dynamics of the collision and the fragmentation process, and the cluster definition in dense and hot media, are still open and are addressed at the end of the paper. A comparison with realistic models and/or a quantitative analysis of the fluctuation properties will be needed to clarify in the next future the nature of the transition observed from compound nucleus evaporation to multi-fragment production. Fluctuations and phase transitionsSince the first inclusive heavy ion experiments, multifragmentation has been tentatively associated to a phase transition or a critical phenomenon. This expectation was triggered by the first pioneering theoretical studies of the nuclear phase diagram [1] which contains a coexistence region delimited, at each temperature below an upper critical value, by two critical points at different asymmetries [2,3].Even more important, the first exclusive multifragmentation studies have shown that multifragmentation is a threshold process occurring at a relatively well defined deposited energy [4,5,6,7]. The wide variation of possible fragment partitions naturally leads to important fluctuations of the associated partition sizes and energies.Different observables have been proposed to measure such fluctuations. Using the general definition of the n−th moment asthe variance of the charge distribution is measured by the second moment M 2 or by the normalized quantity[8]:The root mean square fluctuation per particleof the distribution of the largest fragment Z m detected in each event completes the information. We will also consider the total fluctuationand the fluctuationof the configurational energy per particle associated to each fragme...

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Liquid-gas phase transition in hot nuclei studied with INDRA

et al. 2004

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Thanks to the high detection quality of the INDRA array, signatures related to the dynamics (spinodal decomposition) and thermodynamics (negative microcanonical heat capacity) of a liquid-gas phase transition have been simultaneously studied in multifragmentation events in the Fermi energy domain. The correlation between both types of signals strongly supports the existence of a first order phase transition for hot nuclei.Comment: 9 pages, 2 figures, Invited talk to Nucleus-nucleus 2003 Moscow June 200

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Statistical signatures of critical behavior in small systems

Cited by 52 publications

References 96 publications

Evidence of phase transition in the break up of Kr-projectile nuclei at 0.95A GeV

Evidence of phase transition in the break up of Kr-projectile nuclei at 0.95A GeV

Fluctuations of fragment observables

Liquid-gas phase transition in hot nuclei studied with INDRA

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