1998
DOI: 10.1103/physrevlett.81.770
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Z-Dependent Barriers in Multifragmentation from Poissonian Reducibility and Thermal Scaling

Abstract: We explore the natural limit of binomial reducibility in nuclear multifragmentation by constructing excitation functions for intermediate mass fragments (IMF) of a given element Z. The resulting multiplicity distributions for each window of transverse energy are Poissonian. Thermal scaling is observed in the linear Arrhenius plots made from the average multiplicity of each element. "Emission barriers" are extracted from the slopes of the Arrhenius plots and their possible origin is discussed.

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Cited by 18 publications
(56 citation statements)
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“…We now proceed to analyze the Monte Carlo results in the same way as has been done with nuclear multifragmentation data [28,29,30]. We shall consider first whether the multiplicity distributions for individual fragments manifest Poissonian reducibility.…”
Section: The Three-dimensional Ising Model: a Paradigm Of Liquid-vapomentioning
confidence: 99%
See 3 more Smart Citations
“…We now proceed to analyze the Monte Carlo results in the same way as has been done with nuclear multifragmentation data [28,29,30]. We shall consider first whether the multiplicity distributions for individual fragments manifest Poissonian reducibility.…”
Section: The Three-dimensional Ising Model: a Paradigm Of Liquid-vapomentioning
confidence: 99%
“…This property can occur only if fragments are created independently from one another and it coincides with stochasticity. Both binomial, and its limiting form, Poissonian reducibilities have been extensively documented experimentally for nuclear multifragmentation [28,29,30].…”
Section: The Three-dimensional Ising Model: a Paradigm Of Liquid-vapomentioning
confidence: 99%
See 2 more Smart Citations
“…In previous studies, the concepts of thermalization and reducibility have been introduced to describe the cluster yields of nuclear reactions [2]. Even though the actual physics behind these nuclear collisions are complex, only a small number of parameters are needed to characterize the process.…”
Section: Introductionmentioning
confidence: 99%