Near and Far from Equilibrium Power-Law Statistics

Abstract

We analyze the connection between $p_T$ and multiplicity distributions in a statistical framework. We connect the Tsallis parameters, $T$ and $q$, to physical properties like average energy per particle and the second scaled factorial moment, $F_2=⟨n(n-1)⟩/{⟨n⟩}^2$, measured in multiplicity distributions. Near and far from equilibrium scenarios with master equations for the probability of having $n$ particles, $P_n$, are reviewed based on hadronization transition rates, ${\mu }_n$, from $n$ to $n+1$ particles.

Talk given by T.S.Biro at SQM 2016, Berkeley, 4 pages

References in corpus (2)

• Unified model for network dynamics exhibiting nonextensive statistics
• Statistical Power Law due to Reservoir Fluctuations and the Universal Thermostat Independence Principle

Cited by in corpus (2)

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