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20122023
most citedConsensus in the Age of Blockchains

187 citations · 356 across the 35 of their papers we have counts for

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cond-mat.stat-mech2015★ 4 cited

Minimum Dissipation Principle in Nonlinear Transport

Giorgio Sonnino, Jarah Evslin, Alberto Sonnino

We extend Onsager's minimum dissipation principle to stationary states that are only subject to local equilibrium constraints, even when the transport coefficients depend on the th…

cond-mat.stat-mech2014★ 2 cited

Stationary distribution functions for Tokamak-plasmas in the weak-collisional transport regime by MaxEnt principle

Giorgio Sonnino, Philippe Peeters, Alberto Sonnino +2

In previous works, we derived stationary density distribution functions (DDF) where the local equilibrium is determined by imposing the maximum entropy (MaxEnt) principle, under th…

cond-mat.stat-mech2013★ 2 cited

Reference Distribution Functions for Magnetically Confined Plasmas from the Minimum Entropy Production Theorem and the MaxEnt Principle, subject to the Scale-Invariant Restrictions

Giorgio Sonnino, Alessandro Cardinali, Gyorgy Steinbrecher +3

We derive the expression of the reference distribution function for magnetically confined plasmas far from the thermodynamic equilibrium. The local equilibrium state is fixed by im…

cond-mat.stat-mech2013★ 2 cited

Derivation of Reference Distribution Functions for Tokamak-plasmas by Statistical Thermodynamics

Giorgio Sonnino, Alessandro Cardinali, Philippe Peeters +2

A general approach for deriving the expression of reference distribution functions by statistical thermodynamics is illustrated, and applied to the case of a magnetically confined…

cond-mat.stat-mech2012★ 4 cited

Family of Probability Distributions Derived from Maximal Entropy Principle with Scale Invariant Restrictions

Giorgio Sonnino, György Steinbrecher, Alessandro Cardinali +2

Using statistical thermodynamics, we derive a general expression of the stationary probability distribution for thermodynamic systems driven out of equilibrium by several thermodyn…