Energetic Cost of Statistical Order-Degree Change in a Fermions’ Set
Abstract
:1. Introduction
1.1. Quasi Spin Operators and Exactly Solvable Models
1.2. Goal: Our Route
- The central and well established idea is that fermion-fermion interactions are capable of generating phase transitions (PT) in many-fermions systems. The details of the PT depend on the properties of the extant fermion-fermion interaction.
- We wish to connect phase transitions (or level crossings in a finite system) with changes in the degree of statistical (CDSO) order exhibited by our many fermion system.
- We wish to analyze the fact that CDSO are made at the expense of energy spending.
- We wish to associate a new statistical quantifier to this energy expense.
- We wish to ascertain that this new quantifier is a very good phase transition “detector”.
2. Statistical Order, Disorder, and Disequilibrium
Statistical Order and Disequilibrium Quantifier D
3. Details of the Two Interactions We Are to Confront in This Work
3.1. Present Hamiltonians: (1) Unperturbed , (2) Spin-Flip , and (3) Pairing Ones
3.2. Quasi-Spin Language and the Pairing Operators
3.3. Eigenvalues of H
3.4. Phase Transitions or Level Crossings
4. Statistical Mechanics, Gibbs’ Canonical Ensemble, and H
Scheme of Our Algorithm
- Since our models are analytically solvable, we know the expressions for the exact energies . We also know the temperature T.
- Accordingly, we can construct our probability distribution (PD), whose elements are , with the inverse temperature
- Since we have the we can compute the entropy and the mean energy U, .
- With these quantities we compute the free energy .
- We also know the disequilibrium D, which is a simple function of the , given above in Equation (3).
5. Information Cost (in Free Energy), a New Statistical Quantifier
- If we see increasing statistical order,
- If we see increasing statistical disorder.
The Conjugate Extensive Counterpart of
6. Results Obtained with Our New Quantifier at Finite Temperature T
6.1. Detects the Superconductivity Transition: versus G Plots
6.2. Detects the Spin-Flip Transition: versus V Plots
6.3. The Statistical Extensive Measure F
6.4. Three Dimensional Graphs
7. Conclusions
Author Contributions
Funding
Conflicts of Interest
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Pennini, F.; Plastino, A.; Ferri, G.L.; Plastino, A.R. Energetic Cost of Statistical Order-Degree Change in a Fermions’ Set. Entropy 2022, 24, 752. https://doi.org/10.3390/e24060752
Pennini F, Plastino A, Ferri GL, Plastino AR. Energetic Cost of Statistical Order-Degree Change in a Fermions’ Set. Entropy. 2022; 24(6):752. https://doi.org/10.3390/e24060752
Chicago/Turabian StylePennini, Flavia, Angelo Plastino, Gustavo Luis Ferri, and Angel Ricardo Plastino. 2022. "Energetic Cost of Statistical Order-Degree Change in a Fermions’ Set" Entropy 24, no. 6: 752. https://doi.org/10.3390/e24060752
APA StylePennini, F., Plastino, A., Ferri, G. L., & Plastino, A. R. (2022). Energetic Cost of Statistical Order-Degree Change in a Fermions’ Set. Entropy, 24(6), 752. https://doi.org/10.3390/e24060752