Skip to main content
Log in

Dual interpretations of the nonextensive statistical thermodynamics with parameter transformation

  • Regular Article
  • Published:
The European Physical Journal Plus Aims and scope Submit manuscript

Abstract

In complex systems, due to the invalidity of ergodic property, the time average of observable quantity is not equivalent to its ensemble average, and then, the latter is nonmeasurable. In order to find measurable quantities, the prior probability is introduced, estimated in original Euclidean phase-space with the ergodicity. The prior probability is associated with the ensemble probability through two manners, by, respectively, evoking the second and third choices of energy constraints. Two different ensemble probabilities are inferred through maximum entropy procedure, of which one is predictable and another is not. It can be verified that these two probabilities are equivalent to each other. With the equivalence, the third energy is directly measurable while the second one is indirectly measurable. By doing this, a consistent formalism of statistical thermodynamics is then established, which consists of dual interpretations of ensemble probability and dual Legendre transformations. Lastly, the independence of prior probability leads to an interesting composition law for entropy and energy, with different parameters and even interactions, in which case the ordinary thermodynamic method is verified to be valid.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. C. Tsallis, J. Stat. Phys. 52, 479 (1988)

    ADS  Google Scholar 

  2. A. Adare et al., Phys. Rev. D 83, 052004 (2011)

    ADS  Google Scholar 

  3. R.M. Pickup, R. Cywinski et al., Phys. Rev. Lett. 102, 097202 (2009)

    ADS  Google Scholar 

  4. E. Lutz, F. Renzoni, Nat. Phys. 9, 615 (2013)

    Google Scholar 

  5. R.G. DeVoe, Phys. Rev. Lett. 102, 063001 (2009)

    ADS  Google Scholar 

  6. Z. Huang, G. Su, A. El Kaabouchi, Q.A. Wang, J. Chen, J. Stat. Mech. 2010, L05001 (2010)

    Google Scholar 

  7. J. Prehl, C. Essex, K.H. Hoffman, Entropy 14, 701 (2012)

    ADS  Google Scholar 

  8. J. Du, Phys. Lett. A 329, 262 (2004)

    ADS  Google Scholar 

  9. L. Liu, J. Du, Phys. A 387, 4821 (2008)

    Google Scholar 

  10. H. Yu, J. Du, Ann. Phys. 350, 302 (2014)

    ADS  Google Scholar 

  11. T. Oikonomou, A. Provata, U. Tirnakli, Phys. A 387, 2653 (2008)

    Google Scholar 

  12. O.J. Rolinski, A. Martin, D.J.S. Birch, Ann. N. Y. Acad. Sci. 1130, 314 (2008)

    ADS  Google Scholar 

  13. K. Eftaxias, G. Minadakis, S.M. Potirakis et al., Phys. A 392, 497 (2013)

    Google Scholar 

  14. E.M.F. Curado, C. Tsallis, J. Phys. A 24, L69 (1991)

    ADS  Google Scholar 

  15. C. Tsallis, R.S. Mendes, A.R. Plastino, Phys. A 261, 534 (1998)

    Google Scholar 

  16. S. Martınez, F. Nicolás, F. Pennini et al., Phys. A 286, 489 (2000)

    MathSciNet  Google Scholar 

  17. G.L. Ferri, S. Martinez, A. Plastino, J. Stat. Mech. Theory Exp. 2005, P04009 (2005)

    Google Scholar 

  18. K.-M. Shen, B.-W. Zhang, E.-K. Wang, Phys. A 487, 215 (2017)

    MathSciNet  Google Scholar 

  19. Y. Zheng, J. Du, Contin. Mech. Thermodyn.: CMT 28, 1791 (2016)

    ADS  Google Scholar 

  20. M. Nauenberg, Phys. Rev. E 67(3), 036114 (2003)

    ADS  Google Scholar 

  21. M. Nauenberg, Phys. Rev. E 69(3), 038102 (2004)

    ADS  Google Scholar 

  22. S. Abe, S. Martınez, F. Pennini et al., Phys. Lett. A 281, 126 (2001)

    ADS  Google Scholar 

  23. S. Abe, Phys. A 368, 430 (2006)

    MathSciNet  Google Scholar 

  24. Q.A. Wang, A. Le Méhauté, Chaos Solitons Fractals 15, 537 (2003)

    ADS  Google Scholar 

  25. Q.A. Wang, Chaos Solitons Fractals 12, 1431 (2001)

    ADS  MathSciNet  Google Scholar 

  26. Y. Zheng, H. Yu, J. Du, Contin. Mech. Thermodyn. 31(5), 1503 (2019)

    ADS  MathSciNet  Google Scholar 

  27. Y. Zheng, X. Liu, X. Zhang et al., Phys. A 527, 121304 (2019)

    MathSciNet  Google Scholar 

  28. Y. Zheng, J. Du, L. Liu et al., Eur. Phys. J. Plus 134(6), 309 (2019)

    Google Scholar 

  29. F. Jackson, Mess. Math. 38, 57–60 (1909)

    Google Scholar 

  30. S. Abe, Phys. Lett. A 224, 326–329 (1997)

    ADS  MathSciNet  Google Scholar 

  31. Y. Zheng, J.L. Du, Int. J. Mod. Phys. B 21(6), 947 (2007)

    ADS  Google Scholar 

  32. Y. Zheng, J. Du, Europhys. Lett.: EPL 107(6), 60001 (2014)

    ADS  Google Scholar 

  33. A. Lavagno, G. Kaniadakis, M. Rego-Monteiro, et al. (1996). arXiv:astro-ph/9607147

  34. W.M. Alberico, A. Lavagno, Eur. Phys. J. A 40(3), 313 (2009)

    ADS  Google Scholar 

  35. S. Tripathy, T. Bhattacharyya, P. Garg et al., Eur. Phys. J. A 52(9), 289 (2016)

    ADS  Google Scholar 

  36. G. Livadiotis, D.J. McComas, Astrophys. J. 741(2), 88 (2011)

    ADS  Google Scholar 

  37. P.H. Yoon, J. Geophys. Res. Space Phys. 119(9), 7074–7087 (2014)

    ADS  Google Scholar 

  38. G. Livadiotis, J. Geophys. Res. Space Phys. 120(2), 880–903 (2015)

    ADS  Google Scholar 

  39. L. Telesca, Tectonophysics 494(1–2), 155–162 (2010)

    ADS  Google Scholar 

  40. S. Thurner, F. Kyriakopoulos, C. Tsallis, Phys. Rev. E 76(3), 036111 (2007)

    ADS  Google Scholar 

  41. G. Wilk, Z. Włodarczyk, Phys. Rev. Lett. 84(13), 2770 (2000)

    ADS  Google Scholar 

  42. F. Vallianatos, Nat. Hazards Earth Syst. Sci. 9, 1 (2009)

    Google Scholar 

  43. Q.A. Wang, L. Nivanen, A. Le Mehaute et al., Europhys. Lett.: EPL 65, 606 (2004)

    ADS  Google Scholar 

  44. Y. Zheng, J. Du, Phys. A 420, 41–48 (2015)

    ADS  MathSciNet  Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China under Grant No. 11405092, and also by National Natural Science Foundation of China under Grant No. 11775156.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yahui Zheng.

Appendices

Appendix

In order to improve the (78), let us rewrite down the distribution (25), namely,

$$\begin{aligned} p_{i} =\frac{1}{\bar{{Z}}_{q}^{(3)} }\left[ {1-(1-q){\beta }'(E_{i} -U_{q}^{(3)} )} \right] ^{\frac{1}{1-q}}. \end{aligned}$$
(A.1)

In light of (36), in limit of large particle number, there is \(q\rightarrow 1\); therefore, according to(73) one has the approximate relation

$$\begin{aligned} p_{ij} \simeq p_{i} p_{j}. \end{aligned}$$
(A.2)

Let (A.2)/(73), we have

$$\begin{aligned} (p_{ij} )^{1-q}=(p_{i} )^{1-q_{1} }(p_{j} )^{1-q_{2} }. \end{aligned}$$
(A.3)

In views of the probability (A.1), (29) and the following relation

$$\begin{aligned} c_{q,(1,2)} =c_{q_{1} } c_{q_{2} } , \end{aligned}$$
(A.4)

we have

$$\begin{aligned}&\left[ {1-(1-q){\beta }'(1,2)(E_{ij} -U_{q,(1,2)}^{(3)} )} \right] \nonumber \\&\quad =\left[ {1-(1-q_{1} ){\beta }'(1)(E_{i} -U_{q_{1} ,1}^{(3)} )} \right] \left[ {1-(1-q_{2} ){\beta }'(2)(E_{j} -U_{q_{2} ,2}^{(3)} )} \right] . \end{aligned}$$
(A.5)

With the supposed equilibrium condition,

$$\begin{aligned} {\beta }'(1,2)={\beta }'(1)={\beta }'(2), \end{aligned}$$
(A.6)

we can get simultaneously from (A.5)

$$\begin{aligned} U_{q,(1,2)}^{(3)} =\frac{1-q_{1} }{1-q}U_{q_{1} ,1}^{(3)} +\frac{1-q_{2} }{1-q}U_{q_{2} ,2}^{(3)} , \end{aligned}$$
(A.7)

and

$$\begin{aligned} E_{ij} =\frac{1-q_{1} }{1-q}E_{i} +\frac{1-q_{2} }{1-q}E_{j} +\frac{(1-q_{1} )(1-q_{2} )}{1-q}{\beta }'(E_{i} -U_{q_{1} ,1}^{(3)} )(E_{j} -U_{q_{2} ,2}^{(3)} ).\quad \quad \end{aligned}$$
(A.8)

It can be easily found that the averaged value of (A.8) in the representation of (17) is just the (A.7). Then the (78) is verified. Apparently the deduced equilibrium condition (80) is consistent with the assumption (A.6).

Appendix

In order to improve the (86), let us rewrite down the distribution (19), namely

$$\begin{aligned} p_{i} =\frac{1}{Z_{q}^{(2)} }\left[ {1-(1-q){\beta }'E_{i} } \right] ^{\frac{1}{1-q}}. \end{aligned}$$
(B.1)

Similar to (A.3), we have

$$\begin{aligned} (p_{ij} )^{1-q}=(p_{i} )^{1-q_{1} }(p_{j} )^{1-q_{2} }. \end{aligned}$$
(B.2)

That is

$$\begin{aligned} \frac{\left[ {1-(1-q){\beta }'(1,2)E_{ij} } \right] }{[Z_{q,(1,2)}^{(2)} ]^{1-q}}=\frac{\left[ {1-(1-q_{1} ){\beta }'(1)E_{i} } \right] }{[Z_{q_{1} ,1}^{(2)} ]^{1-q_{1} }}\frac{\left[ {1-(1-q_{2} ){\beta }'(2)E_{j} } \right] }{[Z_{q_{2} ,2}^{(2)} ]^{1-q_{2} }}. \end{aligned}$$
(B.3)

In limit of large particle number, the ensemble partition function could be written as

$$\begin{aligned} Z_{q}^{(2)} =Z_{1}^{N}, \end{aligned}$$
(B.4)

where the \(Z_{\mathrm {1}}\) is single particle partition function defined in the molecular dynamics [28], which is approximately irrelevant of the nonextensive parameter.

So according to the rule (74), we have

$$\begin{aligned} {[Z_{q,(1,2)}^{(2)} ]}^{1-q}=[Z_{q_{1} ,1}^{(2)} ]^{1-q_{1} }[Z_{q_{2} ,2}^{(2)} ]^{1-q_{2} }, \end{aligned}$$
(B.5)

which, with the same equilibrium condition (A.6), leads to

$$\begin{aligned} E_{ij} =\frac{1-q_{1} }{1-q}E_{i} +\frac{1-q_{2} }{1-q}E_{j} -\frac{(1-q_{1} )(1-q_{2} )}{(1-q)}{\beta }'E_{i} E_{j}. \end{aligned}$$
(B.6)

Then, in the representation of (16), one can obtain

$$\begin{aligned} U_{q,(1,2)}^{(2)} =\frac{1-q_{1} }{1-q}c_{q_{2} } U_{q_{1} ,1}^{(2)} +\frac{1-q_{2} }{1-q}c_{q_{1} } U_{q_{2} ,2}^{(2)} -\frac{(1-q_{1} )(1-q_{2} )}{(1-q)}{\beta }'U_{q_{1} ,1}^{(2)} U_{q_{2} ,2}^{(2)}. \end{aligned}$$
(B.7)

The (86) is proved then.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zheng, Y. Dual interpretations of the nonextensive statistical thermodynamics with parameter transformation. Eur. Phys. J. Plus 135, 359 (2020). https://doi.org/10.1140/epjp/s13360-020-00363-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1140/epjp/s13360-020-00363-2

Navigation