Skip to main content
Log in

Legendre duality: from thermodynamics to information geometry

  • Survey Paper
  • Published:
Information Geometry Aims and scope Submit manuscript

Abstract

This paper reviews the role of convex duality in Information Geometry. It clarifies the notion of bi-orthogonal coordinates associated with Legendre duality by treating its two underlying aspects separately: as a dual coordinate system and as a bi-orthogonal frame. It addresses the deformation of exponential families in a way that stills preserves the dually-flat geometry of 1- and (-1)-connections. The deformation involves a metric which generalizes the Fisher–Rao metric controlled by one degree of freedom and a pair of connections controlled by an additional degree of freedom.

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

Data Availability

Data sharing is not applicable to this article as no data sets were generated or analyzed during the current study.

References

  1. Amari, S.: Differential geometry of curved exponential families–curvatures and information loss. Ann Stat. 10(2), 357–385 (1982)

    Article  MathSciNet  Google Scholar 

  2. Amari, S.: Differential-Geometrical Methods in Statistics, Lecture Notes in Statistics, vol. 28. Springer, New York, Berlin (1985)

    Google Scholar 

  3. Amari, S., Nagaoka, H.: Methods of Information Geometry, Translations of Mathematical Monographs, vol. 191. Oxford University Press, Oxford (2000)

    Google Scholar 

  4. Ay, N., Jost, J., Vân Lê, H., Schwachhöfer, L.: Inform. Geom. Springer, Berlin (2017)

    Book  Google Scholar 

  5. Ballian, R.: François Massieu et les potentiels thermodynamiques, Inst. France Acad. Sci. (2015)

  6. Bratteli, O., Robinson, D.W.: Operator algebras and Quantum Statistical Mechanics I. Springer, Berlin (1979)

    Book  Google Scholar 

  7. Bregman, L.M.: The relaxation method of finding a common point of convex sets and its application to the solution of problems in convex programming. USSR Comp. Math. Math. Phys. 7, 200–217 (1967)

    Article  MathSciNet  Google Scholar 

  8. Callen, H.B.: Thermodynamics and an introduction to thermostatistics, 2nd edn. Wiley, Hoboken (1985)

    Google Scholar 

  9. Ciaglia, F.M., Di Cosmo, F., González-Bravo, L.: Can Čencov meet Petz, In: Nielsen, F., Barbaresco, F. (eds.), Geometric Science of Information, LNCS 14072, Springer, pp. 363–371 (2023)

  10. Ciaglia, F.M., Di Nocera, F., Jost, J., Schwachhöfer, L.: Parametric models and information geometry on \(W^*\)-algebras. Info. Geo. (2023). https://doi.org/10.1007/s41884-022-00094-6

    Article  MathSciNet  Google Scholar 

  11. Eguchi, S.: Information geometry and statistical pattern recognition, Sugaku Expositions. Am. Math. Soc. 19, 197–216 (2006)

    Google Scholar 

  12. Gibbs, J.W.: Elementary principles in statistical mechanics. Dover, New York (1960). (Reprint)

    Google Scholar 

  13. Jaynes, E.T.: Information theory and statistical mechanics. II. Phys. Rev. 108, 171–190 (1957)

    Article  ADS  MathSciNet  Google Scholar 

  14. Jaynes, E.T.: Papers on probability, statistics and statistical physics, ed. R.D. Rosenkrantz, Kluwer (1989)

  15. Montrucchio, L., Pistone, G.: Deformed exponential bundle: the linear growth case. In: Nielsen, F., Barbaresco, F. (eds.), Geometric Science of Information, GSI 2017 LNCS proceedings, Springer, pp. 239–246 (2017)

  16. Naudts, J.: Estimators, escort probabilities, and phi-exponential families in statistical physics. J. Ineq. Pure Appl. Math. 5, 102 (2004)

    Google Scholar 

  17. Naudts, J.: Generalised Thermostatistics. Springer, Berlin (2011)

    Book  Google Scholar 

  18. Naudts, J.: Quantum Statistical Manifolds. Entropy 20, 472 (2018). (correction Entropy 20, 796 (2018))

    Article  ADS  MathSciNet  PubMed  PubMed Central  Google Scholar 

  19. Naudts, J.: Quantum statistical manifold: the linear growth case. Rep. Math. Phys. 84, 151–169 (2019)

    Article  MathSciNet  Google Scholar 

  20. Naudts, J.: Exponential arcs in the manifold of vector states on a \(\sigma \)-finite von Neumann algebra. Inf. Geom. 5, 1–30 (2022)

    Article  MathSciNet  Google Scholar 

  21. Naudts, J.: Exponential arcs in manifolds of quantum states. Front. Phys. 11, 1042257 (2023). https://doi.org/10.3389/fphy.2023.1042257

    Article  Google Scholar 

  22. Naudts, J., Zhang, J.: Information geometry under monotone embedding. Part II: Geometry. In: Nielsen, F., Barbaresco, F. (eds.), Geometric Science of Information, GSI 2017 LNCS proceedings, Springer, pp. 215–222 (2017)

  23. Naudts, J., Zhang, J.: Rho-tau embedding and gauge freedom in information geometry. Inform. Geom. 1(1), 79–115 (2018)

    Article  MathSciNet  Google Scholar 

  24. Newton, N.J.: An infinite-dimensional statistical manifold modeled on Hilbert space. J. Funct. Anal. 263, 1661–1681 (2012)

    Article  MathSciNet  Google Scholar 

  25. Pistone, G.: Nonparametric Information Geometry. In: Nielsen, F., Barbaresco, F. (eds.) Geometric Science of Information, pp. 5–36. Springer, Berlin (2013)

    Chapter  Google Scholar 

  26. Pistone, G., Sempi, C.: An infinite-dimensional structure on the space of all the probability measures equivalent to a given one. Ann. Stat. 23, 1543–1561 (1995)

    Article  MathSciNet  Google Scholar 

  27. Ruelle, D.: Statistical Mechanics, Rigorous Results. W.A. Benjamin Inc, New York (1969)

    Google Scholar 

  28. Ruppeiner, G.: Thermodynamics: a Riemannian geometric model. Phys. Rev. A 20, 1608–1613 (1979)

    Article  ADS  CAS  Google Scholar 

  29. Tsallis, C.: Possible generalization of Boltzmann–Gibbs statistics. J. Stat. Phys. 52, 479–487 (1988)

    Article  ADS  MathSciNet  Google Scholar 

  30. Tsallis, C.: What are the numbers that experiments provide? Quimica Nova 17, 468 (1994)

    CAS  Google Scholar 

  31. Weinhold, F.: Metric geometry of equilibrium thermodynamics. J. Chem. Phys. 63, 2479–2483 (1975)

    Article  ADS  MathSciNet  CAS  Google Scholar 

  32. Wong, T.K.L., Yang, J.: Logarithmic divergences: geometry and interpretation of curvature. In: Nielsen, F., Barbaresco, F. (eds.) Geometric Science of Information, pp. 413–422. Springer, Berlin (2019)

    Chapter  Google Scholar 

  33. Zhang, J.: Divergence function, duality, and convex analysis. Neural Comput. 16, 159–195 (2004)

    Article  PubMed  Google Scholar 

  34. Zhang, J.: Nonparametric information geometry: from divergence function to referential-representational biduality on statistical manifolds. Entropy 15, 5384–5418 (2013)

    Article  ADS  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jan Naudts.

Ethics declarations

Conflict of interest

Jun Zhang is a Co-Editor of the journal. Jan Naudts is a board member of the journal. Both were not involved in the peer review or handling of the manuscript. On behalf of all authors, the corresponding author states that there is no other potential conflict of interest to declare.

Additional information

Communicated by Hiroshi Matsuzoe.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Naudts, J., Zhang, J. Legendre duality: from thermodynamics to information geometry. Info. Geo. 7 (Suppl 1), 623–649 (2024). https://doi.org/10.1007/s41884-023-00121-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41884-023-00121-0

Keywords

Navigation