Skip to main content
Log in

Gibbs states of the Hopfield model with extensively many patterns

  • Articles
  • Published:
Journal of Statistical Physics Aims and scope Submit manuscript

Abstract

We consider the Hopfield model withM(N)N patterns, whereN is the number of neurons. We show that if α is sufficiently small and the temperature sufficiently low, then there exist disjoint Gibbs states for each of the stored patterns, almost surely with respect to the distribution of the random patterns. This solves a provlem left open in previous work. The key new ingredient is a self-averaging result on the free energy functional. This result has considerable additional interest and some consequences are discussed. A similar result for the free energy of the Sherrington-Kirkpatrick model is also given.

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. D. J. Amit, H. Gutfreund, and H. Sompolinsky, Statistical mechanics of neural networks near saturation,Ann. Phys. 173:30–67 (1987).

    Google Scholar 

  2. A. Bovier and V. Gayrard, Rigorous results on the thermodynamics of the dilute Hopfield model,J. Stat. Phys. 69:627 (1993).

    Google Scholar 

  3. A. Bovier and V. Gayrard, Rigorous results on the Hopfield model of neural networks,Resenhas IME-USP 2:161–172 (1994).

    Google Scholar 

  4. A. Bovier, V. Gayrard, and P. Picco, Gibbs states of the Hopfield model in the regime of perfect memory,Prob. Theory Related Fields 100:329–363 (1994).

    Google Scholar 

  5. A. Bovier, V. Gayrard, and P. Picco, Large deviation principles for the Hopfield model and the Kac-Hopfield model,Prob. Theory Related Fields (1995), to appear.

  6. L. A. Pastur and A. L. Figotin, Exactly soluble model of a spin glass,Sov. J. Low Temp. Phys. 3(6):378–383 (1977).

    Google Scholar 

  7. L. A. Pastur and A. L. Figotin, On the theory of disordered spin systems,Theor. Math. Phys. 35:403–414 (1978).

    Google Scholar 

  8. J. J. Hopfield, Neural networks and physical systems with emergent collective computational abilities,Proc. Natl. Acad. Sci. USA,79:2554–2558 (1982).

    Google Scholar 

  9. M. Ledoux and M. Talagrand,Probability in Banach Spaces (Springer, Berlin, 1991).

    Google Scholar 

  10. M. Mézard, G. Parisi, and M. A. Virasoro,Spin-Glass Theory and Beyond (World Scientific, Singapore, 1988).

    Google Scholar 

  11. L. Pastur and M. Shcherbina, Absence of self-averaging of the order parameter in the Sherrington-Kirkpatrick model,J. Stat. Phys. 62:1–19 (1991).

    Google Scholar 

  12. L. Pastur, M. Shcherbina, and B. Tirozzi, The replica symmetric solution without the replica trick for the Hopfield model,J. Stat. Phys. 74:1161–1183 (1994).

    Google Scholar 

  13. D. Sherrington and S. Kirkpatrick, Solvable model of a spin glass,Phys. Rev. Lett. 35:1792–1796 (1972).

    Google Scholar 

  14. M. Shcherbina and B. Tirozzi, The free energy for a class of Hopfield models,J. Stat. Phys. 72:113–125 (1992).

    Google Scholar 

  15. V. V. Yurinskii, Exponential inequalities for sums of random vectors,J. Multivariate Anal. 6:473–499 (1976).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bovier, A., Gayrard, V. & Picco, P. Gibbs states of the Hopfield model with extensively many patterns. J Stat Phys 79, 395–414 (1995). https://doi.org/10.1007/BF02179395

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02179395

Key Words

Navigation