Skip to main content

Approximation of Edwards-Anderson Spin-Glass Model Density of States

  • Conference paper
  • First Online:
  • 1850 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11555))

Abstract

We have investigated the density of states of the Edwards-Anderson model and derived an approximation formula which agrees well with the results of numerical experiments. It is important that the formula can well approximate not only the density of states, but also its first and second derivatives, which are most valuable for obtaining the critical parameters of the system. The evaluations can be further used for examining the behavior of 2D Ising models at different temperatures, particularly for tackling Bayesian inference problems and learning algorithms.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Baxter, R.J.: Exactly Solved Models in Statistical Mechanics. Academic Press, London (1982)

    Google Scholar 

  2. Onsager, L.: Crystal Statistics. I. A two-dimensional model with an order–disorder transition. Phys. Rev. 65, 117–149 (1944)

    Google Scholar 

  3. Edwards, S.F., Anderson, P.W.: Theory of spin glasses. J. Phys. F: Metal Phys. 5, 965–974 (1975)

    Google Scholar 

  4. Sherrington, D., Kirkpatrick, P.: Solvable model of a spin-glass. Phys. Rev. Lett. 35(26), 1792–1796 (1975)

    Google Scholar 

  5. Metropolis, N., Ulam, S.: The Monte Carlo Method. J. of Am. Stat. Assoc. 44(247), 335–341 (1949)

    Google Scholar 

  6. Fishman, G.S.: Monte Carlo: Concepts, Algorithms, and Applications. Springer Series in Operations Research and Financial Engineering, 1st edn. Springer, New York (1996). https://doi.org/10.1007/978-1-4757-2553-7

    Google Scholar 

  7. Bielajew, A.F.: Fundamentals of the Monte Carlo method for neutral and charged particle transport. The University of Michigan, Dep. of Nuclear Engineering and Radiological Sciences (2001)

    Google Scholar 

  8. Foulkes, W.M.C., Mitas, L., Needs, R.J., Rajagopal, G.: Quantum Monte Carlo simulations of solids. Rev. Mod. Phys. 73(1), 33–83 (2001)

    Google Scholar 

  9. Binder, K.: Finite Size scaling analysis of Iising model block distribution functions. Z. Phys. B 43, 119–140 (1981)

    Google Scholar 

  10. Binder, K., Luijten, E.: Monte Carlo tests of renormalization-group predictions for critical phenomena in Ising models. Phys. Rep. 344, 179–253 (2001)

    Google Scholar 

  11. Kasteleyn, P.: Dimer statistics and phase transitions. J. Math. Phys. 4(2), 287–293 (1963)

    Google Scholar 

  12. Fisher, M.: On the dimer solution of planar Ising models. J. Math. Phys. 7(10), 1776–1781 (1966)

    Google Scholar 

  13. Karandashev, Ya.M., Malsagov, M.Yu.: Polynomial algorithm for exact calculation of partition function for binary spin model on planar graphs. Opt. Mem. Neural Networks (Inf. Opt.) 26(2), 87–95 (2017)

    Google Scholar 

  14. Schraudolph, N., Kamenetsky, D.: Efficient exact inference in planar Ising models. In: NIPS (2008). https://arxiv.org/abs/0810.4401

  15. Kryzhanovsky, B.V., Malsagov, M.Yu., Karandashev, I.M.: Investigation of finite-size 2D Ising model with a noisy matrix of spin-spin interactions. Entropy 20(8), 585 (2018)

    Google Scholar 

  16. Kryzhanovsky, B.V., Karandashev, I.M., Malsagov, M.Yu.: Dependence of critical temperature on dispersion of connections in 2D grid. In: Huang, T., Lv, J., Sun, C., Tuzikov, Alexander V. (eds.) ISNN 2018. LNCS, vol. 10878, pp. 695–702. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92537-0_79

    Google Scholar 

  17. Karandashev, I.M., Kryzhanovsky, B.V., Malsagov, M.Yu.: Spectral characteristics of a finite 2D Ising model. Opt. Mem. Neural Networks (Inf. Opt.) 27(3), 147–151 (2018)

    Google Scholar 

  18. Häggkvist, R., Rosengren, A., Andrén, D., Kundrotas, P., Lundow, P.H., Markström, K.: Computation of the Ising partition function for 2-dimensional square grids. Phys. Rev. E 69, 046104 (2004)

    Google Scholar 

  19. Beale, P.D.: Exact distribution of energies in the two-dimensional Ising model. Phys. Rev. Lett. 76, 78–81 (1996)

    Google Scholar 

  20. Litinskii, L., Kryzhanovsky, B.: Spectral density and calculation of free energy. Physica A: Stat. Mech. Appl. 510, 702–712 (2018)

    Google Scholar 

  21. Kryzhanovsky, B.V.: Features of the Spectral Density of a Spin System. Dokl. Math. 97(2), 188–192 (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Iakov M. Karandashev .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Malsagov, M.Y., Karandashev, I.M., Kryzhanovsky, B.V. (2019). Approximation of Edwards-Anderson Spin-Glass Model Density of States. In: Lu, H., Tang, H., Wang, Z. (eds) Advances in Neural Networks – ISNN 2019. ISNN 2019. Lecture Notes in Computer Science(), vol 11555. Springer, Cham. https://doi.org/10.1007/978-3-030-22808-8_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-22808-8_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22807-1

  • Online ISBN: 978-3-030-22808-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics