Abstract
Systems with many different interactions pose a challenge to traditional methods of statistical physics. In this paper, we develop the random bond model, which has a huge number of randomly chosen interaction parameters (quenched variables). Using heuristic arguments and Monte-Carlo simulations, we show that for any temperature there exists a sufficiently large system size above which one can forego the complicated quenched averaging familiar from spin glasses, and calculate statistical averages using standard methods of equilibrium statistical mechanics.
| Original language | English |
|---|---|
| Pages (from-to) | 186-198 |
| Number of pages | 13 |
| Journal | Journal of Statistical Physics |
| Volume | 162 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Jan 2016 |
Bibliographical note
Funding Information:We would like to thank Lenin Shagolsem, Dan Stein, Chuck Newman, Matthiew Wyart, David Kessler, Nadav Schnerb, Paul Chaikin and Mitchell Feigenbaum for useful discussion. This work was supported by the I-CORE Program of the Planning and Budgeting Committee and the Israel Science Foundation.
Publisher Copyright:
© 2015, Springer Science+Business Media New York.
Keywords
- Neighborhood identity ordering
- Quenched and annealed average
- Random bond lattice model