Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2008-03-24
Physics
Condensed Matter
Disordered Systems and Neural Networks
15 pages, 8 figures. To appear in: Computer Simulation Studies in Condensed Matter Physics XXI, Eds. D.P. Landau, S.P. Lewis,
Scientific paper
The concept of replica symmetry breaking found in the solution of the mean-field Sherrington-Kirkpatrick spin-glass model has been applied to a variety of problems in science ranging from biological to computational and even financial analysis. Thus it is of paramount importance to understand which predictions of the mean-field solution apply to non-mean-field systems, such as realistic short-range spin-glass models. The one-dimensional spin glass with random power-law interactions promises to be an ideal test-bed to answer this question: Not only can large system sizes-which are usually a shortcoming in simulations of high-dimensional short-range system-be studied, by tuning the power-law exponent of the interactions the universality class of the model can be continuously tuned from the mean-field to the short-range universality class. We present details of the model, as well as recent applications to some questions of the physics of spin glasses. First, we study the existence of a spin-glass state in an external field. In addition, we discuss the existence of ultrametricity in short-range spin glasses. Finally, because the range of interactions can be changed, the model is a formidable test-bed for optimization algorithms.
Hartmann Alexander K.
Katzgraber Helmut G.
Young Patrick A.
No associations
LandOfFree
New Insights from One-Dimensional Spin Glasses does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with New Insights from One-Dimensional Spin Glasses, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and New Insights from One-Dimensional Spin Glasses will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-616066