A Neural Network Model of an Ising Spin Glass

• Authors: K. Wilson , D. Goossens
• Languages of publication: EN

Abstracts

EN

The behaviour of an Ising spin glass (S=1/2) with infinite range interactions is modelled using a numerical simulation based on a neural network. Thermodynamic variables are defined on the network, and are found to obey the Thouless-Anderson-Palmer theory when the applied magnetic field is zero. When a magnetic field is applied along the spin direction, complex field-dependent behaviour appears, including a state in which the Edwards-Anderson order parameter is independent of temperature below the critical temperature.

Keywords

EN

75.10.-b; 75.10.Nr; 84.35.+i

Discipline

• 75.10.Nr: Spin-glass and other random models(for spin glasses and other random magnets, see 75.50.Lk)
• 84.35.+i: Neural networks(for optical neural networks, see 42.79.Ta; see also 07.05.Mh Neural networks, fuzzy logic, artificial intelligence in computers in experimental physics; 87.18.Sn in biological complexity)
• 75.10.-b: General theory and models of magnetic ordering(see also 05.50.+q Lattice theory and statistics)

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2000
• Volume: 97
• Issue: 5
• Pages: 983-986

Dates

published

2000-05

Contributors

author

K. Wilson

• Department of Physics, Monash University, Clayton 3168, Australia

author

D. Goossens

• Department of Physics, Monash University, Clayton 3168, Australia

Identifiers

DOI

10.12693/APhysPolA.97.983