A Neural Network Model of an Ising Spin Glass
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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.
- 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)
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