Learning a spin glass: determining Hamiltonians from metastable states

Details Learning a spin glass: determining Hamiltonians from metastable states Learning a spin glass: determining Hamiltonians from metastable states

1997-12-15

arxiv.org/abs/cond-mat/9712177v1

Physica A 257 (1998) 28-35

Physics

Condensed Matter

Disordered Systems and Neural Networks

5 pages, 1 figure, to appear in Physica A

Scientific paper

10.1016/S0378-4371(98)00126-5

We study the problem of determining the Hamiltonian of a fully connected Ising Spin Glass of $N$ units from a set of measurements, whose sizes needs to be ${\cal O}(N^2)$ bits. The student-teacher scenario, used to study learning in feed-forward neural networks, is here extended to spin systems with arbitrary couplings. The set of measurements consists of data about the local minima of the rugged energy landscape. We compare simulations and analytical approximations for the resulting learning curves obtained by using different algorithms.

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