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Random walk over basins of attraction to construct ising energy landscapes
1Department of Statistics, University of California, Los Angeles, 90095, USA.
Abstract:
An efficient algorithm is developed to construct disconnectivity graphs by a random walk over basins of attraction. This algorithm can detect a large number of local minima, find energy barriers between them, and estimate local thermal averages over each basin of attraction. It is applied to the Sherrington-Kirkpatrick (SK) spin glass Hamiltonian where existing methods have difficulties even for a moderate number of spins. Finite-size results are used to make predictions in the thermodynamic limit that match theoretical approximations and recent findings on the free energy landscapes of SK spin glasses.
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