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- W1518757379 abstract "We first present an exact solution of the one-dimensional random-field Ising model in which spin-updates are made fully synchronously, i.e. in parallel (in contrast to the more conventional Glauber-type sequential rules). We find transitions where the support of local observables turns from a continuous interval into a Cantor set and we show that synchronous and sequential random-field models lead asymptotically to the same physical states. We then proceed to an application of these techniques to recurrent neural networks where 1D short-range interactions are combined with infinite-range ones. Due to the competing interactions these models exhibit phase diagrams with first-order transitions and regions with multiple locally stable solutions for the macroscopic order parameters." @default.
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- W1518757379 date "2001-01-01" @default.
- W1518757379 modified "2023-09-25" @default.
- W1518757379 title "Random field Ising chain and neutral networks with synchronous dynamics" @default.
- W1518757379 doi "https://doi.org/10.1063/1.1358170" @default.
- W1518757379 hasPublicationYear "2001" @default.
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