In this work we present a rigorous and straightforward method to detect the onset of the instability of replica-symmetric theories in information processing systems, which does not require a full replica analysis as in the method originally proposed by de Almeida and Thouless for spin glasses. The method is based on an expansion of the free-energy obtained within one-step of replica symmetry breaking (RSB) around the RS value. As such, it requires solely continuity and differentiability of the free-energy and it is robust to be applied broadly to systems with quenched disorder. We apply the method to the Hopfield model and to neural networks with multi-node Hebbian interactions, as case studies. In the appendices we test the method on the Sherrington–Kirkpatrick and the Ising -spin models, recovering the AT lines known in the literature for these models, as a special limit, which corresponds to assuming that the transition from the RS to the RSB phase can be obtained by varying continuously the order parameters. Our method provides a generalization of the AT approach, which does not rely on this limit and can be applied to systems with discontinuous phase transitions, as we show explicitly for the spherical P-spin model, recovering the known RS instability line.

About the de Almeida–Thouless line in neural networks / Albanese, Linda; Alessandrelli, Andrea; Barra, Adriano; Annibale, Alessia. - In: PHYSICA. A. - ISSN 0378-4371. - 633:(2024). [10.1016/j.physa.2023.129372]

About the de Almeida–Thouless line in neural networks

Adriano Barra;
2024

Abstract

In this work we present a rigorous and straightforward method to detect the onset of the instability of replica-symmetric theories in information processing systems, which does not require a full replica analysis as in the method originally proposed by de Almeida and Thouless for spin glasses. The method is based on an expansion of the free-energy obtained within one-step of replica symmetry breaking (RSB) around the RS value. As such, it requires solely continuity and differentiability of the free-energy and it is robust to be applied broadly to systems with quenched disorder. We apply the method to the Hopfield model and to neural networks with multi-node Hebbian interactions, as case studies. In the appendices we test the method on the Sherrington–Kirkpatrick and the Ising -spin models, recovering the AT lines known in the literature for these models, as a special limit, which corresponds to assuming that the transition from the RS to the RSB phase can be obtained by varying continuously the order parameters. Our method provides a generalization of the AT approach, which does not rely on this limit and can be applied to systems with discontinuous phase transitions, as we show explicitly for the spherical P-spin model, recovering the known RS instability line.
2024
Neural networks; AT line; de Almeida–Thouless line; Replica symmetry breaking; Hopfield model; Dense associative memories
01 Pubblicazione su rivista::01a Articolo in rivista
About the de Almeida–Thouless line in neural networks / Albanese, Linda; Alessandrelli, Andrea; Barra, Adriano; Annibale, Alessia. - In: PHYSICA. A. - ISSN 0378-4371. - 633:(2024). [10.1016/j.physa.2023.129372]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1707713
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