Decoding heat capacity features from the energy landscape.
Physical review. E
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Wales, D. (2017). Decoding heat capacity features from the energy landscape.. Physical review. E, 95 (3-1), 030105. https://doi.org/10.1103/physreve.95.030105
A general scheme is derived to connect transitions in configuration space with features in the heat capacity. A formulation in terms of occupation probabilities for local minima that define the potential energy landscape provides a quantitative description of how contributions arise from competition between different states. The theory does not rely on a structural interpretation for the local minima, so it is equally applicable to molecular energy landscapes and the landscapes defined by abstract functions. Applications are presented for low-temperature solid-solid transitions in atomic clusters, which involve just a few local minima with different morphologies, and for cluster melting, which is driven by the landscape entropy associated with the more numerous high-energy minima. Analyzing these features in terms of the balance between states with increasing and decreasing occupation probabilities provides a direct interpretation of the underlying transitions. This approach enables us to identify a qualitatively different transition that is caused by a single local minimum associated with an exceptionally large catchment volume in configuration space for a machine learning landscape.
External DOI: https://doi.org/10.1103/physreve.95.030105
This record's URL: https://www.repository.cam.ac.uk/handle/1810/289382