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Feshbach Resonances in Cold Collisions: Benchmarking State of the Art ab initio Potential Energy Surfaces
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abstract
High-quality potential energy surfaces (PES) are a prerequisite for quantitative atomistic simulations, with both quantum and classical dynamics approaches. The ultimate test for the validity of a PES are comparisons with judiciously chosen experimental observables. Here we ask whether cold collision measurements are sufficiently informative to validate and distinguish between high-level, state-of-the art PESs for the strongly interacting Ne-H$_2^+$ system. We show that measurement of the final state distributions for a process that involves only several metastable intermediate states is sufficient to identify the PES that captures the long-range interactions properly. Furthermore, we show that a modest increase in the experimental energy resolution will allow for resolving individual Feshbach resonances and enable a quantitative probe of the interactions at short and intermediate range.
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The Bigger the Better? Accurate Molecular Potential Energy Surfaces from Minimalist Neural Networks
A tiny neural network using simple distance-based fingerprints matches the accuracy of million-parameter neural network potentials for small molecules, while evaluating faster and extrapolating more safely.
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