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Bridging constrained random-phase approximation and linear response theory for computing Hubbard parameters

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arxiv 2505.03698 v2 pith:KCQSR2B3 submitted 2025-05-06 cond-mat.str-el

classification cond-mat.str-el
keywords crpatheoryresponsevaluesapproximationconstraineddifferenceslinear
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The predictive accuracy of popular extensions to density-functional theory (DFT) such as DFT+U and DFT plus dynamical mean-field theory (DFT+DMFT) hinges on using realistic values for the screened Coulomb interaction U. Here, we present a systematic comparison of the two most widely used approaches to compute this parameter, i.e. linear response theory (LRT) and the constrained random-phase approximation (cRPA), using a unified framework based on the use of maximally localized Wannier functions. We show that the U in LRT and cRPA can differ as much as 30%. We demonstrate that this discrepancy arises from two main differences: neglecting the response of the exchange-correlation potential in cRPA and additional excitation channels in LRT. By taking these differences into account, we can achieve near perfect agreement between the two techniques. Moreover, we show that in cases with strong hybridization between interacting and screening subspaces, the application of cRPA becomes ambiguous and can lead to unrealistically small U values, while LRT remains well-behaved. Our work formally connects both methods, sheds light on their strengths and limitations, and emphasizes the importance of using a consistent set of Wannier orbitals to ensure transferability of U values between different implementations.

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  1. Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters

    cond-mat.mtrl-sci 2026-07 conditional novelty 5.0 of 10

    Ensemble ML plus brute-force regression formulas predict cRPA-derived Ueff, V, and J for transition-metal oxides from electronic, structural, and elemental descriptors, with reported RMSEs of 0.148, 0.062, and 0.007 eV.

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