Data-driven low-rank approximation for the electron-hole kernel and acceleration of time-dependent GW calculations
Source abstract
Abstract
Many-body interactions are essential for understanding non-linear optics and ultrafast spectroscopy of materials. Recent first principles approaches based on nonequilibrium Green’s function formalisms, such as the time-dependent adiabatic GW (TD-aGW) approach, can predict nonequilibrium dynamics of excited states including electron-hole interactions. However, the high-dimensionality of the electron-hole kernel poses significant computational challenges. Here, we develop a data-driven low-rank approximation for the electron-hole kernel, leveraging localized excitonic effects in the Hilbert space of crystalline systems to achieve significant data compression through singular value decomposition (SVD). We show that the subspace of non-zero singular values remains small even as the k-grid grows, ensuring computational tractability with extremely dense k-grids. This low-rank property enables at least 95% data compression and an order-of-magnitude speedup of TD-aGW calculations. Our approach avoids intensive training processes and eliminates time-accumulated errors, seen in previous approaches, providing a general framework for high-throughput, nonequilibrium simulation of light-driven dynamics in materials.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Sparse and Compressive Sensing Techniques · Model Reduction and Neural Networks · Electromagnetic Scattering and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (83)
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