首页|Yale University Reports Findings in Machine Learning (Machine Learning Many-Body Green’s Functions for Molecular Excitation Spectra)
Yale University Reports Findings in Machine Learning (Machine Learning Many-Body Green’s Functions for Molecular Excitation Spectra)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is the subject of a report. According to newsreporting from New Haven, Connecticut, by NewsRx journalists, research stated, “We present a machinelearning (ML) framework for predicting Green’s functions of molecular systems, from which photoemission spectra and quasiparticle energies at quantum many-body level can be obtained. Kernel ridge regressionis adopted to predict self-energy matrix elements on compact imaginary frequency grids from static anddynamical mean-field electronic features, which gives direct access to real-frequency many-body Green’sfunctions through analytic continuation and Dyson’s equation.”
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