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Kipton M. Barros on Muck Rack

Kipton M. Barros

As seen in: Color Research & Application, Physical Review B
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Articles

Physically interpretable approximations of many-body spectral functions

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By Kipton M. Barros, Los Alamos, Matthew Carbone, Shubhang Goswami
| Physical Review B
The rational function approximation provides a natural and interpretable representation of response functions such as the many-body spectral functions. We apply the vector fitting (VFIT) algorithm to fit a variety of spectral functions calculated from the Holstein model of electron-phonon interactions.
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Machine Learning Framework for Modeling Exciton Polaritons in Molecular Materials

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By Xinyang Li, Nicholas Lubbers, Sergei Tretiak, Kipton M. Barros
| dx.doi.org
Download Hi-Res ImageDownload to MS-PowerPointCite This:J. Chem. Theory Comput. 2024, XXXX, XXX Terms & Conditions Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses).
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Machine learning of consistent thermodynamic models using automatic differentiation

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By Los Alamos, Kipton M. Barros, Timothy C. Germann, David Rosenberger
| Physical Review B
Abstract We propose a data-driven method to describe consistent equations of state (EOS) for arbitrary systems. Complex EOS are traditionally obtained by fitting suitable analytical expressions to thermophysical data. A key aspect of EOS is that the relationships between state variables are given by derivatives of the system free energy.
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