Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1867
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dc.contributor.authorSingh, Ojas-
dc.date.accessioned2022-12-14T05:16:29Z-
dc.date.available2022-12-14T05:16:29Z-
dc.date.issued2022-04-
dc.identifier.urihttp://hdl.handle.net/123456789/1867-
dc.description.abstractIn order to account for the missing electron correlation from the Hartree- Fock method, the Configuration Interaction method uses a variational wave function that is a linear combination of configuration state functions (CSFs) built from spin orbitals. Full CI scales unfavorably with the number of or- bitals and electrons relative to other orbital methods. Hence, implementa- tion of CI is done in Rust using numerous Code Optimizations, making this implementation extremely efficient. To deal with an even bigger systems, se- lected Configuration Interaction is explored, and a very promising Reinforce- ment Learning-based method has been implemented and improved further for excited states energies.en_US
dc.language.isoen_USen_US
dc.publisherIISER Mohalien_US
dc.subjectconfigurationen_US
dc.subjectreinforcement learningen_US
dc.subjectselected CIen_US
dc.titleEfficient implementation of configuration interaction and selected CI Using reinforcement learningen_US
dc.typeThesisen_US
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