{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/computational-approaches-to-efficient","title":"Computational approaches to efficient generation of the stationary state for incoherent light excitation","arxiv_id":"2011.03084","date":"2020-11-05","proceeding":null,"authors":["Ignacio Loaiza","Artur F. Izmaylov","Paul Brumer"],"abstract":"Light harvesting processes are often computationally studied from a time-dependent viewpoint, in line with ultrafast coherent spectroscopy experiments. Yet, natural processes take place in the presence of incoherent light, which induces a stationary state. Such stationary states can be described using the eigenbasis of the molecular Hamiltonian, but for realistic systems a full diagonalization is prohibitively expensive. We propose three efficient computational approaches to obtaining the stationary state that circumvent system Hamiltonian diagonalization. The connection between the incoherent perturbations, decoherence, and Kraus operators is established.","url_abs":"https://arxiv.org/abs/2011.03084v2","url_pdf":"https://arxiv.org/pdf/2011.03084v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"computational-approaches-to-efficient","repo_url":"https://github.com/iloaiza/Incoherent_density","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}