{"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/compressing-greens-function-using","title":"Compressing Green's function using intermediate representation between imaginary-time and real-frequency domains","arxiv_id":"1702.03054","date":"2017-02-10","proceeding":null,"authors":["Hiroshi Shinaoka","Junya Otsuki","Masayuki Ohzeki","Kazuyoshi Yoshimi"],"abstract":"New model-independent compact representations of imaginary-time data are\npresented in terms of the intermediate representation (IR) of analytical\ncontinuation. This is motivated by a recent numerical finding by the authors\n[J. Otsuki et al., arXiv:1702.03056]. We demonstrate the efficiency of the IR\nthrough continuous-time quantum Monte Carlo calculations of an Anderson\nimpurity model. We find that the IR yields a significantly compact form of\nvarious types of correlation functions. The present framework will provide\ngeneral ways to boost the power of cutting-edge diagrammatic/quantum Monte\nCarlo treatments of many-body systems.","url_abs":"http://arxiv.org/abs/1702.03054v3","url_pdf":"http://arxiv.org/pdf/1702.03054v3.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":"abstracts"},"code_links":[{"paper_slug":"compressing-greens-function-using","repo_url":"https://github.com/shinaoka/ir","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}