{"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/weight-optimization-in-multichannel-monte","title":"Weight optimization in multichannel Monte Carlo","arxiv_id":"hep-ph/9405257","date":"1994-05-10","proceeding":null,"authors":["R. Kleiss","R. Pittau"],"abstract":"We discuss the improvement in the accuracy of a Monte Carlo integration that can be obtained by optimization of the `a-priori weights' of the various channels. These channels may be either the strata in a stratified-sampling approach, or the several `approximate' distributions such as are used in event generators for particle phenomenology. The optimization algorithm does not require any initialization, and each Monte Carlo integration point can be used in the evaluation of the integral. We describe our experience with this method in a realistic problem, where an effective increase in program speed by almost an order of magnitude is observed.","url_abs":"https://arxiv.org/abs/hep-ph/9405257v2","url_pdf":"https://arxiv.org/pdf/hep-ph/9405257v2.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":"weight-optimization-in-multichannel-monte","repo_url":"https://github.com/IceColdRefreshment/MonteCarloIntegrator","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"weight-optimization-in-multichannel-monte","repo_url":"https://github.com/cschwan/hep-mc","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"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}