{"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/juliet-a-versatile-modelling-tool-for","title":"Juliet: a versatile modelling tool for transiting and non-transiting exoplanetary systems","arxiv_id":"1812.08549","date":"2018-12-20","proceeding":null,"authors":["Néstor Espinoza","Diana Kossakowski","Rafael Brahm"],"abstract":"Here we present juliet, a versatile tool for the analysis of transits, radial-velocities, or both. juliet is built over many available tools for the modelling of transits, radial-velocities and stochastic processes (here modelled as Gaussian Processes; GPs) in order to deliver a tool/wrapper which can be used for the analysis of transit photometry and radial-velocity measurements from multiple instruments at the same time, using nested sampling algorithms which allows it to not only perform a thorough sampling of the parameter space, but also to perform model comparison via bayesian evidences. In addition, juliet allows to fit transiting and non-transiting multi-planetary systems, and to fit GPs which might share hyperparameters between the photometry and radial-velocities simultaneously (e.g., stellar rotation periods), which might be useful for disentangling stellar activity in radial-velocity measurements. Nested Sampling, Importance Nested Sampling and Dynamic Nested Sampling is performed with publicly available codes which in turn give juliet multi-threading options, allowing it to scale the computing time of complicated multi-dimensional problems. We make juliet publicly available via GitHub.","url_abs":"https://arxiv.org/abs/1812.08549v2","url_pdf":"https://arxiv.org/pdf/1812.08549v2.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":"juliet-a-versatile-modelling-tool-for","repo_url":"https://github.com/nespinoza/juliet","is_official":1,"mentioned_in_paper":1,"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}