Dear all,
I hope you will join us for the November LINCC Tech Talk session that will take place on Thursday, November 14, at 10h PT = 13h ET = 15h CLT = 19h CET on Zoom (https://ls.st/lincc-talks ). We will hear from Tianqing Zhang, who will talk about one of the core project from the LINCC Frameworks.
Redshift Assessment Infrastructure Layers (RAIL), a public code for end-to-end photo-z stress-testing and Rubin-scale production
We present the v1 release of RAIL, an open source Python library for at-scale quantification of probabilistic photo-z uncertainties for generic downstream analyses, initiated by the LSST Dark Energy Science Collaboration with contributions from the LSST Interdisciplinary Network for Collaboration and Computing (LINCC). RAIL provide modular tools for end-to-end stress-testing, including a forward modeling suite to generate realistically complex photometry, a unified API for estimating per-galaxy and ensemble redshift PDFs by an extensible set of algorithms, and built-in metrics of both photo-z PDFs and point estimates. RAIL serves as a flexible toolkit enabling the derivation and optimization of photo-z data products at-scale for a variety of science goals and is not exclusive to LSST data.
LINCC Tech Talks are held on the second Thursday of every month. Events are also advertised at our web page and also provided in calendar form ; and the #lincc-tech-talks LSSTC Slack channel is always available for discussions before, during, and after the talks.