Redshift Assessment Infrastructure Layers (RAIL): Rubin-era photometric redshift stress-testing and at-scale production
Authors:
The RAIL Team,
Jan Luca van den Busch,
Eric Charles,
Johann Cohen-Tanugi,
Alice Crafford,
John Franklin Crenshaw,
Sylvie Dagoret,
Josue De-Santiago,
Juan De Vicente,
Qianjun Hang,
Benjamin Joachimi,
Shahab Joudaki,
J. Bryce Kalmbach,
Arun Kannawadi,
Shuang Liang,
Olivia Lynn,
Alex I. Malz,
Rachel Mandelbaum,
Grant Merz,
Irene Moskowitz,
Drew Oldag,
Jaime Ruiz-Zapatero,
Mubdi Rahman,
Markus M. Rau,
Samuel J. Schmidt
, et al. (8 additional authors not shown)
Abstract:
Virtually all extragalactic use cases of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) require the use of galaxy redshift information, yet the vast majority of its sample of tens of billions of galaxies will lack high-fidelity spectroscopic measurements thereof, instead relying on photometric redshifts (photo-$z$) subject to systematic imprecision and inaccuracy best encap…
▽ More
Virtually all extragalactic use cases of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) require the use of galaxy redshift information, yet the vast majority of its sample of tens of billions of galaxies will lack high-fidelity spectroscopic measurements thereof, instead relying on photometric redshifts (photo-$z$) subject to systematic imprecision and inaccuracy best encapsulated by photo-$z$ probability density functions (PDFs). We present the version 1 release of Redshift Assessment Infrastructure Layers (RAIL), an open source Python library for at-scale probabilistic photo-$z$ estimation, initiated by the LSST Dark Energy Science Collaboration (DESC) with contributions from the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) Frameworks team. RAIL's three subpackages 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 specific to LSST data. We thus describe to the extragalactic science community, including and beyond Rubin the design and functionality of the RAIL software library so that any researcher may have access to its wide array of photo-$z$ characterization and assessment tools.
△ Less
Submitted 12 March, 2026; v1 submitted 5 May, 2025;
originally announced May 2025.
About the connection between vacuum birefringence and the light-light scattering amplitude
Authors:
J. Haissinski,
S. Dagoret,
M. Urban,
F. Zomer
Abstract:
Birefringence phenomena stemming from vacuum polarization are revisited in the framework of coherent scattering. Based on photon-photon scattering, our analysis brings out the direct connection between this process and vacuum birefringence. We show how this procedure can be extended to the Kerr and the Cotton-Mouton birefringences in vacuum, thus providing a unified treatment of various polariza…
▽ More
Birefringence phenomena stemming from vacuum polarization are revisited in the framework of coherent scattering. Based on photon-photon scattering, our analysis brings out the direct connection between this process and vacuum birefringence. We show how this procedure can be extended to the Kerr and the Cotton-Mouton birefringences in vacuum, thus providing a unified treatment of various polarization schemes, including those involving static fields.
△ Less
Submitted 10 November, 2006; v1 submitted 6 October, 2006;
originally announced October 2006.