The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Baryon acoustic oscillations with Lyman-$α$ forests

2 code implementations • 17 Jul 2020 • Hélion du Mas des Bourboux, James Rich, Andreu Font-Ribera, Victoria de Sainte Agathe, James Farr, Thomas Etourneau, Jean-Marc Le Goff, Andrei Cuceu, Christophe Balland, Julian E. Bautista, Jonathan Brinkmann, Joel R. Brownstein, Solène Chabanier, Edmond Chaussidon, Kyle Dawson, Alma X. González-Morales, Julien Guy, Brad W. Lyke, Axel de la Macorra, Adam D. Myers, Christian Nitschelm, Andrea Muñoz Gutiérrez, Nathalie Palanque-Delabrouille, James Parker, Will J. Percival, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider, Hee-Jong Seo, Anže Slosar, Julianna Stermer, M. Vivek, Christophe Yèche, Samantha Youles

We present a measurement of baryonic acoustic oscillations (BAO) from Lyman-$\alpha$ (Ly$\alpha$) absorption and quasars at an effective redshift $z=2. 33$ using the complete extended Baryonic Oscillation Spectroscopic Survey (eBOSS).

Cosmology and Nongalactic Astrophysics

The one-dimensional Ly-alpha forest power spectrum from BOSS

2 code implementations • 25 Jun 2013 • Nathalie Palanque-Delabrouille, Christophe Yèche, Arnaud Borde, Jean-Marc Le Goff, Graziano Rossi, Matteo Viel, Éric Aubourg, Stephen Bailey, Julian Bautista, Michael Blomqvist, Adam Bolton, James S. Bolton, Nicolás G. Busca, Bill Carithers, Rupert A. C. Croft, Kyle S. Dawson, Timothée Delubac, Andreu Font-Ribera, Shirley Ho, David Kirkby, Khee-Gan Lee, Daniel Margala, Jordi Miralda-Escudé, Demitri Muna, Adam D. Myers, Pasquier Noterdaeme, Isabelle Pâris, Patrick Petitjean, Matthew M. Pieri, James Rich, Emmanuel Rollinde, Nicholas P. Ross, David J. Schlegel, Donald P. Schneider, Anže Slosar, David H. Weinberg

We have developed two independent methods to measure the one-dimensional power spectrum of the transmitted flux in the Lyman-$\alpha$ forest.

Cosmology and Nongalactic Astrophysics

Robust Machine Learning Applied to Astronomical Datasets III: Probabilistic Photometric Redshifts for Galaxies and Quasars in the SDSS and GALEX

no code implementations • 21 Apr 2008 • Nicholas M. Ball, Robert J. Brunner, Adam D. Myers, Natalie E. Strand, Stacey L. Alberts, David Tcheng

We apply machine learning in the form of a nearest neighbor instance-based algorithm (NN) to generate full photometric redshift probability density functions (PDFs) for objects in the Fifth Data Release of the Sloan Digital Sky Survey (SDSS DR5).

Robust Machine Learning Applied to Astronomical Datasets II: Quantifying Photometric Redshifts for Quasars Using Instance-Based Learning

no code implementations • 17 Dec 2006 • Nicholas M. Ball, Robert J. Brunner, Adam D. Myers, Natalie E. Strand, Stacey L. Alberts, David Tcheng, Xavier Llorà

The instance-based algorithm is trained on a representative sample of the data and pseudo-blind-tested on the remaining unseen data.

astro-ph