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1. The CAMELS Project: Public Data Release

Author

Francisco Villaescusa-Navarro, Shy Genel, Daniel Anglés-Alcázar, Lucia A. Perez, Pablo Villanueva-Domingo, Digvijay Wadekar, Helen Shao, Faizan G. Mohammad, Sultan Hassan, Emily Moser, Erwin T. Lau, Luis Fernando Machado Poletti Valle, Andrina Nicola, Leander Thiele, Yongseok Jo, Oliver H. E. Philcox, Benjamin D. Oppenheimer, Megan Tillman, ChangHoon Hahn, Neerav Kaushal, Alice Pisani, Matthew Gebhardt, Ana Maria Delgado, Joyce Caliendo, Christina Kreisch, Kaze W. K. Wong, William R. Coulton, Michael Eickenberg, Gabriele Parimbelli, Yueying Ni, Ulrich P. Steinwandel, Valentina La Torre, Romeel Dave, Nicholas Battaglia, Daisuke Nagai, David N. Spergel, Lars Hernquist, Blakesley Burkhart, Desika Narayanan, Benjamin Wandelt, Rachel S. Somerville, Greg L. Bryan, Matteo Viel, Yin Li, Vid Irsic, Katarina Kraljic, Federico Marinacci, and Mark Vogelsberger

Subjects
Cosmology, Hydrodynamical simulations, Astrostatistics, Galaxy formation, Astrophysics, QB460-466
Abstract

The Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4233 cosmological simulations, 2049 N -body simulations, and 2184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper, we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogs, power spectra, bispectra, Ly α spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N -body simulations that have been combined with the Santa Cruz semianalytic model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies, and summary statistics. We provide further technical details on how to access, download, read, and process the data at https://camels.readthedocs.io .

Published
2023
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2. The CAMELS project: public data release.

Author

Francisco Villaescusa-Navarro, Shy Genel, Daniel Anglés-Alcázar, Lucia A. Perez, Pablo Villanueva-Domingo, Digvijay Wadekar, Helen Shao, Faizan G. Mohammad, Sultan Hassan, Emily Moser, Erwin T. Lau, Luis Fernando Machado Poletti Valle, Andrina Nicola, Leander Thiele, Yongseok Jo, Oliver H. E. Philcox, Benjamin D. Oppenheimer, Megan Tillman, ChangHoon Hahn, Neerav Kaushal, Alice Pisani, Matthew Gebhardt, Ana Maria Delgado, Joyce Caliendo, Christina Kreisch, Kaze W. K. Wong, William R. Coulton, Michael Eickenberg, Gabriele Parimbelli, Yueying Ni, Ulrich P. Steinwandel, Valentina La Torre, Romeel Dave, Nicholas Battaglia, Daisuke Nagai, David N. Spergel, Lars Hernquist, Blakesley Burkhart, Desika Narayanan, Benjamin D. Wandelt, Rachel S. Somerville, Greg L. Bryan, Matteo Viel, Yin Li, Vid Irsic, Katarina Kraljic, and Mark Vogelsberger

Published
2022

3. The wide-field, multiplexed, spectroscopic facility WEAVE: Survey design, overview, and simulated implementation

Author

Shoko Jin, Scott C Trager, Gavin B Dalton, J Alfonso L Aguerri, J E Drew, Jesús Falcón-Barroso, Boris T Gänsicke, Vanessa Hill, Angela Iovino, Matthew M Pieri, Bianca M Poggianti, D J B Smith, Antonella Vallenari, Don Carlos Abrams, David S Aguado, Teresa Antoja, Alfonso Aragón-Salamanca, Yago Ascasibar, Carine Babusiaux, Marc Balcells, R Barrena, Giuseppina Battaglia, Vasily Belokurov, Thomas Bensby, Piercarlo Bonifacio, Angela Bragaglia, Esperanza Carrasco, Ricardo Carrera, Daniel J Cornwell, Lilian Domínguez-Palmero, Kenneth J Duncan, Benoit Famaey, Cecilia Fari na, Oscar A Gonzalez, Steve Guest, Nina A Hatch, Kelley M Hess, Matthew J Hoskin, Mike Irwin, Johan H Knapen, Sergey E Koposov, Ulrike Kuchner, Clotilde Laigle, Jim Lewis, Marcella Longhetti, Sara Lucatello, Jairo Méndez-Abreu, Amata Mercurio, Alireza Molaeinezhad, Maria Monguió, Sean Morrison, David N A Murphy, Luis Peralta de Arriba, Isabel Pérez, Ignasi Pérez-Ràfols, Sergio Picó, Roberto Raddi, Mercè Romero-Gómez, Frédéric Royer, Arnaud Siebert, George M Seabroke, Debopam Som, David Terrett, Guillaume Thomas, Roger Wesson, C Clare Worley, Emilio J Alfaro, Carlos Allende Prieto, Javier Alonso-Santiago, Nicholas J Amos, Richard P Ashley, Lola Balaguer-Nú nez, Eduardo Balbinot, Michele Bellazzini, Chris R Benn, Sara R Berlanas, Edouard J Bernard, Philip Best, Daniela Bettoni, Andrea Bianco, Georgia Bishop, Michael Blomqvist, Corrado Boeche, Micol Bolzonella, Silvia Bonoli, Albert Bosma, Nikolay Britavskiy, Gianni Busarello, Elisabetta Caffau, Tristan Cantat-Gaudin, Alfred Castro-Ginard, Guilherme Couto, Juan Carbajo-Hijarrubia, David Carter, Laia Casamiquela, Ana M Conrado, Pablo Corcho-Caballero, Luca Costantin, Alis Deason, Abel de Burgos, Sabrina De Grandi, Paola Di Matteo, Jesús Domínguez-Gómez, Ricardo Dorda, Alyssa Drake, Rajeshwari Dutta, Denis Erkal, Sofia Feltzing, Anna Ferré-Mateu, Diane Feuillet, Francesca Figueras, Matteo Fossati, Elena Franciosini, Antonio Frasca, Michele Fumagalli, Anna Gallazzi, Rubén García-Benito, Nicola Gentile Fusillo, Marwan Gebran, James Gilbert, T M Gledhill, Rosa M González Delgado, Robert Greimel, Mario Giuseppe Guarcello, Jose Guerra, Marco Gullieuszik, Christopher P Haines, Martin J Hardcastle, Amy Harris, Misha Haywood, Amina Helmi, Nauzet Hernandez, Artemio Herrero, Sarah Hughes, Vid Irsic, Pascale Jablonka, Matt J Jarvis, Carme Jordi, Rohit Kondapally, Georges Kordopatis, Jens-Kristian Krogager, Francesco La Barbera, Man I Lam, Søren S Larsen, Bertrand Lemasle, Ian J Lewis, Emilie Lhomé, Karin Lind, Marcello Lodi, Alessia Longobardi, Ilaria Lonoce, Laura Magrini, Jesús Maíz Apellániz, Olivier Marchal, Amparo Marco, Nicolas F Martin, Tadafumi Matsuno, Sophie Maurogordato, Paola Merluzzi, Jordi Miralda-Escudé, Emilio Molinari, Giacomo Monari, Lorenzo Morelli, Christopher J Mottram, Tim Naylor, Ignacio Negueruela, Jose Onorbe, Elena Pancino, Sébastien Peirani, Reynier F Peletier, Lucia Pozzetti, Monica Rainer, Pau Ramos, Shaun C Read, Elena Maria Rossi, Huub J A Röttgering, Jose Alberto Rubi no-Martín, Jose Sabater Montes, José San Juan, Nicoletta Sanna, Ellen Schallig, Ricardo P Schiavon, Mathias Schultheis, Paolo Serra, Timothy W Shimwell, Sergio Simón-Díaz, Russell J Smith, Rosanna Sordo, Daniele Sorini, Caroline Soubiran, Else Starkenburg, Iain A Steele, John Stott, Remko Stuik, Eline Tolstoy, Crescenzo Tortora, Maria Tsantaki, Mathieu Van der Swaelmen, Reinout J van Weeren, Daniela Vergani, Marc A W Verheijen, Kristiina Verro, Jorick S Vink, Miguel Vioque, C Jakob Walcher, Nicholas A Walton, Christopher Wegg, Anne-Marie Weijmans, Wendy L Williams, Andrew J Wilson, Nicholas J Wright, Theodora Xylakis-Dornbusch, Kris Youakim, Stefano Zibetti, Cristina Zurita, Observatoire de la Côte d'Azur (OCA), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Astrophysique de Marseille (LAM), Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Institut de Planétologie et d'Astrophysique de Grenoble (IPAG), Centre National d'Études Spatiales [Toulouse] (CNES)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Météo-France, Galaxies, Etoiles, Physique, Instrumentation (GEPI), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Observatoire astronomique de Strasbourg (ObAS), Université de Strasbourg (UNISTRA)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut d'Astrophysique de Paris (IAP), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche Astrophysique de Lyon (CRAL), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), University of St Andrews. School of Physics and Astronomy, University of St Andrews. Centre for Contemporary Art, Universidad de Alicante. Departamento de Física Aplicada, Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal, and Astrofísica Estelar (AE)

Subjects
Astrofísica, Cosmology and Nongalactic Astrophysics (astro-ph.CO), NDAS, FOS: Physical sciences, Surveys, surveys, QB Astronomy, spectrographs [Instrumentation], observations [Cosmology], Instrumentation and Methods for Astrophysics (astro-ph.IM), Galaxy: general, stars: general, Solar and Stellar Astrophysics (astro-ph.SR), general [Galaxy], QC, QB, instrumentation: spectrographs, general [Stars], Análisis de datos, Instrumentation spectrographs, Astronomy and Astrophysics, general [Galaxies], galaxies: general, Astrophysics - Astrophysics of Galaxies, QC Physics, Astrophysics - Solar and Stellar Astrophysics, Space and Planetary Science, [SDU]Sciences of the Universe [physics], Astrophysics of Galaxies (astro-ph.GA), MCP, cosmology: observations, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, will see first light in late 2022. WEAVE comprises a new 2-degree field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366$-$959\,nm at $R\sim5000$, or two shorter ranges at $R\sim20\,000$. After summarising the design and implementation of WEAVE and its data systems, we present the organisation, science drivers and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for $\sim$3 million stars and detailed abundances for $\sim1.5$ million brighter field and open-cluster stars; (ii) survey $\sim0.4$ million Galactic-plane OBA stars, young stellar objects and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey $\sim400$ neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionised gas in $z1$ million spectra of LOFAR-selected radio sources; (viii) trace structures using intergalactic/circumgalactic gas at $z>2$. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator., 41 pages, 27 figures, accepted for publication by MNRAS

Published
2023
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4. Deep Learning of Dark Energy Spectroscopic Instrument Mock Spectra to Find Damped Lyα Systems

Author

Ben Wang, Jiaqi Zou, Zheng Cai, J. Xavier Prochaska, Zechang Sun, Jiani Ding, Andreu Font-Ribera, Alma Gonzalez, Hiram K. Herrera-Alcantar, Vid Irsic, Xiaojing Lin, David Brooks, Soléne Chabanier, Roger de Belsunce, Nathalie Palanque-Delabrouille, Gregory Tarle, and Zhimin Zhou

Subjects
Particle and Plasma Physics, Space and Planetary Science, Molecular, Astronomy and Astrophysics, Nuclear, Astronomy & Astrophysics, Atomic, Astronomical and Space Sciences, Physical Chemistry (incl. Structural)
Abstract

We have updated and applied a convolutional neural network (CNN) machine-learning model to discover and characterize damped Lyα systems (DLAs) based on Dark Energy Spectroscopic Instrument (DESI) mock spectra. We have optimized the training process and constructed a CNN model that yields a DLA classification accuracy above 99% for spectra that have signal-to-noise ratios (S/N) above 5 per pixel. The classification accuracy is the rate of correct classifications. This accuracy remains above 97% for lower S/N ≈1 spectra. This CNN model provides estimations for redshift and H i column density with standard deviations of 0.002 and 0.17 dex for spectra with S/N above 3 pixel−1. Also, this DLA finder is able to identify overlapping DLAs and sub-DLAs. Further, the impact of different DLA catalogs on the measurement of baryon acoustic oscillations (BAO) is investigated. The cosmological fitting parameter result for BAO has less than 0.61% difference compared to analysis of the mock results with perfect knowledge of DLAs. This difference is lower than the statistical error for the first year estimated from the mock spectra: above 1.7%. We also compared the performances of the CNN and Gaussian Process (GP) models. Our improved CNN model has moderately 14% higher purity and 7% higher completeness than an older version of the GP code, for S/N > 3. Both codes provide good DLA redshift estimates, but the GP produces a better column density estimate by 24% less standard deviation. A credible DLA catalog for the DESI main survey can be provided by combining these two algorithms.

Published
2022

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