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AMON and ANTARES Collaborations (Ayala Solares, H.A. et al); Barrios-Marti, J.; Coleiro, A.; Colomer, M.; Gozzini, R.; Hernandez-Rey, J.J.; Illuminati, G.; Khan-Chowdhury, N.R.; Lotze, M.; Thakore, T.; Zornoza, J.D.; Zuñiga, J. |
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Title |
A Search for Cosmic Neutrino and Gamma-Ray Emitting Transients in 7.3 yr of ANTARES and Fermi LAT Data |
Type |
Journal Article |
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Year |
2019 |
Publication |
Astrophysical Journal |
Abbreviated Journal |
Astrophys. J. |
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Volume |
886 |
Issue |
2 |
Pages |
98 - 8pp |
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Keywords |
BL Lacertae objects: general; cosmic rays; gamma-ray burst: general; gamma rays: general; neutrinos |
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Abstract |
We analyze 7.3 yr of ANTARES high-energy neutrino and Fermi Large Area Telescope (LAT) gamma-ray data in search of cosmic neutrino + gamma-ray (nu + gamma) transient sources or source populations. Our analysis has the potential to detect either individual nu + gamma transient sources (durations delta t less than or similar to 1000 s), if they exhibit sufficient gamma-ray or neutrino multiplicity, or a statistical excess of nu + gamma transients of individually lower multiplicities. Individual high gamma-ray multiplicity events could be produced, for example, by a single ANTARES neutrino in coincidence with a LAT-detected gamma-ray burst. Treating ANTARES track and cascade event types separately, we establish detection thresholds by Monte Carlo scrambling of the neutrino data, and determine our analysis sensitivity by signal injection against these scrambled data sets. We find our analysis is sensitive to nu + gamma transient populations responsible for >5% of the observed gamma-coincident neutrinos in the track data at 90% confidence. Applying our analysis to the unscrambled data reveals no individual nu + gamma events of high significance; two ANTARES track + Fermi gamma-ray events are identified that exceed a once per decade false alarm rate threshold (p = 17%). No evidence for subthreshold nu + gamma source populations is found among the track (p = 39%) or cascade (p = 60%) events. Exploring a possible correlation of high-energy neutrino directions with Fermi gamma-ray sky brightness identified in previous work yields no added support for this correlation. While TXS.0506+056, a blazar and variable (nontransient) Fermi gamma-ray source, has recently been identified as the first source of high-energy neutrinos, the challenges in reconciling observations of the Fermi gamma-ray sky, the IceCube high-energy cosmic neutrinos, and ultrahigh-energy cosmic rays using only blazars suggest a significant contribution by other source populations. Searches for transient sources of high-energy neutrinos thus remain interesting, with the potential for either neutrino clustering or multimessenger coincidence searches to lead to discovery of the first nu + gamma transients. |
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Address  |
[Solares, H. A. Ayala; Cowen, D. F.; DeLaunay, J. J.; Keivani, A.; Mostafa, M.; Murase, K.; Turley, C. F.] Penn State Univ, Dept Phys, 104 Davey Lab, University Pk, PA 16802 USA, Email: cft114@psu.edu |
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Iop Publishing Ltd |
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English |
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0004-637x |
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Notes |
WOS:000503245500001 |
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no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4227 |
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Author |
Trotta, R.; Johannesson, G.; Moskalenko, I.V.; Porter, T.A.; Ruiz de Austri, R.; Strong, A.W. |
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Title |
Constraints on Cosmic-Ray Propagation Models from a Global Bayesian Analysis |
Type |
Journal Article |
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Year |
2011 |
Publication |
Astrophysical Journal |
Abbreviated Journal |
Astrophys. J. |
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Volume |
729 |
Issue |
2 |
Pages |
106 - 16pp |
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Keywords |
astroparticle physics; cosmic rays; diffusion; Galaxy: general; ISM: general; methods: statistical |
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Abstract |
Research in many areas of modern physics such as, e. g., indirect searches for dark matter and particle acceleration in supernova remnant shocks rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays, gamma-rays). While very detailed numerical models of CR propagation exist, a quantitative statistical analysis of such models has been so far hampered by the large computational effort that those models require. Although statistical analyses have been carried out before using semi-analytical models (where the computation is much faster), the evaluation of the results obtained from such models is difficult, as they necessarily suffer from many simplifying assumptions. The main objective of this paper is to present a working method for a full Bayesian parameter estimation for a numerical CR propagation model. For this study, we use the GALPROP code, the most advanced of its kind, which uses astrophysical information, and nuclear and particle data as inputs to self-consistently predict CRs, gamma-rays, synchrotron, and other observables. We demonstrate that a full Bayesian analysis is possible using nested sampling and Markov Chain Monte Carlo methods (implemented in the SuperBayeS code) despite the heavy computational demands of a numerical propagation code. The best-fit values of parameters found in this analysis are in agreement with previous, significantly simpler, studies also based on GALPROP. |
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Address |
[Trotta, R.] Univ London Imperial Coll Sci Technol & Med, Astrophys Grp, Blackett Lab, London SW7 2AZ, England |
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Iop Publishing Ltd |
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0004-637x |
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Notes |
ISI:000288608700029 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
541 |
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Author |
Villaescusa-Navarro, F. et al; Villanueva-Domingo, P. |
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Title |
The CAMELS Project: Public Data Release |
Type |
Journal Article |
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Year |
2023 |
Publication |
Astrophysical Journal Supplement Series |
Abbreviated Journal |
Astrophys. J. Suppl. Ser. |
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Volume |
265 |
Issue |
2 |
Pages |
54 - 14pp |
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Keywords |
Cosmology; Hydrodynamical simulations; Astrostatistics; Galaxy formation |
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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, Lya 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 . |
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Address |
[Villaescusa-Navarro, Francisco; Genel, Shy; Angles-Alcazar, Daniel; Hassan, Sultan; Pisani, Alice; Wong, Kaze W. K.; Coulton, William R.; Steinwandel, Ulrich P.; Spergel, David N.; Burkhart, Blakesley; Wandelt, Benjamin; Somerville, Rachel S.; Bryan, Greg L.; Li, Yin] Flatiron Inst, Ctr Computat Astrophys, 162 5th Ave, New York, NY 10010 USA, Email: camel.simulations@gmail.com |
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IOP Publishing Ltd |
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English |
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ISSN |
0067-0049 |
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Notes |
WOS:000964876300001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5525 |
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Author |
Villaescusa-Navarro, F. et al; Villanueva-Domingo, P. |
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Title |
The CAMELS Multifield Data Set: Learning the Universe's Fundamental Parameters with Artificial Intelligence |
Type |
Journal Article |
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Year |
2022 |
Publication |
Astrophysical Journal Supplement Series |
Abbreviated Journal |
Astrophys. J. Suppl. Ser. |
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Volume |
259 |
Issue |
2 |
Pages |
61 - 14pp |
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Abstract |
We present the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) Multifield Data set (CMD), a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of cosmic gas, dark matter, and stars from more than 2000 distinct simulated universes at several cosmic times. The 2D maps and 3D grids represent cosmic regions that span similar to 100 million light-years and have been generated from thousands of state-of-the-art hydrodynamic and gravity-only N-body simulations from the CAMELS project. Designed to train machine-learning models, CMD is the largest data set of its kind containing more than 70 TB of data. In this paper we describe CMD in detail and outline a few of its applications. We focus our attention on one such task, parameter inference, formulating the problems we face as a challenge to the community. We release all data and provide further technical details at https://camels-multifield-dataset.readthedocs.io. |
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Address |
[Villaescusa-Navarro, Francisco; Nicola, Andrina; Spergel, David N.; Matilla, Jose Manuel Zorrilla; Shao, Helen] Princeton Univ, Dept Astrophys Sci, Peyton Hall, Princeton, NJ 08544 USA, Email: villaescusa.francisco@gmail.com |
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Publisher |
IOP Publishing Ltd |
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English |
Summary Language |
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ISSN |
0067-0049 |
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Notes |
WOS:000780035300001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5194 |
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Author |
Villanueva-Domingo, P.; Gnedin, N.Y.; Mena, O. |
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Title |
Warm Dark Matter and Cosmic Reionization |
Type |
Journal Article |
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Year |
2018 |
Publication |
Astrophysical Journal |
Abbreviated Journal |
Astrophys. J. |
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Volume |
852 |
Issue |
2 |
Pages |
139 - 7pp |
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Keywords |
cosmology: theory; galaxies: formation; intergalactic medium; large-scale structure of universe; methods: numerical |
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Abstract |
In models with dark matter made of particles with keV masses, such as a sterile neutrino, small-scale density perturbations are suppressed, delaying the period at which the lowest mass galaxies are formed and therefore shifting the reionization processes to later epochs. In this study, focusing on Warm Dark Matter (WDM) with masses close to its present lower bound, i.e., around the 3. keV region, we derive constraints from galaxy luminosity functions, the ionization history and the Gunn-Peterson effect. We show that even if star formation efficiency in the simulations is adjusted to match the observed UV galaxy luminosity functions in both CDM and WDM models, the full distribution of Gunn-Peterson optical depth retains the strong signature of delayed reionization in the WDM model. However, until the star formation and stellar feedback model used in modern galaxy formation simulations is constrained better, any conclusions on the nature of dark matter derived from reionization observables remain model-dependent. |
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Address |
[Villanueva-Domingo, Pablo; Mena, Olga] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, Apartado Correos 22085, E-46071 Valencia, Spain, Email: gnedin@fnal.gov |
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Corporate Author |
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Thesis |
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Publisher |
Iop Publishing Ltd |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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ISSN |
0004-637x |
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Notes |
WOS:000422865600009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3455 |
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