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Author |
Giare, W.; Renzi, F.; Melchiorri, A.; Mena, O.; Di Valentino, E. |
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Title |
Cosmological forecasts on thermal axions, relic neutrinos, and light elements |
Type |
Journal Article |
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Year |
2022 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
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Volume |
511 |
Issue |
1 |
Pages |
1373-1382 |
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Keywords |
cosmic background radiation; cosmological parameters; dark matter; early Universe; cosmology: observations |
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Abstract |
One of the targets of future cosmic microwave background (CMB) and baryon acoustic oscillation measurements is to improve the current accuracy in the neutrino sector and reach a much better sensitivity on extra dark radiation in the early Universe. In this paper, we study how these improvements can be translated into constraining power for well-motivated extensions of the standard model of elementary particles that involve axions thermalized before the quantum chromodynamics (QCD) phase transition by scatterings with gluons. Assuming a fiducial Lambda cold dark matter cosmological model, we simulate future data for Stage-IV CMB-like and Dark Energy Spectroscopic Instrument (DESI)-like surveys and analyse a mixed scenario of axion and neutrino hot dark matter. We further account also for the effects of these QCD axions on the light element abundances predicted by big bang nucleosynthesis. The most constraining forecasted limits on the hot relic masses are m(a) less than or similar to 0.92 eV and n-ary sumation m(nu) less than or similar to 0.12 eV at 95 per cent Confidence Level, showing that future cosmic observations can substantially improve the current bounds, supporting multimessenger analyses of axion, neutrino, and primordial light element properties. |
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Address |
[Giare, William; Melchiorri, Alessandro] Univ Roma La Sapienza, Phys Dept, Ple Aldo Moro 2, I-00185 Rome, Italy, Email: william.giare@gmail.com |
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Oxford Univ Press |
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English |
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0035-8711 |
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Conference |
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Notes |
WOS:000770034000012 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5192 |
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Author |
Gammaldi, V.; Zaldivar, B.; Sanchez-Conde, M.A.; Coronado-Blazquez, J. |
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Title |
A search for dark matter among Fermi-LAT unidentified sources with systematic features in machine learning |
Type |
Journal Article |
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Year |
2023 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
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Volume |
520 |
Issue |
1 |
Pages |
1348-1361 |
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Keywords |
astroparticle physics – methods; data analysis – methods; observational – methods; statistical – dark matter – gamma-rays; general |
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Abstract |
Around one-third of the point-like sources in the Fermi-LAT catalogues remain as unidentified sources (unIDs) today. Indeed, these unIDs lack a clear, univocal association with a known astrophysical source. If dark matter (DM) is composed of weakly interacting massive particles (WIMPs), there is the exciting possibility that some of these unIDs may actually be DM sources, emitting gamma-rays from WIMPs annihilation. We propose a new approach to solve the standard, machine learning (ML) binary classification problem of disentangling prospective DM sources (simulated data) from astrophysical sources (observed data) among the unIDs of the 4FGL Fermi-LAT catalogue. We artificially build two systematic features for the DM data which are originally inherent to observed data: the detection significance and the uncertainty on the spectral curvature. We do it by sampling from the observed population of unIDs, assuming that the DM distributions would, if any, follow the latter. We consider different ML models: Logistic Regression, Neural Network (NN), Naive Bayes, and Gaussian Process, out of which the best, in terms of classification accuracy, is the NN, achieving around 93 . 3 per cent +/- 0 . 7 per cent performance. Other ML evaluation parameters, such as the True Ne gativ e and True Positive rates, are discussed in our work. Applying the NN to the unIDs sample, we find that the de generac y between some astrophysical and DM sources can be partially solved within this methodology. None the less, we conclude that there are no DM source candidates among the pool of 4FGL Fermi-LAT unIDs. |
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Address |
[Gammaldi, V; Sanchez-Conde, M. A.; Coronado-Blazquez, J.] Univ Autonoma Madrid, Departamentode Fis Teor, E-28049 Madrid, Spain, Email: viviana.gammaldi@uam.es; |
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Oxford Univ Press |
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English |
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0035-8711 |
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Conference |
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Notes |
WOS:000937053400014 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5489 |
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Author |
Giare, W.; Renzi, F.; Mena, O.; Di Valentino, E.; Melchiorri, A. |
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Title |
Is the Harrison-Zel'dovich spectrum coming back? ACT preference for n(s) similar to 1 and its discordance with Planck |
Type |
Journal Article |
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Year |
2023 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
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Volume |
521 |
Issue |
2 |
Pages |
2911-2918 |
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Keywords |
cosmological parameters; inflation; cosmology: observations; cosmology: theory |
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Abstract |
The Data Release 4 of the Atacama Cosmology Telescope (ACT) shows an agreement with an Harrison-Zel'dovich primordial spectrum (n(s) = 1.009 +/- 0.015), introducing a tension with a significance of 99.3 per cent Confidence Level (CL) with the results from the Planck satellite. The discrepancy on the value of the scalar spectral index is neither alleviated with the addition of large scale structure information nor with the low multipole polarization data. We discuss possible avenues to alleviate the tension relying on either neglecting polarization measurements from ACT or in extending different sectors of the theory. |
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Address |
[Giare, William] Ctr Nazl INFN Studi Avanzati, Galileo Galileo Inst Theoret Phys, Largo Enr Fermi 2, I-50125 Florence, Italy, Email: william.giare@gmail.com |
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Publisher |
Oxford Univ Press |
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English |
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ISSN |
0035-8711 |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000957248500013 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5510 |
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Author |
Schiavone, T.; Montani, G.; Bombacigno, F. |
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Title |
f(R) gravity in the Jordan frame as a paradigm for the Hubble tension |
Type |
Journal Article |
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Year |
2023 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
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Volume |
522 |
Issue |
1 |
Pages |
L72-L77 |
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Keywords |
supernovae: general; galaxies: distances and redshifts; cosmological parameters; dark energy; cosmology: theory |
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Abstract |
We analyse the f(R) gravity in the so-called Jordan frame, as implemented to the isotropic Universe dynamics. The goal of the present study is to show that according to recent data analyses of the supernovae Ia Pantheon sample, it is possible to account for an effective redshift dependence of the Hubble constant. This is achieved via the dynamics of a non-minimally coupled scalar field, as it emerges in the f(R) gravity. We face the question both from an analytical and purely numerical point of view, following the same technical paradigm. We arrive to establish that the expected decay of the Hubble constant with the redshift z is ensured by a form of the scalar field potential, which remains essentially constant for z less than or similar to 0.3, independently if this request is made a priori, as in the analytical approach, or obtained a posteriori, when the numerical procedure is addressed. Thus, we demonstrate that an f(R) dark energy model is able to account for an apparent variation of the Hubble constant due to the rescaling of the Einstein constant by the f(R) scalar mode. |
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Address |
[Schiavone, Tiziano] Univ Pisa, Dept Phys Fermi, Largo Bruno Pontecorvo 3, I-56127 Pisa, Italy, Email: tschiavone@fc.ul.pt |
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Publisher |
Oxford Univ Press |
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English |
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ISSN |
0035-8711 |
ISBN |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:001066034100015 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5672 |
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Author |
de los Rios, M.; Petac, M.; Zaldivar, B.; Bonaventura, N.R.; Calore, F.; Iocco, F. |
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Title |
Determining the dark matter distribution in simulated galaxies with deep learning |
Type |
Journal Article |
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Year |
2023 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
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Volume |
525 |
Issue |
4 |
Pages |
6015-6035 |
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Keywords |
methods: data analysis; software: simulations; galaxies: general; galaxies: haloes; dark matter |
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Abstract |
We present a novel method of inferring the dark matter (DM) content and spatial distribution within galaxies, using convolutional neural networks (CNNs) trained within state-of-the-art hydrodynamical simulations (Illustris-TNG100). Within the controlled environment of the simulation, the framework we have developed is capable of inferring the DM mass distribution within galaxies of mass similar to 10(11)-10(13)M(circle dot) from the gravitationally baryon-dominated internal regions to the DM-rich, baryon-depleted outskirts of the galaxies, with a mean absolute error always below approximate to 0.25 when using photometrical and spectroscopic information. With respect to traditional methods, the one presented here also possesses the advantages of not relying on a pre-assigned shape for the DM distribution, to be applicable to galaxies not necessarily in isolation, and to perform very well even in the absence of spectroscopic observations. |
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Address |
[de los Rios, Martin] Univ Estadual Paulista, ICTP South Amer Inst Fundamental Res, Inst Fis Teor, BR-01140070 Sao Paulo, SP, Brazil, Email: fabio.iocco.astro@gmail.com |
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Publisher |
Oxford Univ Press |
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Language |
English |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0035-8711 |
ISBN |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:001072112100006 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5707 |
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Author |
SCiMMA and SNEWS Collaborations (Baxter, A.L. et al); Colomer, M. |
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Title |
Collaborative experience between scientific software projects using Agile Scrum development |
Type |
Journal Article |
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Year |
2022 |
Publication |
Software-Practice & Experience |
Abbreviated Journal |
Softw.-Pract. Exp. |
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Volume |
52 |
Issue |
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Pages |
2077-2096 |
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Keywords |
Agile; cyberinfrastructure; multimessenger astrophysics; scientific computing; software development |
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Abstract |
Developing sustainable software for the scientific community requires expertise in software engineering and domain science. This can be challenging due to the unique needs of scientific software, the insufficient resources for software engineering practices in the scientific community, and the complexity of developing for evolving scientific contexts. While open-source software can partially address these concerns, it can introduce complicating dependencies and delay development. These issues can be reduced if scientists and software developers collaborate. We present a case study wherein scientists from the SuperNova Early Warning System collaborated with software developers from the Scalable Cyberinfrastructure for Multi-Messenger Astrophysics project. The collaboration addressed the difficulties of open-source software development, but presented additional risks to each team. For the scientists, there was a concern of relying on external systems and lacking control in the development process. For the developers, there was a risk in supporting a user-group while maintaining core development. These issues were mitigated by creating a second Agile Scrum framework in parallel with the developers' ongoing Agile Scrum process. This Agile collaboration promoted communication, ensured that the scientists had an active role in development, and allowed the developers to evaluate and implement the scientists' software requirements. The collaboration provided benefits for each group: the scientists actuated their development by using an existing platform, and the developers utilized the scientists' use-case to improve their systems. This case study suggests that scientists and software developers can avoid scientific computing issues by collaborating and that Agile Scrum methods can address emergent concerns. |
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Address |
[Baxter, Amanda L.; Clark, Michael; Kopec, Abigail; Lang, Rafael F.; Li, Shengchao; Linvill, Mark W.; Milisavljevic, Danny; Weil, Kathryn E.] Purdue Univ, Dept Phys & Astron, W Lafayette, IN 47907 USA, Email: adepoian@purdue.edu; |
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Publisher |
Wiley |
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English |
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ISSN |
0038-0644 |
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Notes |
WOS:000830363800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5305 |
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Author |
Ferrer-Sanchez, A.; Martin-Guerrero, J.; Ruiz de Austri, R.; Torres-Forne, A.; Font, J.A. |
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Title |
Gradient-annihilated PINNs for solving Riemann problems: Application to relativistic hydrodynamics |
Type |
Journal Article |
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Year |
2024 |
Publication |
Computer Methods in Applied Mechanics and Engineering |
Abbreviated Journal |
Comput. Meth. Appl. Mech. Eng. |
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Volume |
424 |
Issue |
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Pages |
116906 - 18pp |
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Keywords |
Riemann problem; Euler equations; Machine learning; Neural networks; Relativistic hydrodynamics |
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Abstract |
We present a novel methodology based on Physics-Informed Neural Networks (PINNs) for solving systems of partial differential equations admitting discontinuous solutions. Our method, called Gradient-Annihilated PINNs (GA-PINNs), introduces a modified loss function that forces the model to partially ignore high-gradients in the physical variables, achieved by introducing a suitable weighting function. The method relies on a set of hyperparameters that control how gradients are treated in the physical loss. The performance of our methodology is demonstrated by solving Riemann problems in special relativistic hydrodynamics, extending earlier studies with PINNs in the context of the classical Euler equations. The solutions obtained with the GA-PINN model correctly describe the propagation speeds of discontinuities and sharply capture the associated jumps. We use the relative l(2) error to compare our results with the exact solution of special relativistic Riemann problems, used as the reference ''ground truth'', and with the corresponding error obtained with a second-order, central, shock-capturing scheme. In all problems investigated, the accuracy reached by the GA-PINN model is comparable to that obtained with a shock-capturing scheme, achieving a performance superior to that of the baseline PINN algorithm in general. An additional benefit worth stressing is that our PINN-based approach sidesteps the costly recovery of the primitive variables from the state vector of conserved variables, a well-known drawback of grid-based solutions of the relativistic hydrodynamics equations. Due to its inherent generality and its ability to handle steep gradients, the GA-PINN methodology discussed in this paper could be a valuable tool to model relativistic flows in astrophysics and particle physics, characterized by the prevalence of discontinuous solutions. |
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Address |
[Ferrer-Sanchez, Antonio; Martin-Guerrero, JoseD.] ETSE UV, Elect Engn Dept, IDAL, Avgda Univ S-N, Valencia 46100, Spain, Email: Antonio.Ferrer-Sanchez@uv.es |
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Publisher |
Elsevier Science Sa |
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English |
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ISSN |
0045-7825 |
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Notes |
WOS:001221797400001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
6126 |
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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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Keywords |
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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 |
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Series Volume |
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Edition |
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ISSN |
0067-0049 |
ISBN |
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Area |
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Conference |
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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 |
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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Publisher |
IOP Publishing Ltd |
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English |
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ISSN |
0067-0049 |
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Expedition |
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Conference |
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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 |
Liang, J.; Singh, B.; McCutchan, E.A.; Dillmann, I.; Birch, M.; Sonzogni, A.A.; Huang, X.; Kang, M.; Wang, J.; Mukherjee, G.; Banerjee, K.; Abriola, D.; Algora, A.; Chen, A.A.; Johnson, T.D.; Miernik, K. |
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Title |
Compilation and Evaluation of Beta-Delayed Neutron Emission Probabilities and Half-Lives for Z > 28 Precursors |
Type |
Journal Article |
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Year |
2020 |
Publication |
Nuclear Data Sheets |
Abbreviated Journal |
Nucl. Data Sheets |
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Volume |
168 |
Issue |
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Pages |
1-116 |
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Abstract |
We present a compilation and evaluation of experimental beta-delayed neutron emission probabilities (P-n) and half-lives (T-1/2) for known or potential beta-delayed neutron precursors with atomic number Z > 28 (Cu-73 – Fr-233). This article includes the recommended values of both of these quantities, together with a compilation of experimental measurements when available. Some notable cases, as well as proposed standards for beta-delayed neutron measurements are also discussed. Evaluated data has also been compared to systematics using three different approaches. The literature cut-off date for this work is August 15, 2020. |
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Address |
[Liang, J.; Singh, B.; Birch, M.; Chen, A. A.] McMaster Univ, Dept Phys & Astron, Hamilton, ON L8S 4M1, Canada, Email: balraj@mcmaster.ca |
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Academic Press Inc Elsevier Science |
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English |
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ISSN |
0090-3752 |
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Notes |
WOS:000575888800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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IFIC @ pastor @ |
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4560 |
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