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Villanueva-Domingo, P.; Villaescusa-Navarro, F.; Genel, S.; Angles-Alcazar, D.; Hernquist, L.; Marinacci, F.; Spergel, D.N.; Vogelsberger, M.; Narayanan, D. |
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Title |
Weighing the Milky Way and Andromeda galaxies with artificial intelligence |
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Journal Article |
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Year |
2023 |
Publication |
Physical Review D |
Abbreviated Journal |
Phys. Rev. D |
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Volume |
107 |
Issue |
10 |
Pages |
103003 - 8pp |
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Abstract |
We present new constraints on the masses of the halos hosting the Milky Way and Andromeda galaxies derived using graph neural networks. Our models, trained on 2,000 state-of-the-art hydrodynamic simulations of the CAMELS project, only make use of the positions, velocities and stellar masses of the galaxies belonging to the halos, and are able to perform likelihood-free inference on halo masses while accounting for both cosmological and astrophysical uncertainties. Our constraints are in agreement with estimates from other traditional methods, within our derived posterior standard deviation. |
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Address |
[Villanueva-Domingo, Pablo; Narayanan, Desika] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, E-46980 Paterna, Spain, Email: pablo.villanueva.domingo@gmail.com; |
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Publisher |
Amer Physical Soc |
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English |
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Edition |
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ISSN |
2470-0010 |
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Notes |
WOS:000988340900001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5539 |
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Author |
Villanueva-Domingo, P.; Villaescusa-Navarro, F.; Angles-Alcazar, D.; Genel, S.; Marinacci, F.; Spergel, D.N.; Hernquist, L.; Vogelsberger, M.; Dave, R.; Narayanan, D. |
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Title |
Inferring Halo Masses with Graph Neural Networks |
Type |
Journal Article |
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Year |
2022 |
Publication |
Astrophysical Journal |
Abbreviated Journal |
Astrophys. J. |
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Volume |
935 |
Issue |
1 |
Pages |
30 - 15pp |
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Keywords |
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Abstract |
Understanding the halo-galaxy connection is fundamental in order to improve our knowledge on the nature and properties of dark matter. In this work, we build a model that infers the mass of a halo given the positions, velocities, stellar masses, and radii of the galaxies it hosts. In order to capture information from correlations among galaxy properties and their phase space, we use Graph Neural Networks (GNNs), which are designed to work with irregular and sparse data. We train our models on galaxies from more than 2000 state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations project. Our model, which accounts for cosmological and astrophysical uncertainties, is able to constrain the masses of the halos with a similar to 0.2 dex accuracy. Furthermore, a GNN trained on a suite of simulations is able to preserve part of its accuracy when tested on simulations run with a different code that utilizes a distinct subgrid physics model, showing the robustness of our method. The PyTorch Geometric implementation of the GNN is publicly available on GitHub (https://github.com/PabloVD/HaloGraphNet). |
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Address |
[Villanueva-Domingo, Pablo] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, E-46980 Paterna, Spain, Email: pablo.villanueva.domingo@gmail.com; |
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Publisher |
IOP Publishing Ltd |
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English |
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ISSN |
0004-637x |
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Notes |
WOS:000838320900001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5325 |
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Permanent link to this record |
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Author |
Villaescusa-Navarro, F.; Vogelsberger, M.; Viel, M.; Loeb, A. |
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Title |
Neutrino signatures on the high-transmission regions of the Lyman alpha forest |
Type |
Journal Article |
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Year |
2013 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
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Volume |
431 |
Issue |
4 |
Pages |
3670-3677 |
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Keywords |
neutrinos; intergalactic medium; quasars: absorption lines; cosmology: theory; large-scale structure of Universe |
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Abstract |
We quantify the impact of massive neutrinos on the statistics of low-density regions in the intergalactic medium as probed by the Lyman alpha forest at redshifts z = 2.2-4. Based on mock but realistic quasar (QSO) spectra extracted from hydrodynamic simulations with cold dark matter, baryons and neutrinos, we find that the probability distribution of weak Lyman alpha absorption features, as sampled by Lyman alpha flux regions at high transmissivity, is strongly affected by the presence of massive neutrinos. We show that systematic errors affecting the Lyman alpha forest reduce but do not erase the neutrino signal. Using the Fisher matrix formalism, we conclude that the sum of the neutrino masses can be measured, using the method proposed in this paper, with a precision smaller than 0.4 eV using a catalogue of 200 high-resolution (signal-to-noise ratio similar to 100) QSO spectra. This number reduces to 0.27 eV by making use of reasonable priors in the other parameters that also affect the statistics of the high-transitivity regions of the Lyman alpha forest. The constraints obtained with this method can be combined with independent bounds from the cosmic microwave background, large-scale structures and measurements of the matter power spectrum from the Lyman alpha forest to produce tighter upper limits on the sum of the masses of the neutrinos. |
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Address |
Univ Valencia, IFIC, CSIC, E-46071 Valencia, Spain, Email: viel@oats.inaf.it |
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Thesis |
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Publisher |
Oxford Univ Press |
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 Issue |
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Edition |
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ISSN |
0035-8711 |
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Notes |
WOS:000319479000057 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
1458 |
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Permanent link to this record |