| Records |
| Author |
Stoppa, F.; Bhattacharyya, S.; Ruiz de Austri, R.; Vreeswijk, P.; Caron, S.; Zaharijas, G.; Bloemen, S.; Principe, G.; Malyshev, D.; Vodeb, V.; Groot, P.J.; Cator, E.; Nelemans, G. |
| Title |
AutoSourceID-Classifier Star-galaxy classification using a convolutional neural network with spatial information |
Type |
Journal Article |
| Year |
2023 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
| Volume |
680 |
Issue |
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Pages |
A109 - 16pp |
| Keywords |
methods: data analysis; techniques: image processing; astronomical databases: miscellaneous; stars: imaging; Galaxies: statistics |
| Abstract |
Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification's reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images.Methods. The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results.Results. We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C's direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy. |
| Address |
[Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Groot, P. J.; Nelemans, G.] Radboud Univ Nijmegen, Dept Astrophys IMAPP, POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: f.stoppa@astro.ru.nl |
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Thesis |
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Publisher  |
Edp Sciences S A |
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 Issue |
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Edition |
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| ISSN |
0004-6361 |
ISBN |
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Expedition |
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Conference |
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| Notes |
WOS:001131898100001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5888 |
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| Author |
AbdusSalam, S.S. et al; Eberhardt, O. |
| Title |
Simple and statistically sound recommendations for analysing physical theories |
Type |
Journal Article |
| Year |
2022 |
Publication |
Reports on Progress in Physics |
Abbreviated Journal |
Rep. Prog. Phys. |
| Volume |
85 |
Issue |
5 |
Pages |
052201 - 11pp |
| Keywords |
particle physics; statistics; methodology |
| Abstract |
Physical theories that depend on many parameters or are tested against data from many different experiments pose unique challenges to statistical inference. Many models in particle physics, astrophysics and cosmology fall into one or both of these categories. These issues are often sidestepped with statistically unsound ad hoc methods, involving intersection of parameter intervals estimated by multiple experiments, and random or grid sampling of model parameters. Whilst these methods are easy to apply, they exhibit pathologies even in low-dimensional parameter spaces, and quickly become problematic to use and interpret in higher dimensions. In this article we give clear guidance for going beyond these procedures, suggesting where possible simple methods for performing statistically sound inference, and recommendations of readily-available software tools and standards that can assist in doing so. Our aim is to provide any physicists lacking comprehensive statistical training with recommendations for reaching correct scientific conclusions, with only a modest increase in analysis burden. Our examples can be reproduced with the code publicly available at Zenodo. |
| Address |
[AbdusSalam, Shehu S.; Fowlie, Andrew] Shahid Beheshti Univ, Dept Phys, Tehran, Iran, Email: andrew.j.fowlie@njnu.edu.cn |
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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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Series Issue |
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Edition |
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| ISSN |
0034-4885 |
ISBN |
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Expedition |
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Conference |
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| Notes |
WOS:000791574900001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5221 |
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| Author |
Villaescusa-Navarro, F. et al; Villanueva-Domingo, P. |
| Title |
The CAMELS Project: Public Data Release |
Type |
Journal Article |
| Year |
2023 |
Publication |
Astrophysical Journal Supplement Series |
Abbreviated Journal |
Astrophys. J. Suppl. Ser. |
| Volume |
265 |
Issue |
2 |
Pages |
54 - 14pp |
| Keywords |
Cosmology; Hydrodynamical simulations; Astrostatistics; Galaxy formation |
| 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 . |
| 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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Thesis |
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| Publisher |
IOP Publishing Ltd |
Place of Publication |
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| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
0067-0049 |
ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
WOS:000964876300001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5525 |
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| Author |
Jueid, A.; Kip, J.; Ruiz de Austri, R.; Skands, P. |
| Title |
Impact of QCD uncertainties on antiproton spectra from dark-matter annihilation |
Type |
Journal Article |
| Year |
2023 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
| Volume |
04 |
Issue |
4 |
Pages |
068 - 15pp |
| Keywords |
cosmic ray theory; dark matter simulations; cosmic ray experiments; Frequentist statistics |
| Abstract |
Dark-matter particles that annihilate or decay can undergo complex sequences of processes, including strong and electromagnetic radiation, hadronisation, and hadron de-cays, before particles that are stable on astrophysical time scales are produced. Antiprotons produced in this way may leave footprints in experiments such as AMS-02. Several groups have reported an excess of events in the antiproton flux in the rigidity range of 10-20 GV. However, the theoretical modeling of baryon production is not straightforward and relies in part on phenomenological models in Monte Carlo event generators. In this work, we assess the impact of QCD uncertainties on the spectra of antiprotons from dark-matter annihila-tion. As a proof-of-principle, we show that for a two-parameter model that depends only on the thermally-averaged annihilation cross section ((o -v)) and the dark-matter mass (Mx), QCD uncertainties can affect the best-fit mass by up to ti 14% (with large uncertainties for large DM masses), depending on the choice of Mx and the annihilation channel (bb over bar or W+W-), and (o -v) by up to ti 10%. For comparison, changes to the underlying diffusion parameters are found to be within 1%-5%, and the results are also quite resilient to the choice of cosmic-ray propagation model. These findings indicate that QCD uncertainties need to be included in future DM analyses. To facilitate full-fledged analyses, we provide the spectra in tabulated form including QCD uncertainties and code snippets to perform mass interpolations and quick DM fits. The code can be found in this GitHub [1] repository. |
| Address |
[Jueid, Adil] Inst Basic Sci IBS, Ctr Theoret Phys Universe, Daejeon 34126, South Korea, Email: adiljueid@ibs.re.kr; |
| 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 Issue |
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Edition |
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| ISSN |
1475-7516 |
ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
WOS:000985779900007 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5532 |
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| Author |
Amerio, A.; Calore, F.; Serpico, P.D.; Zaldivar, B. |
| Title |
Deepening gamma-ray point-source catalogues with sub-threshold information |
Type |
Journal Article |
| Year |
2024 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
| Volume |
03 |
Issue |
3 |
Pages |
055 - 18pp |
| Keywords |
gamma ray theory; Frequentist statistics |
| Abstract |
We propose a novel statistical method to extend Fermi-LAT catalogues of highlatitude -y-ray sources below their nominal threshold. To do so, we rely on the determination of the differential source -count distribution of sub -threshold sources which only provides the statistical flux distribution of faint sources. By simulating ensembles of synthetic skies, we assess quantitatively the likelihood for pixels in the sky with relatively low -test statistics to be due to sources, therefore complementing the source -count distribution with spatial information. Besides being useful to orient efforts towards multi -messenger and multi -wavelength identification of new -y-ray sources, we expect the results to be especially advantageous for statistical applications such as cross -correlation analyses. |
| Address |
[Amerio, Aurelio; Zaldivar, Bryan] Univ Valencia, Inst Fis Corpuscular IFIC, Calle Catedrat Jose Beltran 2, Paterna 46980, Spain, Email: aurelio.amerio@ific.uv.es; |
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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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Edition |
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| ISSN |
1475-7516 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:001194945600003 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
6032 |
| Permanent link to this record |
