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Author |
Stoppa, F.; Ruiz de Austri, R.; Vreeswijk, P.; Bhattacharyya, S.; Caron, S.; Bloemen, S.; Zaharijas, G.; Principe, G.; Vodeb, V.; Groot, P.J.; Cator, E.; Nelemans, G. |
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Title |
AutoSourceID-FeatureExtractor Optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation |
Type |
Journal Article |
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Year |
2023 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal  |
Astron. Astrophys. |
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Volume |
680 |
Issue |
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Pages |
A108 - 14pp |
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Keywords |
astronomical databases: miscellaneous; methods: data analysis; stars: imaging; techniques: image processing |
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Abstract |
Aims. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement. We aim to design a network that can accurately estimate sources' features and their uncertainties from single-band image cutouts, given the approximated locations of the sources provided by the previously developed code AutoSourceID-Light (ASID-L) or other external catalogues. This work serves as a proof of concept, showing the potential of machine learning in estimating astronomical features when trained on meticulously crafted synthetic images and subsequently applied to real astronomical data.Methods. The algorithm presented here, AutoSourceID-FeatureExtractor (ASID-FE), uses single-band cutouts of 32x32 pixels around the localised sources to estimate flux, sub-pixel centre coordinates, and their uncertainties. ASID-FE employs a two-step mean variance estimation (TS-MVE) approach to first estimate the features and then their uncertainties without the need for additional information, for example the point spread function (PSF). For this proof of concept, we generated a synthetic dataset comprising only point sources directly derived from real images, ensuring a controlled yet authentic testing environment.Results. We show that ASID-FE, trained on synthetic images derived from the MeerLICHT telescope, can predict more accurate features with respect to similar codes such as SourceExtractor and that the two-step method can estimate well-calibrated uncertainties that are better behaved compared to similar methods that use deep ensembles of simple MVE networks. Finally, we evaluate the model on real images from the MeerLICHT telescope and the Zwicky Transient Facility (ZTF) to test its transfer learning abilities. |
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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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Edp Sciences S A |
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English |
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ISSN |
0004-6361 |
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Conference |
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Notes |
WOS:001131898100003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5887 |
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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. |
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Title |
AutoSourceID-Classifier Star-galaxy classification using a convolutional neural network with spatial information |
Type |
Journal Article |
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Year |
2023 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
680 |
Issue |
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Pages |
A109 - 16pp |
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Keywords |
methods: data analysis; techniques: image processing; astronomical databases: miscellaneous; stars: imaging; Galaxies: statistics |
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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. |
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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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Publisher |
Edp Sciences S A |
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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 |
0004-6361 |
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Expedition |
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Conference |
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Notes |
WOS:001131898100001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5888 |
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Author |
ANTARES Collaboration (Albert, A. et al); Barrios-Marti, J.; Coleiro, A.; Hernandez-Rey, J.J.; Illuminati, G.; Lotze, M.; Tönnis, C.; Zornoza, J.D.; Zuñiga, J. |
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Title |
An Algorithm for the Reconstruction of Neutrino-induced Showers in the ANTARES Neutrino Telescope |
Type |
Journal Article |
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Year |
2017 |
Publication |
Astronomical Journal |
Abbreviated Journal |
Astron. J. |
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Volume |
154 |
Issue |
6 |
Pages |
275 - 9pp |
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Keywords |
neutrinos; telescopes |
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Abstract |
Muons created by nu(mu) charged current (CC) interactions in the water surrounding the ANTARES neutrino telescope have been almost exclusively used so far in searches for cosmic neutrino sources. Due to their long range, highly energetic muons inducing Cherenkov radiation in the water are reconstructed with dedicated algorithms that allow for the determination of the parent neutrino direction with a median angular resolution of about 0 degrees.4 for an E-2 neutrino spectrum. In this paper, an algorithm optimized for accurate reconstruction of energy and direction of shower events in the ANTARES detector is presented. Hadronic showers of electrically charged particles are produced by the disintegration of the nucleus both in CC and neutral current interactions of neutrinos in water. In addition, electromagnetic showers result from the CC interactions of electron neutrinos while the decay of a tau lepton produced in nu(tau) CC interactions will, in most cases, lead to either a hadronic or an electromagnetic shower. A shower can be approximated as a point source of photons. With the presented method, the shower position is reconstructed with a precision of about 1 m; the neutrino direction is reconstructed with a median angular resolution between 2 degrees and 3 degrees in the energy range of 1-1000 TeV. In this energy interval, the uncertainty on the reconstructed neutrino energy is about 5%-10%. The increase in the detector sensitivity due to the use of additional information from shower events in the searches for a cosmic neutrino flux is also presented. |
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Address |
[Albert, A.; Drouhin, D.; Racca, C.] Univ Haute Alsace, GRPHE, Inst Univ Technol Colmar, 34 Rue Grillenbreit,BP 50568, F-68008 Colmar, France |
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Corporate Author |
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Publisher |
Iop Publishing Ltd |
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English |
Summary Language |
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Original Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0004-6256 |
ISBN |
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Expedition |
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Conference |
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Notes |
WOS:000425438400001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3498 |
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| Permanent link to this record |
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Author |
ANTARES Collaboration (Aguilar, J.A. et al); Bigongiari, C.; Dornic, D.; Emanuele, U.; Gomez-Gonzalez, J.P.; Hernandez-Rey, J.J.; Mangano, S.; Salesa, F.; Toscano, S.; Yepes, H.; Zornoza, J.D.; Zuñiga, J. |
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Title |
Zenith distribution and flux of atmospheric muons measured with the 5-line ANTARES detector |
Type |
Journal Article |
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Year |
2010 |
Publication |
Astroparticle Physics |
Abbreviated Journal |
Astropart Phys. |
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Volume |
34 |
Issue |
3 |
Pages |
179-184 |
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Keywords |
Atmospheric muons; Neutrino telescope; Depth-intensity relation |
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Abstract |
The ANTARES high-energy neutrino telescope is a three-dimensional array of about 900 photomultipliers distributed over 12 mooring lines installed in the Mediterranean Sea. Between February and November 2007 it acquired data in a 5-line configuration. The zenith angular distribution of the atmospheric muon flux and the associated depth-intensity relation are measured and compared with previous measurements and Monte Carlo expectations. An evaluation of the systematic effects due to uncertainties on environmental and detector parameters is presented. |
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Address |
[Bazzotti, M.; Biagi, S.; Carminati, G.; Giacomelli, G.; Margiotta, A.; Spurio, M.] Dipartimento Fis Univ, I-40127 Bologna, Italy, Email: Annarita.Margiotta@bo.infn.it |
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Publisher |
Elsevier Science Bv |
Place of Publication |
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Language |
English |
Summary Language |
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Original 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 |
0927-6505 |
ISBN |
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Conference |
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Notes |
ISI:000282496000005 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ elepoucu @ |
Serial |
373 |
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| Permanent link to this record |
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Author |
ANTARES Collaboration (Aguilar, J.A. et al); Bigongiari, C.; Dornic, D.; Emanuele, U.; Gomez-Gonzalez, J.P.; Hernandez-Rey, J.J.; Mangano, S.; Salesa, F.; Toscano, S.; Yepes, H.; Zornoza, J.D.; Zuñiga, J. |
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Title |
A fast algorithm for muon track reconstruction and its application to the ANTARES neutrino telescope |
Type |
Journal Article |
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Year |
2011 |
Publication |
Astroparticle Physics |
Abbreviated Journal |
Astropart Phys. |
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Volume |
34 |
Issue |
9 |
Pages |
652-662 |
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Keywords |
Neutrino telescope; Track reconstruction |
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Abstract |
An algorithm is presented, that provides a fast and robust reconstruction of neutrino induced upward-going muons and a discrimination of these events from downward-going atmospheric muon background in data collected by the ANTARES neutrino telescope. The algorithm consists of a hit merging and hit selection procedure followed by fitting steps for a track hypothesis and a point-like light source. It is particularly well-suited for real time applications such as online monitoring and fast triggering of optical follow-up observations for multi-messenger studies. The performance of the algorithm is evaluated with Monte Carlo simulations and various distributions are compared with that obtained in ANTARES data. |
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Address |
[Carminati, G.] Leiden Univ, NL-2300 RA Leiden, Netherlands, Email: brunner@ifh.de |
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Corporate Author |
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Thesis |
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Publisher |
Elsevier Science Bv |
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 |
0927-6505 |
ISBN |
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Conference |
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Notes |
ISI:000289329100002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
608 |
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| Permanent link to this record |
