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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 |
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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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Edp Sciences S A |
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English |
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0004-6361 |
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WOS:001131898100001 |
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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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Dorigo, T. et al; Ramos, A.; Ruiz de Austri, R. |
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Title |
Toward the end-to-end optimization of particle physics instruments with differentiable programming |
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Journal Article |
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Year |
2023 |
Publication |
Reviews in Physics |
Abbreviated Journal |
Rev. Phys. |
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Volume |
10 |
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Pages |
100085 - pp |
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Abstract |
The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, due to the large dimensionality of the space of possible choices for geometry, detection technology, materials, data-acquisition, and information-extraction techniques, and the interdependence of the related parameters. On the other hand, massive potential gains in performance over standard, “experience-driven” layouts are in principle within our reach if an objective function fully aligned with the final goals of the instrument is maximized through a systematic search of the configuration space. The stochastic nature of the involved quantum processes make the modeling of these systems an intractable problem from a classical statistics point of view, yet the construction of a fully differentiable pipeline and the use of deep learning techniques may allow the simultaneous optimization of all design parameters. |
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no |
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yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
6096 |
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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 |
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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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Elsevier Science Sa |
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English |
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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 |
Roszkowski, L.; Ruiz de Austri, R.; Trotta, R.; Tsai, Y.L.S.; Varley, T.A. |
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Title |
Global fits of the nonuniversal Higgs model |
Type |
Journal Article |
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Year |
2011 |
Publication |
Physical Review D |
Abbreviated Journal |
Phys. Rev. D |
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Volume |
83 |
Issue |
1 |
Pages |
015014 - 19pp |
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Abstract |
We carry out global fits to the nonuniversal Higgs Model (NUHM), applying all relevant present-day constraints. We present global probability maps for the NUHM parameters and observables (including collider signatures, direct, and indirect detection quantities), both in terms of posterior probabilities and in terms of profile likelihood maps. We identify regions of the parameter space where the neutralino dark matter in the model is either binolike, or else higgsinolike with mass close to 1 TeV and a spin-independent scattering cross section similar to 10(-9)-10(-8) pb. We trace the occurrence of the higgsinolike region to be a consequence of a mild focusing effect in the running of one of the Higgs masses, the existence of which in the NUHM we identify in our analysis. Although the usual binolike neutralino is more prominent, higgsinolike dark matter cannot be excluded, however its significance strongly depends on the prior and statistics used to assess it. We note that, despite experimental constraints often favoring different regions of parameter space to the constrained minimal supersymmetric standard model, most observational consequences appear fairly similar, which will make it challenging to distinguish the two models experimentally. |
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Address |
[Roszkowski, Leszek; Tsai, Yue-Lin Sming; Varley, Tom A.] Univ Sheffield, Dept Phys & Astron, Sheffield S3 7RH, S Yorkshire, England, Email: L.Roszkowski@sheffield.ac.uk |
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Amer Physical Soc |
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English |
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ISSN |
1550-7998 |
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Notes |
ISI:000286765800007 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
586 |
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Author |
Cabrera, M.E.; Casas, J.A.; Ruiz de Austri, R.; Trotta, R. |
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Title |
Quantifying the tension between the Higgs mass and (g-2)(mu) in the constrained MSSM |
Type |
Journal Article |
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Year |
2011 |
Publication |
Physical Review D |
Abbreviated Journal |
Phys. Rev. D |
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Volume |
84 |
Issue |
1 |
Pages |
015006 - 7pp |
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Abstract |
Supersymmetry has often been invoked as the new physics that might reconcile the experimental muon magnetic anomaly, a(mu), with the theoretical prediction (basing the computation of the hadronic contribution on e(+)e(-) data). However, in the context of the constrained minimal supersymmetric standard model (CMSSM), the required supersymmetric contributions (which grow with decreasing supersymmetric masses) are in potential tension with a possibly large Higgs mass (which requires large stop masses). In the limit of very large m(h) supersymmetry gets decoupled, and the CMSSM must show the same discrepancy as the standard model with a(mu). But it is much less clear for which size of m(h) does the tension start to be unbearable. In this paper, we quantify this tension with the help of Bayesian techniques. We find that for m(h) >= 125 GeV the maximum level of discrepancy given the current data (similar to 3.2 sigma) is already achieved. Requiring less than 3 sigma discrepancy, implies m(h) less than or similar to 120 GeV. For a larger Higgs mass we should give up either the CMSSM model or the computation of a(mu) based on e(+)e(-); or accept living with such an inconsistency. |
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Address |
[Cabrera, ME; Casas, JA] UAM, IFT UAM CSIC, Inst Fis Teor, Madrid 28049, Spain, Email: maria.cabrera@uam.es |
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Publisher |
Amer Physical Soc |
Place of Publication |
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Language |
English |
Summary Language |
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Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1550-7998 |
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Notes |
WOS:000292547200003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
680 |
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