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Author |
Maso-Ferrando, A.; Sanchis-Gual, N.; Font, J.A.; Olmo, G.J. |
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Title |
Birth of baby universes from gravitational collapse in a modified-gravity scenario |
Type |
Journal Article |
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Year |
2023 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
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Volume |
06 |
Issue |
6 |
Pages |
028 - 19pp |
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Keywords  |
modified gravity; Wormholes |
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Abstract |
We consider equilibrium models of spherical boson stars in Palatini f (R) = R + CR2 gravity and study their collapse when perturbed. The Einstein-Klein-Gordon system is solved using a recently established correspondence in an Einstein frame representation. We find that, in that frame, the endpoint is a nonrotating black hole surrounded by a quasi -stationary cloud of scalar field. However, the dynamics in the f (R) frame is dramatically different. The innermost region of the collapsing object exhibits the formation of a finite -size, exponentially-expanding baby universe connected with the outer (parent) universe via a minimal area surface (a throat or umbilical cord). Our simulations indicate that this surface is at all times hidden inside a horizon, causally disconnecting the baby universe from observers above the horizon. The implications of our findings in other areas of gravitational physics are also discussed. |
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Address |
[Maso-Ferrando, Andreu; Olmo, Gonzalo J.] Univ Valencia, Ctr Mixto, CSIC, Dept Fis Teor, Valencia 46100, Spain, Email: andreu.maso@uv.es; |
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Publisher |
IOP Publishing Ltd |
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Language |
English |
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ISSN |
1475-7516 |
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Conference |
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Notes |
WOS:001025474200010 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5577 |
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Author |
Herrero-Garcia, J.; Landini, G.; Vatsyayan, D. |
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Title |
Asymmetries in extended dark sectors: a cogenesis scenario |
Type |
Journal Article |
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Year |
2023 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
05 |
Issue |
5 |
Pages |
049 - 41pp |
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Keywords |
Models for Dark Matter; Particle Nature of Dark Matter |
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Abstract |
The observed dark matter relic abundance may be explained by different mechanisms, such as thermal freeze-out/freeze-in, with one or more symmetric/asymmetric components. In this work we investigate the role played by asymmetries in determining the yield and nature of dark matter in non-minimal scenarios with more than one dark matter particle. In particular, we show that the energy density of a particle may come from an asymmetry, even if the particle is asymptotically symmetric by nature. To illustrate the different effects of asymmetries, we adopt a model with two dark matter components. We embed it in a multi-component cogenesis scenario that is also able to reproduce neutrino masses and the baryon asymmetry. In some cases, the model predicts an interesting monochromatic neutrino line that may be searched for at neutrino telescopes. |
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Address |
[Herrero-Garcia, Juan] Univ Valencia, Dept Fis Teor, C Catedrat Jose Beltran 2, E-46980 Paterna, Spain, Email: juan.herrero@ific.uv.es; |
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Publisher |
Springer |
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Language |
English |
Summary Language |
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Series Editor |
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Series Volume |
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Edition |
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ISSN |
1029-8479 |
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Conference |
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Notes |
WOS:000988319500002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5550 |
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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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Corporate Author |
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Publisher |
Edp Sciences S A |
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 |
0004-6361 |
ISBN |
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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 |
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 |
Place of Publication |
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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 |
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 |
NEXT Collaboration (Haefner, J. et al); Benlloch-Rodriguez, J.M.; Carcel, S.; Carrion, J.V.; Martin-Albo, J.; Martinez-Vara, M.; Muñoz Vidal, J.; Novella, P.; Querol, M.; Romo-Luque, C.; Sorel, M.; Uson, A. |
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Title |
Reflectance and fluorescence characteristics of PTFE coated with TPB at visible, UV, and VUV as a function of thickness |
Type |
Journal Article |
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Year |
2023 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
18 |
Issue |
3 |
Pages |
P03016 - 21pp |
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Keywords |
Materials for gaseous detectors; Particle tracking detectors (Gaseous detectors); Time projection chambers |
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Abstract |
Polytetrafluoroethylene (PTFE) is an excellent diffuse reflector widely used in light collection systems for particle physics experiments. In noble element systems, it is often coated with tetraphenyl butadiene (TPB) to allow detection of vacuum ultraviolet scintillation light. In this work this dependence is investigated for PTFE coated with TPB in air for light of wavelengths of 200 nm, 260 nm, and 450 nm. The results show that TPB-coated PTFE has a reflectance of approximately 92% for thicknesses ranging from 5 mm to 10 mm at 450 nm, with negligible variation as a function of thickness within this range. A cross-check of these results using an argon chamber supports the conclusion that the change in thickness from 5 mm to 10 mm does not affect significantly the light response at 128 nm. Our results indicate that pieces of TPB-coated PTFE thinner than the typical 10 mm can be used in particle physics detectors without compromising the light signal. |
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Address |
[Hauptman, J.] Iowa State Univ, Dept Phys & Astron, Ames, IA 50011 USA, Email: adam.fahs@mail.utoronto.ca |
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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 Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
ISBN |
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Area |
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Conference |
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Notes |
WOS:000971136300003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5526 |
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