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Author (up) Olmo, G.J.; Rubiera-Garcia, D.; Sanchez-Puente, A.
Title Accelerated observers and the notion of singular spacetime Type Journal Article
Year 2018 Publication Classical and Quantum Gravity Abbreviated Journal Class. Quantum Gravity
Volume 35 Issue 5 Pages 055010 - 18pp
Keywords general relativity; geodesic behaviour; black holes; spacetime singularities; modified theories of gravity
Abstract Geodesic completeness is typically regarded as a basic criterion to determine whether a given spacetime is regular or singular. However, the principle of general covariance does not privilege any family of observers over the others and, therefore, observers with arbitrary motions should be able to provide a complete physical description of the world. This suggests that in a regular spacetime, all physically acceptable observers should have complete paths. In this work we explore this idea by studying the motion of accelerated observers in spherically symmetric spacetimes and illustrate it by considering two geodesically complete black hole spacetimes recently described in the literature. We show that for bound and locally unbound accelerations, the paths of accelerated test particles are complete, providing further support to the regularity of such spacetimes.
Address [Olmo, Gonzalo J.; Sanchez-Puente, Antonio] Univ Valencia, Dept Fis Teor, CSIC, Ctr Mixto, E-46100 Valencia, Spain, Email: gonzalo.olmo@uv.es;
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0264-9381 ISBN Medium
Area Expedition Conference
Notes WOS:000424042100001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 3473
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Author (up) Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G.
Title Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge Type Journal Article
Year 2021 Publication Astronomy & Astrophysics Abbreviated Journal Astron. Astrophys.
Volume 656 Issue Pages A62 - 18pp
Keywords catalogs; gamma rays: general; astroparticle physics; methods: numerical; methods: data analysis; techniques: image processing
Abstract Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.
Address [Panes, Boris] Pontificia Univ Catolica Chile, Ave Vicuna Mackenna 4860, Macul, Region Metropol, Chile, Email: bapanes@gmail.com
Corporate Author Thesis
Publisher Edp Sciences S A Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0004-6361 ISBN Medium
Area Expedition Conference
Notes WOS:000725877600001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5053
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Author (up) Schiavone, T.; Montani, G.; Bombacigno, F.
Title f(R) gravity in the Jordan frame as a paradigm for the Hubble tension Type Journal Article
Year 2023 Publication Monthly Notices of the Royal Astronomical Society Abbreviated Journal Mon. Not. Roy. Astron. Soc.
Volume 522 Issue 1 Pages L72-L77
Keywords supernovae: general; galaxies: distances and redshifts; cosmological parameters; dark energy; cosmology: theory
Abstract We analyse the f(R) gravity in the so-called Jordan frame, as implemented to the isotropic Universe dynamics. The goal of the present study is to show that according to recent data analyses of the supernovae Ia Pantheon sample, it is possible to account for an effective redshift dependence of the Hubble constant. This is achieved via the dynamics of a non-minimally coupled scalar field, as it emerges in the f(R) gravity. We face the question both from an analytical and purely numerical point of view, following the same technical paradigm. We arrive to establish that the expected decay of the Hubble constant with the redshift z is ensured by a form of the scalar field potential, which remains essentially constant for z less than or similar to 0.3, independently if this request is made a priori, as in the analytical approach, or obtained a posteriori, when the numerical procedure is addressed. Thus, we demonstrate that an f(R) dark energy model is able to account for an apparent variation of the Hubble constant due to the rescaling of the Einstein constant by the f(R) scalar mode.
Address [Schiavone, Tiziano] Univ Pisa, Dept Phys Fermi, Largo Bruno Pontecorvo 3, I-56127 Pisa, Italy, Email: tschiavone@fc.ul.pt
Corporate Author Thesis
Publisher Oxford Univ Press Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0035-8711 ISBN Medium
Area Expedition Conference
Notes WOS:001066034100015 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5672
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Author (up) Trotta, R.; Johannesson, G.; Moskalenko, I.V.; Porter, T.A.; Ruiz de Austri, R.; Strong, A.W.
Title Constraints on Cosmic-Ray Propagation Models from a Global Bayesian Analysis Type Journal Article
Year 2011 Publication Astrophysical Journal Abbreviated Journal Astrophys. J.
Volume 729 Issue 2 Pages 106 - 16pp
Keywords astroparticle physics; cosmic rays; diffusion; Galaxy: general; ISM: general; methods: statistical
Abstract Research in many areas of modern physics such as, e. g., indirect searches for dark matter and particle acceleration in supernova remnant shocks rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays, gamma-rays). While very detailed numerical models of CR propagation exist, a quantitative statistical analysis of such models has been so far hampered by the large computational effort that those models require. Although statistical analyses have been carried out before using semi-analytical models (where the computation is much faster), the evaluation of the results obtained from such models is difficult, as they necessarily suffer from many simplifying assumptions. The main objective of this paper is to present a working method for a full Bayesian parameter estimation for a numerical CR propagation model. For this study, we use the GALPROP code, the most advanced of its kind, which uses astrophysical information, and nuclear and particle data as inputs to self-consistently predict CRs, gamma-rays, synchrotron, and other observables. We demonstrate that a full Bayesian analysis is possible using nested sampling and Markov Chain Monte Carlo methods (implemented in the SuperBayeS code) despite the heavy computational demands of a numerical propagation code. The best-fit values of parameters found in this analysis are in agreement with previous, significantly simpler, studies also based on GALPROP.
Address [Trotta, R.] Univ London Imperial Coll Sci Technol & Med, Astrophys Grp, Blackett Lab, London SW7 2AZ, England
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0004-637x ISBN Medium
Area Expedition Conference
Notes ISI:000288608700029 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 541
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