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Author Benisty, D.; Olmo, G.J.; Rubiera-Garcia, D.
Title Singularity-Free and Cosmologically Viable Born-Infeld Gravity with Scalar Matter Type Journal Article
Year 2021 Publication Symmetry-Basel Abbreviated Journal Symmetry-Basel
Volume 13 Issue 11 Pages 2108 - 24pp
Keywords (down) metric-affine gravity; non-singular cosmologies; born-infeld gravity; observational constraints; scalar fields
Abstract The early cosmology, driven by a single scalar field, both massless and massive, in the context of Eddington-inspired Born-Infeld gravity, is explored. We show the existence of nonsingular solutions of bouncing and loitering type (depending on the sign of the gravitational theory's parameter, epsilon) replacing the Big Bang singularity, and discuss their properties. In addition, in the massive case, we find some new features of the cosmological evolution depending on the value of the mass parameter, including asymmetries in the expansion/contraction phases, or a continuous transition between a contracting phase to an expanding one via an intermediate loitering phase. We also provide a combined analysis of cosmic chronometers, standard candles, BAO, and CMB data to constrain the model, finding that for roughly |epsilon|& LSIM;5 & BULL;10-8m2 the model is compatible with the latest observations while successfully removing the Big Bang singularity. This bound is several orders of magnitude stronger than the most stringent constraints currently available in the literature.
Address [Benisty, David] Univ Cambridge, Ctr Math Sci, DAMTP, Wilberforce Rd, Cambridge CB3 0WA, England, Email: benidav@post.bgu.ac.il;
Corporate Author Thesis
Publisher Mdpi Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes WOS:000726717400001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5040
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Author HAWC Collaboration (Alfaro, R. et al); Salesa Greus, F.
Title Validation of standardized data formats and tools for ground-level particle-based gamma-ray observatories Type Journal Article
Year 2022 Publication Astronomy & Astrophysics Abbreviated Journal Astron. Astrophys.
Volume 667 Issue Pages A36 - 12pp
Keywords (down) methods; data analysis; gamma rays; general
Abstract Context. Ground-based gamma-ray astronomy is still a rather young field of research, with strong historical connections to particle physics. This is why most observations are conducted by experiments with proprietary data and analysis software, as is usual in the particle physics field. However, in recent years, this paradigm has been slowly shifting toward the development and use of open-source data formats and tools, driven by upcoming observatories such as the Cherenkov Telescope Array (CTA). In this context, a community-driven, shared data format (the gamma-astro-data-format, or GADF) and analysis tools such as Gammapy and ctools have been developed. So far, these efforts have been led by the Imaging Atmospheric Cherenkov Telescope community, leaving out other types of ground-based gamma-ray instruments. Aims. We aim to show that the data from ground particle arrays, such as the High-Altitude Water Cherenkov (HAWC) observatory, are also compatible with the GADF and can thus be fully analyzed using the related tools, in this case, Gammapy. Methods. We reproduced several published HAWC results using Gammapy and data products compliant with GADF standard. We also illustrate the capabilities of the shared format and tools by producing a joint fit of the Crab spectrum including data from six different gamma-ray experiments. Results. We find excellent agreement with the reference results, a powerful confirmation of both the published results and the tools involved. Conclusions. The data from particle detector arrays such as the HAWC observatory can be adapted to the GADF and thus analyzed with Gammapy. A common data format and shared analysis tools allow multi-instrument joint analysis and effective data sharing. To emphasize this, a sample of Crab nebula event lists is made public with this paper. Because of the complementary nature of pointing and wide-field instruments, this synergy will be distinctly beneficial for the joint scientific exploitation of future observatories such as the Southern Wide-field Gamma-ray Observatory and CTA.
Address [Albert, A.; Durocher, M.; Harding, J. P.] Los Alamos Natl Lab, Phys Div, Los Alamos, NM USA, Email: laura.olivera-nieto@mpi-hd.mpg.de
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:000879223700008 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5408
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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.
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 Pages A109 - 16pp
Keywords (down) 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
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:001131898100001 Approved no
Is ISI yes International Collaboration yes
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.
Title Determining the dark matter distribution in simulated galaxies with deep learning Type Journal Article
Year 2023 Publication Monthly Notices of the Royal Astronomical Society Abbreviated Journal Mon. Not. Roy. Astron. Soc.
Volume 525 Issue 4 Pages 6015-6035
Keywords (down) methods: data analysis; software: simulations; galaxies: general; galaxies: haloes; dark matter
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.
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
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:001072112100006 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5707
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Author Assam, I.; Vijande, J.; Ballester, F.; Perez-Calatayud, J.; Poppe, B.; Siebert, F.A.
Title Evaluation of dosimetric effects of metallic artifact reduction and tissue assignment on Monte Carlo dose calculations for I-125 prostate implants Type Journal Article
Year 2022 Publication Medical Physics Abbreviated Journal Med. Phys.
Volume 49 Issue Pages 6195-6208
Keywords (down) metallic artifact reduction; Monte Carlo dosimetry; post-implant CT; prostate brachytherapy; tissue assignment schemes; voxelized virtual patient model
Abstract Purpose Monte Carlo (MC) simulation studies, aimed at evaluating the magnitude of tissue heterogeneity in I-125 prostate permanent seed implant brachytherapy (BT), customarily use clinical post-implant CT images to generate a virtual representation of a realistic patient model (virtual patient model). Metallic artifact reduction (MAR) techniques and tissue assignment schemes (TAS) are implemented on the post-implant CT images to mollify metallic artifacts due to BT seeds and to assign tissue types to the voxels corresponding to the bright seed spots and streaking artifacts, respectively. The objective of this study is to assess the combined influence of MAR and TAS on MC absorbed dose calculations in post-implant CT-based phantoms. The virtual patient models used for I-125 prostate implant MC absorbed dose calculations in this study are derived from the CT images of an external radiotherapy prostate patient without BT seeds and prostatic calcifications, thus averting the need to implement MAR and TAS. Methods The geometry of the IsoSeed I25.S17plus source is validated by comparing the MC calculated results of the TG-43 parameters for the line source approximation with the TG-43U1S2 consensus data. Four MC absorbed dose calculations are performed in two virtual patient models using the egs_brachy MC code: (1) TG-43-based D-w,w-TG(43), (2) D-w,D-w-MBDC that accounts for interseed scattering and attenuation (ISA), (3) D-m,D-m that examines ISA and tissue heterogeneity by scoring absorbed dose in tissue, and (4) D-w,D-m that unlike D-m,D-m scores absorbed dose in water. The MC absorbed doses (1) and (2) are simulated in a TG-43 patient phantom derived by assigning the densities of every voxel to 1.00 g cm(-3) (water), whereas MC absorbed doses (3) and (4) are scored in the TG-186 patient phantom generated by mapping the mass density of each voxel to tissue according to a CT calibration curve. The MC absorbed doses calculated in this study are compared with VariSeed v8.0 calculated absorbed doses. To evaluate the dosimetric effect of MAR and TAS, the MC absorbed doses of this work (independent of MAR and TAS) are compared to the MC absorbed doses of different I-125 source models from previous studies that were calculated with different MC codes using post-implant CT-based phantoms generated by implementing MAR and TAS on post-implant CT images. Results The very good agreement of TG-43 parameters of this study and the published consensus data within 3% validates the geometry of the IsoSeed I25.S17plus source. For the clinical studies, the TG-43-based calculations show a D-90 overestimation of more than 4% compared to the more realistic MC methods due to ISA and tissue composition. The results of this work generally show few discrepancies with the post-implant CT-based dosimetry studies with respect to the D-90 absorbed dose metric parameter. These discrepancies are mainly Type B uncertainties due to the different I-125 source models and MC codes. Conclusions The implementation of MAR and TAS on post-implant CT images have no dosimetric effect on the I-125 prostate MC absorbed dose calculation in post-implant CT-based phantoms.
Address [Assam, Isong; Siebert, Frank-Andre] UKSH, Clin Radiotherapy Radiooncol, Campus Kiel, Kiel, Germany, Email: Isong.Assam@uksh.de
Corporate Author Thesis
Publisher Wiley Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0094-2405 ISBN Medium
Area Expedition Conference
Notes WOS:000835807200001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5321
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