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Author Ferreira, M.N.; Papavassiliou, J. url  doi
openurl 
  Title Gauge Sector Dynamics in QCD Type Journal Article
  Year 2023 Publication Particles Abbreviated Journal Particles  
  Volume 6 Issue 1 Pages 312-363  
  Keywords continuum Schwinger function methods; emergence of hadron mass; gluon mass generation; lattice QCD; non-perturbative quantum field theory; quantum chromodynamics; Schwinger-Dyson equations; Schwinger mechanism  
  Abstract The dynamics of the QCD gauge sector give rise to non-perturbative phenomena that are crucial for the internal consistency of the theory; most notably, they account for the generation of a gluon mass through the action of the Schwinger mechanism, the taming of the Landau pole, the ensuing stabilization of the gauge coupling, and the infrared suppression of the three-gluon vertex. In the present work, we review some key advances in the ongoing investigation of this sector within the framework of the continuum Schwinger function methods, supplemented by results obtained from lattice simulations.  
  Address [Ferreira, Mauricio Narciso; Papavassiliou, Joannis] Univ Valencia, Dept Theoret Phys, E-46100 Valencia, Spain, Email: ansonar@uv.es;  
  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 (up) ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000959126400001 Approved no  
  Is ISI yes International Collaboration no  
  Call Number IFIC @ pastor @ Serial 5504  
Permanent link to this record
 

 
Author Arnalte-Mur, P.; Labatie, A.; Clerc, N.; Martinez, V.J.; Starck, J.L.; Lachieze-Rey, M.; Saar, E.; Paredes, S. url  doi
openurl 
  Title Wavelet analysis of baryon acoustic structures in the galaxy distribution Type Journal Article
  Year 2012 Publication Astronomy & Astrophysics Abbreviated Journal Astron. Astrophys.  
  Volume 542 Issue Pages A34 - 11pp  
  Keywords large-scale structure of Universe; distance scale; galaxies: cluster: general; methods: data analysis; methods: statistical  
  Abstract Context. Baryon acoustic oscillations (BAO) are imprinted in the density field by acoustic waves travelling in the plasma of the early universe. Their fixed scale can be used as a standard ruler to study the geometry of the universe. Aims. The BAO have been previously detected using correlation functions and power spectra of the galaxy distribution. We present a new method to detect the real-space structures associated with BAO. These baryon acoustic structures are spherical shells of relatively small density contrast, surrounding high density central regions. Methods. We design a specific wavelet adapted to search for shells, and exploit the physics of the process by making use of two different mass tracers, introducing a specific statistic to detect the BAO features. We show the effect of the BAO signal in this new statistic when applied to the Lambda – cold dark matter (Lambda CDM) model, using an analytical approximation to the transfer function. We confirm the reliability and stability of our method by using cosmological N-body simulations from the MareNostrum Institut de Ciencies de l'Espai (MICE). Results. We apply our method to the detection of BAO in a galaxy sample drawn from the Sloan Digital Sky Survey (SDSS). We use the “main” catalogue to trace the shells, and the luminous red galaxies (LRG) as tracers of the high density central regions. Using this new method, we detect, with a high significance, that the LRG in our sample are preferentially located close to the centres of shell-like structures in the density field, with characteristics similar to those expected from BAO. We show that stacking selected shells, we can find their characteristic density profile. Conclusions. We delineate a new feature of the cosmic web, the BAO shells. As these are real spatial structures, the BAO phenomenon can be studied in detail by examining those shells.  
  Address [Arnalte-Mur, P.; Martinez, V. J.] Univ Valencia, Astron Observ, Valencia 46071, Spain, Email: pablo.arnalte-mur@durham.ac.uk  
  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 (up) 0004-6361 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000305803300021 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 1088  
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Author ANTARES Collaboration (Adrian-Martinez, S. et al); Barrios-Marti, J.; Bigongiari, C.; Emanuele, U.; Gomez-Gonzalez, J.P.; Hernandez-Rey, J.J.; Lambard, G.; Mangano, S.; Sanchez-Losa, A.; Yepes, H.; Zornoza, J.D.; Zuñiga, J. url  doi
openurl 
  Title Search for muon neutrinos from gamma-ray bursts with the ANTARES neutrino telescope using 2008 to 2011 data Type Journal Article
  Year 2013 Publication Astronomy & Astrophysics Abbreviated Journal Astron. Astrophys.  
  Volume 559 Issue Pages A9 - 11pp  
  Keywords neutrinos; gamma-ray burst: general; methods: numerical  
  Abstract Aims. We search for muon neutrinos in coincidence with GRBs with the ANTARES neutrino detector using data from the end of 2007 to 2011. Methods. Expected neutrino fluxes were calculated for each burst individually. The most recent numerical calculations of the spectra using the NeuCosmA code were employed, which include Monte Carlo simulations of the full underlying photohadronic interaction processes. The discovery probability for a selection of 296 GRBs in the given period was optimised using an extended maximum-likelihood strategy. Results. No significant excess over background is found in the data, and 90% confidence level upper limits are placed on the total expected flux according to the model.  
  Address [Adrian-Martinez, S.; Ardid, M.; Larosa, G.; Martinez-Mora, J. A.] Univ Politecn Valencia, Inst Invest Gestio Integrada Zones Costaneres IGI, Gandia 46730, Spain, Email: criviere@cppm.in2p3.fr;  
  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 (up) 0004-6361 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000327847200009 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 1691  
Permanent link to this record
 

 
Author Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G. url  doi
openurl 
  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 (up) 0004-6361 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000725877600001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5053  
Permanent link to this record
 

 
Author Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Bhattacharyya, S.; Caron, S.; Johannesson, G.; Ruiz de Austri, R.; van den Oetelaar, C.; Zaharijas, G.; Groot, P.J.; Cator, E.; Nelemans, G. url  doi
openurl 
  Title AutoSourceID-Light Fast optical source localization via U-Net and Laplacian of Gaussian Type Journal Article
  Year 2022 Publication Astronomy & Astrophysics Abbreviated Journal Astron. Astrophys.  
  Volume 662 Issue Pages A109 - 8pp  
  Keywords astronomical databases; miscellaneous; methods; data analysis; stars; imaging; techniques; image processing  
  Abstract Aims. With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. Methods. We show that the ASID-L algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter provides outstanding performance in the localization of sources. A U-Net network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location. Results. Using ASID-L on the optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with SExtractor and show that our method outperforms this more widely used method. ASID-L rapidly detects more sources not only in low- and mid-density fields, but particularly in areas with more than 150 sources per square arcminute. The training set and code used in this paper are publicly available.  
  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 (up) 0004-6361 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000818665600009 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5291  
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