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Author Bertone, G.; Bozorgnia, N.; Kim, J.S.; Liem, S.; McCabe, C.; Otten, S.; Ruiz de Austri, R.
Title (down) Identifying WIMP dark matter from particle and astroparticle data Type Journal Article
Year 2018 Publication Journal of Cosmology and Astroparticle Physics Abbreviated Journal J. Cosmol. Astropart. Phys.
Volume 03 Issue 3 Pages 026 - 42pp
Keywords dark matter detectors; dark matter experiments; dark matter theory
Abstract One of the most promising strategies to identify the nature of dark matter consists in the search for new particles at accelerators and with so-called direct detection experiments. Working within the framework of simplified models, and making use of machine learning tools to speed up statistical inference, we address the question of what we can learn about dark matter from a detection at the LHC and a forthcoming direct detection experiment. We show that with a combination of accelerator and direct detection data, it is possible to identify newly discovered particles as dark matter, by reconstructing their relic density assuming they are weakly interacting massive particles (WIMPs) thermally produced in the early Universe, and demonstrating that it is consistent with the measured dark matter abundance. An inconsistency between these two quantities would instead point either towards additional physics in the dark sector, or towards a non-standard cosmology, with a thermal history substantially different from that of the standard cosmological model.
Address [Bertone, Gianfranco; Bozorgnia, Nassim; Liem, Sebastian] Univ Amsterdam, GRAPPA Inst, Inst Theoret Phys Amsterdam, Sci Pk 904, NL-1098 XH Amsterdam, Netherlands, Email: g.bertone@uva.nl;
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 1475-7516 ISBN Medium
Area Expedition Conference
Notes WOS:000427501000002 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 3522
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Author Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G.
Title (down) 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 Bertone, G.; Cerdeño, D.G.; Fornasa, M.; Ruiz de Austri, R.; Trotta, R.
Title (down) Identification of dark matter particles with LHC and direct detection data Type Journal Article
Year 2010 Publication Physical Review D Abbreviated Journal Phys. Rev. D
Volume 82 Issue 5 Pages 055008 - 7pp
Keywords
Abstract Dark matter (DM) is currently searched for with a variety of detection strategies. Accelerator searches are particularly promising, but even if weakly interacting massive particles are found at the Large Hadron Collider (LHC), it will be difficult to prove that they constitute the bulk of the DM in the Universe Omega(DM). We show that a significantly better reconstruction of the DM properties can be obtained with a combined analysis of LHC and direct detection data, by making a simple Ansatz on the weakly interacting massive particles local density rho(0)((chi) over bar1), i.e., by assuming that the local density scales with the cosmological relic abundance, (rho(0)((chi) over bar1)/rho(DM)) = (Omega(0)((chi) over bar1)/Omega(DM)). We demonstrate this method in an explicit example in the context of a 24-parameter supersymmetric model, with a neutralino lightest supersymmetric particle in the stau coannihilation region. Our results show that future ton-scale direct detection experiments will allow to break degeneracies in the supersymmetric parameter space and achieve a significantly better reconstruction of the neutralino composition and its relic density than with LHC data alone.
Address [Bertone, G.] Univ Zurich, Inst Theoret Phys, CH-8057 Zurich, Switzerland
Corporate Author Thesis
Publisher Amer Physical Soc Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1550-7998 ISBN Medium
Area Expedition Conference
Notes ISI:000281741400005 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ elepoucu @ Serial 380
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Author Ghosh, P.; Lopez-Fogliani, D.E.; Mitsou, V.A.; Muñoz, C.; Ruiz de Austri, R.
Title (down) Hunting physics beyond the standard model with unusual W-+/- and Z decays Type Journal Article
Year 2015 Publication Physical Review D Abbreviated Journal Phys. Rev. D
Volume 91 Issue 3 Pages 035020 - 8pp
Keywords
Abstract Nonstandard on-shell decays of W-+/- and Z bosons are possible within the framework of extended supersymmetric models, i.e., with singlet states and/or new couplings compared to the minimal supersymmetric standard model. These modes are typically encountered in regions of the parameter space with light singlet-like scalars, pseudoscalars, and neutralinos. In this letter we emphasize how these states can lead to novel signals at colliders from Z- or W-+/--boson decays with prompt or displaced multileptons/tau jets/jets/photons in the final states. These new modes would give distinct evidence of new physics even when direct searches remain unsuccessful. We discuss the possibilities of probing these new signals using the existing LHC run-I data set. We also address the same in the context of the LHC run-II, as well as for the future colliders. We exemplify our observations with the “mu from v” supersymmetric standard model, where three generations of right-handed neutrino superfields are used to solve shortcomings of the minimal supersymmetric standard model. We also extend our discussion for other variants of supersymmetric models that can accommodate similar signatures.
Address [Ghosh, Pradipta; Munoz, Carlos] Univ Autonoma Madrid, Dept Fis Teor, E-28049 Madrid, Spain, Email: pradipta.ghosh@uam.es;
Corporate Author Thesis
Publisher Amer Physical Soc Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1550-7998 ISBN Medium
Area Expedition Conference
Notes WOS:000352305400009 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 2185
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Author Cabrera, M.E.; Casas, J.A.; Mitsou, V.A.; Ruiz de Austri, R.; Terron, J.
Title (down) Histogram comparison tools for the search of new physics at LHC. Application to the CMSSM Type Journal Article
Year 2012 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 04 Issue 4 Pages 133 - 27pp
Keywords Beyond Standard Model; Supersymmetric Standard Model; Statistical Methods
Abstract We propose a rigorous and effective way to compare experimental and theoretical histograms, incorporating the different sources of statistical and systematic uncertainties. This is a useful tool to extract as much information as possible from the comparison between experimental data with theoretical simulations, optimizing the chances of identifying New Physics at the LHC. We illustrate this by showing how a search in the CMSSM parameter space, using Bayesian techniques, can effectively find the correct values of the CMSSM parameters by comparing histograms of events with multijets + missing transverse momentum displayed in the effective-mass variable. The procedure is in fact very efficient to identify the true supersymmetric model, in the case supersymmetry is really there and accessible to the LHC.
Address [Eugenia Cabrera, Maria; Alberto Casas, J.] UAM, IFT UAM CSIC, Inst Fis Teor, E-28049 Madrid, Spain, Email: maria.cabrera@uam.es;
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1126-6708 ISBN Medium
Area Expedition Conference
Notes WOS:000304148100059 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ pastor @ Serial 1053
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