|   | 
Details
   web
Records
Author Cabrera, M.E.; Casas, J.A.; Mitsou, V.A.; Ruiz de Austri, R.; Terron, J.
Title (up) 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
Permanent link to this record
 

 
Author LHCb Collaboration (Aaij, R. et al); Martinez-Vidal, F.; Oyanguren, A.; Ruiz Valls, P.; Sanchez Mayordomo, C.
Title (up) Identification of beauty and charm quark jets at LHCb Type Journal Article
Year 2015 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 10 Issue Pages P06013 - 29pp
Keywords Performance of High Energy Physics Detectors; Analysis and statistical methods
Abstract Identification of jets originating from beauty and charm quarks is important for measuring Standard Model processes and for searching for new physics. The performance of algorithms developed to select b- and c-quark jets is measured using data recorded by LHCb from proton-proton collisions at root s = 7TeV in 2011 and at root s = 8TeV in 2012. The efficiency for identifying a b (c) jet is about 65%(25%) with a probability for misidentifying a light-parton jet of 0.3% for jets with transverse momentum pT > 20GeV and pseudorapidity 2 : 2 < eta < 4.2. The dependence of the performance on the pT and eta of the jet is also measured.
Address [Bediaga, I.; De Miranda, J. M.; Ferreira Rodrigues, F.; Gomes, A.; Massafferri, A.; Osorio Rodrigues, B.; dos Reis, A. C.; Rodrigues, A. B.] Ctr Brasileiro Pesquisas Fis, Rio De Janeiro, Brazil
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 1748-0221 ISBN Medium
Area Expedition Conference
Notes WOS:000358004200029 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 2314
Permanent link to this record
 

 
Author LHCb Collaboration (Aaij, R. et al); Jashal, B.K.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Vidal, J.
Title (up) Identification of charm jets at LHCb Type Journal Article
Year 2022 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 17 Issue 2 Pages P02028 - 23pp
Keywords Analysis and statistical methods; Pattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors
Abstract The identification of charm jets is achieved at LHCb for data collected in 2015-2018 using a method based on the properties of displaced vertices reconstructed and matched with jets. The performance of this method is determined using a dijet calibration dataset recorded by the LHCb detector and selected such that the jets are unbiased in quantities used in the tagging algorithm. The charm-tagging efficiency is reported as a function of the transverse momentum of the jet. The measured efficiencies are compared to those obtained from simulation and found to be in good agreement.
Address [Leite, J. Baptista; Bediaga, I; Torres, M. Cruz; De Miranda, J. M.; dos Reis, A. C.; Gomes, A.; Massafferri, A.; Machado, D. Torres] Ctr Brasileiro Pesquisas Fis CBPF, Rio De Janeiro, Brazil, Email: dcraik@cern.ch
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 1748-0221 ISBN Medium
Area Expedition Conference
Notes WOS:000770368300015 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5177
Permanent link to this record
 

 
Author Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G.
Title (up) 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
Permanent link to this record
 

 
Author Renner, J.; Cervera-Villanueva, A.; Hernando, J.A.; Izmaylov, A.; Monrabal, F.; Muñoz, J.; Nygren, D.; Gomez-Cadenas, J.J.
Title (up) Improved background rejection in neutrinoless double beta decay experiments using a magnetic field in a high pressure xenon TPC Type Journal Article
Year 2015 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 10 Issue Pages P12020 - 19pp
Keywords Pattern recognition, cluster finding, calibration and fitting methods; Double-beta decay detectors; Time projection chambers; Particle tracking detectors (Gaseous detectors)
Abstract We demonstrate that the application of an external magnetic field could lead to an improved background rejection in neutrinoless double-beta (0 nu beta beta) decay experiments using a high-pressure xenon (HPXe) TPC. HPXe chambers are capable of imaging electron tracks, a feature that enhances the separation between signal events (the two electrons emitted in the 0 nu beta beta decay of Xe-136) and background events, arising chiefly from single electrons of kinetic energy compatible with the end-point of the 0 nu beta beta decay (Q(beta beta)). Applying an external magnetic field of sufficiently high intensity (in the range of 0.5-1 Tesla for operating pressures in the range of 5-15 atmospheres) causes the electrons to produce helical tracks. Assuming the tracks can be properly reconstructed, the sign of the curvature can be determined at several points along these tracks, and such information can be used to separate signal (0 nu beta beta) events containing two electrons producing a track with two different directions of curvature from background (single-electron) events producing a track that should spiral in a single direction. Due to electron multiple scattering, this strategy is not perfectly efficient on an event-by-event basis, but a statistical estimator can be constructed which can be used to reject background events by one order of magnitude at a moderate cost (about 30%) in signal efficiency. Combining this estimator with the excellent energy resolution and topological signature identification characteristic of the HPXe TPC, it is possible to reach a background rate of less than one count per ton-year of exposure. Such a low background rate is an essential feature of the next generation of 0 nu beta beta experiments, aiming to fully explore the inverse hierarchy of neutrino masses.
Address [Renner, J.; Imzaylov, A.; Monrabal, F.; Munoz, J.; Gomez-Cadenas, J. J.] CSIC, Inst Fis Corpuscular IFIC, Calle Catedrat Jose Beltran 2, Valencia 46980, Spain, Email: jrenner@ific.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 1748-0221 ISBN Medium
Area Expedition Conference
Notes WOS:000369998500053 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 2549
Permanent link to this record