IFIC Home

IFIC Literature Database

Home |  Show All |  Simple Search |  Advanced Search
Quick Search:
1-10 of 27 records found matching your query:
toggle visibility Search & Display Options
Select All    Deselect All << 1 2 3 >>
List View
 | 
Citations
 | 
Details
   print
  Records Links
Author (down) Sanchis-Lozano, M.A.; Sanz, V. url  doi
openurl 
  Title Observable imprints of primordial gravitational waves on the temperature anisotropies of the cosmic microwave background Type Journal Article
  Year 2024 Publication Physical Review D Abbreviated Journal Phys. Rev. D  
  Volume 109 Issue 6 Pages 063529 - 11pp  
  Keywords  
  Abstract We examine the contribution of tensor modes, in addition to the dominant scalar ones, on the temperature anisotropies of the cosmic microwave background (CMB). To this end, we analyze in detail the temperature two -point angular correlation function C(Theta) from the Planck 2018 dataset, focusing on large angles (Theta greater than or similar to 120 degrees) corresponding to small l multipoles. A hierarchical set of infrared cutoffs are naturally introduced to the scalar and tensor power spectra of the CMB by invoking an extra Kaluza-Klein spatial dimension compactifying at about the grand unified theory scale between the Planck epoch and the start of inflation. We associate this set of lower scalar and tensor cutoffs with the parity of the multipole expansion of the C(Theta) function. By fitting the Planck 2018 data we compute the multipole coefficients, thereby reproducing the well-known odd -parity preference in angular correlations seen by all three satellite missions: Cosmic Background Explorer, WMAP, and Planck. Our fits improve significantly once tensor modes are included in the analysis, hence providing a hint of the imprints of primordial gravitational waves on the temperature correlations observed in the CMB today. To conclude, we suggest a relationship between, on the one hand, the lack of (positive) large -angle correlations and the odd -parity dominance in the CMB and, on the other hand, the effect of primordial gravitational waves on the CMB temperature anisotropies.  
  Address [Sanchis-Lozano, Miguel -Angel; Sanz, Veronica] Univ Valencia, Dept Fis Teor, CSIC, Valencia 46100, Spain, Email: miguel.angel.sanchis@ific.uv.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 2470-0010 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001195716600006 Approved no  
  Is ISI yes International Collaboration no  
  Call Number IFIC @ pastor @ Serial 6038  
Permanent link to this record
 
 
Author (down) LHC BSM Reinterpretation Forum (Abdallah, W. et al); Mitsou, V.A.; Sanz, V. url  doi
openurl 
  Title Reinterpretation of LHC results for new physics: status and recommendations after run 2 Type Journal Article
  Year 2020 Publication Scipost Physics Abbreviated Journal SciPost Phys.  
  Volume 9 Issue 2 Pages 022 - 45pp  
  Keywords  
  Abstract We report on the status of efforts to improve the reinterpretation of searches and measurements at the LHC in terms of models for new physics, in the context of the LHC Reinterpretation Forum. We detail current experimental offerings in direct searches for new particles, measurements, technical implementations and Open Data, and provide a set of recommendations for further improving the presentation of LHC results in order to better enable reinterpretation in the future. We also provide a brief description of existing software reinterpretation frameworks and recent global analyses of new physics that make use of the current data.  
  Address [Abdallah, Waleed; Dutta, Juhi] Harish Chandra Res Inst HBNI, Allahabad 211019, Uttar Pradesh, India, Email: Andy.Buckley@glasgow.ac.uk;  
  Corporate Author Thesis  
  Publisher Scipost Foundation Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2542-4653 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000573102600007 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4547  
Permanent link to this record
 
 
Author (down) Lessa, A.; Sanz, V. url  doi
openurl 
  Title Going beyond Top EFT Type Journal Article
  Year 2024 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 04 Issue 4 Pages 107 - 29pp  
  Keywords SMEFT; Dark Matter at Colliders; Supersymmetry  
  Abstract We present a new way to interpret Top Standard Model measurements going beyond the SMEFT framework. Instead of the usual paradigm in Top EFT, where the main effects come from tails in momenta distributions, we propose an interpretation in terms of new physics which only shows up at loop-level. The effects of these new states, which can be lighter than required within the SMEFT, appear as distinctive structures at high momenta, but may be suppressed at the tails of distributions. As an illustration of this phenomena, we present the explicit case of a UV model with a Z \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \mathcal{Z} $$\end{document} 2 symmetry, including a Dark Matter candidate and a top-partner. This simple UV model reproduces the main features of this class of signatures, particularly a momentum-dependent form factor with more structure than the SMEFT. As the new states can be lighter than in SMEFT, we explore the interplay between the reinterpretation of direct searches for colored states and Dark Matter, and Top measurements, made by ATLAS and CMS in the differential t t over bar \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ t\overline{t} $$\end{document} final state. We also compare our method with what one would expect using the SMEFT reinterpretation, finding that using the full loop information provides a better discriminating power.  
  Address [Lessa, Andre] Univ Fed ABC, Ctr Ciencias Nat & Humanas, BR-09210580 Santo Andre, SP, Brazil, Email: andre.lessa@ufabc.edu.br  
  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 1029-8479 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001205498200004 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 6108  
Permanent link to this record
 
 
Author (down) Khosa, C.K.; Sanz, V.; Soughton, M. url  doi
openurl 
  Title Using machine learning to disentangle LHC signatures of Dark Matter candidates Type Journal Article
  Year 2021 Publication Scipost Physics Abbreviated Journal SciPost Phys.  
  Volume 10 Issue 6 Pages 151 - 26pp  
  Keywords  
  Abstract We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and propose a set of benchmark models for the study: a typical WIMP Dark Matter candidate in the form of a SUSY neutralino, a pseudo-Goldstone impostor in the shape of an Axion-Like Particle, and a light Dark Matter impostor whose interactions are mediated by a heavy particle. All these benchmarks are tensioned against each other, and against the main SM background (Z+jets). Our analysis uses both the leading-order kinematic features as well as the information of an additional hard jet. We explore different representations of the data, from a simple event data sample with values of kinematic variables fed into a Logistic Regression algorithm or a Fully Connected Neural Network, to a transformation of the data into images related to probability distributions, fed to Deep and Convolutional Neural Networks. We also study the robustness of our method against including detector effects, dropping kinematic variables, or changing the number of events per image. In the case of signals with more combinatorial possibilities (events with more than one hard jet), the most crucial data features are selected by performing a Principal Component Analysis. We compare the performance of all these methods, and find that using the 2D images of the combined information of multiple events significantly improves the discrimination performance.  
  Address [Khosa, Charanjit Kaur; Sanz, Veronica; Soughton, Michael] Univ Sussex, Dept Phys & Astron, Brighton BN1 9QH, E Sussex, England, Email: Charanjit.Kaur@sussex.ac.uk;  
  Corporate Author Thesis  
  Publisher Scipost Foundation Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2542-4653 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000680038800002 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4927  
Permanent link to this record
 
 
Author (down) Khosa, C.K.; Sanz, V.; Soughton, M. url  doi
openurl 
  Title A simple guide from machine learning outputs to statistical criteria in particle physics Type Journal Article
  Year 2022 Publication Scipost Physics Core Abbreviated Journal SciPost Phys. Core  
  Volume 5 Issue 4 Pages 050 - 31pp  
  Keywords  
  Abstract In this paper we propose ways to incorporate Machine Learning training outputs into a study of statistical significance. We describe these methods in supervised classification tasks using a CNN and a DNN output, and unsupervised learning based on a VAE. As use cases, we consider two physical situations where Machine Learning are often used: high-pT hadronic activity, and boosted Higgs in association with a massive vector boson.  
  Address [Khosa, Charanjit Kaur] Univ Bristol, HH Wills Phys Lab, Tyndall Ave, Bristol BS8 1TL, Avon, England, Email: Charanjit.Kaur@bristol.ac.uk;  
  Corporate Author Thesis  
  Publisher Scipost Foundation 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:000929724800002 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5475  
Permanent link to this record
 
 
Author (down) Khosa, C.K.; Sanz, V. url  doi
openurl 
  Title On the Impact of the LHC Run 2 Data on General Composite Higgs Scenarios Type Journal Article
  Year 2022 Publication Advances in High Energy Physics Abbreviated Journal Adv. High. Energy Phys.  
  Volume 2022 Issue Pages 8970837 - 13pp  
  Keywords  
  Abstract We study the impact of Run 2 LHC data on general composite Higgs scenarios, where nonlinear effects, mixing with additional scalars, and new fermionic degrees of freedom could simultaneously contribute to the modification of Higgs properties. We obtain new experimental limits on the scale of compositeness, the mixing with singlets and doublets with the Higgs, and the mass and mixing angle of top-partners. We also show that for scenarios where new fermionic degrees of freedom are involved in electroweak symmetry breaking, there is an interesting interplay among Higgs coupling measurements, boosted Higgs properties, SMEFT global analyses, and direct searches for single and double production of vector-like quarks.  
  Address [Khosa, Charanjit K.] Univ Genoa, Dipartimento Fis, Via Dodecaneso 33, I-16146 Genoa, Italy, Email: khosacharanjit@gmail.com;  
  Corporate Author Thesis  
  Publisher Hindawi Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1687-7357 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000766325700001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5153  
Permanent link to this record
 
 
Author (down) Khosa, C.K.; Sanz, V. url  doi
openurl 
  Title Anomaly Awareness Type Journal Article
  Year 2023 Publication Scipost Physics Abbreviated Journal SciPost Phys.  
  Volume 15 Issue 2 Pages 053 - 24pp  
  Keywords  
  Abstract We present a new algorithm for anomaly detection called Anomaly Awareness. The algorithm learns about normal events while being made aware of the anomalies through a modification of the cost function. We show how this method works in different Particle Physics situations and in standard Computer Vision tasks. For example, we apply the method to images from a Fat Jet topology generated by Standard Model Top and QCD events, and test it against an array of new physics scenarios, including Higgs production with EFT effects and resonances decaying into two, three or four subjets. We find that the algorithm is effective identifying anomalies not seen before, and becomes robust as we make it aware of a varied-enough set of anomalies.  
  Address [Khosa, Charanjit K.] Univ Manchester, Dept Phys & Astron, Manchester M13 9PL, England  
  Corporate Author Thesis  
  Publisher Scipost Foundation Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2542-4653 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001048488200002 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5610  
Permanent link to this record
 
 
Author (down) Khosa, C.K.; Mars, L.; Richards, J.; Sanz, V. url  doi
openurl 
  Title Convolutional neural networks for direct detection of dark matter Type Journal Article
  Year 2020 Publication Journal of Physics G Abbreviated Journal J. Phys. G  
  Volume 47 Issue 9 Pages 095201 - 20pp  
  Keywords dark matter; dark matter detection; neural networks; xenon1T; WIMPs  
  Abstract The XENON1T experiment uses a time projection chamber (TPC) with liquid xenon to search for weakly interacting massive particles (WIMPs), a proposed dark matter particle, via direct detection. As this experiment relies on capturing rare events, the focus is on achieving a high recall of WIMP events. Hence the ability to distinguish between WIMP and the background is extremely important. To accomplish this, we suggest using convolutional neural networks (CNNs); a machine learning procedure mainly used in image recognition tasks. To explore this technique we use XENON collaboration open-source software to simulate the TPC graphical output of dark matter signals and main backgrounds. A CNN turns out to be a suitable tool for this purpose, as it can identify features in the images that differentiate the two types of events without the need to manipulate or remove data in order to focus on a particular region of the detector. We find that the CNN can distinguish between the dominant background events (ER) and 500 GeV WIMP events with a recall of 93.4%, precision of 81.2% and an accuracy of 87.2%.  
  Address [Khosa, Charanjit K.; Mars, Lucy; Richards, Joel; Sanz, Veronica] Univ Sussex, Dept Phys & Astron, Brighton BN1 9QH, E Sussex, England, Email: charanjit.kaur@sussex.ac.uk;  
  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 0954-3899 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000555607800001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4485  
Permanent link to this record
 
 
Author (down) Kasieczka, G. et al; Sanz, V. url  doi
openurl 
  Title The LHC Olympics 2020: a community challenge for anomaly detection in high energy physics Type Journal Article
  Year 2021 Publication Reports on Progress in Physics Abbreviated Journal Rep. Prog. Phys.  
  Volume 84 Issue 12 Pages 124201 - 64pp  
  Keywords anomaly detection; machine learning; unsupervised learning; weakly supervised learning; semisupervised learning; beyond the standard model; model-agnostic methods  
  Abstract A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.  
  Address [Kasieczka, Gregor] Univ Hamburg, Inst Expt Phys, Hamburg, Germany, Email: gregor.kasieczka@uni-hamburg.de;  
  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 0034-4885 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000727698500001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5039  
Permanent link to this record
 
 
Author (down) Huang, F.; Sanz, V.; Shu, J.; Xue, X. url  doi
openurl 
  Title LIGO as a probe of dark sectors Type Journal Article
  Year 2021 Publication Physical Review D Abbreviated Journal Phys. Rev. D  
  Volume 104 Issue 10 Pages 095001 - 9pp  
  Keywords  
  Abstract We show how current LIGO data is able to probe interesting theories beyond the Standard Model, particularly dark sectors where a dark Higgs boson triggers symmetry breaking via a first-order phase transition. We use publicly available LIGO O2 data to illustrate how these sectors, even if disconnected from the Standard Model, can be probed by gravitational wave detectors. We link the LIGO measurements with the model content and mass scale of the dark sector, finding that current O2 data are testing a broad set of scenarios that can be mapped into many different types of dark-sector models where the breaking of SU(N) theories with Nf fermions is triggered by a dark Higgs boson at scales ? similar or equal to 108-109 GeV with reasonable parameters for the scalar potential.  
  Address [Huang, Fei; Shu, Jing; Xue, Xiao] Chinese Acad Sci, Inst Theoret Phys, CAS Key Lab Theoret Phys, Beijing 100190, Peoples R China, Email: huangf4@uci.edu;  
  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 2470-0010 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000716446500001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5021  
Permanent link to this record
Select All    Deselect All << 1 2 3 >>
List View
 | 
Citations
 | 
Details
   print
toggle visibility
Save Citations:
Export Records:
Home CQL Search  |  Library Search  |  Show Record  |  Extract Citations Help
ific federMinisterio de Ciencia e InnovaciónAgencia Estatal de Investigaciongva