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Author Cepedello, R.; Esser, F.; Hirsch, M.; Sanz, V.
Title Mapping the SMEFT to discoverable models Type Journal Article
Year 2022 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 09 Issue 9 Pages 229 - 34pp
Keywords SMEFT; Other Weak Scale BSM Models
Abstract The matching of specific new physics scenarios onto the SMEFT framework is a well-understood procedure. The inverse problem, the matching of the SMEFT to UV scenarios, is more difficult and requires the development of new methods to perform a systematic exploration of models. In this paper we use a diagrammatic technique to construct in an automated way a complete set of possible UV models (given certain, well specified assumptions) that can produce specific groups of SMEFT operators, and illustrate its use by generating models with no tree-level contributions to four-fermion (4F) operators. Those scenarios, which only contribute to 4F at one-loop order, can contain relatively light particles that could be discovered at the LHC in direct searches. For this class of models, we find an interesting interplay between indirect SMEFT and direct searches. We discuss some examples on how this interplay would look like when combining low-energy observables with the SMEFT Higgs-fermion analyses and searches for resonance at the LHC.
Address [Cepedello, Ricardo] Univ Wurzburg, Inst Theoret Phys & Astrophys, Emil Hilb Weg 22, D-97074 Wurzburg, Germany, Email: ricardo.cepedello@physik.uni-wuerzburg.de;
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 (up) WOS:000861474500009 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5361
Permanent link to this record
 
 
Author Khosa, C.K.; Sanz, V.; Soughton, M.
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 (up) WOS:000929724800002 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5475
Permanent link to this record
 
 
Author Gomez Ambrosio, R.; ter Hoeve, J.; Madigan, M.; Rojo, J.; Sanz, V.
Title Unbinned multivariate observables for global SMEFT analyses from machine learning Type Journal Article
Year 2023 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 03 Issue 3 Pages 033 - 66pp
Keywords SMEFT; Higgs Properties
Abstract Theoretical interpretations of particle physics data, such as the determination of the Wilson coefficients of the Standard Model Effective Field Theory (SMEFT), often involve the inference of multiple parameters from a global dataset. Optimizing such interpretations requires the identification of observables that exhibit the highest possible sensitivity to the underlying theory parameters. In this work we develop a flexible open source frame-work, ML4EFT, enabling the integration of unbinned multivariate observables into global SMEFT fits. As compared to traditional measurements, such observables enhance the sensitivity to the theory parameters by preventing the information loss incurred when binning in a subset of final-state kinematic variables. Our strategy combines machine learning regression and classification techniques to parameterize high-dimensional likelihood ratios, using the Monte Carlo replica method to estimate and propagate methodological uncertainties. As a proof of concept we construct unbinned multivariate observables for top-quark pair and Higgs+Z production at the LHC, demonstrate their impact on the SMEFT parameter space as compared to binned measurements, and study the improved constraints associated to multivariate inputs. Since the number of neural networks to be trained scales quadratically with the number of parameters and can be fully parallelized, the ML4EFT framework is well-suited to construct unbinned multivariate observables which depend on up to tens of EFT coefficients, as required in global fits.
Address [Ambrosio, Raquel Gomez] Univ Milano Bicocca, Dipartimento Fis G Occhialini, Piazza Sci 3, I-20126 Milan, Italy, Email: raquel.gomezambrosio@unito.it;
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 (up) WOS:000946004000003 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5501
Permanent link to this record
 
 
Author Khosa, C.K.; Sanz, V.
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 (up) WOS:001048488200002 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5610
Permanent link to this record
 
 
Author Cepedello, R.; Esser, F.; Hirsch, M.; Sanz, V.
Title SMEFT goes dark: Dark Matter models for four-fermion operators Type Journal Article
Year 2023 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 09 Issue 9 Pages 081 - 47pp
Keywords SMEFT; Dark Matter at Colliders; Specific BSM Phenomenology
Abstract We study ultra-violet completions for d = 6 four-fermion operators in the standard model effective field theory (SMEFT), focusing on models that contain cold dark matter candidates. Via a diagrammatic method, we generate systematically lists of possible UV completions, with the aim of providing sets of models, which are complete under certain, well specified assumptions. Within these lists of models we rediscover many known DM models, as diverse as R-parity conserving supersymmetry or the scotogenic neutrino mass model. Our lists, however, also contain many new constructions, which have not been studied in the literature so far. We also briefly discuss how our DM models could be constrained by reinterpretations of LHC searches and the prospects for HL-LHC and future lepton colliders.
Address [Cepedello, Ricardo] Univ Wurzburg, Inst Theoret Phys & Astrophys, D-97074 Wurzburg, Germany, Email: ricardo.cepedello@physik.uni-wuerzburg.de;
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 (up) WOS:001067194100002 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5688
Permanent link to this record
 
 
Author Conde, D.; Castillo, F.L.; Escobar, C.; García, C.; Garcia Navarro, J.E.; Sanz, V.; Zaldívar, B.; Curto, J.J.; Marsal, S.; Torta, J.M.
Title Forecasting Geomagnetic Storm Disturbances and Their Uncertainties Using Deep Learning Type Journal Article
Year 2023 Publication Space Weather Abbreviated Journal Space Weather
Volume 21 Issue 11 Pages e2023SW003474 - 27pp
Keywords geomagnetic storms; deep learning; forecasting; SYM-H; uncertainties; hyper-parameter optimization
Abstract Severe space weather produced by disturbed conditions on the Sun results in harmful effects both for humans in space and in high-latitude flights, and for technological systems such as spacecraft or communications. Also, geomagnetically induced currents (GICs) flowing on long ground-based conductors, such as power networks, potentially threaten critical infrastructures on Earth. The first step in developing an alarm system against GICs is to forecast them. This is a challenging task given the highly non-linear dependencies of the response of the magnetosphere to these perturbations. In the last few years, modern machine-learning models have shown to be very good at predicting magnetic activity indices. However, such complex models are on the one hand difficult to tune, and on the other hand they are known to bring along potentially large prediction uncertainties which are generally difficult to estimate. In this work we aim at predicting the SYM-H index characterizing geomagnetic storms multiple-hour ahead, using public interplanetary magnetic field (IMF) data from the Sun-Earth L1 Lagrange point and SYM-H data. We implement a type of machine-learning model called long short-term memory (LSTM) network. Our scope is to estimate the prediction uncertainties coming from a deep-learning model in the context of forecasting the SYM-H index. These uncertainties will be essential to set reliable alarm thresholds. The resulting uncertainties turn out to be sizable at the critical stages of the geomagnetic storms. Our methodology includes as well an efficient optimization of important hyper-parameters of the LSTM network and robustness tests.
Address [Conde, D.; Escobar, C.; Garcia, C.; Garcia, J. E.; Sanz, V.; Zaldivar, B.] Univ Valencia, CSIC, Ctr Mixto, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: Daniel.Conde@ific.uv.es
Corporate Author Thesis
Publisher Amer Geophysical Union 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 (up) WOS:001104189700001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5804
Permanent link to this record
 
 
Author Sanchis-Lozano, M.A.; Sanz, V.
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 (up) WOS:001195716600006 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ pastor @ Serial 6038
Permanent link to this record
 
 
Author Lessa, A.; Sanz, V.
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 (up) WOS:001205498200004 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 6108
Permanent link to this record
 
 
Author Cepedello, R.; Esser, F.; Hirsch, M.; Sanz, V.
Title Fermionic UV models for neutral triple gauge boson vertices Type Journal Article
Year 2024 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 07 Issue 7 Pages 275 - 28pp
Keywords Effective Field Theories; SMEFT; Specific BSM Phenomenology; Vector-Like Fermions
Abstract Searches for anomalous neutral triple gauge boson couplings (NTGCs) provide important tests for the gauge structure of the standard model. In SMEFT (“standard model effective field theory”) NTGCs appear only at the level of dimension-8 operators. While the phenomenology of these operators has been discussed extensively in the literature, renormalizable UV models that can generate these operators are scarce. In this work, we study a variety of extensions of the SM with heavy fermions and calculate their matching to d = 8 NTGC operators. We point out that the complete matching of UV models requires four different CP-conserving d = 8 operators and that the single CPC d = 8 operator, most commonly used by the experimental collaborations, does not describe all possible NTGC form factors. Despite stringent experimental constraints on NTGCs, limits on the scale of UV models are relatively weak, because their contributions are doubly suppressed (being d = 8 and 1-loop). We suggest a series of benchmark UV scenarios suitable for interpreting searches for NTGCs in the upcoming LHC runs, obtain their current limits and provide estimates for the expected sensitivity of the high-luminosity LHC.
Address [Cepedello, Ricardo] Univ Granada, Dept Fis Teor & Cosmos, Campus Fuentenueva, E-18071 Granada, Spain, Email: ricepe@ugr.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 1029-8479 ISBN Medium
Area Expedition Conference
Notes (up) WOS:001282227200003 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 6222
Permanent link to this record
 
 
Author Perez-Curbelo, J.; Roser, J.; Muñoz, E.; Barrientos, L.; Sanz, V.; Llosa, G.
Title Improving Compton camera imaging of multi-energy radioactive sources by using machine learning algorithms for event selection Type Journal Article
Year 2025 Publication Radiation Physics and Chemistry Abbreviated Journal Radiat. Phys. Chem.
Volume 226 Issue Pages 112166 - 11pp
Keywords Compton cameras imaging; Event selection; Neural networks; Image reconstruction
Abstract Event selection and background reduction for Compton camera imaging of multi-energy radioactive sources has been performed by employing neural networks. A Compton camera prototype with detectors made of LaBr3 crystals coupled to silicon photomultiplier arrays was used to acquire experimental data from a circular array of Na-22 sources. The prototype and two arrays of Na-22 sources were simulated with GATE v8.2 Monte Carlo code, to obtain data for neural network training. Neural network models were trained on simulated data for event classification. The optimum models were found by using Weights & Biases platform tools. The trained models were used to classify simulated and real data for selecting signal events and rejecting background prior to image reconstruction. The models performed well on simulated data. The image obtained with experimental data showed an improvement with respect to event selection with energy cuts. The method is promising for Compton camera imaging of multi-energy radioactive sources.
Address [Perez-Curbelo, J.; Roser, J.; Munoz, E.; Barrientos, L.; Sanz, V.; Llosa, G.] CSIC UV, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: Javier.Perez.Curbelo@ific.uv.es
Corporate Author Thesis
Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0969-806x ISBN Medium
Area Expedition Conference
Notes (up) WOS:001325220200001 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ pastor @ Serial 6269
Permanent link to this record