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Author |
Gomez Ambrosio, R.; ter Hoeve, J.; Madigan, M.; Rojo, J.; Sanz, V. |
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Title |
Unbinned multivariate observables for global SMEFT analyses from machine learning |
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Journal Article |
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Year |
2023 |
Publication  |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
03 |
Issue |
3 |
Pages |
033 - 66pp |
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Keywords |
SMEFT; Higgs Properties |
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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. |
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Address |
[Ambrosio, Raquel Gomez] Univ Milano Bicocca, Dipartimento Fis G Occhialini, Piazza Sci 3, I-20126 Milan, Italy, Email: raquel.gomezambrosio@unito.it; |
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Springer |
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English |
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1029-8479 |
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WOS:000946004000003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5501 |
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Author |
Cepedello, R.; Esser, F.; Hirsch, M.; Sanz, V. |
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Title |
SMEFT goes dark: Dark Matter models for four-fermion operators |
Type |
Journal Article |
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Year |
2023 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
09 |
Issue |
9 |
Pages |
081 - 47pp |
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Keywords |
SMEFT; Dark Matter at Colliders; Specific BSM Phenomenology |
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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. |
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Address |
[Cepedello, Ricardo] Univ Wurzburg, Inst Theoret Phys & Astrophys, D-97074 Wurzburg, Germany, Email: ricardo.cepedello@physik.uni-wuerzburg.de; |
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Springer |
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1029-8479 |
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WOS:001067194100002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5688 |
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Author |
Esser, F.; Madigan, M.; Sanz, V.; Ubiali, M. |
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Title |
On the coupling of axion-like particles to the top quark |
Type |
Journal Article |
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Year |
2023 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
09 |
Issue |
9 |
Pages |
063 - 39pp |
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Abstract |
In this paper we explore the coupling of a light axion-like particle (ALP) to top quarks. We use high-energy LHC probes, and examine both the direct probe to this coupling in associated production of a top-pair with an ALP, and the indirect probe through loop-induced gluon fusion to an ALP leading to top pairs. Using the latest LHC Run II data, we provide the best limit on this coupling. We also compare these limits with those obtained from loop-induced couplings in diboson final states, finding that the +MET channel is the best current handle on this coupling. |
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Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
6083 |
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Author |
Lessa, A.; Sanz, V. |
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Title |
Going beyond Top EFT |
Type |
Journal Article |
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Year |
2024 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
04 |
Issue |
4 |
Pages |
107 - 29pp |
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Keywords |
SMEFT; Dark Matter at Colliders; Supersymmetry |
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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. |
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Address |
[Lessa, Andre] Univ Fed ABC, Ctr Ciencias Nat & Humanas, BR-09210580 Santo Andre, SP, Brazil, Email: andre.lessa@ufabc.edu.br |
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Publisher |
Springer |
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English |
Summary Language |
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ISSN |
1029-8479 |
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Notes |
WOS:001205498200004 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
6108 |
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Author |
Khosa, C.K.; Mars, L.; Richards, J.; Sanz, V. |
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Title |
Convolutional neural networks for direct detection of dark matter |
Type |
Journal Article |
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Year |
2020 |
Publication |
Journal of Physics G |
Abbreviated Journal |
J. Phys. G |
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Volume |
47 |
Issue |
9 |
Pages |
095201 - 20pp |
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Keywords |
dark matter; dark matter detection; neural networks; xenon1T; WIMPs |
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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%. |
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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; |
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Corporate Author |
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Publisher |
Iop Publishing Ltd |
Place of Publication |
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English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0954-3899 |
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Notes |
WOS:000555607800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4485 |
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