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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 |
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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  |
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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no |
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yes |
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yes |
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Call Number |
IFIC @ pastor @ |
Serial |
6083 |
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Author |
Khosa, C.K.; Sanz, V.; Soughton, M. |
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Title |
Using machine learning to disentangle LHC signatures of Dark Matter candidates |
Type |
Journal Article |
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Year |
2021 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
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Volume |
10 |
Issue |
6 |
Pages |
151 - 26pp |
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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. |
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[Khosa, Charanjit Kaur; Sanz, Veronica; Soughton, Michael] Univ Sussex, Dept Phys & Astron, Brighton BN1 9QH, E Sussex, England, Email: Charanjit.Kaur@sussex.ac.uk; |
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Scipost Foundation |
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English |
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2542-4653 |
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WOS:000680038800002 |
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no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4927 |
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Author |
Barenboim, G.; Hirn, J.; Sanz, V. |
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Title |
Symmetry meets AI |
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Journal Article |
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Year |
2021 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
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11 |
Issue |
1 |
Pages |
014 - 11pp |
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We explore whether Neural Networks (NNs) can discover the presence of symmetries as they learn to perform a task. For this, we train hundreds of NNs on a decoy task based on well-controlled Physics templates, where no information on symmetry is provided. We use the output from the last hidden layer of all these NNs, projected to fewer dimensions, as the input for a symmetry classification task, and show that information on symmetry had indeed been identified by the original NN without guidance. As an interdisciplinary application of this procedure, we identify the presence and level of symmetry in artistic paintings from different styles such as those of Picasso, Pollock and Van Gogh. |
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[Barenboim, Gabriela; Hirn, Johannes; Sanz, Veronica] Univ Valencia, CSIC, Dept Fis Teor, E-46100 Burjassot, Spain |
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Scipost Foundation |
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2542-4653 |
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Notes |
WOS:000680039500002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4920 |
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Author |
Bonilla, J.; Brivio, I.; Gavela, M.B.; Sanz, V. |
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Title |
One-loop corrections to ALP couplings |
Type |
Journal Article |
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Year |
2021 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
11 |
Issue |
11 |
Pages |
168 - 57pp |
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Keywords |
Beyond Standard Model; Effective Field Theories; Renormalization Group |
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The plethora of increasingly precise experiments which hunt for axion-like particles (ALPs), as well as their widely different energy reach, call for the theoretical understanding of ALP couplings at loop-level. We derive the one-loop contributions to ALP-SM effective couplings, including finite corrections. The complete leading-order – dimension five – effective linear Lagrangian is considered. The ALP is left off-shell, which is of particular impact on LHC and accelerator searches of ALP couplings to gamma gamma, ZZ, WW, Z gamma gluons and fermions. All results are obtained in the covariant Rg gauge. A few phenomenological consequences are also explored as illustration, with flavour diagonal channels in the case of fermions: in particular, we explore constraints on the coupling of the ALP to top quarks, that can be extracted from LHC data, from astrophysical sources and from Dark Matter direct detection experiments such as PandaX, LUX and XENONIT. Furthermore, we clarify the relation between alternative ALP bases, the role of gauge anomalous couplings and their interface with chirality-conserving and chirality-flip fermion interactions, and we briefly discuss renormalization group aspects. |
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[Bonilla, J.; Gavela, M. B.] Univ Autonoma Madrid, Dept Fis Teor, E-28049 Madrid, Spain, Email: jesus.bonilla@ua.m.es; |
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Springer |
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English |
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ISSN |
1029-8479 |
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Notes |
WOS:000721914800006 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5029 |
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Author |
Cranmer, K. et al; Sanz, V. |
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Title |
Publishing statistical models: Getting the most out of particle physics experiments |
Type |
Journal Article |
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Year |
2022 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
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Volume |
12 |
Issue |
1 |
Pages |
037 - 55pp |
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Abstract |
The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases – including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits – we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results. |
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[Cranmer, Kyle; Held, Alexander] NYU, New York, NY 10003 USA, Email: kyle.cranmer@nyu.edu; |
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Scipost Foundation |
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English |
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Series Volume |
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Edition |
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ISSN |
2542-4653 |
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Notes |
WOS:000807448000032 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5255 |
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