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Author |
LHC BSM Reinterpretation Forum (Abdallah, W. et al); Mitsou, V.A.; Sanz, V. |
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Title |
Reinterpretation of LHC results for new physics: status and recommendations after run 2 |
Type |
Journal Article |
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Year |
2020 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
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Volume |
9 |
Issue |
2 |
Pages |
022 - 45pp |
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Keywords |
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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. |
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Address |
[Abdallah, Waleed; Dutta, Juhi] Harish Chandra Res Inst HBNI, Allahabad 211019, Uttar Pradesh, India, Email: Andy.Buckley@glasgow.ac.uk; |
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Scipost Foundation |
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Language  |
English |
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ISSN |
2542-4653 |
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Notes |
WOS:000573102600007 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4547 |
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Author |
Folgado, M.G.; Sanz, V. |
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Title |
On the Interpretation of Nonresonant Phenomena at Colliders |
Type |
Journal Article |
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Year |
2021 |
Publication |
Advances in High Energy Physics |
Abbreviated Journal |
Adv. High. Energy Phys. |
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Volume |
2021 |
Issue |
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Pages |
2573471 - 12pp |
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Abstract |
With null results in resonance searches at the LHC, the physics potential focus is now shifting towards the interpretation of nonresonant phenomena. An example of such shift is the increased popularity of the EFT programme. We can embark on such programme owing to the good integrated luminosity and an excellent understanding of the detectors, which will allow these searches to become more intense as the LHC continues. In this paper, we provide a framework to perform this interpretation in terms of a diverse set of scenarios, including (1) generic heavy new physics described at low energies in terms of a derivative expansion, such as in the EFT approach; (2) very light particles with derivative couplings, such as axions or other light pseudo-Goldstone bosons; and (3) the effect of a quasicontinuum of resonances, which can come from a number of strongly coupled theories, extradimensional models, clockwork set-ups, and their deconstructed cousins. These scenarios are not equivalent despite all nonresonance, although the matching among some of them is possible, and we provide it in this paper. |
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Address |
[Folgado, Miguel G.; Sanz, Veronica] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, E-46980 Valencia, Spain, Email: migarfol@ific.uv.es |
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Publisher |
Hindawi Ltd |
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English |
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Edition |
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ISSN |
1687-7357 |
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Notes |
WOS:000636258800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4775 |
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Author |
Ellis, J.; Madigan, M.; Mimasu, K.; Sanz, V.; You, T. |
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Title |
Top, Higgs, diboson and electroweak fit to the Standard Model effective field theory |
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 |
04 |
Issue |
4 |
Pages |
279 - 78pp |
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Keywords |
Effective Field Theories; Beyond Standard Model; Higgs Physics |
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Abstract |
The search for effective field theory deformations of the Standard Model (SM) is a major goal of particle physics that can benefit from a global approach in the framework of the Standard Model Effective Field Theory (SMEFT). For the first time, we include LHC data on top production and differential distributions together with Higgs production and decay rates and Simplified Template Cross-Section (STXS) measurements in a global fit, as well as precision electroweak and diboson measurements from LEP and the LHC, in a global analysis with SMEFT operators of dimension 6 included linearly. We present the constraints on the coefficients of these operators, both individually and when marginalised, in flavour-universal and top-specific scenarios, studying the interplay of these datasets and the correlations they induce in the SMEFT. We then explore the constraints that our linear SMEFT analysis imposes on specific ultra-violet completions of the Standard Model, including those with single additional fields and low-mass stop squarks. We also present a model-independent search for deformations of the SM that contribute to between two and five SMEFT operator coefficients. In no case do we find any significant evidence for physics beyond the SM. Our underlying Fitmaker public code provides a framework for future generalisations of our analysis, including a quadratic treatment of dimension-6 operators. |
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Address |
[Ellis, John; Mimasu, Ken] Kings Coll London, Dept Phys, Theoret Particle Phys & Cosmol Grp, London WC2R 2LS, England, Email: john.ellis@cern.ch; |
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Publisher |
Springer |
Place of Publication |
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Language |
English |
Summary Language |
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Abbreviated Series Title |
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Series Volume |
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Edition |
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ISSN |
1029-8479 |
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Notes |
WOS:000658918100001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4857 |
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Author |
Barenboim, G.; Hirn, J.; Sanz, V. |
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Title |
Symmetry meets AI |
Type |
Journal Article |
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Year |
2021 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
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Volume |
11 |
Issue |
1 |
Pages |
014 - 11pp |
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Keywords |
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Abstract |
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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Address |
[Barenboim, Gabriela; Hirn, Johannes; Sanz, Veronica] Univ Valencia, CSIC, Dept Fis Teor, E-46100 Burjassot, Spain |
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Publisher |
Scipost Foundation |
Place of Publication |
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Language |
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 |
2542-4653 |
ISBN |
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Area |
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Expedition |
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Conference |
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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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| Permanent link to this record |
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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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Keywords |
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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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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; |
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Corporate Author |
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Thesis |
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Publisher |
Scipost Foundation |
Place of Publication |
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Editor |
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Language |
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 |
2542-4653 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000680038800002 |
Approved |
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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| Permanent link to this record |
