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Author |
Casas, J.A.; Moreno, J.M.; Rius, N.; Ruiz de Austri, R.; Zaldivar, B. |
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Title |
Fair scans of the seesaw. Consequences for predictions on LFV processes |
Type |
Journal Article |
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Year |
2011 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
03 |
Issue |
3 |
Pages |
034 - 22pp |
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Keywords |
Neutrino Physics; Supersymmetric Standard Model |
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Abstract |
We give a straightforward procedure to scan the seesaw parameter-space, using the common “R-parametrization”, in a complete way. This includes a very simple rule to incorporate the perturbativity requirement as a condition for the entries of the R-matrix. As a relevant application, we show that the somewhat propagated belief that BR(mu -> e, gamma) in supersymmetric seesaw models depends strongly on the value of theta(13) is an “optical effect” produced by incomplete scans, and does not hold after a careful analytical and numerical study. When the complete scan is done, BR(mu -> e, gamma) gets very insensitive to theta(13). This holds even if the right-handed neutrino masses are kept constant or under control (as is required for succesful leptogenesis). In most cases the values of BR(mu -> e, gamma) are larger than the experimental upper bound. Including (unflavoured) leptogenesis does not introduce any further dependence on theta(13), although decreases the typical value of BR(mu -> e, gamma). |
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Address |
[Alberto Casas, J.; Moreno, Jesus M.; Zaldivar, Bryam] UAM, IFT UAM CSIC, Inst Fis Teor, Madrid 28049, Spain, Email: alberto.casas@uam.es |
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Springer |
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English |
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ISSN |
1126-6708 |
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Notes |
ISI:000289295200034 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
612 |
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Permanent link to this record |
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Author |
Casas, J.A.; Gomez Vargas, G.A.; Moreno, J.M.; Quilis, J.; Ruiz de Austri, R. |
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Title |
Extended Higgs-portal dark matter and the Fermi-LAT Galactic Center Excess |
Type |
Journal Article |
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Year |
2018 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
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Volume |
06 |
Issue |
6 |
Pages |
031 - 16pp |
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Keywords |
dark matter theory; dark matter experiments |
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Abstract |
In the present work, we show that the Galactic Center Excess (GCE) emission, as recently updated by the Fermi-LAT Collaboration, could be explained by a mixture of Fermi bubbles-like emission plus dark matter (DM) annihilation, in the context of a scalar-singlet Higgs portal scenario (SHP). In fact, the standard SHP, where the DM particle, S, only has renormalizable interactions with the Higgs, is non-operational due to strong constraints, especially from DM direct detection limits. Thus we consider the most economical extension, called ESHP (for extended SHP), which consists solely in the addition of a second (more massive) scalar singlet in the dark sector. The second scalar can be integrated-out, leaving a standard SHP plus a dimension-6 operator. Mainly, this model has only two relevant parameters (the DM mass and the coupling of the dim-6 operator). DM annihilation occurs mainly into two Higgs bosons, SS -> hh. We demonstrate that, despite its economy, the ESHP model provides an excellent fit to the GCE (with p-value similar to 0.6-0.7) for very reasonable values of the parameters, in particular, ms similar or equal to 130 GeV. This agreement of the DM candidate to the GCE properties does not clash with other observables and keep the S – particle relic density at the accepted value for the DM content in the universe. |
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Address |
[Casas, J. A.; Moreno, J. M.; Quilis, J.] Univ Autonoma Madrid, Inst Fis Teor, CSIC, E-28049 Madrid, Spain, Email: j.alberto.casas@gmail.com; |
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Publisher |
Iop Publishing Ltd |
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English |
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ISSN |
1475-7516 |
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Conference |
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Notes |
WOS:000435710700001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3626 |
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Permanent link to this record |
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Author |
Caron, S.; Ruiz de Austri, R.; Zhang, Z.Y. |
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Title |
Mixture-of-Theories training: can we find new physics and anomalies better by mixing physical theories? |
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 |
03 |
Issue |
3 |
Pages |
004 - 37pp |
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Keywords |
Specific BSM Phenomenology; Supersymmetry |
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Abstract |
Model-independent search strategies have been increasingly proposed in recent years because on the one hand there has been no clear signal for new physics and on the other hand there is a lack of a highly probable and parameter-free extension of the standard model. For these reasons, there is no simple search target so far. In this work, we try to take a new direction and ask the question: bearing in mind that we have a large number of new physics theories that go beyond the Standard Model and may contain a grain of truth, can we improve our search strategy for unknown signals by using them “in combination”? In particular, we show that a signal hypothesis based on a large, intermingled set of many different theoretical signal models can be a superior approach to find an unknown BSM signal. Applied to a recent data challenge, we show that “mixture-of-theories training” outperforms strategies that optimize signal regions with a single BSM model as well as most unsupervised strategies. Applications of this work include anomaly detection and the definition of signal regions in the search for signals of new physics. |
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Address |
[Caron, Sascha; Zhang, Zhongyi] Radboud Univ Nijmegen, High Energy Phys, Heyendaalseweg 135, NL-6525 AJ Nijmegen, Netherlands, Email: scaron@nikhef.nl; |
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Springer |
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English |
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Edition |
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ISSN |
1029-8479 |
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Conference |
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Notes |
WOS:000943095100001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5494 |
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Permanent link to this record |
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Author |
Caron, S.; Kim, J.S.; Rolbiecki, K.; Ruiz de Austri, R.; Stienen, B. |
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Title |
The BSM-AI project: SUSY-AI-generalizing LHC limits on supersymmetry with machine learning |
Type |
Journal Article |
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Year |
2017 |
Publication |
European Physical Journal C |
Abbreviated Journal |
Eur. Phys. J. C |
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Volume |
77 |
Issue |
4 |
Pages |
257 - 25pp |
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Abstract |
A key research question at the Large Hadron Collider is the test of models of new physics. Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: it requires time consuming generation of scattering events, simulation of the detector response, event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiments. In the BSM-AI project we approach this challenge with a new idea. A machine learning tool is devised to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters. A first example is SUSY-AI, trained on the phenomenological supersymmetric standard model (pMSSM). About 300,000 pMSSM model sets – each tested against 200 signal regions by ATLAS – have been used to train and validate SUSY-AI. The code is currently able to reproduce theATLAS exclusion regions in 19 dimensions with an accuracy of at least 93%. It has been validated further within the constrained MSSM and the minimal natural supersymmetric model, again showing high accuracy. SUSY-AI and its future BSM derivatives will help to solve the problem of recasting LHC results for any model of new physics. SUSY-AI can be downloaded from http://susyai.hepforge.org/. An on-line interface to the program for quick testing purposes can be found at http://www.susy-ai.org/. |
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Address |
[Caron, Sascha; Stienen, Bob] Radboud Univ Nijmegen, IMAPP, Nijmegen, Netherlands, Email: krolb@fuw.edu.pl |
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Corporate Author |
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Thesis |
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Publisher |
Springer |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Edition |
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ISSN |
1434-6044 |
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Conference |
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Notes |
WOS:000400079300001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3097 |
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Permanent link to this record |
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Author |
Caron, S.; Gomez-Vargas, G.A.; Hendriks, L.; Ruiz de Austri, R. |
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Title |
Analyzing gamma rays of the Galactic Center with deep learning |
Type |
Journal Article |
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Year |
2018 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
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Volume |
05 |
Issue |
5 |
Pages |
058 - 24pp |
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Keywords |
gamma ray experiments; dark matter simulations |
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Abstract |
We present the application of convolutional neural networks to a particular problem in gamma ray astronomy. Explicitly, we use this method to investigate the origin of an excess emission of GeV gamma rays in the direction of the Galactic Center, reported by several groups by analyzing Fermi-LAT data. Interpretations of this excess include gamma rays created by the annihilation of dark matter particles and gamma rays originating from a collection of unresolved point sources, such as millisecond pulsars. We train and test convolutional neural networks with simulated Fermi-LAT images based on point and diffuse emission models of the Galactic Center tuned to measured gamma ray data. Our new method allows precise measurements of the contribution and properties of an unresolved population of gamma ray point sources in the interstellar diffuse emission model. The current model predicts the fraction of unresolved point sources with an error of up to 10% and this is expected to decrease with future work. |
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Address |
[Caron, Sascha; Hendriks, Luc] Radboud Univ Nijmegen, Fac Sci, Inst Math Astrophys & Particle Phys, Mailbox 79,POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: scaron@cern.ch; |
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Corporate Author |
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Thesis |
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Publisher |
Iop Publishing Ltd |
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 |
1475-7516 |
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:000432869300005 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3582 |
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Permanent link to this record |