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Carcamo Hernandez, A. E., Valle, J. W. F., & Vaquera-Araujo, C. A. (2020). Simple theory for scotogenic dark matter with residual matter-parity. Phys. Lett. B, 809, 135757–10pp.
Abstract: Dark matter stability can result from a residual matter-parity symmetry surviving spontaneous breaking of an extended gauge symmetry. We propose the simplest scotogenic dark matter completion of the original SVS theory [1], in which the “dark sector” particles as well as matter-parity find a natural theoretical origin within the model. We briefly comment on its main features.
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Carcamo Hernandez, A. E., Vishnudath, K. N., & Valle, J. W. F. (2023). Linear seesaw mechanism from dark sector. J. High Energy Phys., 09(9), 046–18pp.
Abstract: We propose a minimal model where a dark sector seeds neutrino mass generation radiatively within the linear seesaw mechanism. Neutrino masses are calculable, since treelevel contributions are forbidden by symmetry. They arise from spontaneous lepton number violation by a small Higgs triplet vacuum expectation value. Lepton flavour violating processes e.g. μ-> e gamma can be sizeable, despite the tiny neutrino masses. We comment also on dark-matter and collider implications.
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Carlomagno, J. P., Gomez Dumm, D., Izzo Villafañe, M. F., Noguera, S., & Scoccola, N. N. (2022). Charged pseudoscalar and vector meson masses in strong magnetic fields in an extended NJL model. Phys. Rev. D, 106(9), 094035–17pp.
Abstract: The mass spectrum of pi(+) and rho(+) mesons in the presence of a static uniform magnetic field (B) over right arrow is studied within a two-flavor Nambu-Jona-Lasinio-like model. We improve previous calculations, taking into account the effect of Schwinger phases carried by quark propagators and using an expansion of meson fields in terms of the solutions of the corresponding equations of motion for nonzero B. It is shown that the meson polarization functions are diagonal in this basis. Our numerical results for the rho(+) meson spectrum are found to disfavor the existence of a meson condensate induced by the magnetic field. In the case of the pi(+) meson, pi-rho mixing effects are analyzed for the meson lowest-energy state. The predictions of the model are compared with available lattice QCD results.
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Carlomagno, J. P., Gomez Dumm, D., Noguera, S., & Scoccola, N. N. (2022). Neutral pseudoscalar and vector meson masses under strong magnetic fields in an extended NJL model: Mixing effects. Phys. Rev. D, 106(7), 074002–20pp.
Abstract: Mixing effects on the mass spectrum of light neutral pseudoscalar and vector mesons in the presence of an external uniform magnetic field (B) over right arrow are studied in the framework of a two-flavor Nambu-Jona-Lasinio (NJL)-like model. The model includes isoscalar and isovector couplings both in the scalar-pseudoscalar and vector sectors, and also incorporates flavor mixing through a ' t Hooft-like term. Numerical results for the B dependence of meson masses are compared with present lattice QCD results. In particular, it is shown that the mixing between pseudoscalar and vector meson states leads to a significant reduction of the mass of the lightest state. The role of chiral symmetry and the effect of the alignment of quark magnetic moments in the presence of the magnetic field are discussed.
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Caron, S., Eckner, C., Hendriks, L., Johannesson, G., Ruiz de Austri, R., & Zaharijas, G. (2023). Mind the gap: the discrepancy between simulation and reality drives interpretations of the Galactic Center Excess. J. Cosmol. Astropart. Phys., 06(6), 013–56pp.
Abstract: The Galactic Center Excess (GCE) in GeV gamma rays has been debated for over a decade, with the possibility that it might be due to dark matter annihilation or undetected point sources such as millisecond pulsars (MSPs). This study investigates how the gamma-ray emission model (-yEM) used in Galactic center analyses affects the interpretation of the GCE's nature. To address this issue, we construct an ultra-fast and powerful inference pipeline based on convolutional Deep Ensemble Networks. We explore the two main competing hypotheses for the GCE using a set of-yEMs with increasing parametric freedom. We calculate the fractional contribution (fsrc) of a dim population of MSPs to the total luminosity of the GCE and analyze its dependence on the complexity of the ryEM. For the simplest ryEM, we obtain fsrc = 0.10 f 0.07, while the most complex model yields fsrc = 0.79 f 0.24. In conclusion, we find that the statement about the nature of the GCE (dark matter or not) strongly depends on the assumed ryEM. The quoted results for fsrc do not account for the additional uncertainty arising from the fact that the observed gamma-ray sky is out-of-distribution concerning the investigated ryEM iterations. We quantify the reality gap between our ryEMs using deep-learning-based One-Class Deep Support Vector Data Description networks, revealing that all employed ryEMs have gaps to reality. Our study casts doubt on the validity of previous conclusions regarding the GCE and dark matter, and underscores the urgent need to account for the reality gap and consider previously overlooked “out of domain” uncertainties in future interpretations.
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Caron, S., Ruiz de Austri, R., & Zhang, Z. Y. (2023). Mixture-of-Theories training: can we find new physics and anomalies better by mixing physical theories? J. High Energy Phys., 03(3), 004–37pp.
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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Carquin, E., Neill, N. A., Helo, J. C., & Hirsch, M. (2019). Exotic colored fermions and lepton number violation at the LHC. Phys. Rev. D, 99(11), 115028–9pp.
Abstract: Majorana neutrino mass models with a scale of lepton number violation of order tem-electron-volts potentially lead to signals at the LHC. Here, we consider an extension of the standard model with a colored octet fermion and a scalar leptoquark. This model generates neutrino masses at two-loop order. We make a detailed Monte Carlo study of the lepton number violating signal at the LHC in this model, including a simulation of standard model backgrounds. Our forecast predicts that the LHC with 300/fb should be able to probe this model up to color-octet fermion masses in the range of (2.6-2.7) TeV, depending on the lepton flavor of the final state.
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Carrasco, J., & Zurita, J. (2024). Emerging jet probes of strongly interacting dark sectors. J. High Energy Phys., 01(1), 034–23pp.
Abstract: A strongly interacting dark sector can give rise to a class of signatures dubbed dark showers, where in analogy to the strong sector in the Standard Model, the dark sector undergoes its own showering and hadronization, before decaying into Standard Model final states. When the typical decay lengths of the dark sector mesons are larger than a few centimeters (and no larger than a few meters) they give rise to the striking signature of emerging jets, characterized by a large multiplicity of displaced vertices.In this article we consider the general reinterpretation of the CMS search for emerging jets plus prompt jets into arbitrary new physics scenarios giving rise to emerging jets. More concretely, we consider the cases where the SM Higgs mediates between the dark sector and the SM, for several benchmark decay scenarios. Our procedure is validated employing the same model than the CMS emerging jet search. We find that emerging jets can be the leading probe in regions of parameter space, in particular when considering the so-called gluon portal and dark photon portal decay benchmarks. With the current 16.1 fb-1 of luminosity this search can exclude down to O\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \mathcal{O} $$\end{document}(20)% exotic branching ratio of the SM Higgs, but a naive extrapolation to the 139 fb-1 luminosity employed in the current model-independent, indirect bound of 16 % would probe exotic branching ratios into dark quarks down to below 10 %. Further extrapolating these results to the HL-LHC, we find that one can pin down exotic branching ratio values of 1%, which is below the HL-LHC expectations of 2.5-4 %. We make our recasting code publicly available, as part of the LLP Recasting Repository.
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Carrasco-Ribelles, L. A., Pardo-Mas, J. R., Tortajada, S., Saez, C., Valdivieso, B., & Garcia-Gomez, J. M. (2021). Predicting morbidity by local similarities in multi-scale patient trajectories. J. Biomed. Inform., 120, 103837–9pp.
Abstract: Patient Trajectories (PTs) are a method of representing the temporal evolution of patients. They can include information from different sources and be used in socio-medical or clinical domains. PTs have generally been used to generate and study the most common trajectories in, for instance, the development of a disease. On the other hand, healthcare predictive models generally rely on static snapshots of patient information. Only a few works about prediction in healthcare have been found that use PTs, and therefore benefit from their temporal dimension. All of them, however, have used PTs created from single-source information. Therefore, the use of longitudinal multi-scale data to build PTs and use them to obtain predictions about health conditions is yet to be explored. Our hypothesis is that local similarities on small chunks of PTs can identify similar patients concerning their future morbidities. The objectives of this work are (1) to develop a methodology to identify local similarities between PTs before the occurrence of morbidities to predict these on new query individuals; and (2) to validate this methodology on risk prediction of cardiovascular diseases (CVD) occurrence in patients with diabetes. We have proposed a novel formal definition of PTs based on sequences of longitudinal multi-scale data. Moreover, a dynamic programming methodology to identify local alignments on PTs for predicting future morbidities is proposed. Both the proposed methodology for PT definition and the alignment algorithm are generic to be applied on any clinical domain. We validated this solution for predicting CVD in patients with diabetes and we achieved a precision of 0.33, a recall of 0.72 and a specificity of 0.38. Therefore, the proposed solution in the diabetes use case can result of utmost utility to secondary screening.
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Carrio, F. (2022). The Data Acquisition System for the ATLAS Tile Calorimeter Phase-II Upgrade Demonstrator. IEEE Trans. Nucl. Sci., 69(4), 687–695.
Abstract: The tile calorimeter (TileCal) is the central hadronic calorimeter of the ATLAS experiment at the large hadron collider (LHC). In 2025, the LHC will be upgraded leading to the high luminosity LHC (HL-LHC). The HL-LHC will deliver an instantaneous luminosity up to seven times larger than the LHC nominal luminosity. The ATLAS Phase-II upgrade (2025-2027) will accommodate the subdetectors to the HL-LHC requirements. As part of this upgrade, the majority of the TileCal on-detector and off-detector electronics will be replaced using a new readout strategy, where the on-detector electronics will digitize and transmit digitized detector data to the off-detector electronics at the bunch crossing frequency (40 MHz). In the counting rooms, the off-detector electronics will compute reconstructed trigger objects for the first-level trigger and will store the digitized samples in pipelined buffers until the reception of a trigger acceptance signal. The off-detector electronics will also distribute the LHC clock to the on-detector electronics embedded within the digital data stream. The TileCal Phase-II upgrade project has undertaken an extensive research and development program that includes the development of a Demonstrator module to evaluate the performance of the new clock and readout architecture envisaged for the HL-LHC. The Demonstrator module equipped with the latest version of the on-detector electronics was built and inserted into the ATLAS experiment. The Demonstrator module is operated and read out using a Tile PreProcessor (TilePPr) Demonstrator which enables backward compatibility with the present ATLAS Trigger and Data AcQuisition (TDAQ), and the timing, trigger, and command (TTC) systems. This article describes in detail the main hardware and firmware components of the clock distribution and data acquisition systems for the Demonstrator module, focusing on the TilePPr Demonstrator.
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