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Stadler, J., Boehm, C., & Mena, O. (2020). Is it mixed dark matter or neutrino masses? J. Cosmol. Astropart. Phys., 01(1), 039–18pp.
Abstract: In this paper, we explore a scenario where the dark matter is a mixture of interacting and non interacting species. Assuming dark matter-photon interactions for the interacting species, we find that the suppression of the matter power spectrum in this scenario can mimic that expected in the case of massive neutrinos. Our numerical studies include present limits from Planck Cosmic Microwave Background data, which render the strength of the dark matter photon interaction unconstrained when the fraction of interacting dark matter is small. Despite the large entangling between mixed dark matter and neutrino masses, we show that future measurements from the Dark Energy Instrument (DESI) could help in establishing the dark matter and the neutrino properties simultaneously, provided that the interaction rate is very close to its current limits and the fraction of interacting dark matter is at least of O (10%). However, for that region of parameter space where a small fraction of interacting DM coincides with a comparatively large interaction rate, our analysis highlights a considerable degeneracy between the mixed dark matter parameters and the neutrino mass scale.
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Fernandez Casani, A., Orduña, J. M., Sanchez, J., & Gonzalez de la Hoz, S. (2021). A Reliable Large Distributed Object Store Based Platform for Collecting Event Metadata. J. Grid Comput., 19(3), 39–19pp.
Abstract: The Large Hadron Collider (LHC) is about to enter its third run at unprecedented energies. The experiments at the LHC face computational challenges with enormous data volumes that need to be analysed by thousands of physics users. The ATLAS EventIndex project, currently running in production, builds a complete catalogue of particle collisions, or events, for the ATLAS experiment at the LHC. The distributed nature of the experiment data model is exploited by running jobs at over one hundred Grid data centers worldwide. Millions of files with petabytes of data are indexed, extracting a small quantity of metadata per event, that is conveyed with a data collection system in real time to a central Hadoop instance at CERN. After a successful first implementation based on a messaging system, some issues suggested performance bottlenecks for the challenging higher rates in next runs of the experiment. In this work we characterize the weaknesses of the previous messaging system, regarding complexity, scalability, performance and resource consumption. A new approach based on an object-based storage method was designed and implemented, taking into account the lessons learned and leveraging the ATLAS experience with this kind of systems. We present the experiment that we run during three months in the real production scenario worldwide, in order to evaluate the messaging and object store approaches. The results of the experiment show that the new object-based storage method can efficiently support large-scale data collection for big data environments like the next runs of the ATLAS experiment at the LHC.
Keywords: Grid computing; Hadoop file system; Object-Based storage
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Cottin, G., Helo, J. C., Hirsch, M., Titov, A., & Wang, Z. S. (2021). Heavy neutral leptons in effective field theory and the high-luminosity LHC. J. High Energy Phys., 09(9), 039–34pp.
Abstract: Heavy neutral leptons (HNLs) with masses around the electroweak scale are expected to be rather long-lived particles, as a result of the observed smallness of the active neutrino masses. In this work, we study long-lived HNLs in NRSMEFT, a Standard Model (SM) extension with singlet fermions to which we add non-renormalizable operators up to dimension-6. Operators which contain two HNLs can lead to a sizable enhancement of the production cross sections, compared to the minimal case where HNLs are produced only via their mixing with the SM neutrinos. We calculate the expected sensitivities for the ATLAS detector and the future far-detector experiments: AL3X, ANUBIS, CODEX-b, FASER, MATHUSLA, and MoEDAL-MAPP in this setup. The sensitive ranges of the HNL mass and of the active-heavy mixing angle are much larger than those in the minimal case. We study both, Dirac and Majorana, HNLs and discuss how the two cases actually differ phenomenologically, for HNL masses above roughly 100 GeV.
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Herrero-Garcia, J., Patrick, R., & Scaffidi, A. (2022). A semi-supervised approach to dark matter searches in direct detection data with machine learning. J. Cosmol. Astropart. Phys., 02, 039–19pp.
Abstract: The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general philosophy more concrete by applying modern machine learning techniques to dark matter direct detection. We do this by encoding and decoding the graphical representation of background events in the XENONnT experiment with a convolutional variational autoencoder. We describe a methodology that utilizes the `anomaly score' derived from the reconstruction loss of the convolutional variational autoencoder as well as a pre-trained standard convolutional neural network, in a semi-supervised fashion. Indeed, we observe that optimum results are obtained only when both unsupervised and supervised anomaly scores are considered together. A data set that has a higher proportion of anomaly score is deemed anomalous and deserves further investigation. Contrary to classical analyses, in principle all information about the events is used, preventing unnecessary information loss. Lastly, we demonstrate the reach of learning-focused anomaly detection in this context by comparing results with classical inference, observing that, if tuned properly, these techniques have the potential to outperform likelihood-based methods.
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Achterberg, A., van Beekveld, M., Caron, S., Gomez-Vargas, G. A., Hendriks, L., & Ruiz de Austri, R. (2017). Implications of the Fermi-LAT Pass 8 Galactic Center excess on supersymmetric dark matter. J. Cosmol. Astropart. Phys., 12(12), 040–23pp.
Abstract: The Fermi Collaboration has recently updated their analysis of gamma rays from the center of the Galaxy. They reconfirm the presence of an unexplained emission feature which is most prominent in the region of 1-10 GeV, known as the Galactic Center GeV excess (GCE). Although the GCE is now fi rmly detected, an interpretation of this emission as a signal of self-annihilating dark matter (DM) particles is not unambiguously possible due to systematic effects in the gamma-ray modeling estimated in the Galactic Plane. In this paper we build a covariance matrix, collecting different systematic uncertainties investigated in the Fermi Collaboration's paper that affect the GCE spectrum. We show that models where part of the GCE is due to annihilating DM is still consistent with the new data. We also re-evaluate the parameter space regions of the minimal supersymmetric Standard Model (MSSM) that can contribute dominantly to the GCE via neutralino DM annihilation. All recent constraints from DM direct detection experiments such as PICO, LUX, PandaX and Xenon1T, limits on the annihilation cross section from dwarf spheroidal galaxies and the Large Hadron Collider limits are considered in this analysis. Due to a slight shift in the energy spectrum of the GC excess with respect to the previous Fermi analysis, and the recent limits from direct detection experiments, we find a slightly shifted parameter region of the MSSM, compared to our previous analysis, that is consistent with the GCE. Neutralinos with a mass between 85-220 GeV can describe the excess via annihilation into a pair of W-bosons or top quarks. Remarkably, there are models with low fine-tuning among the regions that we have found. The complete set of solutions will be probed by upcoming direct detection experiments and with dedicated searches in the upcoming data of the Large Hadron Collider.
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