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ANTARES Collaboration(Albert, A. et al), Barrios-Marti, J., Coleiro, A., Colomer, M., Hernandez-Rey, J. J., Illuminati, G., et al. (2018). The search for neutrinos from TXS 0506+056 with the ANTARES telescope. Astrophys. J. Lett., 863(2), L30–6pp.
Abstract: The results of three different searches for neutrino candidates, associated with the IceCube-170922A event or from the direction of TXS 0506+056, by the ANTARES neutrino telescope, are presented. The first search refers to the online follow-up of the IceCube alert; the second is based on the standard time-integrated method employed by the Collaboration to search for point-like neutrino sources; the third uses information from the IceCube time-dependent analysis that reported bursting activity centered on 2014 December 13, as input for an ANTARES time-dependent analysis. The online follow-up and the time-dependent analysis yield no events related to the source. The time-integrated study performed over a period from 2007 to 2017 fits 1.03 signal events, which corresponds to a p-value of 3.4% (not considering trial factors). Only for two other astrophysical objects in our candidate list has a smaller p-value been found. When considering that 107 sources have been investigated, the post-trial p-value for TXS 0506+056 corresponds to 87%.
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ATLAS Collaboration(Aaboud, M. et al), Alvarez Piqueras, D., Bailey, A. J., Barranco Navarro, L., Cabrera Urban, S., Castillo Gimenez, V., et al. (2019). Search for pair production of Higgs bosons in the b(b)over-barb(b)over-bar final state using proton-proton collisions at root s=13 TeV with the ATLAS detector. J. High Energy Phys., 01(1), 030–49pp.
Abstract: A search for Higgs boson pair production in the bbbb final state is carried out with up to 36.1 fb(-1) of LHC proton-proton collision data collected at s=13 TeV with the ATLAS detector in 2015 and 2016. Three benchmark signals are studied: a spin-2 graviton decaying into a Higgs boson pair, a scalar resonance decaying into a Higgs boson pair, and Standard Model non-resonant Higgs boson pair production. Two analyses are carried out, each implementing a particular technique for the event reconstruction that targets Higgs bosons reconstructed as pairs of jets or single boosted jets. The resonance mass range covered is 260-3000 GeV. The analyses are statistically combined and upper limits on the production cross section of Higgs boson pairs times branching ratio to bbbb are set in each model. No significant excess is observed; the largest deviation of data over prediction is found at a mass of 280 GeV, corresponding to 2.3 standard deviations globally. The observed 95% confidence level upper limit on the non-resonant production is 13 times the Standard Model prediction.
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Coloma, P., Esteban, I., Gonzalez-Garcia, M. C., & Menendez, J. (2020). Determining the nuclear neutron distribution from Coherent Elastic neutrino-Nucleus Scattering: current results and future prospects. J. High Energy Phys., 08(8), 030–22pp.
Abstract: Coherent Elastic neutrino-Nucleus Scattering (CE nu NS), a process recently measured for the first time at ORNL's Spallation Neutron Source, is directly sensitive to the weak form factor of the nucleus. The European Spallation Source (ESS), presently under construction, will generate the most intense pulsed neutrino flux suitable for the detection of CE nu NS. In this paper we quantify its potential to determine the root mean square radius of the point-neutron distribution, for a variety of target nuclei and a suite of detectors. To put our results in context we also derive, for the first time, a constraint on this parameter from the analysis of the energy and timing data of the CsI detector at the COHERENT experiment.
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HAWC Collaboration(Albert, A. et al), & Salesa Greus, F. (2021). Evidence of 200 TeV Photons from HAWC J1825-134. Astrophys. J. Lett., 907(2), L30–9pp.
Abstract: The Earth is bombarded by ultrarelativistic particles, known as cosmic rays (CRs). CRs with energies up to a few PeV (=10(15) eV), the knee in the particle spectrum, are believed to have a Galactic origin. One or more factories of PeV CRs, or PeVatrons, must thus be active within our Galaxy. The direct detection of PeV protons from their sources is not possible since they are deflected in the Galactic magnetic fields. Hundred TeV gamma-rays from decaying pi(0), produced when PeV CRs collide with the ambient gas, can provide the decisive evidence of proton acceleration up to the knee. Here we report the discovery by the High Altitude Water Cerenkov (HAWC) observatory of the gamma-ray source, HAWC J1825-134, whose energy spectrum extends well beyond 200 TeV without a break or cutoff. The source is found to be coincident with a giant molecular cloud. The ambient gas density is as high as 700 protons cm(-3). While the nature of this extreme accelerator remains unclear, CRs accelerated to energies of several PeV colliding with the ambient gas likely produce the observed radiation.
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Villanueva-Domingo, P., Villaescusa-Navarro, F., Angles-Alcazar, D., Genel, S., Marinacci, F., Spergel, D. N., et al. (2022). Inferring Halo Masses with Graph Neural Networks. Astrophys. J., 935(1), 30–15pp.
Abstract: Understanding the halo-galaxy connection is fundamental in order to improve our knowledge on the nature and properties of dark matter. In this work, we build a model that infers the mass of a halo given the positions, velocities, stellar masses, and radii of the galaxies it hosts. In order to capture information from correlations among galaxy properties and their phase space, we use Graph Neural Networks (GNNs), which are designed to work with irregular and sparse data. We train our models on galaxies from more than 2000 state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations project. Our model, which accounts for cosmological and astrophysical uncertainties, is able to constrain the masses of the halos with a similar to 0.2 dex accuracy. Furthermore, a GNN trained on a suite of simulations is able to preserve part of its accuracy when tested on simulations run with a different code that utilizes a distinct subgrid physics model, showing the robustness of our method. The PyTorch Geometric implementation of the GNN is publicly available on GitHub (https://github.com/PabloVD/HaloGraphNet).
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