Yamamoto, H. (2021). The International Linear Collider Project-Its Physics and Status. Symmetry-Basel, 13(4), 674–15pp.
Abstract: The discovery of Higgs particle has ushered in a new era of particle physics. Even though the list of members of the standard theory of particle physics is now complete, the shortcomings of the theory became ever more acute. It is generally considered that the best solution to the problems is an electron-positron collider that can study Higgs particle with high precision and high sensitivity; namely, a Higgs factory. Among a few candidates for Higgs factory, the International Linear Collider (ILC) is currently the most advanced in its program. In this article, we review the physics and the project status of the ILC including its energy expandability.
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Mosbech, M. R., Boehm, C., Hannestad, S., Mena, O., Stadler, J., & Wong, Y. Y. Y. (2021). The full Boltzmann hierarchy for dark matter-massive neutrino interactions. J. Cosmol. Astropart. Phys., 03(3), 066–31pp.
Abstract: The impact of dark matter-neutrino interactions on the measurement of the cosmological parameters has been investigated in the past in the context of massless neutrinos exclusively. Here we revisit the role of a neutrino-dark matter coupling in light of ongoing cosmological tensions by implementing the full Boltzmann hierarchy for three massive neutrinos. Our tightest 95% CL upper limit on the strength of the interactions, parameterized via u(chi) = sigma(0)/sigma(Th) (m(chi)/100GeV)(-1), is u(chi) <= 3.34 . 10(-4), arising from a combination of Planck TTTEEE data, Planck lensing data and SDSS BAO data. This upper bound is, as expected, slightly higher than previous results for interacting massless neutrinos, due to the correction factor associated with neutrino masses. We find that these interactions significantly relax the lower bounds on the value of sigma 8 that is inferred in the context of Lambda CDM from the Planck data, leading to agreement within 1-2 sigma with weak lensing estimates of sigma 8, as those from KiDS1000. However, the presence of these interactions barely affects the value of the Hubble constant H-0.
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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cardillo, F., Castillo, F. L., et al. (2021). Search for dark matter in association with an energetic photon in pp collisions at root s=13 TeV with the ATLAS detector. J. High Energy Phys., 02(2), 226–46pp.
Abstract: A search for dark matter is conducted in final states containing a photon and missing transverse momentum in proton-proton collisions at root s = 13 TeV. The data, collected during 2015-2018 by the ATLAS experiment at the CERN LHC, correspond to an integrated luminosity of 139 fb(-1). No deviations from the predictions of the Standard Model are observed and 95% confidence-level upper limits between 2.45 fb and 0.5 fb are set on the visible cross section for contributions from physics beyond the Standard Model, in different ranges of the missing transverse momentum. The results are interpreted as 95% confidence-level limits in models where weakly interacting dark-matter candidates are pair-produced via an s-channel axial-vector or vector mediator. Dark-matter candidates with masses up to 415 (580) GeV are excluded for axial-vector (vector) mediators, while the maximum excluded mass of the mediator is 1460 (1470) GeV. In addition, the results are expressed in terms of 95% confidence-level limits on the parameters of a model with an axion-like particle produced in association with a photon, and are used to constrain the coupling g(aZ gamma) of an axion-like particle to the electroweak gauge bosons.
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NEXT Collaboration(Martinez-Lema, G. et al), Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., Diaz, J., Felkai, R., et al. (2021). Sensitivity of the NEXT experiment to Xe-124 double electron capture. J. High Energy Phys., 02(2), 203–25pp.
Abstract: Double electron capture by proton-rich nuclei is a second-order nuclear process analogous to double beta decay. Despite their similarities, the decay signature is quite different, potentially providing a new channel to measure the hypothesized neutrinoless mode of these decays. The Standard-Model-allowed two-neutrino double electron capture (2 nu EC EC) has been predicted for a number of isotopes, but only observed in Kr-78, Ba-130 and, recently, Xe-124. The sensitivity to this decay establishes a benchmark for the ultimate experimental goal, namely the potential to discover also the lepton-number-violating neutrinoless version of this process, 0 nu EC EC. Here we report on the current sensitivity of the NEXT-White detector to Xe-124 2 nu EC EC and on the extrapolation to NEXT-100. Using simulated data for the 2 nu EC EC signal and real data from NEXT-White operated with Xe-124-depleted gas as background, we define an optimal event selection that maximizes the NEXT-White sensitivity. We estimate that, for NEXT-100 operated with xenon gas isotopically enriched with 1 kg of Xe-124 and for a 5-year run, a sensitivity to the 2 nu EC EC half-life of 6 x 10(22) y (at 90% confidence level) or better can be reached.
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NEXT Collaboration(Kekic, M. et al), Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., Diaz, J., Felkai, R., et al. (2021). Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment. J. High Energy Phys., 01(1), 189–22pp.
Abstract: Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high-energy physics. In this paper, we attempt to understand the potential of CNNs for event classification in the NEXT experiment, which will search for neutrinoless double-beta decay in Xe-136. To do so, we demonstrate the usage of CNNs for the identification of electron-positron pair production events, which exhibit a topology similar to that of a neutrinoless double-beta decay event. These events were produced in the NEXT-White high-pressure xenon TPC using 2.6 MeV gamma rays from a Th-228 calibration source. We train a network on Monte Carlo-simulated events and show that, by applying on-the-fly data augmentation, the network can be made robust against differences between simulation and data. The use of CNNs offers significant improvement in signal efficiency and background rejection when compared to previous non-CNN-based analyses.
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