Abstract: Dark photon dark matter will resonantly convert into visible photons when the dark photon mass is equal to the plasma frequency of the ambient medium. In cosmological contexts, this transition leads to an extremely efficient, albeit short-lived, heating of the surrounding gas. Existing work in this field has been predominantly focused on understanding the implications of these resonant transitions in the limit that the plasma frequency of the Universe can be treated as being perfectly homogeneous, i.e. neglecting inhomogeneities in the electron number density. In this work we focus on the implications of heating from dark photon dark matter in the presence of inhomogeneous structure (which is particularly relevant for dark photons with masses in the range 10(-15) eV less than or similar to m(A ') less than or similar to 10(-12) eV), emphasizing both the importance of inhomogeneous energy injection, as well as the sensitivity of cosmological observations to the inhomogeneities themselves. More specifically, we derive modified constraints on dark photon dark matter from the Ly-alpha forest, and show that the presence of inhomogeneities allows one to extend constraints to masses outside of the range that would be obtainable in the homogeneous limit, while only slightly relaxing their strength. We then project sensitivity for near-future cosmological surveys that are hoping to measure the 21cm transition in neutral hydrogen prior to reionization, and demonstrate that these experiments will be extremely useful in improving sensitivity to masses near similar to 10(-14) eV, potentially by several orders of magnitude. Finally, we discuss implications for reionization, early star formation, and late-time y-type spectral distortions, and show that probes which are inherently sensitive to the inhomogeneous state of the Universe could resolve signatures unique to the light dark photon dark matter scenario, and thus offer a fantastic potential for a positive detection.

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.

Abstract: In experiments searching for neutrinoless double-beta decay, the possibility of identifying the two emitted electrons is a powerful tool in rejecting background events and therefore improving the overall sensitivity of the experiment. In this paper we present the first measurement of the efficiency of a cut based on the different event signatures of double and single electron tracks, using the data of the NEXT-White detector, the first detector of the NEXT experiment operating underground. Using a Th-228 calibration source to produce signal-like and background-like events with energies near 1.6 MeV, a signal efficiency of 71.6 +/- 1.5(stat) +/- 0.3(sys) % for a background acceptance of 20.6 +/- 0.4(stat) +/- 0.3(sys)% is found, in good agreement with Monte Carlo simulations. An extrapolation to the energy region of the neutrinoless double beta decay by means of Monte Carlo simulations is also carried out, and the results obtained show an improvement in background rejection over those obtained at lower energies.

Abstract: This article presents a new set of proton parton distribution functions, AT-LASepWZVjet20, produced in an analysis at next-to-next-to-leading order in QCD. The new data sets considered are the measurements of W+ and W- boson and Z boson production in association with jets in pp collisions at root s = 8 TeV performed by the ATLAS experiment at the LHC with integrated luminosities of 20.2 fb(-1) and 19.9 fb(-1), respectively. The analysis also considers the ATLAS measurements of differential W-+/- and Z boson production at root s = 7 TeV with an integrated luminosity of 4.6 fb(-1) and deep-inelastic-scattering data from e(+/-) p collisions at the HERA accelerator. An improved determination of the sea-quark densities at high Bjorken x is shown, while confirming a strange-quark density similar in size to the up- and down-sea-quark densities in the range x less than or similar to 0.02 found by previous ATLAS analyses.

Abstract: The normalized differential cross section for top-quark pair production in association with at least one jet is studied as a function of the inverse of the invariant mass of the t (t) over bar + 1-jet system. This distribution can be used for a precise determination of the top-quark mass since gluon radiation depends on the mass of the quarks. The experimental analysis is based on proton-proton collision data collected by the ATLAS detector at the LHC with a centre-of-mass energy of 7TeV corresponding to an integrated luminosity of 4.6 fb(-1). The selected events were identified using the lepton+jets top-quark-pair decay channel, where lepton refers to either an electron or a muon. The observed distribution is compared to a theoretical prediction at next-to-leading-order accuracy in quantum chromodynamics using the pole-mass scheme. With this method, the measured value of the top-quark pole mass, m(t)(pole), is: m(t)(pole) t = 173.7 +/- 1.5 (stat.) +/- 1.4 (syst.)(-0.5)(+1.0) (theory) GeV. This result represents the most precise measurement of the top-quark pole mass to date.