The ArgoNeuT collaboration presents measurements of inclusive muon neutrino and antineutrino charged current differential cross sections on argon in the Fermilab NuMI beam operating in the low energy antineutrino mode. The results are reported in terms of outgoing muon angle and momentum at a mean neutrino energy of 9.6 GeV (neutrinos) and 3.6 GeV (antineutrinos), in the range $0^\circ < \theta_\mu < 36^\circ$ and $0 < p_\mu < 25$ GeV/$c$, for both neutrinos and antineutrinos.
The charge ratio, $R_\mu = N_{\mu^+}/N_{\mu^-}$, for cosmogenic multiple-muon events observed at an under- ground depth of 2070 mwe has been measured using the magnetized MINOS Far Detector. The multiple-muon events, recorded nearly continuously from August 2003 until April 2012, comprise two independent data sets imaged with opposite magnetic field polarities, the comparison of which allows the systematic uncertainties of the measurement to be minimized. The multiple-muon charge ratio is determined to be $R_\mu = 1.104 \pm 0.006 {\rm \,(stat.)} ^{+0.009}_{-0.010} {\rm \,(syst.)} $. This measurement complements previous determinations of single-muon and multiple-muon charge ratios at underground sites and serves to constrain models of cosmic ray interactions at TeV energies.
Production of K^{+} mesons in charged-current \nu_{\mu} interactions on plastic scintillator (CH) is measured using MINERvA exposed to the low-energy NuMI beam at Fermilab. Timing information is used to isolate a sample of 885 charged-current events containing a stopping K^{+} which decays at rest. The differential cross section in K^{+} kinetic energy, d\sigma/dT_{K}, is observed to be relatively flat between 0 and 500 MeV. Its shape is in good agreement with the prediction by the \textsc{genie} neutrino event generator when final-state interactions are included, however the data rate is lower than the prediction by 15\%.
A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons ($\tau_\mathrm{h}$) that originate from genuine tau leptons in the CMS detector against $\tau_\mathrm{h}$ candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a $\tau_\mathrm{h}$ candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine $\tau_\mathrm{h}$ to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient $\tau_\mathrm{h}$ reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved $\tau_\mathrm{h}$ reconstruction method are validated with LHC proton-proton collision data at $\sqrt{s} =$ 13 TeV.
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