59 research outputs found

    The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking

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    Particle track reconstruction in dense environments such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC) is a challenging pattern recognition problem. Traditional tracking algorithms such as the combinatorial Kalman Filter have been used with great success in LHC experiments for years. However, these state-of-the-art techniques are inherently sequential and scale poorly with the expected increases in detector occupancy in the HL-LHC conditions. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problem thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as GPUs. This contribution will describe our initial explorations into this relatively unexplored idea space. We will discuss the use of recurrent (LSTM) and convolutional neural networks to find and fit tracks in toy detector data

    IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads

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    The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2–3 billion to deliver one new drug. This is both too expensive and too slow, especially in emergencies like the COVID-19 pandemic. In silico methodologies need to be improved both to select better lead compounds, so as to improve the efficiency of later stages in the drug discovery protocol, and to identify those lead compounds more quickly. No known methodological approach can deliver this combination of higher quality and speed. Here, we describe an Integrated Modeling PipEline for COVID Cure by Assessing Better LEads (IMPECCABLE) that employs multiple methodological innovations to overcome this fundamental limitation. We also describe the computational framework that we have developed to support these innovations at scale, and characterize the performance of this framework in terms of throughput, peak performance, and scientific results. We show that individual workflow components deliver 100 × to 1000 × improvement over traditional methods, and that the integration of methods, supported by scalable infrastructure, speeds up drug discovery by orders of magnitudes. IMPECCABLE has screened ∼ 1011 ligands and has been used to discover a promising drug candidate. These capabilities have been used by the US DOE National Virtual Biotechnology Laboratory and the EU Centre of Excellence in Computational Biomedicine

    First Results from The GlueX Experiment

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    The GlueX experiment at Jefferson Lab ran with its first commissioning beam in late 2014 and the spring of 2015. Data were collected on both plastic and liquid hydrogen targets, and much of the detector has been commissioned. All of the detector systems are now performing at or near design specifications and events are being fully reconstructed, including exclusive production of π0\pi^{0}, η\eta and ω\omega mesons. Linearly-polarized photons were successfully produced through coherent bremsstrahlung and polarization transfer to the ρ\rho has been observed.Comment: 8 pages, 6 figures, Invited contribution to the Hadron 2015 Conference, Newport News VA, September 201

    New constraints on oscillation parameters from Ve appearance and Vu disappearance in the NOvA experiment

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    For full abstract please refer to Official URL link”, or if there is a document attached which contains the abstract, “For full abstract please refer to attached documen

    First measurement of neutrino oscillation parameters using neutrinos and antineutrinos by NOvA

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    The NOvA experiment has seen a 4.4σ signal of ν̄e appearance in a 2 GeV ν̄μ beam at a distance of 810 km. Using 12.33×1020 protons on target delivered to the Fermilab NuMI neutrino beamline, the experiment recorded 27 ν̄μ→ν̄e candidates with a background of 10.3 and 102 ν̄μ→ν̄μ candidates. This new antineutrino data are combined with neutrino data to measure the parameters |Δm322|=2.48-0.06+0.11×10-3 eV2/c4 and sin2θ23 in the ranges from (0.53-0.60) and (0.45-0.48) in the normal neutrino mass hierarchy. The data exclude most values near δCP=π/2 for the inverted mass hierarchy by more than 3σ and favor the normal neutrino mass hierarchy by 1.9σ and θ23 values in the upper octant by 1.6σ

    Measurement of the Double-Differential Muon-neutrino Charged-Current Inclusive Cross Section in the NOvA Near Detector

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    We report cross-section measurements of the final-state muon kinematics for \numu charged-current interactions in the NOvA near detector using an accumulated 8.09×1020\times10^{20} protons-on-target (POT) in the NuMI beam. We present the results as a double-differential cross section in the observed outgoing muon energy and angle, as well as single-differential cross sections in the derived neutrino energy, EνE_\nu, and square of the four-momentum transfer, Q2Q^2. We compare the results to inclusive cross-section predictions from various neutrino event generators via χ2\chi^2 calculations using a covariance matrix that accounts for bin-to-bin correlations of systematic uncertainties. These comparisons show a clear discrepancy between the data and each of the tested predictions at forward muon angle and low Q2Q^2, indicating a missing suppression of the cross section in current neutrino-nucleus scattering models

    An Improved Measurement of Neutrino Oscillation Parameters by the NOvA Experiment

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    We present new νμνe\nu_\mu\rightarrow\nu_e, νμνμ\nu_\mu\rightarrow\nu_\mu, νμνe\overline{\nu}_\mu\rightarrow\overline{\nu}_e, and νμνμ\overline{\nu}_\mu\rightarrow\overline{\nu}_\mu oscillation measurements by the NOvA experiment, with a 50% increase in neutrino-mode beam exposure over the previously reported results. The additional data, combined with previously published neutrino and antineutrino data, are all analyzed using improved techniques and simulations. A joint fit to the νe\nu_e, νμ\nu_\mu, νe\overline{\nu}_e, and νμ\overline{\nu}_\mu candidate samples within the 3-flavor neutrino oscillation framework continues to yield a best-fit point in the normal mass ordering and the upper octant of the θ23\theta_{23} mixing angle, with Δm322=(2.41±0.07)×103\Delta m^{2}_{32} = (2.41\pm0.07)\times 10^{-3} eV2^2 and sin2θ23=0.570.04+0.03\sin^2\theta_{23} = 0.57^{+0.03}_{-0.04}. The data disfavor combinations of oscillation parameters that give rise to a large asymmetry in the rates of νe\nu_e and νe\overline{\nu}_e appearance. This includes values of the CP-violating phase in the vicinity of δCP=π/2\delta_\text{CP} = \pi/2 which are excluded by >3σ>3\sigma for the inverted mass ordering, and values around δCP=3π/2\delta_\text{CP} = 3\pi/2 in the normal ordering which are disfavored at 2σ\sigma confidence.Comment: 11 pages, 6 figures. Supplementary material attached (7 figures
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