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  1. ABSTRACT We report the discovery of the closest known black hole candidate as a binary companion to V723 Mon. V723 Mon is a nearby ($d\sim 460\, \rm pc$), bright (V ≃ 8.3 mag), evolved (Teff, giant ≃ 4440 K, and Lgiant ≃ 173 L⊙) red giant in a high mass function, f(M) = 1.72 ± 0.01 M⊙, nearly circular binary (P = 59.9 d, e ≃ 0). V723 Mon is a known variable star, previously classified as an eclipsing binary, but its All-Sky Automated Survey, Kilodegree Extremely Little Telescope, and Transiting Exoplanet Survey Satellite light curves are those of a nearly edge-on ellipsoidal variable. Detailed models of the lightmore »curves constrained by the period, radial velocities, and stellar temperature give an inclination of $87.0^{\circ ^{+1.7^\circ }}_{-1.4^\circ }$, a mass ratio of q ≃ 0.33 ± 0.02, a companion mass of Mcomp = 3.04 ± 0.06 M⊙, a stellar radius of Rgiant = 24.9 ± 0.7 R⊙, and a giant mass of Mgiant = 1.00 ± 0.07 M⊙. We identify a likely non-stellar, diffuse veiling component with contributions in the B and V band of ${\sim }63{{\ \rm per\ cent}}$ and ${\sim }24{{\ \rm per\ cent}}$, respectively. The SED and the absence of continuum eclipses imply that the companion mass must be dominated by a compact object. We do observe eclipses of the Balmer lines when the dark companion passes behind the giant, but their velocity spreads are low compared to observed accretion discs. The X-ray luminosity of the system is $L_{\rm X}\simeq 7.6\times 10^{29}~\rm ergs~s^{-1}$, corresponding to L/Ledd ∼ 10−9. The simplest explanation for the massive companion is a single compact object, most likely a black hole in the ‘mass gap’.« less
  2. Abstract The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hardmore »scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.« less
    Free, publicly-accessible full text available December 1, 2023
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  4. Abstract The EXO-200 experiment searched for neutrinoless double-beta decay of 136 Xe with a single-phase liquid xenon detector. It used an active mass of 110 kg of 80.6%-enriched liquid xenon in an ultra-low background time projection chamber with ionization and scintillation detection and readout. This paper describes the design and performance of the various support systems necessary for detector operation, including cryogenics, xenon handling, and controls. Novel features of the system were driven by the need to protect the thin-walled detector chamber containing the liquid xenon, to achieve high chemical purity of the Xe, and to maintain thermal uniformity acrossmore »the detector.« less
    Free, publicly-accessible full text available February 1, 2023
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  7. Abstract This article presents the reconstruction of the electromagnetic activity from electrons and photons (showers) used in the MicroBooNE deep learning-based low energy electron search. The reconstruction algorithm uses a combination of traditional and deep learning-based techniques to estimate shower energies. We validate these predictions using two ν μ -sourced data samples: charged/neutral current interactions with final state neutral pions and charged current interactions in which the muon stops and decays within the detector producing a Michel electron. Both the neutral pion sample and Michel electron sample demonstrate agreement between data and simulation. Further, the absolute shower energy scale ismore »shown to be consistent with the relevant physical constant of each sample: the neutral pion mass peak and the Michel energy cutoff.« less
    Free, publicly-accessible full text available December 1, 2022
  8. A bstract The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affectsmore »the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 93.7% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in ν μ CC interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.« less
    Free, publicly-accessible full text available December 1, 2022
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