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The major challenge posed by the high instantaneous luminosity in the High Luminosity LHC (HL-LHC) motivates efficient and fast reconstruction of charged particle tracks in a high pile-up environment. While there have been efforts to use modern techniques like vectorization to improve the existing classic Kalman Filter based reconstruction algorithms, we take a fundamentally different approach by doing a bottom-up reconstruction of tracks. Our algorithm, called Line Segment Tracking, constructs small track stubs from adjoining detector regions, and then successively links these track stubs that are consistent with typical track trajectories. Since the production of these track stubs is localized, they can be made in parallel, which lends way into using architectures like GPUs and multi-CPUs to take advantage of the parallelism. We establish an implementation of our algorithm in the context of the CMS Phase-2 Tracker which runs on NVIDIA Tesla V100 GPUs, and measure the physics performance and the computing time. 

Abstract We describe the discovery of a solar neighborhood ( d = 468 pc) binary system with a main-sequence sunlike star and a massive noninteracting black hole candidate. The spectral energy distribution of the visible star is described by a single stellar model. We derive stellar parameters from a high signal-to-noise Magellan/MIKE spectrum, classifying the star as a main-sequence star with T eff = 5972 K, log g = 4.54 , and M = 0.91 M ⊙ . The spectrum shows no indication of a second luminous component. To determine the spectroscopic orbit of the binary, we measured the radial velocities of this system with the Automated Planet Finder, Magellan, and Keck over four months. We show that the velocity data are consistent with the Gaia astrometric orbit and provide independent evidence for a massive dark companion. From a combined fit of our spectroscopic data and the astrometry, we derive a companion mass of 11.39 − 1.31 + 1.51 M ⊙ . We conclude that this binary system harbors a massive black hole on an eccentric ( e = 0.46 ± 0.02), 185.4 ± 0.1 day orbit. These conclusions are independent of El-Badry et al., who recently reported the discovery of the same system. A joint fit to all available data yields a comparable period solution but a lower companion mass of 9.32 − 0.21 + 0.22 M ⊙ . Radial velocity fits to all available data produce a unimodal solution for the period that is not possible with either data set alone. The combination of both data sets yields the most accurate orbit currently available. 

Abstract We show that a small but measurable shift in the eclipse midpoint time of eclipsing binary (EBs) stars of ∼0.1 s over a decade baseline can be used to directly measure the Galactic acceleration of stars in the Milky Way at ∼kiloparsec distances from the Sun. We consider contributions to the period drift rate from dynamical mechanisms other than the Galaxy’s gravitational field and show that the Galactic acceleration can be reliably measured using a sample of Kepler EBs with orbital and stellar parameters from the literature. The contribution from tidal decay we estimate here is an upper limit assuming the stars are not tidally synchronized. We find there are about 200 detached EBs that have estimated timing precision better than 0.5 s, and for which other dynamical effects are subdominant to the Galactic signal. We illustrate the method with a prototypical, precisely timed EB using an archival Kepler light curve and a modern synthetic HST light curve (which provides a decade baseline). This novel method establishes a realistic possibility to constrain dark matter substructure and the Galactic potential using eclipse timing to measure Galactic accelerations, along with other emerging new methods, including pulsar timing and extreme-precision radial velocity observations. This acceleration signal grows quadratically with time. Therefore, given baselines established in the near future for distant EBs, we can expect to measure the period drift in the future with space missions like JWST and the Roman Space Telescope. 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.