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  1. Abstract We report on the design and performance of the B icep3 instrument and its first three-year data set collected from 2016 to 2018. B icep3 is a 52 cm aperture refracting telescope designed to observe the polarization of the cosmic microwave background (CMB) on degree angular scales at 95 GHz. It started science observation at the South Pole in 2016 with 2400 antenna-coupled transition-edge sensor bolometers. The receiver first demonstrated new technologies such as large-diameter alumina optics, Zotefoam infrared filters, and flux-activated SQUIDs, allowing ∼10× higher optical throughput compared to the Keck design. B icep3 achieved instrument noise equivalentmore »temperatures of 9.2, 6.8, and 7.1 μ K CMB s and reached Stokes Q and U map depths of 5.9, 4.4, and 4.4 μ K arcmin in 2016, 2017, and 2018, respectively. The combined three-year data set achieved a polarization map depth of 2.8 μ K arcmin over an effective area of 585 square degrees, which is the deepest CMB polarization map made to date at 95 GHz.« less
    Free, publicly-accessible full text available March 1, 2023
  2. For the past decade, the BICEP/Keck collaboration has been operating a series of telescopes at the Amundsen-Scott South Pole Station measuring degree-scale B-mode polarization imprinted in the Cosmic Microwave Background (CMB) by primordial gravitational waves (PGWs). These telescopes are compact refracting polarimeters mapping about 2% of the sky, observing at a broad range of frequencies to account for the polarized foreground from Galactic synchrotron and thermal dust emission. Our latest publication "BK18" utilizes the data collected up to the 2018 observing season, in conjunction with the publicly available WMAP and Planck data, to constrain the tensor-to-scalar ratio r. It particularlymore »includes (1) the 3-year BICEP3 data which is the current deepest CMB polarization map at the foreground-minimum 95 GHz; and (2) the Keck 220 GHz map with a higher signal-to-noise ratio on the dust foreground than the Planck 353 GHz map. We fit the auto- and cross-spectra of these maps to a multicomponent likelihood model (ΛCDM+dust+synchrotron+noise+r) and find it to be an adequate description of the data at the current noise level. The likelihood analysis yields σ(r)=0.009. The inference of r from our baseline model is tightened to r0.05=0.014+0.010−0.011 and r0.05<0.036 at 95% confidence, meaning that the BICEP/Keck B-mode data is the most powerful existing dataset for the constraint of PGWs. The up-coming BICEP Array telescope is projected to reach σ(r)≲0.003 using data up to 2027.« less
    Free, publicly-accessible full text available March 1, 2023
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  4. Free, publicly-accessible full text available October 1, 2022
  5. 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
  6. Abstract The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed tomore »meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.« less
    Free, publicly-accessible full text available December 1, 2023