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  1. ; ; ; ; ; ; ; ; ; ; et al ( , Computing and Software for Big Science)
    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
  2. ; ; ; ; ; ; ; ; ; ; et al ( , Computing and Software for Big Science)
    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
  3. ; ; ; ; ; ; ; ( , Bulletin of the American Meteorological Society)
    Accepted Manuscript Full Text Available
  4. ; ; ( , International journal of production research)
    Integrating renewable energy into the manufacturing facility is the ultimate key to realising carbon-neutral operations. Although many firms have taken various initiatives to reduce the carbon footprint of their facilities, there are few quantitative studies focused on cost analysis and supply reliability of integrating intermittent wind and solar power. This paper aims to fill this gap by addressing the following question: shall we adopt power purchase agreement (PPA) or onsite renewable generation to realise the eco-economic benefits? We tackle this complex decision-making problem by considering two regulatory options: government carbon incentives and utility pricing policy. A stochastic programming model ismore »formulated to search for the optimal mix of onsite and offsite renewable power supply. The model is tested extensively in different regions under various climatic conditions. Three findings are obtained. First, in a long term onsite generation and PPA can avoid the price volatility in the spot or wholesale electricity market. Second, at locations where the wind speed is below 6 m/s, PPA at $70/MWh is preferred over onsite wind generation. Third, compared to PPA and wind generation, solar generation is not economically competitive unless the capacity cost is down below USD1.5 M per MW.« less
    Full Text Available 
  5. ; ; ; ; ; ; ; ; ; ; et al ( , Bulletin of the American Meteorological Society)
    Full Text Available 
  6. ; ; ; ; ; ; ; ; ; ( , Bulletin of the American Meteorological Society)
    Phenology is the study of recurring events in nature and their relationships with climate. The word derives from the Greek phaínō ‘appear’ and logos ‘reason’, emphasizing the focus on observing events and understanding why they occur (Demarée and Rutishauser 2009). Phenological recording has a history that dates back many centuries (Linneaus and Bark 1753; Aono and Kazui 2008). More recently, advances in monitoring technologies have enabled automated and remotely sensed observations, complemented by increasing citizen science participation in monitoring efforts. Phenological information can also be derived from widespread environmental monitoring stations around the globe.
    Accepted Manuscript Full Text Available
  7. ; ; ; ; ; ; ; ; ; ; et al ( , Bulletin of the American Meteorological Society)
    null (Ed.)
    Full Text Available 
  8. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review D)
    Free, publicly-accessible full text available May 1, 2023
  9. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review D)
    Free, publicly-accessible full text available May 1, 2023
  10. ; ; ; ; ; ; ; ; ; ; et al ( , The European Physical Journal C)
    Abstract The energy response of the ATLAS calorimeter is measured for single charged pions with transverse momentum in the range $$10more »situ single-particle measurements. The calorimeter response to single-pions is observed to be overestimated by $${\sim }2\%$$ ∼ 2 % across a large part of the $$p_{\text {T}}$$ p T spectrum in the central region and underestimated by $${\sim }4\%$$ ∼ 4 % in the endcaps in the ATLAS simulation. The uncertainties in the measurements are $${\lesssim }1\%$$ ≲ 1 % for $$15« less
    Free, publicly-accessible full text available March 1, 2023