The ATLAS experiment is preparing for data taking at 14 TeV collision energy. A rich discovery physics program is being prepared in addition to the detailed study of Standard Model processes which will be produced in abundance. The ATLAS multi-level trigger system is designed to accept one event in 2 • 10B to enable the selection of rare and unusual physics events. The ATLAS calorimeter system is a precise instrument, which includes liquid Argon electromagnetic and hadronic components as well as a scintillator-tile hadronic calorimeter. All these components are used in the various levels of the trigger system. A wide physics coverage is ensured by inclusively selecting events with candidate electrons, photons, taus, jets or those with large missing transverse energy. The commissioning of the trigger system is being performed with cosmic ray events and by replaying simulated Monte Carlo events through the trigger and data acquisition system.
In this paper, we present the computational task-management tool Ganga, which allows for the specification, submission, bookkeeping and post-processing of computational tasks on a wide set of distributed resources. Ganga has been developed to solve a problem increasingly common in scientific projects, which is that researchers must regularly switch between different processing systems, each with its own command set, to complete their computational tasks. Ganga provides a homogeneous environment for processing data on heterogeneous resources. We give examples from High Energy Physics, demonstrating how an analysis can be developed on a local system and then transparently moved to a Grid system for processing of all available data. Ganga has an API that can be used via an interactive interface, in scripts, or through a GUI. Specific knowledge about types of tasks or computational resources is provided at run-time through a plugin system, making new developments easy to integrate. We give an overview of the Ganga architecture, give examples of current use, and demonstrate how Ganga can be used in many different areas of science.
The first collider search for dark matter arising from a strongly coupled hidden sector is presented and uses a data sample corresponding to 138 fb−1, collected with the CMS detector at the CERN LHC, at $$ \sqrt{s} $$ s = 13 TeV. The hidden sector is hypothesized to couple to the standard model (SM) via a heavy leptophobic Z′ mediator produced as a resonance in proton-proton collisions. The mediator decay results in two “semivisible” jets, containing both visible matter and invisible dark matter. The final state therefore includes moderate missing energy aligned with one of the jets, a signature ignored by most dark matter searches. No structure in the dijet transverse mass spectra compatible with the signal is observed. Assuming the Z′ boson has a universal coupling of 0.25 to the SM quarks, an inclusive search, relevant to any model that exhibits this kinematic behavior, excludes mediator masses of 1.5–4.0 TeV at 95% confidence level, depending on the other signal model parameters. To enhance the sensitivity of the search for this particular class of hidden sector models, a boosted decision tree (BDT) is trained using jet substructure variables to distinguish between semivisible jets and SM jets from background processes. When the BDT is employed to identify each jet in the dijet system as semivisible, the mediator mass exclusion increases to 5.1 TeV, for wider ranges of the other signal model parameters. These limits exclude a wide range of strongly coupled hidden sector models for the first time.
As part of its HL-LHC upgrade program, the CMS Collaboration is developing a High Granularity Calorimeter (CE) to replace the existing endcap calorimeters. The CE is a sampling calorimeter with unprecedented transverse and longitudinal readout for both electromagnetic (CE-E) and hadronic (CE-H) compartments. The calorimeter will be built with ∼30,000 hexagonal silicon modules. Prototype modules have been constructed with 6-inch hexagonal silicon sensors with cell areas of 1.1 cm 2 , and the SKIROC2-CMS readout ASIC. Beam tests of different sampling configurations were conducted with the prototype modules at DESY and CERN in 2017 and 2018. This paper describes the construction and commissioning of the CE calorimeter prototype, the silicon modules used in the construction, their basic performance, and the methods used for their calibration.
The GridPP Collaboration is building a UK computing Grid for particle physics, as part of the international effort towards computing for the Large Hadron Collider. The project, funded by the UK Particle Physics and Astronomy Research Council (PPARC), began in September 2001 and completed its first phase 3 years later. GridPP is a collaboration of approximately 100 researchers in 19 UK university particle physics groups, the Council for the Central Laboratory of the Research Councils and CERN, reflecting the strategic importance of the project. In collaboration with other European and US efforts, the first phase of the project demonstrated the feasibility of developing, deploying and operating a Grid-based computing system to meet the UK needs of the Large Hadron Collider experiments. This note describes the work undertaken to achieve this goal. S Supplementary documentation is available from stacks.iop.org/JPhysG/32/N1. References to sections S1, S2.1, etc are to sections within this online supplement.
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