ATLAS

Abstract:

A search for an invisibly decaying Higgs boson or dark matter candidates produced in association with a leptonically decaying Z boson in proton–proton collisions at s=13 TeV is presented. This search uses 36.1 fb−1 of data collected by the ATLAS experiment at the Large Hadron Collider. No significant deviation from the expectation of the Standard Model backgrounds is observed. Assuming the Standard Model ZH production cross-section, an observed (expected) upper limit of 67% (39%) at the 95% confidence level is set on the branching ratio of invisible decays of the Higgs boson with mass mH=125 GeV. The corresponding limits on the production cross-section of the ZH process with the invisible Higgs boson decays are also presented. Furthermore, exclusion limits on the dark matter candidate and mediator masses are reported in the framework of simplified dark matter models.

Abstract:

© Published under licence by IOP Publishing Ltd. The ATLAS Eventlndex System has amassed a set of key quantities for a large number of ATLAS events into a Hadoop based infrastructure for the purpose of providing the experiment with a number of event-wise services. Collecting this data in one place provides the opportunity to investigate various storage formats and technologies and assess which best serve the various use cases as well as consider what other benefits alternative storage systems provide. In this presentation we describe how the data are imported into an Oracle RDBMS (relational database management system), the services we have built based on this architecture, and our experience with it. We've indexed about 26 billion real data events thus far and have designed the system to accommodate future data which has expected rates of 5 and 20 billion events per year. We have found this system offers outstanding performance for some fundamental use cases. In addition, profiting from the co-location of this data with other complementary metadata in ATLAS, the system has been easily extended to perform essential assessments of data integrity and completeness and to identify event duplication, including at what step in processing the duplication occurred.

Abstract:

© Published under licence by IOP Publishing Ltd. Conditions data (for example: alignment, calibration, data quality) are used extensively in the processing of real and simulated data in ATLAS. The volume and variety of the conditions data needed by different types of processing are quite diverse, so optimizing its access requires a careful understanding of conditions usage patterns. These patterns can be quantified by mining representative log files from each type of processing and gathering detailed information about conditions usage for that type of processing into a central repository.