Browsing UA Faculty Publications by Publisher "E D P SCIENCES"
Now showing items 1-3 of 3
The Astrolabe Project: Identifying and Curating Astronomical ‘Dark Data’ through Development of Cyberinfrastructure ResourcesAs research datasets and analyses grow in complexity, data that could be valuable to other researchers and to support the integrity of published work remain uncurated across disciplines. These data are especially concentrated in the "Long Tail" of funded research, where curation resources and related expertise are often inaccessible. In the domain of astronomy, it is undisputed that uncurated "dark data" exist, but the scope of the problem remains uncertain. The "Astrolabe" Project is a collaboration between University of Arizona researchers, the CyVerse cyberinfrastructure environment, and the American Astronomical Society, with a mission to identify and ingest previously-uncurated astronomical data, and to provide a robust computational environment for analysis and sharing of data, as well as services for authors wishing to deposit data associated with publications. Following expert feedback obtained through two workshops held in 2015 and 2016, Astrolabe is funded in part by National Science Foundation. The system is being actively developed within CyVerse, and Astrolabe collaborators are soliciting heterogeneous datasets and potential users for the prototype system. Astrolabe team members are currently working to characterize the properties of uncurated astronomical data, and to develop automated methods for locating potentially-useful data to be targeted for ingest into Astrolabe, while cultivating a user community for the new data management system.
Prompt atmospheric neutrino flux from the various QCD modelsWe evaluate the prompt atmospheric neutrino flux using the different QCD models for heavy quark production including the b quark contribution. We include the nuclear correction and find it reduces the fluxes by 10% - 50% according to the models. Our heavy quark results are compared with experimental data from RHIC, LHC and LHCb.
Upgrade of ATLAS data quality monitoring for multithreaded reconstructionATLAS is embarking on a project to multithread its reconstruction software in time for use in Run 3 of the LHC. One component that must be migrated is the histogramming infrastructure used for data quality monitoring of the reconstructed data. This poses unique challenges due to its large memory footprint which forms a bottleneck for parallelization and the need to accommodate relatively inexperienced developers. We discuss plans for the upgraded framework.