L. Heinrich

HEPData: a repository for high energy physics data

The Durham High Energy Physics Database (HEPData) has been built up over the past four decades as a unique open-access repository for scattering data from experimental particle physics papers. It comprises data points underlying several thousand publications. Over the last two years, the HEPData software has been completely rewritten using modern computing technologies as an overlay on the Invenio v3 digital library framework. The software is open source with the new site available at this https URL now replacing the previous site at this http URL. In this write-up, we describe the development of the new site and explain some of the advantages it offers over the previous platform.

Lead-tungstate scintillator studies for a fast low-energy calorimeter

Detector cells consisting of fast lead-tungstate crystals viewed by avalanche photo-diodes were designed, built and bench-tested. It was found that cooling the crystals to -20 C, using two avalanche photo-diodes per crystal, and using fast pulse shaping provided the light yield, low noise, and fast response needed for use in 100 MeV calorimetry at high beam rates. The achieved stochastic term coefficient is 0.8% and the time response is characterized by a single decay term of 24 ns.

Analysis preservation in ATLAS

Long before data taking, ATLAS established a policy that all analyses need to be preserved. In the initial data-taking period, this has been achieved by various tools and techniques. ATLAS is now reviewing the analysis preservation with the aim of bringing coherence and robustness to the process and with a clearer view of the level of reproducibility that is reasonably achievable. The secondary aim is to reduce the load on the analysts. Once complete, this will serve for our internal preservation needs but also provide a basis for any subsequent sharing of analysis results with external parties.

Analysis Preservation and Systematic Reinterpretation within the ATLAS experiment

The LHC data analysis software used in order to derive and publish experimental results is an important asset that is necessary to preserve in order to fully exploit the scientific potential of a given measurement. An important use-case is the re-usability of the analysis procedure in the context of new scientific studies such as the reinterpretation of searches for new physics in terms of signal models that not studied in the original publication (RECAST). We present the usage of the graph-based workflow description language yadage to drive the reinterpretation of preserved HEP analyses. The analysis software is preserved using Docker containers, while the workflow structure is preserved using plain JSON documents. This allows the re-execution of complex analysis workflows on modern distributed container orchestration systems and enables a systematic reinterpretation service based on such preserved analysis.

Yadage and Packtivity – analysis preservation using parametrized workflows

Preserving data analyses produced by the collaborations at LHC in a parametrized fashion is crucial in order to maintain reproducibility and re-usability. We argue for a declarative description in terms of individual processing steps - packtivities - linked through a dynamic directed acyclic graph (DAG) and present an initial set of JSON schemas for such a description and an implementation - yadage - capable of executing workflows of analysis preserved via Linux containers.