Abstract
The Faster Analysis Software Taskforce (FAST) is a small, European group of HEP researchers that have been investigating and developing modern software approaches to improve HEP analyses. We present here an overview of the key product of this effort: a set of packages that allows a complete implementation of an analysis using almost exclusively YAML files. Serving as an analysis description language (ADL), this toolset builds on top of the evolving technologies from the Scikit-HEP and IRIS-HEP projects as well as industry-standard libraries such as Pandas and Matplotlib. Data processing starts with event-level data (the trees) and can proceed by adding variables, selecting events, performing complex user-defined operations and binning data, as defined in the YAML description. The resulting outputs (the tables) are stored as Pandas dataframes which can be programmatically manipulated and converted to plots or inputs for fitting frameworks. No longer just a proof-of-principle, these tools are now being used in CMS analyses, the LUX-ZEPLIN experiment, and by students on several other experiments. In this talk we will showcase these tools through examples, highlighting how they address the different experiments’ needs, and compare them to other similar approaches.
Highlights
Producing high-quality research papers in High-Energy Physics (HEP) involves processing petabytes of data, applying the latest knowledge for the specific experiment and the statistical evaluation of the end-results and their uncertainties. This process often involves the use of experiment specific software frameworks, community packages as well as researcher-written code
The key aims of the Faster Analysis Software Taskforce (FAST) are to: a) reduce the amount of researcher-written code to minimize mistakes, b) lower the entry requirements for new researchers, c) make it easier to share, and d) provide an abstraction between the analysis itself and the processing system that runs over the data
The mechanism used to load stages extensible; if fast-carpenter does not provide a stage that you need for your analysis, it is easy to write it and include it in your workflow
Summary
Producing high-quality research papers in High-Energy Physics (HEP) involves processing petabytes of data, applying the latest knowledge for the specific experiment and the statistical evaluation of the end-results and their uncertainties. The key aims of the Faster Analysis Software Taskforce (FAST) are to: a) reduce the amount of researcher-written code to minimize mistakes, b) lower the entry requirements for new researchers, c) make it easier to share, and d) provide an abstraction between the analysis itself and the processing system that runs over the data. New datasets can become available as a physics run continues, simulations are extended, or existing data is reprocessed through early stages. Input data are described as one or more data sets in YAML files that are generated and interpreted using the fast-curator package.
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