Oct 10 – 14, 2016
San Francisco Marriott Marquis
America/Los_Angeles timezone

Giving pandas ROOT to chew on: experiences with the XENON1T Dark Matter experiment

Oct 10, 2016, 2:00 PM
GG C1 (San Francisco Mariott Marquis)


San Francisco Mariott Marquis

Oral Track 2: Offline Computing Track 2: Offline Computing


Daniela Remenska (eScience engineer)


In preparation for the XENON1T Dark Matter data acquisition, we have
prototyped and implemented a new computing model. The XENON signal and data processing
software is developed fully in Python 3, and makes extensive use of generic scientific data
analysis libraries, such as the SciPy stack. A certain tension between modern “Big Data”
solutions and existing HEP frameworks is typically experienced in smaller particle physics
experiments. ROOT is still the “standard” data format in our field, defined by large experiments
(ATLAS, CMS). To ease the transition, our computing model caters to both analysis paradigms,
leaving the choice of using ROOT-specific C++ libraries, or alternatively, Python and its data
analytics tools, as a front-end choice of developing physics algorithms. We present our path on
harmonizing these two ecosystems, which allowed us to use off-the-shelf software libraries (e.g.,
NumPy, SciPy, scikit-learn, matplotlib) and lower the cost of development and maintenance.
To analyse the data, our software allows researchers to easily create “mini-trees”; small, tabular
ROOT structures for Python analysis, which can be read directly into pandas DataFrame
structures. One of our goals was making ROOT available as a cross-platform binary for an
easy installation from the Anaconda Cloud (without going through the “dependency hell”). In
addition to helping us discover dark matter interactions, lowering this barrier helps shift the
particle physics toward non-domain-specific code.

Primary Keyword (Mandatory) Analysis tools and techniques
Secondary Keyword (Optional) Career and diversity issues
Tertiary Keyword (Optional) Data processing workflows and frameworks/pipelines

Primary author

Daniela Remenska (eScience engineer)


Christopher Tunnell Dr Jason Maassen (eScince engineer) Jeff Templon (Nikhef National institute for subatomic physics (NL)) Mr Jelle Aalbers (PhD student) Mr Stefan Verhoeven (eSicence engineer)

Presentation materials