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UID:pretalx-scipy-2026-BG3PSA@pretalx.com
DTSTART;TZID=CST:20260715T131500
DTEND;TZID=CST:20260715T134500
DESCRIPTION:At CERN's Large Hadron Collider\, we collide protons at near li
 ght-speed to discover new particles and understand fundamental physics. Py
 thon is becoming the primary language for analyzing this data\, marking a 
 significant evolution from the Fortran and C++ workflows of previous decad
 es.\n\nThis talk explores the modern Python-based analysis pipeline of Hig
 h-Energy Physics (HEP) and the technical challenges it addresses. We'll pr
 esent how we handle nested\, jagged data structures and work with data at 
 the petabyte scale using the community-driven Scikit-HEP ecosystem of spec
 ialized tools for efficient and high-performance data analysis.\n\nWe'll s
 how how we're building a Python stack that integrates with distributed com
 puting frameworks and leverages GPU acceleration. Beyond domain-specific a
 nalysis tools\, HEP's transition to Python has driven improvements to the 
 broader Python packaging ecosystem\, including contributions to cibuildwhe
 el\, the development of scikit-build-core\, and advances in pybind11\, ben
 efiting anyone building Python packages with compiled extensions.
DTSTAMP:20260622T110113Z
LOCATION:University Hall
SUMMARY:Discovering Particles: How we analyze petabytes of particle collisi
 on data using python - Iason Krommydas
URL:https://pretalx.com/scipy-2026/talk/BG3PSA/
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