reconstruction framework for radio detectors of high-energy neutrinos
-
Updated
Mar 24, 2021 - Python
reconstruction framework for radio detectors of high-energy neutrinos
Computational and historical research framework associated with Beating Substrate Theory (BST), a reconstruction-oriented generative framework investigating emergent physical organization from coherent substrate dynamics.
Reusable ICARUS IaaS workflow for ML inference through Triton/EAF, using NuGraph2 as the benchmark path from local validation to grid-scale stress testing.
Add a description, image, and links to the reconstruction-framework topic page so that developers can more easily learn about it.
To associate your repository with the reconstruction-framework topic, visit your repo's landing page and select "manage topics."