Data Analysis and Machine Learning Models for High Energy Physics and Particle Physics experiments associated with ATLAS and CMS detectors.
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Updated
Mar 10, 2020 - Jupyter Notebook
Data Analysis and Machine Learning Models for High Energy Physics and Particle Physics experiments associated with ATLAS and CMS detectors.
Cosmic muons telescope based on plastic scintillators, SiPMs and gaseous detector
Tensor based engine for calculating neutrino oscillation probabilities in a fast, flexible, and differentiable way
A simulation of the Bloch Beamline at the MAX IV synchrotron in Lund, Sweden. The simulation is implemented in the McXtrace meta-language using ANSI-C.
This is a transformer model that does particle track fitting
🔍 Explore a unification framework where Standard Model observables emerge as Casimir eigenvalues, enabling precise predictions for future experiments.
I present a candidate unification framework in which Standard Model observables emerge as Casimir eigenvalues of the exceptional structures E8 × H4. The approach requires no free parameters: all 25 observables derive from fixed group-theoretic invariants (Coxeter numbers, exponents, degrees, and the golden ratio). Deviation from experiment is 0.07%
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