A Deep learning library for neutrino telescopes
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Updated
Nov 5, 2024 - Python
A Deep learning library for neutrino telescopes
Monte Carlo-based data analysis
Code to compute exact two- and three-neutrino oscillation probabilities using SU(2) and SU(3) expansions
Neutrino oscillation probability calculator
The official repository for MaCh3
Global Neutrino Analysis
NeUtrino Detection and Ranging (NUDAR): earth modeling and neutrino detection simulation software
Neutrino oscillations in vacuum for 2 and 3 flavors.
Using deep learning techniques to measure neutrino oscillations. (MSci Project)
Rafelski, J., Steinmetz, A., & Yang, C. T. Dynamic fermion flavor mixing through transition dipole moments. International Journal of Modern Physics A 38.31 (2023): 2350163.
Contribution to the Harald Fritzsch Memorial Volume edited by Gerhard Buchalla, Dieter Lüst and Zhi-Zhong Xing.
Visualization of neutrino oscillations
In this dataset, we have 130K observations with 50 features. The features are measurements of Cherenkov light and scintillation light using hit topology and timing. There are 36.5K observations for electron neutrinos and 93.5K observations for muon neutrinos, which yields an imbalance ratio of 0.39
a lite version of codebase (with all assets removed) Only stores the most important scripts and programs
Summation method to evaluate (anti)neutrino spectrum from reactors
Code for computing the bipolar neutrino oscillations in core-collapse supernovae.
recent neutrino physics papers monitor
Quantum Simulations of three flavour Neutrino Oscillations using the PMNS theory, in a subspace of a two-qubit Hilbert space.
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