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A Deep learning library for neutrino telescopes
Python tools for working with the IceCube public data.
A lightweight event generator for new physics in neutrino-nucleus scattering.
This repository contains the code used to perform the analysis described in the paper "A stacked search for spatial coincidences between IceCube neutrinos and radio pulsars" (https://arxiv.org/abs/2306.03427). The code is written in Python 3.10 and uses the following packages: numpy, scipy, matplotlib, pandas, numba, multiprocessing.
Magnetic moments of astrophysical neutrino (supernova and ultra high-energy neutrinos)
NuSD is a Geant4-based simulation framework developed to perform simulation studies on various segmented scintillation detectors.
A Monte Carlo simulation of the electromagnetic cascade to compute the neutrino spectrum from cascade development.
Rafelski, J., Birrell, J., Steinmetz, A. and Yang, C.T. A short survey of matter-antimatter evolution in the primordial universe. Universe 9.7 (2023): 309.
Contribution to the Harald Fritzsch Memorial Volume edited by Gerhard Buchalla, Dieter Lüst and Zhi-Zhong Xing.
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.
Steinmetz, A. Modern topics in relativistic spin dynamics and magnetism. PhD dissertation. University of Arizona, 2023.
Investigating coincident source-neutrino detections through simulations.
A Convolutional Neural Network Implementation for the CHIPS Water Cherenkov R&D Project.
Central repository for scripts handling ZTF Target of Opportunity requests using AMPEL. This includes neutrino, GRB and GW events.
Title: Convolution Neural Networks for the CHIPS Neutrino Detector R&D Project
A collection of limits on heavy neutral leptons, including their nuSMEFT interactions
Calculation of the effective number of neutrino species Neff in the Standard Model considering QED corrections but neglecting neutrino oscillations.
This code provides the possibility to perform gravitational waves follow-ups with a neutrino telescope.
Classical and Quantum Machine Learning tools for an High Energy Physics task - Final project for Laboratory of Computational Physics module B
Allows user to specify different sources of reactor neutrino isotope fluxes and a list of weights, and generates an output neutrino spectrum
Reconstructing the average antineutrino direction with the PROPSECT detector.
Visualisation of the Geant4 MEMPHYS simulation done with softinex tools.
UCL PHAS0056 (Machine Learning for Physicists) Final Project. Applying ML techniques to the binary classification and energy reconstruction of simulated neutrino events in LArTPCs
{EPITECH} | Second year | Math project
Visualization of neutrino oscillations
The goal of this competition is to predict a neutrino particle’s direction, with a model based on data from the "IceCube" detector.
This repo is the codes used for the neutrino/W bosons reconstruction from fully leptonic decay related to the Bell Study in the HWW* decay at the ATLAS experiment, CERN.