Monte Carlo-based data analysis
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Updated
Sep 2, 2024 - Python
Monte Carlo-based data analysis
Python tools for working with the IceCube public data.
Unbinned likelihood analysis code for astroparticle physics datasets
This project aims to incorporate the effects of hole ice into the clsim photon propagation simulation of the icecube neutrino observatory.
Bayesian constraints on the astrophysical neutrino population from IceCube data
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.
A Supernova TEst Routine for IceCube Analysis
IceCube Astrophysical Flavor analysis using Bayesian inference
Technical specification and documentation for BWS IceCubes, a friendly alternative to AWS Snowballs.
Play and learn with the TinyFPGA development board featuring a Lattice iCE40 LP8K FPGA with a very compact footprint.
Simulation of the Optics of the Imaging Air-Cherenkov Telescopes IceAct with Geant4
Astrophysical Neutrino Anisotropy
Scripts to test dark matter point source candidates using IceCube public PS data.
An OpenCL-based photon-tracking simulation using a (source-based) ray tracing algorithm modeling scattering and absorption of light in the deep glacial ice at the South Pole or Mediterranean sea water.
IceCube - Neutrinos in Deep Ice
Kaggle competition (2023). Predict neutrino particle direction with Deep Graph Neural Networks.
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