Deconvolution algorithms popular in Cherenkov astronomy


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Deconvolution estimates the probability density function of a latent quantity by relating this quantity to other, measurable quantities. It is frequently used in Cherenkov astronomy, where the energy distribution of cosmic particles is estimated from data taken by a telescope.

Getting Started

You can install this package with the Julia package manager (Julia-0.7 and above):

] add CherenkovDeconvolution

The example directory provides you with some usage examples. More information is to be found on our website.

Current Status

CherenkovDeconvolution.jl implements our enhanced version of the Dortmund Spectrum Estimation Algorithm (DSEA+), the Regularized Unfolding (RUN) method, and the Iterative Bayesian Unfolding (IBU). An extensive set of experiments is taken out on these algorithms in another repository.

We also ported this package to Python, calling it CherenkovDeconvolution.py.

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Last Touched

25 days ago


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