  The Distributed Electronic Cosmic-ray Observatory (DECO) is a cell phone app
that uses a cell phone camera image sensor to detect cosmic-ray particles and
particles from radioactive decay. Images recorded by DECO are classified by a
convolutional neural network (CNN) according to their morphology. In this
project, we develop a GEANT4-derived simulation of particle interactions inside
the CMOS sensor using the Allpix$^2$ modular framework. We simulate muons,
electrons, and photons with energy range 10 keV to 100 GeV, and their deposited
energy agrees well with expectations. Simulated events are recorded and
processed in a similar way as data images taken by DECO, and the result shows
both similar image morphology with data events and good quantitative data-Monte
Carlo agreement.
