Instead, the detectors monitor for other particles that are produced when a cosmic ray strikes a molecule in Earth’s upper atmosphere. A collision like this causes a massive chain reaction of secondary particles – known as an air shower – that cascades downward. By the time one of these air showers reaches the ground, it can cover an area of up to 10,000 acres (40 square kilometers) and contain over 10 billion secondary particles – such as electrons, photons, and muons.The CRAYFIS project focuses on tracking one specific type of secondary particle produced by cosmic-ray air showers: muons. As it turns out, smartphone cameras use technology that is very similar to that found in particle detectors. With just a simple app, a smartphone camera can effectively be tuned to detect muons produced in air showers. With enough smartphone detectors spread over a wide enough area, the researchers believe they can retrace the paths of air showers, which would help them calculate where in the sky the initial cosmic rays came from.After a volunteer installs the CRAYFIS app on their smartphone, they leave the phone facing down overnight so that photons do not trigger the camera sensor. The app then captures megapixel images and scans through them at up to 15 frames per second. If the app’s algorithm detects any potential muon events, it sends the data back to the CRAYFIS server. Although it sounds like this would lead to a lot of detections, the researchers say that less than 1 in 500 image frames would capture a muon track.But herein lies the problem: Even if the researchers can rally the millions of idle phones they need for the study, they are still faced with the task of separating true detections from background noise. Unsurprisingly, they already have found a solution.“A trigger algorithm is required to eliminate background data,” said Andrei Ustyuzhanin, head of LAMBDA, in a press release. “We created a neural network for the detection of muon signals, which can be used on any mobile phone fast enough to process a video stream. A special feature makes it possible to use the algorithm on something as simple as a mobile phone, meaning that they can now analyze responses to cosmic rays.”The neural network relies on a technique the researchers call lazy convolution. First, the trigger algorithm analyzes a high-resolution image to identify any potential areas of interest. If it doesn’t find anything noteworthy, it throws out the image (hence the lazy). However, if the algorithm finds a potential muon track, it flags the region for follow-up, discarding the rest of the image and repeating the process over again.As the algorithm strips away more and more noise with each iteration, it refines the initial path of the triggering muon. With enough phones synched together in a massive array, the researchers think they can trace the paths of specific air showers – and, therefore, their progenitor cosmic rays.If successful, the CRAYFIS project will enable astrophysicists around the world to sift through massive amounts of data to help pin down the mysterious origins of ultra-high energy cosmic rays. Furthermore, the authors note in the study that “the proposed method [for detecting muons with mobile phones] does not contain any application-specific assumptions and can be, in principle, applied to a wide range of problems.”So, if you have ever wanted to participate in real astronomical research with the possibility of becoming a published author, CRAYFIS is for you. If not, I still recommend you stay tuned to the CRAYFIS project, because with the help of millions of citizen scientists, it may reveal the mysterious origins of cosmic rays.To join the hunt for cosmic rays, simply download a beta version of the app at https://crayfis.io/