Reconstructing High-Fidelity Light Yield Maps for Surface LArTPCs Using Crossing Cosmic Muons
This paper presents a method for reconstructing high-fidelity, voxelized 3D light yield maps in surface liquid argon time projection chambers by utilizing crossing cosmic muons and solving a regularized inverse problem, which significantly improves spatial accuracy and stability compared to detector-wide averages.
Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Deep underground, physicists are building massive tanks filled with liquid argon, a substance as cold as deep space, to catch the faint signals of neutrinos. These ghostly particles, which zip through the Earth almost without interacting, are key to understanding the universe's most fundamental forces. When a neutrino does collide with an atom inside the tank, it creates a flash of light and a trail of electric charge. Scientists use the electric charge to see exactly where the collision happened, but the light offers a second, powerful way to measure the energy of the event. To turn that flash of light into a precise energy measurement, researchers need to know exactly how bright the light is at every single point inside the tank. If the light is dimmer in one corner than another, a simple average calculation would give the wrong answer for any event happening in that corner. The challenge is that the light does not shine evenly; it fades as it travels and is caught more easily near the sensors than far away.
A team of researchers has developed a new way to map this uneven brightness, creating a detailed three-dimensional picture of how much light the detector sees at every location. They tested their method using a computer simulation of a large, real-world detector called ProtoDUNE-VD, which is a prototype for a much larger experiment being built deep underground in South Dakota. Instead of using a special light source to measure the tank, they used the natural rain of cosmic rays that constantly bombards the Earth. These are high-energy particles from space, mostly muons, that pass straight through the detector like needles through a block of cheese. As these muons travel, they leave a trail of light and charge. By tracking the path of thousands of these muons and counting how much light they produced along the way, the researchers could work backward to figure out the brightness of the detector at every point the muons crossed.
The process is like solving a giant puzzle where the pieces are the paths of the muons and the picture is the map of light. Each muon travels through many small sections of the tank, called voxels. The researchers knew how much energy a muon loses as it moves through liquid argon, so they could calculate how much light should have been created in each section it crossed. They then compared this expected amount to the actual amount of light the sensors recorded. By combining the data from tens of thousands of muons, they built a massive system of equations that allowed them to solve for the unknown brightness of every single voxel. To make sure the result was physically possible, they added a rule that the brightness could never be negative. They also added a smoothing rule to prevent the map from having wild, unrealistic spikes or dips in brightness, ensuring the final picture looked like a natural, continuous field of light rather than a noisy, jagged mess.
When they compared their new map to a highly accurate computer model of how the detector should behave, the results were striking. The map they built from the muon tracks successfully recovered the main features of the detector's light response. It correctly showed that the light is brighter near the sensors and dimmer in the middle of the tank. The method was sensitive enough to notice when the researchers changed the setup of the sensors in the simulation, such as removing a group of light detectors from the bottom of the tank; the new map immediately showed a drop in brightness in that specific area. The researchers found that using the smoothing rule made the map much more accurate. Without it, the map was full of random errors and empty spots where the calculation had failed to find a value. With the smoothing, the errors dropped by nearly half, and the map looked much closer to the true, expected behavior of the detector.
This work proves that scientists can use the natural stream of cosmic rays to calibrate the light sensors in these massive detectors without needing to install complex, artificial light sources inside the tank. While the study was performed entirely in a computer simulation, the method is designed to be applied to real data from detectors on the surface of the Earth, where cosmic muons are abundant. The researchers showed that their technique can handle different sizes of map sections and different numbers of muon tracks, finding that a few tens of thousands of muons are enough to create a stable and reliable map. This approach offers a practical way to ensure that future neutrino experiments can measure the energy of particle collisions with high precision, turning the chaotic rain of cosmic rays into a precise tool for mapping the invisible light inside the world's largest liquid argon tanks.
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