Active Pixel sensors play a crucial role in enabling successful low-light scientific experiments due to their inherent advantages and capabilities. Such devices not only offer high spatial resolution but also feature individual pixels with integrated amplifiers, allowing for direct signal amplification at the pixel level. This results in reduced readout noise and improved signal-to-noise ratio (SNR), which are particularly vital when dealing with limited photon counts in low-light environments. This holds particularly true for scientific CMOS (sCMOS) sensors, acknowledged as an advanced evolution of Active Pixel sensors. However, despite their advantages, such sensors can still exhibit limitations such as higher cost and presence of noise artifacts that should be closely investigated. In particular, CYGNO project fits in a global effort aimed at direct detection of Dark Matter particles. CYGNO collaboration intends to build a detector based on a Time Projection Chamber making use of Gas Electron Multipliers for the amplification of ionization electrons. The GEM multiplication process produces photons that can be readout by a high-resolution sCMOS sensor. Such detection system is being designed to have enough sensitivity to detect low-energy particles and to measure released energy with enough granularity so to reconstruct direction and energy profile along their trajectories. The image sensor has an important role in the detector performance, having a direct impact on the SNR of the experiment. This work proposes a study on the performance of three different sCMOS sensors with respect to their sensitivity to low-energy particles and their intrinsic noise, which are of the utmost importance for various scientific experiments.
Read full abstract