GPU ACCELERATED MICROWAVE KINETIC INDUCTANCE DETECTOR (MKID) READOUT SYSTEM

Abstract

Microwave Kinetic Inductance Detectors (MKIDs) have proven to be valuable instruments for detecting weak signals in the microwave and millimeter-wave spectrum ranges in many scientific domains. Their novel operating principle, which is based on the detection of kinetic inductance changes in superconducting resonators, has led to applications in astronomy, quantum computing, and materials science. The efficient reading of MKID arrays, on the other hand, creates computational challenges and frequently necessitates the use of advanced data processing techniques. While effective, traditional readout systems based on Field Programmable Gate Arrays (FPGA) have limitations in terms of flexibility and development simplicity. This study looks into the possibility of Graphics Processing Unit (GPU) acceleration to overcome these difficulties. Using an example from current research, this research demonstrates how GPU acceleration can improve MKID readout systems, improve performance, and facilitate adjustments. In addition to speeding up development, the integration of GPUs opens up novel opportunities for MKID applications across scientific disciplines.