2021/11/02 by Jacob M. Miller, Nicholas Zobrist, Gerhard Ulbricht +1
Engineering · Mathematics · Physics and Astronomy · #Advanced Semiconductor Detectors and Materials #Artificial intelligence #Component (thermodynamics) #Computational physics #Computer science #Detector #Energy (signal processing) #Inductance #Kinetic energy #Kinetic inductance #Mathematics #Microwave #Nuclear physics #Optics #Optoelectronics #Photon #Photon counting #Photon energy #Physics #Principal component analysis #Pulse (music) #Quantum mechanics #Radiation Detection and Scintillator Technologies #Radio Frequency Integrated Circuit Design #Resolution (logic) #Statistics #Superconducting and THz Device Technology #Terahertz technology and applications #Voltage #astro-ph.IM
paper · pdf · doi:10.1117/1.jatis.7.4.048003
arxiv created 2021/11/02 · openalex publication_date 2021/11/19 · arxiv updated 2022/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
We develop a photon energy measurement scheme for single photon counting Microwave Kinetic Inductance Detectors (MKIDs) that uses principal component analysis (PCA) to measure the energy of an incident photon from the signal ("photon pulse") generated by the detector. PCA can be used to characterize a photon pulse using an arbitrarily large number of features and therefore PCA-based energy measurement does not rely on the assumption of an energy-independent pulse shape that is made in standard filtering techniques. A PCA-based method for energy measurement is especially useful in applications where the detector is operating near its saturation energy and pulse shape varies strongly with photon energy. It has been shown previously that PCA using two principal components can be used as an energy-measurement scheme. We extend upon these ideas and develop a method for measuring the energies of photons by characterizing their pulse shapes using any number of principal components and any number of calibration energies. Applying this technique with 50 principal components, we show improvements to a previously-reported energy resolution for Thermal Kinetic Inductance Detectors (TKIDs) from 75 eV to 43 eV at 5.9 keV. We also apply this technique with 50 principal components to data from an optical to near-IR MKID and achieve energy resolutions that are consistent with the best results from existing analysis techniques.