Improving the energy resolution of photon counting Microwave Kinetic Inductance Detectors using principal component analysis

TL;DR

This paper introduces a PCA-based method for photon energy measurement in MKIDs that improves energy resolution by utilizing multiple principal components, especially near detector saturation conditions.

Contribution

It extends PCA-based energy measurement to use any number of principal components and calibration energies, enhancing resolution in MKIDs and TKIDs.

Findings

Improved energy resolution for TKIDs from 75 eV to 43 eV at 5.9 keV.

Achieved energy resolutions in optical/near-IR MKIDs comparable to existing best methods.

Demonstrated PCA's effectiveness in handling pulse shape variations near detector saturation.

Abstract

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.