# Characterization of Cameras for the COSMO K-Coronagraph

## TL;DR

This paper characterizes the digital camera errors affecting the K-Coronagraph, develops correction methods for nonlinearity and ADC errors, and demonstrates their importance for achieving scientific accuracy in solar observations.

## Contribution

It provides a detailed analysis of camera digitization errors, derives correction techniques, and demonstrates their effectiveness for high-precision solar polarimetry.

## Key findings

- Quantization errors are negligible for the MV-D1024E camera due to its bit depth.
- ADC and nonlinearity errors can cause systematic measurement errors exceeding science requirements.
- Pixel-wise correction of nonlinearity reduces residual errors to below 0.1%.

## Abstract

Digital image sensors are ubiquitous in astronomical instrumentation and it is well known that they suffer from issues that must be corrected for data to be scientifically useful. I present discussion on errors resulting from digitization and characterization of nonlinearity and ADC errors of the PhotonFocus MV-D1024E cameras selected for the K-Coronagraph of the Coronal Solar Magnetism Observatory. I derive an analytic expression for quantization errors. The MV-D1024E camera has adequate bit depth for which quantization error is not an issue. I show that this is not the case for all cameras, particularly those with deep wells and low read noise. The impact of nonlinearity and ADC errors on science observations of the K-Coronagraph is analyzed using a simplified telescope model. Errors caused by the camera ADCs result in systematic errors in the measurement of the polarimetric signal of several times $10^{-9}~B_\odot$, which is about an order of magnitude above the desired sensitivity. I demonstrate a method for post-facto data correction using a lookup table and derive parameters from camera characterization measurements that were made with a lab setup. Nonlinearity is traditionally addressed with a global correction. I show through analysis of calibration data that for the MV-D1024E this correction leaves residual systematic errors after dark and gain correction of up to 1% of the signal. I demonstrate that a pixel-wise correction of nonlinearity reduces the errors to below 0.1%. These corrections are necessary for the K-Coronagraph data products to meet the science requirements. They have been implemented in the instrument data acquisition system and data reduction pipeline. While no other instruments besides the K-Coronagraph or cameras besides the MV-D1024E are discussed here, the results are illustrative for all instruments and cameras.