Analysis of the uncertainties in the determination of the stokes parameters employing the proof of concept prototype of the spectropolarimeter for the Galileo Solar Space Telescope (GSST/INPE) - Adriany Rodrigues Barbosa (2021)
The study of the solar magnetic field is of great importance for our high-tech society. It is the key driver of many solar phenomena and has a huge impact on the terrestrial space environment. A better understanding of the Sun's magnetic field is fundamental to understand better how the Sun influences the Earth. Therefore, the development of technologies for studying the Sun is essential. In particular, the methods to measure the solar magnetic field are using ground-based or space-borne telescopes. The most reliable and accurate technique for solar magnetic field measurements is based on spectropolarimetry, i.e., the solar spectrums in terms of intensity and polarization (Stokes vector). INPE's solar physics group is developing a spectropolarimeter Proof of Concept Prototype of the Spectropolarimeter (PCPS) through the Galileo Solar Space Telescope (GSST) Project. Within the master's project, the PCPS capabilities to determine the Stokes vector and the related uncertainties are investigated. The PCPS camera was characterized, and the Mueller Matrix for an Etalon state was estimated. During the exchange program (BEPE) at the MPS, SUSI / SUNRISE was analyzed. The SUSI cameras were studied, and also the theoretical Mueller matrix of the instrument. We used data from the Solar Optical Telescope (SOT) / Hinode to study image calibration. The SOT camera's readout defects were corrected, and the influence of radiation bands/cosmic ray spikes on the data was examined. We performed a simulation to validate the Mueller Matrix of the proof of concept. In the simulation, our Mueller matrix was multiplied by the estimated HMI Stokes parameters. The results show that in all polarization states, the intensity changes due to the polarization effect of sunspots. Therefore, we can obtain the Stokes parameter by PCPS by comparing the models output with the observed value.