Due to the fact that we cannot directly measure the physical properties of astrophysical bodies, all our quantitative knowledge about the Universe is based on the interpretation of the observed light emitted by these objects (i.e. remote sensing). In this course, we will focus on:
- The generation and propagation of light in the Solar and stellar atmospheres;
- Its interaction with Earth’s atmosphere and with our instruments;
- Methods for inferring the physical characteristics of the object (temperature, chemical composition, magnetic field, etc.) from the light we are receiving.
To this end, we will combine concepts from electromagnetism, optics, quantum mechanics, and probabilistic inference. Besides the astrophysical applications, the course will equip the students with tools they can use in their careers, both in science and in other areas related to STEM. The lectures will be reinforced with hands-on exercises in python with a brief critical introduction to python programming.
The following topics will be addressed in lectures:
- Introduction to telescopes and image formation; Atmospheric effects and image restoration.
- Spectral discriminators: spectrographs and filtergraphs
- Polarimetry: anisotropy as sources of polarization, polarimetric modulation and demodulation.
- Basics of spectral line formation: absorption, emission, and scattering. Zeeman effect and polarization due to the magnetic field.
- Parameter inference: Model fitting, probabilistic inference, uncertainty estimation
Practical exercises will include problem solving, use of scientific software, participation in remote observing with Europe’s largest solar telescope GREGOR (Tenerife, Spain), analysis of GREGOR data from the KIS Science Data Centre archive.
Minimum requirements: 2 years of undergraduate physics with electromagnetism. Course is open to bachelor and master students.
Recommended: introductory quantum/atomic physics, mathematical methods for physicists (Fourier transforms, linear algebra, matrix diagonalization, eigenvalues), and introductory programming.
- Introduction to spectropolarimetry. Del Toro Iniesta. Cambridge Univ. Press. 2003
- The Sun: an introduction. M. Stix, SpringerLink, 2003
- Inverse problems in Astronomy, I.J.D. Craig & J.C. Brown, CRC Press, 1986
- Numerical Recipes, the Art of Scientific Programming, 3rd edition, C. Press et al., Cambridge University Press, 2007