| Summary: | The characterisation of exoplanet atmospheres is crucial to understanding planet formation, the exploration of extreme atmospheric physics, finding habitable worlds, and searching for extraterrestrial life, but challenged by the overwhelming star-to-exoplanet flux contrast. High-resolution cross-correlation spectroscopy (HRCCS) overcomes this challenge by resolving individual exoplanetary spectral lines and disentangling them from the stellar and telluric lines using their difference in Doppler shift. In this thesis, I demonstrate how HRCCS can constrain the chemistry and dynamics of a range of exoplanet atmospheres. I developed a data reduction pipeline for the MMT Exoplanet Atmosphere Survey to detect carbon monoxide emission lines in the atmosphere of WASP-33 b, the first time in an exoplanet atmosphere. This provides unambiguous evidence of a thermal inversion in its atmosphere. These results are a proof of concept that the ARIES/MMT combination can be used to study exoplanet atmospheres even at R=15,000 and I further investigate the data quality limitations of this survey on the warm sub-Saturn HD 46375 A b. Recently, cross-correlation-to-log-likelihood (CC-to-log(L)) mappings suitable for HRCCS of exoplanet atmospheres emerged which constrain atmospheric abundances and the P-T profile. I use these mappings to constrain the water abundance of $\tau$ B\"oo A b and further constrain the chemistry and P-T structure WASP-33 b. I contributed a new method to use the scale parameter of a CC-to-log(L) mapping with a 3D global circulation model (GCM) to show it is consistent with an eastward hot spot offset in WASP-33 b. This demonstrates that HRS is capable of constraining atmospheric dynamics, even at a spectral resolution of R=15,000. I further compare 1D and 3D simulated datasets to investigate the climate of WASP-18 A b. These models produce very different synthetic spectra, highlighting the need to better understand the physics that needs to be included in realistic simulations of ultra hot Jupiters. In conclusion, these results show the power of 3D GCMs and CC-to-log(L) mappings combined with HRCCS to constrain exoplanet atmospheres.
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