Strongly Interacting Fermi-Fermi Mixtures of Dy and K: Monte Carlo Simulations and Trapping Potential Control

Ultracold gases with strong interactions have been studied to a great extent with the help of Feshbach resonances, and have been used as precisely controllable models for other systems that are not easily accessible experimentally. Fermionic gases are especially interesting, because they can be used to simulate many-body physics present in primordial matter, neutron stars, atomic nuclei or condensed matter systems, particularly superconductors. Since interactions in cold fermions are in general only present if the particles are not identical, most experiments have been working with two spin states of a single atomic species. Changing the number ratio of the two spins can lead to interesting new pairing phenomena, some of which have been studied extensively in recent years. Mass-imbalanced systems have been theoretically predicted to exhibit new exotic interaction regimes and phases that go beyond the physics of spin mixtures. This thesis reports on the efforts to realize a strongly interacting mass-imbalanced Fermi-Fermi mixture of Dy and K that features collisional stability as well as tunability of interaction strength and trapping geometry. Feshbach resonances have become a ubiquitous tool to control the interaction strength in ultracold gases. With the identification of a broad Feshbach resonance close to 217 G, we were able to realize a resonantly interacting sample of Dy and K. A detailed characterization of the resonance was conducted to extract relevant parameters. In the expanding mixture, the resonant interspecies interaction causes a hydrodynamic behavior which leads to a bimodal density profile. The influence of mass-imbalance and other experimental parameters on the hydrodynamic expansion have been studied with the help of a Monte Carlo simulation, and the results have been found to be in good agreement with the experimental data. The simulation model has been developed and characterized as part of this thesis and can serve as a model to gain understand
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Dissertation Universität Innsbruck 2023