Supersolid phases of ultracold bosons trapped in optical lattices dressed with Rydberg $p$-states
Authors: Mathieu Barbier, Henrik Lütjeharms, Walter Hofstetter
Abstract: Engineering quantum phases with spontaneously broken symmetries is a major goal of research in different fields. Trapped ultracold Rydberg-excited atoms in optical lattices are a promising platform for realizing quantum phases with broken lattice translational symmetry since they are interacting over distances larger than the lattice constant. Although numerous theoretical works on trapped Rydberg-excited gases have predicted such phases, in particular density wave or supersolid phases, their experimental observation proves to be difficult due to challenges such as scattering processes and the limited experimentally achievable coupling strength. Most of these previous studies have focused on isotropically interacting gases dressed with Rydberg $s$-states, while the effect of anisotropic interactions due to Rydberg-excited $p$-states in trapped quantum gases remains much less investigated. Additionally, it was shown that the excitation scheme used to excite Rydberg $p$-states possesses advantages regarding achievable coupling strengths and limitation of scattering processes compared to its $s$-state counterpart, which makes the investigation of Rydberg $p$-state dressed quantum gases even more interesting. In the present work, we study the extended, two-component Bose-Hubbard model, realized with a bosonic quantum gas with Rydberg-excited $p$-states trapped in an optical lattice, within Gutzwiller mean-field theory. We compute the ground state phase diagram and investigate its different regimes. By comparison to the phase diagram of the isotropic case, we find the anisotropic interaction to be more advantageous for the observation of supersolid phases.
Explore the paper tree
Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant
Look for similar papers (in beta version)
By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.