YQI Talk - Hannah Lange - LMU Munich

 

Since the discovery of superconductivity in the cuprates, identifying the minimal ingredients required for high-Tc superconductivity has remained a central open question. Motivated by the recent discovery of a nickelate superconductor with bilayer structure, I will present a minimal bilayer model in which inter- and intralayer magnetic interactions - but no interlayer hopping - are present: a mixed-dimensional (mixD) t-J bilayer. There are three main motivations for studying this model: (i) It hosts rich physics including a crossover from a Bose-Einstein condensate to Bardeen-Cooper-Schrieffer regime, as well as different pairing symmetries relevant to a variety of materials beyond bilayer nickelates. These features can be interpreted in terms of a Feshbach resonance between different pairing channels. (ii) The model can be realized in analog quantum simulators and, combined with local control, enables direct measurements of pair correlations in experiments, illustrating the power of hybrid analog–digital simulation platforms. (iii) We show that the model can be simulated efficiently using machine-learning–based representations of quantum many-body states, specifically neural quantum states (NQS). I will introduce this method, compare it to conventional numerical approaches, and discuss possible synergies with quantum simulators and tensor-network techniques.

With the two mixD model layers interpreted as separate orbitals, our work represents the first multiband simulation using NQS, indicating that NQS have now advanced to the point where they can tackle increasingly realistic models relevant to materials.