Design and control of strongly correlated quantum matter: from materials to programmable quantum hardware

Abstract

This thesis makes three contributions to the understanding, control, and design of strongly correlated quantum matter. First, motivated by recent experiments reporting light-induced superconductivity, magnetism, and charge order, this thesis develops a unified description of photoexcited quantum materials. We show that seemingly disparate nonequilibrium phenomena can often be interpreted in terms of emergent order parameters and their collective dynamical fluctuations, providing a framework for modeling complex driven many-body systems with competing equilibrium phases. We propose experimental tests of this framework, several of which have already been realized, and highlight the role of programmable quantum simulators as platforms for studying driven many-body physics and probing emergent nonequilibrium order. Second, the thesis investigates atomically thin materials, with a primary focus on transition metal dichalcogenides (TMDs), as a platform for exploring strongly interacting quantum matter and for designing electro-optical quantum devices. In addition to electrical tunability, TMDs are direct band-gap semiconductors exhibiting sharp excitonic resonances in the optical frequency range, enabling optical manipulation of these materials. At relevant carrier densities, interactions dominate, leading to rich and unconventional behavior. To this end, we report the observation of Wigner crystallization, interlayer electron coherence, magnon hydrodynamics, and excitonic superradiance. Finally, motivated by rapid progress in programmable neutral-atom quantum simulation and computation, this thesis introduces a general algorithmic framework for {\it inverse quantum simulation} aimed at quantum material design. Target material characteristics are encoded as a cost function, which is minimized on quantum hardware to prepare a many-body state with the desired properties in quantum memory. Hamiltonian learning is then used to reconstruct a low-energy Hamiltonian for which this state is an approximate ground state, yielding a physically interpretable model that can guide experimental realization. This framework extends the scope of quantum simulators from exploring quantum many-body systems to designing and discovering new quantum materials.