Molecular Quantum Impurities

Interfacing quantum systems with light is crucial for advancing quantum technology, which stands as a defining challenge of our era. Molecular impurities embedded in solid hosts hold immense potential, yet they currently face several hurdles, including: (i) a limited comprehension of their behavior, (ii) the absence of a clear exploration strategy to unlock their vast potential, and (iii) their static and nondeterministic implementation within solids, a characteristic shared with many alternative approaches. We develop: (i) a predictive theory for molecular impurities in host materials based on first principles. (ii) A systematic machine-learning approach to identify new molecular guest-host matches. (iii) Smart molecule-host systems which allow dynamic (un)loading of the molecular impurity – a miniature version of cold atoms in optical traps. In our initial work (Öhman et al., 2026), we found that a combination of cheminformatics, density-functional theory, machine-learning potentials, and classification can identify promising new candidates. Building on this basis, we envision a collaborative approach between theory and experiment to find the perfect combination of guest molecule and host crystal for each application as quantum light-matter interface.