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Thermodynamics with strong light-matter interaction

The interplay between light and matter, encompassing molecules and condensed matter, has a rich historical background. Techniques that leverage these interactions to discern the properties of molecules and condensed matter—such as spectroscopy—are ubiquitously employed across fields like chemistry, physics, and biology.

While light-matter interactions hold paramount experimental significance, they often exhibit a "weak coupling" from a theoretical standpoint. This characteristic allows them to be studied using perturbative approaches. A classic example is the application of time-dependent perturbation theory, which yields the renowned "Fermi’s Golden Rule." This rule has been instrumental in elucidating numerous spectroscopic experimental findings.

Nevertheless, the interaction between light (photons) and matter (electrons or vibrational/phonon modes) can also be pronounced, especially within optical cavities. Here, the wavefunction of a photon intermixes with that of an electron or vibration. In such scenarios, the conventional perturbation approach falls short in modeling light-matter interactions. Instead, one must view photons and electrons or vibrations as an integrated system. Unlike the predominantly detection-oriented weak light-matter interactions, strong interactions offer avenues to actively modify matter's properties.

These pronounced light-matter interactions give rise to a myriad of captivating phenomena, including alterations in excitonic states and modulations in chemical reaction rates. Our research focus gravitates towards discerning the changes in the ground state properties of multi-molecule systems instigated by these strong interactions. Given that the merging of electronic and photon states can recalibrate intermolecular dynamics, we harness machine learning to model these interactions. Further, we employ molecular dynamics simulations to elucidate the structural and thermodynamic attributes of multi-molecule systems within optical cavities.

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