Geometry optimization of large molecules with quantum Monte Carlo

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The availability of advanced computational tools to accurately and efficiently describe light-induced processes in complex systems is key to the development of new technologies for artificial photosynthesis, photo-catalysis, bio-imaging, and photo-medical applications. Computing excited states, however, is highly demanding for electronic structure methods, which often struggle to ensure accuracy or to treat the large, relevant system sizes. To overcome these limitations, we will work in the alternative framework of quantum Monte Carlo methods which use stochastic algorithms to solve the Schrödinger equation, scale well with system size, and offer a balanced description of the ground and electronic excited states. Here, we intend to further push this methodology and extend its applicability to the computation of structural properties of large molecular systems in the ground and excite states. To this aim, we will accelerate the computation of interatomic forces required to determine optimal structures and reaction pathways, by developing improved estimators characterized by small fluctuations and reduced bias. This will allow for considerably shorter Monte Carlo simulations and equally accurate structures with the use of simpler wave functions and, therefore, open the possibility to treat significantly larger systems. Furthermore, we plan to extend and explore the use of the more accurate and robust diffusion Monte Carlo method to structural relaxation. The advances achieved via these developments will be demonstrated on the study of the photoinduced switching mechanism of donor-acceptor Stenhouse adduct molecules, a novel class of synthetic photoswitches with promising applications in material science and biological systems.