New Models for Electronic Structure Prediction and Analysis

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Most of the worlds major technological and societal challenges are being addressed through research in chemistry, including health, climate change, energy, security, and food supply. With rapid advances in computational power over the last two decades, advanced research computing (ARC) has now become an indispensable research tool in the chemical sciences and many other fields. Research scientists routinely rely on computational simulations to complement, and often exceed, what can be achieved with experiments alone, securing ARC as a transformative modern technology with broad socioeconomic impact in Canada. Unfortunately however, modern computational techniques for modelling chemical systems scale very poorly with molecular size, leading to a practical limit on the scope of molecular species accessible by computational means. Consequently, if computational techniques are to be reliably applied to the ever-increasing scope of important problems in chemistry, radically new computational models are required. Additionally, as the prevalence of computational simulation in chemistry expands, there is a concurrent need for techniques to distill relevant insight and meaning from resultant data, particularly for predictions of detailed electronic structures in quantum chemistry.