Title: The power of data science and optics in chemistry
Today, exact quantum dynamics simulations face the “curse of dimensionality,” in which computational cost grows exponentially as the dimensionality of molecular systems increases. This limits exact grid-based quantum dynamics simulations to the smallest molecular systems. Low-rank tensor-network approaches provide a way to surmount this curse for many chemical systems, as they can exponentially reduce computational cost for weakly coupled molecular systems. Our work capitalizes on the native advantages of tensor networks and the high degree of entanglement possible on quantum computers to develop new approaches to simulate molecular systems. In addition, we demonstrate that reflectionless scattering mode theory from optics can be reformulated in quantum mechanics to reveal the existence of long-sought-after quantum mechanical parity-time reversal (PT) symmetry behavior in standard ultracold-atom scattering experiments, a discovery which opens the door to the development of powerful quantum technologies.