State of the Art Analog Quantum Hamiltonian Dynamics Simulations with GPUs

Analog Hamiltonian quantum dynamics simulations are critical for a range of application areas from photovoltaics, batteries, materials science and quantum processor design. Simulating the time dynamics of open quantum systems is computationally intensive due to the necessity of solving differential equations, for example the time-dependent Schrodinger Equation or the Lindblad Master Equation. These differential equations can be represented via matrix math at the lowest level and gain significant speedup from GPU computing techniques. We present new capabilities for accelerating analog quantum Hamiltonian dynamics simulations multiple orders of magnitude beyond existing CPU implementations and an order of magnitude faster than existing GPU implementations to further accelerate quantum processors design cycles.