Case Study: Goldman Sachs advances quantum Monte Carlo simulation with QC Ware

Goldman Sachs explores Monte Carlo quantum algorithms with QC Ware, cutting iterations from millions to thousands

Goldman Sachs faced the challenge of speeding up Monte Carlo simulations for derivative pricing, a process that requires millions of iterations on classical computers. They partnered with quantum computing vendor QC Ware to explore how quantum algorithms could provide a significant speed-up, even on near-term hardware.

QC Ware developed novel quantum Monte Carlo algorithms specifically designed to run on near-term quantum computers, drastically reducing the number of required iterations. This joint research provided Goldman Sachs with a better understanding of the constraints and potential of current quantum technology for solving their business problems.

Goldman Sachs