The variational quantum eigensolver (VQE) is a key algorithm for molecular simulation invented by Zapata founders. With bp, we ran tens of thousands of hours of computing to explore how soon VQE can make an impact for quantum chemistry use cases. We benchmarked VQE on various quantum hardware backends, and advanced proprietary techniques to make VQE more viable in the near-term.
While a working enterprise-scale VQE solution is likely still years away, we discovered other use cases that could go into production much sooner. We expanded beyond chemistry to include use cases in finance, cybersecurity, and logistics, and accelerated bp's Quantum Center of Expertise team.
Discover new alloys, catalysts, carbon capture solvents, battery materials, solar cell materials and other industrial chemicals.
Optimize the manufacturing process for chemicals and materials.
Design more efficient nuclear reactors.
Optimize the location of solar panels, wind turbines, mines and other energy production sites to maximize output and minimize costs.
Optimize oil and gas well drilling routes to maximize production rates while minimizing costs.
More accurately model fluid dynamics.
Predict the optimal times to service pipelines and other energy infrastructure.
Optimize delivery routes and pipeline network layouts to reduce fuel costs, carbon emissions, and delivery times.
Optimize the design of energy grids to maximize reliability, resilience and efficiency while minimizing costs.
Optimize the scheduling of high-power computing tasks to mitigate battery exhaustion, for example, on edge electronics.
