Microsoft bolsters quantum platform with gen AI, molecular simulation capabilities

Researchers can ask Generative Chemistry for molecules with desired characteristics, as well as provide information about their targeted application and let the system help determine relevant molecular properties, according to Microsoft. The feature not only will provide them with candidates matching their parameters, but also suggest molecules that have not been seen before with useful properties tuned for a specific application, and whose synthesis is feasible in a reasonable number of steps.

Density Functional Theory (DFT) is a method used across a variety of molecular simulations that helps researchers to simulate and study the electronic structure of atoms, molecules and nanoparticles, as well as surfaces and interfaces. Such DFT simulations can be complex and compute-intensive to optimize and run, often requiring the use of supercomputers.

Microsoft has now added Accelerated DFT as a managed service to Azure Quantum Elements to run these simulations at what the company said is “an unprecedented speed;” that is, an order of magnitude faster compared to PySCF, a widely used open-source DFT code, according to the post.


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