High‑accuracy, High‑throughput Chemical Property Prediction On Demand
Incremental Full Configuration Interaction (iFCI) Methods
Incremental-FCI employs the many-body expansion coupled with virtual orbital selection, providing a polynomial-scaling approximation to FCI, which can recover FCI energies to within chemical accuracy.
Machine Learning (ML)-based solvers
QEMIST Cloud includes DFT-and CCSD(T)-trained machine learning models that are 1000x faster than their corresponding quantum chemistry methods.
Cloud-optimized Density Functional Theory (DFT) implementations
DFT methods designed to run on high performance cloud infrastructure for high-throughput calculations, fast and efficient ground-state energy calculations and geometry optimization.
Powered by AI, elevated by quantum computing
QEMIST Cloud continually learns from every simulation to accelerate subsequent simulation. It also enables seamless experimentation on real quantum devices. QEMIST Cloud integrates with our open-source quantum computing SDK, Tangelo, so you can connect and use quantum devices from different providers, supporting rapid experimentation.
Reimagine how chemistry is simulated
Shape the future of chemistry and materials innovation by joining our growing list of illustrious researchers, customers and design partners, including DOW and DIC.