Computer-Aided Materials Design
In Silico Drug Design
Harnessing the combined power of emerging quantum computing technologies and state-of-the-art classical techniques, the Quantum-Enabled Molecular ab Initio Simulation Toolkit, or QEMIST, is 1QBit’s innovative solution to a fundamental and intractable problem in chemistry: ab initio simulation of molecules.
The accurate prediction of the electronic structure of a molecule is key to the design of new materials, such as drug compounds and catalyst molecules, by helping to anticipate a material’s properties before its synthesis in the lab. However, obtaining this information using classical computers is computationally intensive, and the resources required for an exact solution scale exponentially with the size of the problem. Attempts to provide approximate approaches to this problem on classical computers have been to date either limited to small-sized systems or compromising on the accuracy of the simulation.
QEMIST is designed to enable the accurate calculation of molecular properties by leveraging advanced problem decomposition (PD) techniques and quantum computing. The variety of PD techniques implemented in QEMIST enables massively parallel simulations by breaking down a computational chemistry task into smaller, independent subproblems. These subproblems can use a combination of interfaces to various classical and quantum solvers to achieve a higher level of accuracy for large-scale, practical molecular simulations.
Leverages automated and highly optimized problem decomposition techniques to break down complex simulation tasks into smaller independent subproblems that can be handled accurately and in parallel for large-scale practical molecular simulations.
Implements state-of-the-art quantum and classical algorithms to determine molecular electronic structure, a fundamental problem in predicting the structure, reactivity, and properties of molecular systems.
Relies on ab initio electronic structure theory, which consists of a systematically improvable hierarchy of methods that rapidly converge toward the exact solution.
Operates on a modular, platform-agnostic architecture that allows users to continually leverage the most-advanced quantum computing platforms as they scale alongside classical platforms.
While this is an exciting start, there’s much more to QEMIST to explore with 1QBit. Consider becoming an Industry Partner to unlock the full potential of QEMIST for your high-value problems.
Microsoft and 1QBit Collaborate to Advance Materials Science
Together, 1QBit and Microsoft have developed an implementation of the variational quantum eigensolver (VQE) algorithm that works with Python and Q# and demonstrated the integration of the QDK with QEMIST through an example of density matrix embedding theory (DMET) for resource-efficient, larger-scale quantum simulations… Read More.