“Implementing computational chemistry to discover new materials and drugs will be one of the most fruitful areas of leveraging quantum computing,” said Doug, executive editor of Quantum Computing Reports
“The resulting discoveries will have a huge impact on many areas of society in the coming years,” Finke said. “However, doing this effectively requires careful pairing of people with extensive knowledge of molecular chemistry with those with extensive knowledge of quantum computing and Teams of others with knowledge of quantum algorithms. QC
This partnership between Ware and Covestro should prove to be a very effective combination, and we look forward to seeing the results of their research in the coming years. ”

The agreement is in line with Covestro’s goal of strengthening the company’s digital R&D process, paving the way for carbon neutrality by achieving full circles. The collaboration combines Covestro’s expertise in classical computational chemistry and empirical manufacturing techniques, as well as QC
Ware’s lead in classical and quantum algorithms.

“We hope that quantum computing will help us solve simulation problems that state-of-the-art classical computing cannot,” said Torsten Heinemann, head of innovation at Covestro Group.
Ware’s joint research over the next five years is aimed at developing new tools that our R&D teams can use to develop new material categories and more efficient production processes that require fewer resources. We hope this work will help take our R&D efforts to a whole new level and accelerate the pace at which we develop innovations. ”

The agreement follows a year-long collaboration on a proof-of-concept project exploring the possibility of modeling large-scale molecules required for industrial applications on near-term quantum computers. The results of this project are outlined in two recently published papers:

The first paper introduces new quantum technologies that can significantly reduce the quantum computing resources required to design new materials and chemical processes. These techniques reduce circuit depth and connectivity requirements, key components that will be used with sufficient quantum hardware in production applications.

The second paper introduces a new method for computing energy gradients on quantum computers, a key property used by industrial computational chemists to model chemical reactions, catalysts, products, transition states and catalytic properties.

“Computational chemists are not only interested in the ground state energy of molecules – they are interested in key properties such as atomic forces, color and light absorption properties or electrical conductivity. In our use of QC
Before Ware’s paper, these properties were difficult to compute on near-term quantum computers, but now we think we have a very tractable path forward,” said Christian, an expert on advanced computing concepts and quantum computing at Covestro Digital R&D.
Gogolin said.

“To provide real value to computational chemists, we need to build new quantum computing tools with capabilities unmatched by conventional computers. We are working with Covestro to achieve this by building a complete solution that The scheme combines the best high-performance classical techniques for preprocessing and postprocessing with advanced quantum algorithms reserved for the crux of computational problems.” QC
Robert Parrish, head of chemical simulation at Ware, said.