Quantum computing

Quantum computing may significantly widen the range of chemical systems: Covestro

The discovery of new catalysts, enabling more efficient chemical processes and recycling routes, and the design of new chemical products, may all benefit from such enhanced simulation capabilities.
Covestro and Google are co-operating on research for novel computer technology. They are expanding on the innovation leadership with quantum computing.

Here, Christian Gogolin, Expert in Quantum Computing at Covestro, speaks about the initiative. Excerpts from an interview:

DQINDIA Online | DATAQUEST

Christian Gogolin, Expert in Quantum Computing at Covestro

DQ: How can quantum computing benefit chemistry?

Christian Gogolin: Quantum computing is an emerging, novel computing paradigm that has the potential to make certain calculations feasible that will remain impossible on classical computing devices. Quantum computers appear to be particularly good at simulating quantum mechanical processes, such as those happening during chemical reactions in molecules.

DQ: What are the new, groundbreaking perspectives opening up?

Christian Gogolin: In the future, quantum computing may significantly widen the range of chemical systems that can be accurately simulated, which will open up new possibilities for discovery in chemistry, and thus, for the chemical industry. The discovery of new catalysts, enabling more efficient chemical processes and recycling routes, and the design of new chemical products, may all benefit from such enhanced simulation capabilities.

DQ: The anatomy of a superconducting qubit is interesting. Have you broken any new ground?

Christian Gogolin:  We are not working on quantum computing hardware, but rather, want to further the development of quantum computing algorithms and software. Here, we have already broken new ground by proposing a new kind of ansatz for so-called variational quantum algorithms, which combines the ideas from quantum computing with such additions from classical computational chemistry.

DQ: Amplifiers, etc., are still a large research effort. Noise and errors will be there with us for a while. How are you developing algorithms?

Christian Gogolin: That’s very correct! Quantum computing hardware is still very limited, but improving at a fast pace. When developing algorithms with the aim of already doing something practically useful with the noisy quantum computers of the medium term future one needs to take this into account.

Algorithms must be designed such that they have some amount of inherent robustness to noise and mitigation techniques must be employed to correct the outcomes. This means that developing algorithms for quantum computers is quite different from classical algorithm development.

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