New algorithm by Riverlane accelerates quantum chemistry
28 Feb 2019

A Generalised Variational Quantum Eigensolver paper

"A Generalised Variational Quantum Eigensolver" paper by Riverlane research

One of the most compelling uses of a quantum computer is to find approximate solutions to the Schrodinger equation. Such ab initio or first-principles calculations form an important part of the computational chemistry tool-kit and are used to understand features of large molecules such as the active site of an enzyme in a chemical reaction or are coupled with molecular mechanics to guide the design of better drugs.

Riverlane's paper, “Accelerated Variational Quantum Eigensolver“, has just been accepted for publication in the leading journal for quantum algorithms, Physical Review Letters. It demonstrates a new method for accelerating the variational quantum eigensolver (VQE) algorithm that underlies all current work in quantum chemistry.

The VQE algorithm uses circuits that grow slowly with the problem size. This makes it very attractive for near term uses on noisy quantum computers as the program is able to finish within the time limit set by the hardware. But as coherence times improve there is an opportunity to perform additional quantum computing to refine the result and decrease the total runtime of VQE. Acccelerated-VQE takes advantage of this and offers a scalable speed-up, now and in the future.

Steve Brierley, CEO, commented “I’m extremely proud of Oscar and Daochen – this was their first paper and having that published in PRL is a big deal. The result means as quantum computers continue to scale up, our software just gets faster!”