Quantum chemistry may not be the “killer app” for quantum computers after all

Quantum chemistry calculations that could advance drug development or agriculture have recently emerged as a promising “killer application” of quantum computers, but a new analysis suggests this is unlikely to be the case.

Progress in building quantum computers has greatly accelerated in recent years, but it remains an open question what uses are most likely to justify the ongoing investment in this technology. One popular contender is solving problems in quantum chemistry, such as calculating the energy levels of molecules relevant for biomedicine or industry. This requires accounting for the behavior of many quantum particles – electrons in the molecule – simultaneously, so it seems like a good match for computers made from many quantum parts.

However, Xavier Waintal at CEA Grenoble in France and his colleagues have now shown that two leading quantum computing algorithms for this task may actually have, at best, limited use.

“My personal thinking is that it’s probably doomed, not proven doomed, but probably doomed,” he says about using quantum computers for molecular energy calculations.

The researchers split their mathematical analysis in two parts, one pertaining to existing quantum computers, which are all prone to errors, and one concerning future quantum computers that would be “fault-tolerant”, or fully error-proof.

When using error-prone, or noisy, quantum computers, molecular energy levels can be calculated with the variational quantum eigensolver (VQE) algorithm, but the accuracy of its results depends on how severe that noisiness is.

The team’s analysis found that for VQE to compete on accuracy with chemistry algorithms that can run on conventional computers, quantum computers’ noisiness must be suppressed so severely that they would effectively have to be fault-tolerant. Notably, a practical fault-tolerant quantum computer has not been made yet.

Several quantum computing companies are aiming to build fault-tolerant quantum within five years and those devices could compute molecules’ energies with a different algorithm called quantum phase estimation (QPE). Here, the issue of errors is nearly eliminated, but the study underscores a problem that goes by the ominous name of “orthogonality catastrophe”.

Put simply, this means that as the size of molecules increases, the likelihood that QPE can calculate its lowest energy level decreases exponentially. As a result, team member Thibaud Louvet at the French quantum computing company Quobly says that even with great quantum computers, there would only be a small number of cases where using them to run QPE would be the most practical and best choice. In his view, being able to run this algorithm should be seen more as a benchmark of quantum computers’ maturity than something that could become a mainstay for working chemists.

“It is easy to over-hype the prospects of quantum computers in this domain, with many thinking that the advent of quantum computers will instantly render any classical approach to quantum chemistry obsolete,” says George Booth at King’s College London, who wasn’t involved in the work. “This study is clear to point out significant challenges for accurate molecular simulation, which will remain even in the ‘fault-tolerant era’, and cast doubt on whether quantum chemistry is really such a quick win for quantum computers.”

But he says there are still other ways in which quantum computers could be used in chemistry. For example, they could simulate how chemical systems change after being perturbed, such as being hit with laser light.