A hydrogen atom, for instance, has one positively charged proton and one electron and is easy to simulate on a laptop – you could even work out its chemistry by hand. Helium, next step along on the periodic table, has two protons, orbited by two negatively charged electrons – but it’s more challenging to simulate, because the electrons are entangled, so the state of one is linked to the state of the other, which means they all need to be calculated simultaneously.
“We can’t really predict how electrons are going to behave right now,” says Zapata’s Christopher Savoie. “If we can get into a world where we’re simulating it on a computer, we can be more predictive and do fewer actual laboratory experiments.” It is, he says, as if Airbus were still testing planes by building small-scale models and throwing them into the sky. “You cannot simulate chemical processes that you’re interested in,” says Google’s Sergio Boixo.
There are three ways in which quantum computers can help improve our understanding of reactions at the molecular level. The first approach involves building a specific computer to model the problem you’re trying to solve – physically recreating the molecule with the right number of qubits corresponding to its actual structure.
Key to solving that problem is understanding the structure of FeMoco, a complex molecule at the heart of the enzyme that’s too difficult for classical computers to model. In 2017, a research team from Microsoft and ETH Zurich demonstrated that a quantum computer with a hundred logical qubits could solve this problem – but acknowledged that they would need up to a million physical qubits to form them.
The ability to potentially identify new compounds is one reason why the medical industry is excited about quantum computing. We have already seen how quantum computers should be able to process data from MRI scans more efficiently and accurately, but they could also save billions in drug design, by enabling companies to quickly identify new compounds, and then simulate their effects without having to synthesise them.
Variational quantum algorithms use a hybrid of quantum and classical computers to speed up calculations. In a, Peter Johnson – lead research scientist and founder at Zapata – draws a comparison with the way Google Maps finds you the best route home in a reasonable amount of time. “The app does not search through all possible routes,” he writes. “Instead, it ends up searching through a well-motivated subset of routes and partial routes.
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