Getty Images
Many companies are now offering access to general-purpose quantum computers, but they are not currently being used to solve real-world problems because they are hampered by issues with the number and quality of qubits. Most of the users are either doing research projects or just gaining experience programming in the system in the hope that future computers will help them.
There are quantum systems based on commercially used superconducting hardware. It’s just not a general purpose computer.
D-Wave provides a so-called quantum annealer. The hardware is a large collection of linked superconducting devices that use quantum effects to reach the energy ground state of the system. If properly constructed, this final state represents the solution to the mathematical problem. The Annealer cannot solve all mathematical problems in the same way that general-purpose quantum computers created by Google, IBM, and others can. But they can be used to solve various optimization problems.
It can introduce errors into the system, but the consequences are relatively minor as they tend to leave the system with solutions that are close to the mathematically optimal solution.
Unlike general-purpose quantum computers, it has not been mathematically proven that quantum annealers can consistently outperform classical computers. However, unlike general-purpose quantum computers, they have had high bit counts, high connectivity, and reasonable error rates for several years. And many companies are now using them to solve real-world problems.
drug search
One company relying on D-Wave hardware is POLARISqb. POLARISqb works in the field of drug discovery, identifying potential drug molecules with software for companies to test them in biological systems. That general approach is widespread in the pharmaceutical industry. This means identifying diseases caused by inappropriate protein activity and finding molecules that alter protein function in ways that alleviate the disease.
If we know the three-dimensional structure of a protein and the portion of the protein that is required for its function, we can use computer modeling to see how well the drug molecule binds to that portion. This kind of modeling is computationally expensive, but still cheaper than synthesizing molecules and testing them in cells. This is also part of his POLARISqb process, rear We use a quantum annealer that is used to identify molecules to test in detailed modeling.
“We design a large virtual chemical space and then use a quantum computer to search that chemical space to find the most suitable molecule,” POLARISqb founder Shahar Keinan told Ars. The notion of “best” goes far beyond simply having a molecule stick tightly to a protein.
“We’re not just looking for molecules with a single property, we’re looking for molecules with a whole profile of properties that give us what we’re looking for,” said Keinan. “The molecule should not be too big or too small. It should be sufficiently soluble, but not too soluble. It must also have something that can be relatively easily synthesized.
