While many companies are now offering access to general-purpose quantum computers, they are currently not being used to solve real-world problems, being held back by qubit count and quality issues. Most of their users are either conducting research projects or simply gaining experience programming on the systems in anticipation that a future computer will be useful.
There are quantum systems based on superconducting hardware that are used commercially; It’s just that they’re not general-purpose computers.
D-Wave offers a so-called quantum annealer. The hardware is a large collection of interconnected superconducting devices that use quantum effects to achieve ground energetic states for the system. When properly configured, this final state represents the solution to a math problem. Annealers cannot solve the same range of math problems as general-purpose quantum computers like those made by Google, IBM, and others. But they can be used to solve a variety of optimization problems.
While the systems can suffer from errors, the consequences are relatively minor as they tend to leave the systems with a solution that is mathematically close to an optimal one.
Unlike general-purpose quantum computers, it has not been mathematically proven that quantum annealers can consistently outperform conventional computers. But unlike general-purpose quantum computers, they’ve had high bit counts, good connectivity, and reasonable error rates for a number of years. And a number of companies are now using them to solve real-world problems.
Addiction to drugs
One of the companies that relies on D-Wave hardware is POLARISqb, which works in drug discovery, identifying potential drug molecules in software so companies can test them in biological systems. His general approach is widely used in the pharmaceutical industry: identify a disease caused by inappropriate activity of a protein, and then find a molecule that alters the protein’s function in a way that ameliorates the disease.
If you know the three-dimensional structure of the protein and which parts of the protein are needed for its functions, you can use computer models to see how well drug molecules bind to that part. This type of modeling is computationally intensive, but still cheaper than synthesizing the molecule and testing it on cells. It is also part of the POLARISqb process – but it comes after this Using a quantum annealer used to identify molecules to test with detailed modeling.
“We design a virtual large chemical space and use a quantum computer to search that chemical space to find the best molecules,” Shahar Keinan, founder of POLARISqb, told Ars. The concept of “best” here goes well beyond molecules that just cling tightly to a protein.
“We’re not just looking for molecules that have a single property; we’re looking for molecules that have an entire property profile that gives us what we’re looking for,” Keinan said. “The molecule must not be too big or too small; the molecule must be soluble enough, but not too soluble. It also needs to be something that can be synthesized relatively easily.
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