AWS launches quantum computing service Braket

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Amazon Web Services is preparing to roll out a quantum computing service for its cloud customers. The platform, called Amazon Braket, will provide on-demand access to quantum systems from three different start-ups.

The service was recently presented at re:Invent, the cloud provider’s annual conference. Braket is intended as a service that allows companies to become familiar with quantum technology and discover potential uses.

The three systems offered are all based on different designs. The Rigetti Computing system works with superconductors, an IonQ system works with ion traps, and the third system of D-Wave systems works with an approach called “quantum glowing”. This gives companies a choice of three rather different approaches, thus also freeing up the opportunity to test these systems against each other.

According to Silicon Angle, none of the three systems offered through Braket are capable of running advanced business applications. However, they do provide a useful environment for companies to learn how to handle quantum computers, and to find ways to deploy any potential large-scale, production-ready quantum machines of the future.

Different approaches

Analyst Patrick Moorhead of Moor Insights & Strategy states that AWS spreads its chances with quantum partners who each have a different approach. “D-Wave is using quantum annealing, IonQ uses trapped ions and Rigetti uses superconducting,” he noted. ”[I] was a bit disappointed to not see Honeywell since it has the most sophisticated trapped ion approach we have seen. I suppose its partnering with Azure could have been an issue.”

Tools

A number of tools are added to the service to make the learning curve less steep for users. For example, the service includes a simulation environment powered by classic computers, which developers can use to build quantum algorithms. They can then test them before they are used on one of the actual quantum machines. In addition, Braket supports the popular Jupyter Notebook algorithm development toolkit that many researchers have known for some time.