Google spots unusual memory behavior of anyon particles

Our intuition tells us that it should be impossible to determine if two identical objects have been swapped, but that might not always be the case in the world of quantum mechanics.

Researchers at Google Quantum AI have made a breakthrough in observing the peculiar behavior of particles called non-Abelian anyons, which have the ability to retain a “memory” when exchanged, despite being identical.

In a recent study, the Google Quantum AI team used their superconducting quantum processors to observe the behavior of non-Abelian anyons for the first time ever. They demonstrated how these particles could be manipulated to perform quantum computations. This discovery has opened up new possibilities for topological quantum computation, where operations are performed by braiding non-Abelian anyons like strings.

Trond I. Andersen, a member of the Google Quantum AI team, expressed excitement about the research, stating, “Observing the bizarre behavior of non-Abelian anyons for the first time really highlights the type of exciting phenomena we can now access with quantum computers.”

The researchers prepared their superconducting qubits in a special entangled state resembling a checkerboard pattern. By manipulating the quantum state of the qubits, they transformed the checkerboard pattern into polygons, with specific vertices hosting the non-Abelian anyons. The team successfully moved these anyons around and observed their interactions with other particles.

The experiments yielded intriguing results: particles disappeared, reappeared, and transformed as they braided with each other. The researchers also observed a measurable change in the quantum state when two non-Abelian anyons were swapped, a phenomenon never seen before.

In addition to understanding the behavior of non-Abelian anyons, the team demonstrated how braiding these particles could be used for quantum computations. By braiding multiple non-Abelian anyons together, they created a quantum entangled state known as the Greenberger-Horne-Zeilinger (GHZ) state.

These findings have implications not only for Google Quantum AI but also for other quantum computing efforts, including Microsoft’s approach. The ability to manipulate non-Abelian anyons holds promise for fault-tolerant topological quantum computing.

Quantinuum, a quantum computing company, also released a complementary study demonstrating non-Abelian braiding using a trapped-ion quantum processor. This further reinforces the potential of non-Abelian anyons in quantum computing. Andersen looks forward to seeing how other quantum computing groups utilize non-Abelian anyons and whether their peculiar behavior can unlock the path to fault-tolerant topological quantum computing.

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