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Amazon joins the quantum computing race with a chip designed for error correction


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joins the quantum computing race with a chip designed for error correction

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that it has created its own quantum computing chip, joining
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and
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in a push to take this potentially transformative technology from the theoretical to the practical. Ocelot is a prototype that’s intended to test the effectiveness of
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Web Services’ quantum error correction architecture. Compared with other chip methods, the company claims Ocelot can reduce the cost of implementing quantum error correction by up to 90 percent.

Quantum computing could solve complicated problems exponentially faster than standard computers by using quantum bits, or qubits, rather than traditional bits that store a computer’s information as 1s and 0s. Rather than representing only a 1 or a 0, qubits can represent a proportion of both 1 and 0 at the same time. Ocelot takes this a step farther with its use of “cat qubits,” named for the famous

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thought experiment, which can “intrinsically suppress certain forms of errors,” according to
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.

Error rate is one of the key limitations of current quantum computing, because the qubits are so sensitive to minute changes in their environments. Electromagnetic interference from a WiFi network can be enough to disturb a qubit and cause it to make mistakes. Adding more qubits to a chip means faster calculations, but also more mistakes.

Ocelot consists of five data qubits (the cat qubits), five “buffer circuits” to stabilize them and four qubits for detecting errors on the cat qubits. “We selected our qubit and architecture with quantum error correction as the top requirement,” said Oskar Painter, director of quantum hardware at AWS. “We believe that if we’re going to make practical quantum computers, quantum error correction needs to come first.”

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claimed that its Willow chip, announced in December, was able to reduce errors as more qubits were added. Ocelot is another step toward reducing errors and making useful quantum computers a reality.



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