IBM to invest $100 mn to build a 100,000-qubit supercomputer by 2033

By IANS | Published: May 21, 2023 07:48 PM2023-05-21T19:48:03+5:302023-05-21T20:00:19+5:30

New Delhi, May 21 Tech major IBM on Sunday announced a $100 million collaboration with the University of ...

IBM to invest $100 mn to build a 100,000-qubit supercomputer by 2033 | IBM to invest $100 mn to build a 100,000-qubit supercomputer by 2033

IBM to invest $100 mn to build a 100,000-qubit supercomputer by 2033

New Delhi, May 21 Tech major IBM on Sunday announced a $100 million collaboration with the University of Tokyo and the University of Chicago to develop a quantum-centric supercomputer powered by 100,000 qubits by 2033.

According to the company, a 100,000-qubit system would serve as a foundation to address some of the world's most pressing problems that even the most advanced supercomputers of today may never be able to solve.

"We have achieved significant progress along our roadmap and mission to globally establish useful quantum technology, so much so that we can now, with our partners, truly begin to explore and develop a new class of supercomputing anchored by quantum," IBM Chairman and CEO Arvind Krishna said in a statement.

By the end of 2023, IBM intends to debut three cornerstones of its necessary architecture for quantum-centric supercomputers.

One is the new 133-qubit 'IBM Heron' processor, a complete redesign of IBM's previous generations of quantum processors, with a new two-qubit gate to allow higher performance.

The second is the introduction of IBM Quantum System Two, a new flagship system designed to be modular and flexible to introduce elements of scaling in its underlying components, including classical control electronics and high-density cryogenic wiring infrastructure.

This system is expected to be operational by the end of 2023, the company said.

The third is the introduction of middleware for quantum, a set of tools to run workloads on both classical and quantum processors, which includes tools for decomposing, parallel execution and reconstructing workloads to enable efficient solutions at scale.

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