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IBM advances towards error-mitigation quantum computing

by on14 November 2024


Better at herding the cats

IBM has announced a series of developments to make limited but functional quantum calculations possible ahead of the much-anticipated arrival of error-corrected quantum computing.

While these changes are not revolutionary individually, collectively, they have significantly enhanced the efficiency and accuracy of operations across IBM’s hardware and software stacks.

Biggish Blue has introduced the second version of IBM’s Heron processor, which has  133 qubits. This advancement takes the processor beyond the capabilities of classical computer simulations, provided it operates with sufficiently low errors.

IBM Vice President Jay Gambetta explained that Revision 2 of Heron addresses TLS (two-level system) errors, which limit device coherence.

"If you see this sort of defect, which can be a dipole or just some electronic structure that is caught on the surface, that is what we believe is limiting the coherence of our devices," Gambetta said.

Adjusting the operating frequency of qubits can prevent these coherence issues, which are adjustments made during the Heron chip’s calibration.

In addition to hardware improvements, IBM has rewritten the software controlling the system, resulting in a dramatic speed-up.

"After learning from the community, seeing how to run larger circuits, [we were able to] almost better define what it should be and rewrite the whole stack towards that," Gambetta said.

This update reduced the time for specific operations from 122 hours to just a few hours, benefiting customers by reducing hardware time costs and potentially lowering error rates by shortening calculation durations.

Despite these advancements, significant calculations still face error risks. IBM is therefore focusing on error mitigation, a strategy it first outlined last year. The challenge lies in the computational difficulty of error mitigation, which increases with the qubit count.

IBM has optimised this process using algorithmic improvements and tensor methods that use GPUs.

"They've got algorithmic improvements, and the method that uses tensor methods [now] uses the GPU," Gambetta said, indicating a multifaceted approach to enhancing quantum computing performance.

 

Last modified on 14 November 2024
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