Quantum Machines and Nvidia use machine learning to get closer to an error-corrected quantum computer | TechCrunch
Briefly

from TechCrunch4 months ago
At first glance, calibration may seem like a one-shot problem: You calibrate the processor before you start running the algorithm on it. But it's not that simple.
TechCrunchhttps://techcrunch.com/2024/11/02/quantum-machines-and-nvidia-use-machine-learning-to-get-closer-to-an-error-corrected-quantum-computer/
If we can frequently recalibrate it using these kinds of techniques and underlying hardware, then we can improve the performance and keep the fidelity [high] over a long time.
TechCrunchhttps://techcrunch.com/2024/11/02/quantum-machines-and-nvidia-use-machine-learning-to-get-closer-to-an-error-corrected-quantum-computer/
The holy grail, he said, is to run quantum error correction. We're not there yet. Instead, this collaboration focused on calibration.
TechCrunchhttps://techcrunch.com/2024/11/02/quantum-machines-and-nvidia-use-machine-learning-to-get-closer-to-an-error-corrected-quantum-computer/
Those compute engines were small and limited, but that's not a problem with Nvidia's extremely powerful DGX platform.
TechCrunchhttps://techcrunch.com/2024/11/02/quantum-machines-and-nvidia-use-machine-learning-to-get-closer-to-an-error-corrected-quantum-computer/
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#quantum-computing #nvidia #quantum-error-correction #reinforcement-learning #partnership
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