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  3. IonQ and Synopsys Accelerate CAE Computer-Aided Engineering Workloads by 14.6% via Trapped-Ion Hardware

Quantum Computing Report

IonQ and Synopsys Accelerate CAE Computer-Aided Engineering Workloads by 14.6% via Trapped-Ion Hardware

IonQ, Synopsys, and NVIDIA have successfully demonstrated quantum-accelerated performance gains in large-scale Computer-Aided Engineering (CAE) workflows, reducing total execution time by up to 14.6%. Their joint research, awarded 1st Place Best Paper at IEEE Quantum Week 2026, utilized a quantum matrix reordering algorithm embedded in classical simulation suites like Ansys LS-DYNA. This innovation optimizes matrix equations, leading to significant time and memory savings in industrial design pi

Continue with the complete report on the publisher’s website.

Read full article at Quantum Computing Report
Q

By Quantum Computing Report

18 September 2026|1 min read
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