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Academic partner; graduate researcher co-authored the study
Hybrid quantum optimization has had a cost problem: solve a big problem by breaking it into pieces, and each piece needs a custom quantum circuit tuned by trial and error — run, measure, adjust, repeat, often hundreds of times. A joint research effort from IonQ, Oak Ridge National Laboratory (ORNL), NVIDIA, and the University of Tennessee, Knoxville (UT) shows a trained generative model can write those circuits in a single pass, eliminating the tuning loop entirely.
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