# Beyond Barren Plateaus: Quantum Variational Algorithms Are Swamped With Traps

@inproceedings{Anschuetz2022BeyondBP, title={Beyond Barren Plateaus: Quantum Variational Algorithms Are Swamped With Traps}, author={Eric R. Anschuetz and Bobak Toussi Kiani}, year={2022} }

One of the most important properties of classical neural networks is how surprisingly trainable they are, though their training algorithms typically rely on optimizing complicated, nonconvex loss functions. Previous results have shown that unlike the case in classical neural networks, variational quantum models are often not trainable. The most studied phenomenon is the onset of barren plateaus in the training landscape of these quantum models, typically when the models are very deep. This…

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