This lecture is organised as part of the CERN QTI online lecture series.

In this talk, we will dive into the topic of barren plateaus and investigate a new method to avoid them. Barren plateaus appear to be a major obstacle for using variational quantum algorithms to simulate large-scale quantum systems or to replace traditional machine learning algorithms. They can be caused by multiple factors such as the expressivity of the ansatz, excessive entanglement, the locality of observables under consideration, or even hardware noise. Classical splitting of parametric ansatz circuits is proposed to avoid barren plateaus. Classical splitting is realised by subdividing an N qubit ansatz into multiple ansätze that consist of O(logN) qubits. The presenter will show that such an approach allows for avoiding barren plateaus and carry out numerical experiments, and perform binary classification on classical and quantum datasets.

For more details, visit: https://indico.cern.ch/event/1248668/.

The recording of this talk is now available at: https://www.youtube.com/watch?v=GMajdgdiU_g