Virtual Talk: Problem-tailored variational quantum algorithms

Sophia Economou
Virginia Tech

The performance of variational quantum algorithms (VQAs) critically depends on the objective function, which in turn relies on the form of the variational ansatz. A good ansatz translates to relatively shallow circuits and involves a low number of classical optimization parameters. These features can be achieved more easily if the ansatz knows something about the problem that is simulated. In this talk, I will give a brief background on VQAs and present our techniques for problem-tailored ansatze. These include symmetry-preserving circuits, the ADAPT-VQE algorithm, and a pulse-based VQE, which we named ctrl-VQE. Our simulations show that these techniques outperform competing ansatze in terms of circuit depth, accuracy, and trainability.

Presentation (PDF File)

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