Dynamic Quantum Variational Ansatz

Quantum Approximate Optimization Algorithm is a variational algorithm that uses both classical and quantum resources to find the approximate solution to combinatorial optimization problems. The algorithm attempts to find the best solution by classically optimizing the expectation value of the objective function in the variational ansatz. We discuss a new algorithm based on a "Dynamic Quantum Variational Ansatz" (DQVA) for the maximum independent set problem that dynamically reduces the depth of the circuit used in preparing the variational ansatz employed in the quantum optimization [1]. The algorithm can be also applied to other constrained combinatorial optimization problems.

[1] Zain H. Saleem, Bilal Tariq and Martin Suchara, “Approaches to Constrained Quantum Approximate Optimization” arXiv:2010.06660v2, October 2020.