Press "Enter" to skip to content

Testing the performance of VQE on Knapsack problem variations

The present work is about the VQE performance on special cases of Ising Problems. The importance of the starting point and the ansatz selection in the algorithm convergence is highlighted. We show how the algorithm performance is dramatically improved when a good starting point is given. The starting point is directly related with the ansatz (variational form) choice since the ansatz election spans the search space that can be tracked in the optimization problem. As Ising Problems always have diagonal Hamiltonians, and therefore, the solution will always be a state of the computational basis, it is not clear that entangled ansatze help algorithm convergence. We present the comparative performance of VQE using several types of ansatze tested on different classical optimization algorithms.

Laura Gatti Dorpich
Director of Development – Quantum South

Professor – Universidad de Montevideo

PhD candidate from the Polytechnic University of Madrid. Laura’s main field of study is discrete sets of gates for quantum computing. She is the co-founder of Quantum-South, a quantum computing spin-off of University of Montevideo founded in 2019 in Uruguay. Quantum-South develops quantum software for cargo solutions.  Laura is also interested in development and technological change and is trying to figure out how quantum computing could be an open door to the future for developing countries.