Hamiltonian-Oriented Homotopy QAOA
Authors: Akash Kundu, Ludmila Botelho, Adam Glos
Abstract: The classical homotopy optimization approach has the potential to deal with highly nonlinear landscape, such as the energy landscape of QAOA problems. Following this motivation, we introduce Hamiltonian-Oriented Homotopy QAOA (HOHo-QAOA), that is a heuristic method for combinatorial optimization using QAOA, based on classical homotopy optimization. The method consists of a homotopy map that produces an optimization problem for each value of interpolating parameter. Therefore, HOHo-QAOA decomposes the optimization of QAOA into several loops, each using a mixture of the mixer and the objective Hamiltonian for cost function evaluation. Furthermore, we conclude that the HOHo-QAOA improves the search for low energy states in the nonlinear energy landscape and outperforms other variants of QAOA.
Tools for this paper
Ask questions about this paper to our AI assistant
You can also chat with multiple papers at once here.
The previous summary was created more than a year ago and can be re-run (if necessary) by clicking on the Run button below.
Look for similar papers (in beta version)
We compare the title and abstract with papers indexed in our database. For arXiv papers, we search within the same category; for DOI and other sources, we search across sources and subjects. You can rerun the search as our database grows.
Disclaimer: The AI-based summarization tool and virtual assistant provided on this website may not always provide accurate and complete summaries or responses. We encourage you to carefully review and evaluate the generated content to ensure its quality and relevance to your needs.