Graph representation learning for parameter transferability in quantum approximate optimization algorithm
The quantum approximate optimization algorithm (QAOA) is one of the most promising
candidates for achieving quantum advantage through quantum-enhanced combinatorial …
candidates for achieving quantum advantage through quantum-enhanced combinatorial …
Classical symmetries and the quantum approximate optimization algorithm
We study the relationship between the Quantum Approximate Optimization Algorithm
(QAOA) and the underlying symmetries of the objective function to be optimized. Our …
(QAOA) and the underlying symmetries of the objective function to be optimized. Our …
Vqne: Variational quantum network embedding with application to network alignment
Learning of network embedding with vector-based node representation has attracted wide
attention over the decade. It differs from the general setting of graph node embedding …
attention over the decade. It differs from the general setting of graph node embedding …
[PDF][PDF] Classical symmetries and QAOA
R Shaydulin, S Hadfield, T Hogg… - ar** nodes in two different networks have similar attributes and neighborhood …
Quantum and Classical Multilevel Algorithms for (Hyper) Graphs
R Shaydulin - 2020 - search.proquest.com
Combinatorial optimization problems on (hyper) graphs are ubiquitous in science and
industry. Because many of these problems are NP-hard, development of sophisticated …
industry. Because many of these problems are NP-hard, development of sophisticated …