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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 …
[HTML][HTML] Scaling whole-chip QAOA for higher-order Ising spin glass models on heavy-hex graphs
We show that the quantum approximate optimization algorithm (QAOA) for higher-order,
random coefficient, heavy-hex compatible spin glass Ising models has strong parameter …
random coefficient, heavy-hex compatible spin glass Ising models has strong parameter …
Hybrid quantum-classical multilevel approach for maximum cuts on graphs
Combinatorial optimization is one of the fields where near term quantum devices are being
utilized with hybrid quantum-classical algorithms to demonstrate potentially practical …
utilized with hybrid quantum-classical algorithms to demonstrate potentially practical …
Trainability barriers in low-depth qaoa landscapes
The Quantum Alternating Operator Ansatz (QAOA) is a prominent variational quantum
algorithm for solving combinatorial optimization problems. Its effectiveness depends on …
algorithm for solving combinatorial optimization problems. Its effectiveness depends on …
Artificial Intelligence for Quantum Computing
On the Effects of Small Graph Perturbations in the MaxCut Problem by QAOA
We investigate the Maximum Cut (MaxCut) problem on different graph classes with the
Quantum Approximate Optimization Algorithm (QAOA) using symmetries. In particular …
Quantum Approximate Optimization Algorithm (QAOA) using symmetries. In particular …