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Analyzing the Quantum Approximate Optimization Algorithm: Ansätze, Symmetries, and Lie Algebras

Sujay Kazi ^1,2,3, Martín Larocca ^2,4,*, Marco Farinati ⁵, Patrick J. Coles^6,2, M. Cerezo ^7,†, and Robert Zeier ^8,‡

¹Courant Institute of Mathematical Sciences, New York University, New York, New York 10012, USA
²Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
³Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708, USA
⁴Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
⁵Departamento de Matemática, FCEN, Universidad de Buenos Aires (IMAS-CONICET), Buenos Aires, Argentina
⁶Normal Computing Corporation, New York, New York, USA
⁷Information Sciences, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
⁸Forschungszentrum Jülich GmbH, Peter Grünberg Institute, Quantum Control (PGI-8), 54245 Jülich, Germany

^*Contact author: larocca@lanl.gov
^†Contact author: cerezo@lanl.gov
^‡Contact author: r.zeier@fz-juelich.de

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Articles Citing

Analyzing the Quantum Approximate Optimization Algorithm: Ansätze, Symmetries, and Lie Algebras

Ground-state reachability for variational quantum eigensolvers: a Rydberg-atom case study

LCQNN: linear combination of quantum neural networks

On the dynamical Lie algebras of quantum approximate optimization algorithms

Quantum simulation of massive Thirring and Gross-Neveu models for arbitrary number of flavors

Variational decision diagrams for quantum-inspired machine-learning applications

A dynamical Lie-algebraic framework for Hamiltonian engineering and quantum control

Classification of dynamical Lie algebras generated by spin interactions on undirected graphs

Equivariant Quantum Approximate Optimization Algorithm

Quantum Computing for Predictive Transport Modeling: A Systematic Literature Review and Future Research Needs

No title available

No title available

Controllability of the periodic quantum Ising spin chain and the Onsager algebra

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