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Convergence of digitized-counterdiabatic QAOA: circuit depth versus free parameters
New Journal of PhysicsRecently, digitized-counterdiabatic (CD) quantum approximate optimization algorithm (QAOA) has been proposed to make QAOA converge to the solution of an optimization problem in fewer steps, inspired by Trotterized CD driving in continuous-time quantum ...
Mara Vizzuso +3 more
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Amplitude amplification-inspired QAOA: Improving the success probability for solving 3SAT [PDF]
, 2023 A. Mandl +4 more
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Quantum Alternating Operator Ansatz (QAOA) beyond low depth with gradually changing unitaries [PDF]
, 2023 Vladimir Kremenetski +4 more
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Towards Optimizations of Quantum Circuit Simulation for Solving Max-Cut Problems with QAOA [PDF]
, 2023 Yu‐Cheng Lin +3 more
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Quantum approximate optimization via learning-based adaptive optimization
Communications PhysicsCombinatorial optimization problems are ubiquitous and computationally hard to solve in general. Quantum approximate optimization algorithm (QAOA), one of the most representative quantum-classical hybrid algorithms, is designed to solve combinatorial ...
Lixue Cheng +3 more
doaj +1 more source
Domain wall encoding of integer variables for quantum annealing and QAOA [dataset]
, 2019 Nicholas Chancellor
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Universal Resources for QAOA and Quantum Annealing
The Quantum Approximate Optimization Algorithm (QAOA) is a variational ansatz that resembles the Trotterized dynamics of a Quantum Annealing (QA) protocol. This work formalizes this connection formally and empirically, showing the angles of a multilayer QAOA circuit converge to universal QA trajectories.
Díez-Valle, Pablo +3 more
openaire +2 more sources
Pattern or Not? QAOA Parameter Heuristics and Potentials of Parsimony [PDF]
Vincent Eichenseher +3 more
openalex +1 more source