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Two-parameter counter-diabatic driving in quantum annealing
We introduce a two-parameter approximate counter-diabatic term into the Hamiltonian of the transverse-field Ising model for quantum annealing to accelerate convergence to the solution, generalizing an existing single-parameter approach.
Quantum Physics Statistical Mechanics
Quantum Expectation-Maximization Algorithm
Clustering algorithms are a cornerstone of machine learning applications.
Perspectives of quantum annealing: Methods and implementations
Quantum annealing is a computing paradigm that has the ambitious goal of efficiently solving large-scale combinatorial optimization problems of practical importance.
Quantum Physics
