Classical Optimization Archives

Describe the role of classical optimization methods in the VQE algorithm and provide an example of how these methods are integrated into the optimization loop within TensorFlow Quantum.

Tuesday, 11 June 2024 by EITCA Academy

The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm that leverages the power of quantum computers to solve eigenvalue problems, particularly finding the ground state energy of a given Hamiltonian. This is achieved by combining a quantum subroutine for evaluating the expectation values of the Hamiltonian with a classical optimization loop that iteratively updates

Published in Artificial Intelligence, EITC/AI/TFQML TensorFlow Quantum Machine Learning, Variational Quantum Eigensolver (VQE), Variational Quantum Eigensolver (VQE) in Tensorflow Quantum for single qubit Hamiltonians, Examination review

Tagged under: Artificial Intelligence, Classical Optimization, Machine Learning, Quantum Computing, TensorFlow Quantum, VQE

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Describe the role of classical optimization methods in the VQE algorithm and provide an example of how these methods are integrated into the optimization loop within TensorFlow Quantum.