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Which is an example of the use of VQE?
In the tutorial tutorial_vqe_bond_dissociation, we use VQE to explore the potential energy surface of molecules to simulate chemical reactions. Another interesting application is to probe the lowest-lying states of molecules in specific sectors of the Hilbert space. For example, see the tutorial tutorial_vqe_spin_sectors.
How is VQE an application of the Ritz variational principle?
It is an application of the Ritz variational principle, where a quantum computer is trained to prepare the ground state of a given molecule. The inputs to the VQE algorithm are a molecular Hamiltonian and a parametrized circuit preparing the quantum state of the molecule.
How is the ground state of a Hamiltonian obtained?
The ground state of the target Hamiltonian is obtained by performing an iterative minimization of the cost function. The optimization is carried out by a classical optimizer which leverages a quantum computer to evaluate the cost function and calculate its gradient at each optimization step.
When to use variational quantum Eigensolver ( VQE )?
The Variational-Quantum-Eigensolver (VQE) [1, 2] is a quantum/classical hybrid algorithm that can be used to find eigenvalues of a (often large) matrix (H).
Is the qaoa algorithm the same as VQE?
VQE and QAOA algorithms are so called variational algorithm and can run almost the same steps. The point to learn is Let’s see a simple example. We can install it using this command, Qubit is used in quantum computer and can take a superposition of |0> state and |1> state.
How does the quantum subroutine of VQE work?
Practically, the quantum subroutine of VQE amounts to preparing a state based off of a set of parameters vec ( θ) and performing a series of measurements in the appropriate basis. The paramaterized state (or ansatz) preparation can be tricky in these algorithms and can dramatically affect performance.