Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Variational Quantum Eigensolver× | Estimativa de Fase Quântica× | |
|---|---|---|
| Área | Computação quântica | Computação quântica |
| Família | Machine learning | Machine learning |
| Ano de origem≠ | 2014 | 1995 |
| Autor original≠ | Alberto Peruzzo | Alexei Kitaev |
| Tipo≠ | Hybrid quantum-classical algorithm | Subroutine algorithm |
| Fonte seminal≠ | Peruzzo, A., McClean, J., Shadbolt, P., et al. (2014). A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5, 4213. DOI ↗ | Kitaev, A. Y. (1995). Quantum measurements and the Abelian stabilizer problem. arXiv preprint quant-ph/9511026. link ↗ |
| Outros nomes | VQE, hybrid quantum-classical | QPE, phase kickback |
| Relacionados≠ | 4 | 3 |
| Resumo≠ | The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm designed to find the lowest eigenvalue (ground state energy) of a quantum Hamiltonian. Introduced by Peruzzo et al. in 2014, it exploits the variational principle to combine the power of quantum circuits with classical optimization to solve chemistry and materials science problems on near-term quantum devices. | Quantum Phase Estimation (QPE) is a fundamental quantum subroutine that estimates the eigenvalues of a unitary operator. Developed by Alexei Kitaev in 1995, QPE combines controlled unitary evolution with the quantum Fourier transform to extract eigenvalues from quantum states with exponential precision scaling. |
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