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| Eigensolver Cuántico Variacional× | Estimación de Fase Cuántica× | |
|---|---|---|
| Campo | Computación cuántica | Computación cuántica |
| Familia | Machine learning | Machine learning |
| Año de origen≠ | 2014 | 1995 |
| Autor original≠ | Alberto Peruzzo | Alexei Kitaev |
| Tipo≠ | Hybrid quantum-classical algorithm | Subroutine algorithm |
| Fuente 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 ↗ |
| Alias | VQE, hybrid quantum-classical | QPE, phase kickback |
| Relacionados≠ | 4 | 3 |
| Resumen≠ | 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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