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| Quantum Phase Estimation× | Variationskvanteigensolver× | |
|---|---|---|
| Ämnesområde | Kvantdatorteknik | Kvantdatorteknik |
| Familj | Machine learning | Machine learning |
| Ursprungsår≠ | 1995 | 2014 |
| Upphovsperson≠ | Alexei Kitaev | Alberto Peruzzo |
| Typ≠ | Subroutine algorithm | Hybrid quantum-classical algorithm |
| Ursprungskälla≠ | Kitaev, A. Y. (1995). Quantum measurements and the Abelian stabilizer problem. arXiv preprint quant-ph/9511026. link ↗ | Peruzzo, A., McClean, J., Shadbolt, P., et al. (2014). A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5, 4213. DOI ↗ |
| Alias | QPE, phase kickback | VQE, hybrid quantum-classical |
| Närliggande≠ | 3 | 4 |
| Sammanfattning≠ | 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. | 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. |
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