Machine learningVariational Algorithm
Variational Quantum Eigensolver
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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Sources
- Peruzzo, A., McClean, J., Shadbolt, P., et al. (2014). A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5, 4213. DOI: 10.1038/ncomms5213 ↗
- McClean, J. R., Romero, J., Aspuru-Guzik, A. (2016). The theory of variational hybrid quantum-classical algorithms. New Journal of Physics, 18, 023023. DOI: 10.1088/1367-2630/18/2/023023 ↗
- Cao, Y., Romero, J., Aspuru-Guzik, A. (2021). Potential of quantum computing for drug discovery. IBM Journal of Research and Development, 62, 6:1-6:20. DOI: 10.1147/JRD.2018.2888987 ↗