手法を比較

	変分量子固有値ソルバー	Quantum Monte Carlo
分野	量子コンピューティング	量子コンピューティング
系統	Machine learning	Machine learning
提唱年	2014	1953
提唱者	Alberto Peruzzo	Nicholas Metropolis and colleagues
種類	Hybrid quantum-classical algorithm	Monte Carlo simulation
原典	Peruzzo, A., McClean, J., Shadbolt, P., et al. (2014). A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5, 4213.	Metropolis, N., Rosenbluth, A. W., et al. (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21, 1087–1092.
別名	VQE, hybrid quantum-classical	QMC, variational Monte Carlo, diffusion Monte Carlo
関連	4	3
概要	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 Monte Carlo (QMC) is a stochastic computational method for computing ground state properties of quantum many-body systems. Combining classical Monte Carlo sampling with quantum mechanics, QMC approaches are among the most accurate methods available for electronic structure and condensed matter physics, achieving sub-percent accuracy for many systems.