
A hybrid algorithm for finding ground states of quantum systems using a parameterized quantum circuit and classical optimization.The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm designed to find the ground state energy of a quantum system—the lowest energy state, which determines many of the system's properties. It is a leading candidate for near-term quantum computing because it works with the noisy, limited-scale quantum hardware available today. VQE is particularly relevant for quantum chemistry, where it can simulate molecular structures and reactions that are intractable for classical computers, and for condensed matter physics, where it helps study strongly correlated materials.
The algorithm was proposed in 2014 by Alberto Peruzzo and colleagues, building on earlier ideas of quantum variational methods. It has since become a cornerstone of the Noisy Intermediate-Scale Quantum (NISQ) era.
VQE uses a parameterized quantum circuit, often called an ansatz, to prepare a trial quantum state. The circuit's parameters are adjusted by a classical optimizer. For each set of parameters, the quantum computer measures the expectation value of the system's Hamiltonian—the operator representing total energy—on the prepared state. This measurement is fed back to the classical optimizer, which tweaks the parameters to minimize the energy. The process iterates until convergence, at which point the circuit prepares a state approximating the ground state, and the measured energy approximates the ground state energy.
VQE is used in quantum chemistry simulations, such as calculating molecular ground states for drug discovery and materials design, and in optimization problems that can be mapped to finding ground states of quantum Hamiltonians.
VQE was one of the first algorithms to demonstrate a quantum advantage for a chemistry problem when it was used in 2017 to compute the ground state of a beryllium hydride molecule on a superconducting quantum processor.









