VQE Overview with PennyLane

VQE Overview with PennyLane

This PennyLane demo is the central introduction to the Variational Quantum Eigensolver (VQE), the flagship near-term quantum algorithm for quantum chemistry, applied here to compute the ground-state energy of a molecule. VQE finds the lowest eigenvalue of a molecule's electronic Hamiltonian by preparing a parameterized trial state (ansatz) on a quantum computer, measuring its energy expectation value, and using a classical optimizer to vary the parameters until the energy is minimized, relying on the variational principle that any trial energy upper-bounds the true ground state. The tutorial walks through the full PennyLane chemistry workflow: defining a molecule and using PennyLane's qchem module to build its qubit Hamiltonian, constructing a chemically-motivated ansatz that prepares correlated electronic states, defining the energy as an expectation value, and optimizing the parameters with gradient-based optimization powered by PennyLane's automatic differentiation. It computes the ground-state energy of a small molecule (such as hydrogen) and compares it to the exact result. As the canonical quantum-chemistry demo, it gives the essential, reusable template for molecular ground-state calculations in PennyLane.

Run it

pip install -r requirements.txt
python demo.py

Source and license

Imported from demonstrations_v2/tutorial_vqe/demo.py in PennyLaneAI/demos at c52c0abeb5122218aa96b38eea848864cce7323f, under the Apache License 2.0. Original authors: Xanadu and the PennyLane community. The upstream LICENSE is included alongside this example.