Topic
10 courses · 16 tutorials
Prof. Elias Fernandez-Combarro Alvarez, University of Oviedo
CERN openlab's free lecture series on quantum computing covering qubits, quantum algorithms, QAOA, VQE, and quantum machine learning. Taught by a University of Oviedo professor with no physics background required.
IonQ
IonQ Researchers
IonQ's free 4-part lecture series on quantum programming. Covers quantum algorithms, circuits, programming with multiple SDKs, and quantum chemistry including VQE. Taught by IonQ researchers.
PennyLane
Xanadu / Community
Xanadu's collection of hundreds of interactive PennyLane tutorials, including 50+ quantum machine learning demos covering VQE, QAOA, quantum kernels, quantum neural networks, and more.
IBM Quantum
IBM Quantum (Victoria Lipinska and others)
IBM's free introductory VQE course aimed at chemistry. Hamiltonians, ansatze, classical optimizers, ground-state energies and bond lengths with Qiskit patterns. About 6 to 10 hours.
IBM Quantum
Max Rossmannek, Julian Schuhmacher, Alexander Miessen, and Laurin Fischer, IBM Quantum
Free openHPI course on quantum simulation for chemistry and materials science, developed with IBM Quantum. Covers the second quantization, molecular Hamiltonians, VQE for molecular ground states, and Qiskit Nature.
IBM Quantum
IBM's free eight-hour course on hybrid variational algorithms. Covers cost functions, ansatze, optimizers, VQE, SSVQE and VQD, using IBM Quantum primitives.
Prof. Dan Boneh and Will Zeng, Stanford
Stanford's CS269Q quantum computer programming course materials from Spring 2019, taught by Dan Boneh and Will Zeng. Lecture slides and project assignments cover pyQuil programming, benchmarking, VQE, QAOA, and error correction.
Quantinuum
Quantinuum's InQuanto tutorial series for quantum chemistry simulation. 18+ tutorials from basic VQE to advanced molecular simulation of Fe4N2 on real Quantinuum hardware. Free to read; running the notebooks requires an InQuanto licence or trial.
IBM Quantum
IBM's free ten-hour course on quantum approaches to matrix diagonalization, including VQE, sample-based quantum diagonalization (SQD) and sample-based Krylov methods, with discussion of classical versus quantum scaling.
IBM Quantum
Julien Gacon, Dr. Daniel J. Egger, Dr. Stefan Woerner, Lucia Cuervo Valor (IBM Quantum)
Free openHPI course on quantum approaches to combinatorial optimization, developed with IBM Quantum. Covers QAOA, VQE, and the quadratic unconstrained binary optimization (QUBO) framework with Qiskit implementation.
Variational Quantum Eigensolver: ansatz design, optimizer choice, barren plateaus, and an H2 ground-state calculation with Qiskit's Estimator primitive.
Set up molecular Hamiltonians in OpenFermion, apply Jordan-Wigner mapping to convert fermionic operators to Pauli strings, and build a VQE circuit in Cirq.
Run variational quantum algorithms using Amazon Braket Hybrid Jobs: managed classical compute + quantum access in one job, with checkpointing and cost tracking.
Build a complete quantum chemistry pipeline: encode the H2 Hamiltonian with OpenFermion, transform it to qubits via Jordan-Wigner, then find the ground state energy using VQE on Qiskit's statevector simulator.
How quantum computers simulate molecular systems: from second quantization and fermion-to-qubit mappings to VQE and the active space approximation.
Implement the Variational Quantum Eigensolver (VQE) in PyQuil to find the ground state energy of molecular hydrogen. Build the Hamiltonian, parameterized ansatz, and classical optimization loop.
A complete walkthrough of VQE for the hydrogen molecule in Qiskit Nature, from PySCF driver and Jordan-Wigner mapping through UCCSD ansatz and classical optimization.
Build a complete VQE implementation for H2 using Cirq's parametric gates, OpenFermion for the qubit Hamiltonian, scipy for classical optimization, and the parameter shift rule for exact gradients.
Implement the Variational Quantum Eigensolver to find the ground state energy of a hydrogen molecule using PennyLane and gradient-based optimization.
Use Q# and the Microsoft.Quantum.Chemistry library to simulate molecular ground state energies, covering Jordan-Wigner encoding, Broombridge data, and phase estimation.
Full VQE for LiH using PennyLane's qchem module: molecular Hamiltonian, Hartree-Fock initial state, UCCSD ansatz, optimization, and potential energy surface scan.
Walk through a real VQE simulation in PennyLane: build the H2 Hamiltonian, construct a UCCSD ansatz, and converge to the ground state energy in under 50 iterations.
A complete end-to-end VQE simulation of the water molecule using Qiskit Nature: PySCFDriver setup, active space reduction from 10 electrons in 7 orbitals to 4 electrons in 4 orbitals, Jordan-Wigner mapping, UCCSD ansatz, and comparison with Hartree-Fock and CCSD references.
How VQE works: the variational principle, ansatz design, classical optimizer loop, and a complete Qiskit implementation for finding the ground state of a simple Hamiltonian.
Set up and run a molecular ground state energy calculation in Qiskit Nature: driver setup, active space selection, Jordan-Wigner mapping, and VQE optimization.
How to implement the Variational Quantum Eigensolver (VQE) using tket's parameterized circuits and scipy optimization.