course
Classiq Quantum Computing Tutorials
Classiq engineering and research team
2 courses · 8 tutorials
course
Classiq engineering and research team
course
Hasso Plattner Institute / IBM Quantum
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.
Build the Quantum Approximate Optimization Algorithm from scratch in Qiskit to solve MaxCut on small graphs. Understand the circuit structure, cost function, and how to tune the depth parameter p.
Implement the Quantum Approximate Optimisation Algorithm to solve the MaxCut graph problem using PennyLane, and understand how QAOA bridges quantum computing and combinatorial optimisation.
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.
Implement a simplified ADAPT-VQE algorithm in PennyLane. Build an operator pool, greedily select operators by gradient magnitude, grow the ansatz iteratively, and compare convergence against fixed UCCSD for the H2 molecule.
How to implement the Variational Quantum Eigensolver (VQE) using tket's parameterized circuits and scipy optimization.
Implement the Quantum Approximate Optimization Algorithm to solve a small Max-Cut problem using Cirq, with parameterized circuits and classical optimization.