PennyLane Codebook: Interactive Quantum ML Learning
Xanadu / PennyLane Team
5 courses · 9 tutorials
Xanadu / PennyLane Team
Purdue University
D-Wave
D-Wave
D-Wave
Use D-Wave's Constrained Quadratic Model (CQM) sampler to solve optimization problems with explicit constraints, eliminating the need for manual QUBO penalty encoding.
How Qiskit's transpiler transforms abstract circuits into hardware-executable form: qubit mapping, SWAP insertion, gate decomposition, and optimization passes.
Write your first quantum annealing program with D-Wave Ocean, formulate a simple QUBO problem and solve it with the simulated annealing sampler.
Install the D-Wave Ocean SDK, formulate a simple optimization problem as a QUBO, and solve it using D-Wave's quantum annealer or simulator.
Use D-Wave's Leap hybrid solver service to solve large optimization problems that are too big for the QPU alone: LeapHybridSampler, problem formulation, and interpreting solutions.
Run QAOA on Max-Cut in PennyLane end to end: encode the graph as a cost Hamiltonian, parameterize the variational circuit, and optimize toward the maximum partition.
Implement the Quantum Approximate Optimization Algorithm to solve a small Max-Cut problem using Cirq, with parameterized circuits and classical optimization.
Learn how to formulate combinatorial optimization problems as QUBO matrices for D-Wave, including penalty terms for constraints and a worked number partitioning example.
A clear comparison of quantum annealing and gate-based quantum computing: how they work, what problems they solve best, and when to choose each approach.