course
PennyLane Codebook: Interactive Quantum ML Learning
Xanadu / PennyLane Team
optimization
1 course · 9 tutorials
Courses
Free Tutorials
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- beginner
- 20 min read
Getting Started with D-Wave Ocean SDK
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.
- →
- beginner
- 20 min
Quantum Annealing vs Gate-Based Quantum Computing
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.
- →
- intermediate
- 14 min read
Advanced D-Wave: Hybrid Solvers and Leap
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.
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- intermediate
- 13 min read
Constrained Optimization with D-Wave's CQM Sampler
Use D-Wave's Constrained Quadratic Model (CQM) sampler to solve optimization problems with explicit constraints, eliminating the need for manual QUBO penalty encoding.
- →
- intermediate
- 15 min read
QAOA for Max-Cut with PennyLane
Implement the Quantum Approximate Optimization Algorithm for the Max-Cut problem in PennyLane: graph encoding, cost Hamiltonian, circuit construction, and parameter optimization.
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- intermediate
- 13 min read
Circuit Transpilation in Qiskit
How Qiskit's transpiler transforms abstract circuits into hardware-executable form: qubit mapping, SWAP insertion, gate decomposition, and optimization passes.
- →
- beginner
- 20 min read
Hello World in D-Wave Ocean
Write your first quantum annealing program with D-Wave Ocean, formulate a simple QUBO problem and solve it with the simulated annealing sampler.
- →
- intermediate
- 20 min read
QAOA for Max-Cut in Cirq
Implement the Quantum Approximate Optimization Algorithm to solve a small Max-Cut problem using Cirq, with parameterized circuits and classical optimization.
- →
- intermediate
- 25 min read
QUBO Formulation: Translating Problems for D-Wave
Learn how to formulate combinatorial optimization problems as QUBO matrices for D-Wave, including penalty terms for constraints and a worked number partitioning example.