Cutting and Quantum ML

Run circuits wider than the device with cutting, then meet variational circuits, data encoding and QAOA.

7 lessons21 exercises88 min

1. 01Circuit cuttingCut a gate, run the halves, recombine: the sampling overhead and when it pays off.14 min
2. 02Classical ML vs. Quantum ML: The Hybrid LoopHow a neural network and a variational quantum model learn, side by side, and an honest look at when QML helps.12 min
3. 03Variational circuitsParameterised gates, a cost function and a classical optimiser: the loop behind VQE and QAOA.12 min
4. 04Data encodingBasis, angle and amplitude encoding: how classical data enters a circuit and what each choice costs.10 min
5. 05Hands-On 2-Qubit Variational ClassifierEncode a point with two RX gates, entangle, rotate with one trainable RY, and tune θ until the two classes separate.14 min
6. 06Observables, Hamiltonians & Real ApplicationsTurn 0/1 counts into ⟨Z⟩, measure X and Y by rotating first, and add Pauli terms into the energy that chemistry and optimisation minimise.14 min
7. 07QAOA on a small graphCost and mixer layers for MaxCut, read off the cut from the histogram, and understand the depth p.12 min