2 courses · 13 tutorials
Udemy
Hoang Quy La
A hands-on Udemy course by Hoang Quy La covering qubits, quantum gates, and quantum circuits in Python with Cirq and Qiskit, plus the Deutsch-Jozsa algorithm, Grover's algorithm, the quantum Fourier transform, quantum phase estimation, variational quantum circuits, and an introduction to quantum error correction.
Google Quantum AI
Google Quantum AI's free self-paced tutorial series for the Cirq quantum programming framework. Covers circuit construction, noise models, algorithm implementation, and access to Google's Quantum Virtual Machine via Google Colab.
Model realistic quantum hardware noise in Cirq: depolarizing channels, amplitude damping, bit-flip channels, and using DensityMatrixSimulator for noisy circuit simulation.
Build and simulate random quantum circuits on the Google Sycamore topology using Cirq. Implement FSimGate with Sycamore parameters, realistic noise models, and cross-entropy benchmarking (XEB) to measure circuit fidelity.
Build your first hybrid quantum-classical machine learning model with TensorFlow Quantum - create a parameterized circuit, wrap it as a Keras layer, and train it with gradient descent.
Learn Google's Cirq framework, build quantum circuits with fine-grained control over qubit placement and gate timing, and run them on Google's quantum hardware.
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.
Use Cirq's CliffordSimulator to efficiently simulate large stabilizer circuits, enabling 100+ qubit experiments on a laptop.
Build the Quantum Fourier Transform in Cirq one rotation at a time. Verifies against the classical DFT, explains the bit reversal, and shows where the speedup actually comes from.
Use Cirq's transformer framework to route circuits onto device topologies, optimize gate sequences, and reduce circuit depth.
Implement the Quantum Approximate Optimization Algorithm to solve a small Max-Cut problem using Cirq, with parameterized circuits and classical optimization.
Define custom quantum gates in Cirq from unitary matrices, use the fermionic simulation gate (FSimGate), and build parameterized custom operations.
Characterize noise in Cirq circuits using cross-entropy benchmarking and depolarizing error models. Validate against Google Quantum AI hardware specifications.
Use Cirq's tools for simulating Google-style superconducting circuits: fSim gates, GridQubits, device topology, and the cross-entropy benchmarking protocol.
Write your first quantum program in Cirq, create a Bell state using GridQubits and Moments, run it on the Cirq simulator.