/quantum-computing-intro

Afternotes on the "Practical introduction to Quantum Computing: from qubits to quantum machine learning and beyond" CERN course

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practical intro to quantum computing

Afternotes and exercises on the Practical introduction to quantum computing: from qubits to quantum machine learning and beyond course given by Elías F. Combarro at CERN (Nov 2020).

Slides and course material can be found here.

  • Lesson 1: Introduction - November 6
    • Resources:
    • Contents:
      • What is quantum computing?
      • Applications of quantum computing.
      • Hardware and software for quantum computing.
      • Elements of the quantum circuit model.
      • Introduction to the IBM Quantum Experience.
  • Lesson 2: One and two-qubit systems (Part 1) - November 13
    • Contents:
      • Quantum key distribution with the BB84 protocol.
      • Two-qubit gates.
      • The CHSH game.
  • Lesson 3: One and two-qubit systems (Part 2) - November 20
    • Contents:
      • Quantum teleportation.
      • Superdense coding.
      • Deutsch algorithm.
  • Lesson 4: Multiqubit systems - November 27
    • Contents:
      • Multiqubit gates and universality.
      • Quantum parallelism.
      • Deutsch-Jozsa algorithm.
      • Grover algorithm.
      • Shor algorithm.
      • HHL algorithm.
  • Lesson 5: Quantum algorithms for combinatorial optimization - December 4
    • Contents:
      • Quantum adiabatic computing and quantum annealing.
      • Introduction to D-Wave Leap.
      • Quantum Approximate Optimization Algorithm.
  • Lesson 6: Quantum variational algorithms and quantum machine learning - December 11
    • Contents:
      • Variational Quantum Eigensolver.
      • Introduction to Quantum Machine Learning (QSVM, QGAN, Quantum Classifiers...)
  • Lesson 7: The future of quantum computing - December 18
    • Contents:
      • Quantum error correction.
      • What is Quantum Supremacy?
      • Prospects for quantum computing.

Additional resources