Online Resources

Online Resources about Quantum Science, especially about Quantum Computing.


This list of resources reflects my knowledge as in March 2022.


About Quantum Mechanics and Quantum Computing:


A selection of software and platforms for quantum computing:

  • IBM Quantum - Open-source SDK (Qiskit, Quantum Composer, Quantum Lab), for running on IBM’s computers or simulators.

  • Google Quantum AI - Cirq Python library and Quantum Computing Services on simulators or on Sycamore & co.

  • Rigetti Forest - Rigetti’s software for its own quantum computers.

  • Microsoft Q# & Azure Quantum - Microsoft’s SDK, for running on the Microsoft Quantum Network of hardware and simulators.

  • Amazon Braket - Run quantum algorithms on Rigetti or D-Wave hardware or on a AWS simulator. See pricing (!).

  • QuTech QuantumInspire - Run quantum algorithms on simulators or hardware backends. Graphical interface to program in QASM (Quantum Assembly Language).


  • Qiskit tutorials: Chemistry, Optimization, Finance

  • Xanadu Quantum Codebook: “The Codebook is an experimental, exercise-based introduction to quantum computing. Rather than just reading a textbook or tutorial, or executing some pre-written code cells, the Codebook is an active learning resource in which you will learn by doing.”

Additional software resources:

  • TensorFlow Quantum - a quantum machine learning library for rapid prototyping of hybrid quantum-classical ML models. The announcement gives a good summary of its purpose and how it works.

See also the overview article by R. LaRose in the Quantum Journal [75].

Python Packages

Python packages that I have played with:

  • Qiskit (IBM) - “Qiskit is an open source SDK for working with quantum computers at the level of pulses, circuits and application modules.”

  • QuTiP - “Quantum Toolbox in Python, QuTiP is open-source software for simulating the dynamics of open quantum systems.”

  • PennyLane (Xanadu) - “A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.”

  • Strawberry Fields (Xanadu) - “A cross-platform Python library for simulating and executing programs on quantum photonic hardware.”

Python packages that I am planning to play with:

  • Cirq - “Cirq is a Python software library for writing, manipulating, and optimizing quantum circuits, and then running them on quantum computers and quantum simulators. “

  • pyGSTi - “Gate Set Tomography, pyGSTi is an open-source software for modeling and characterizing noisy quantum information processors (QIPs), i.e., systems of one or more qubits.”

See also: