Today an important contribution to the quantum computing community was published on PLOS ONE. The paper was authored by Mark Fingerhuth and Tomáš Babej, founders of our alumni company ProteinQure, and Peter Wittek, academic director of our Quantum Machine Learning program based at the University of Toronto.

The paper is a collection and review of open-source software in quantum technologies that gives credit to the authors of these projects and highlights best practices to foster the growing community of quantum software developers.

The paper is also intended for computer scientists and IT professionals who are interested in quantum computing but do not know where to start. The survey provides an introduction to the pragmatic aspects of using quantum computers today. For example, the paper provides an excellent overview of workflows for algorithms running on quantum computers, as shown in this example of a gate model software stack:

This work is an important step towards making quantum computing mainstream. With the growth of open-source software dedicated to quantum programming, the barrier to entry continues to drop.

The growth of a robust open-source community is a key indicator of the development of the industry as a whole, since building quantum computing applications will require multidisciplinary teams from diverse industr

y and academic backgrounds. Anyone interested in exploring practical tools for programming this kind of emerging hardware should read this paper.


The pace of development in quantum computing mirrors the rapid advances made in machine learning and artificial intelligence. It is natural to ask whether quantum technologies could boost learning algorithms: this field of inquiry is called quantum-enhanced machine learning. Peter Wittek, Academic Director of the CDL Quantum Machine Learning program, is launching a course to show what benefits current and future quantum technologies can provide to machine learning, focusing on algorithms that are challenging with classical digital computers. They have put a strong emphasis on implementing the protocols, using open source frameworks in Python. Prominent researchers in the field will give guest lectures to provide extra depth to each major topic. These guest lecturers include Alán Aspuru-Guzik, Seth Lloyd, Roger Melko, and Maria Schuld.

Enroll for the course today!