For founders pursuing commercial opportunities at the intersection of quantum computing and machine learning.

The Quantum Stream at CDL-Toronto brings together entrepreneurs, investors, AI experts, leading quantum information researchers, and quantum hardware companies (D-Wave Systems, Rigetti Computing, and Xanadu) to build ventures in the nascent domain of quantum machine learning and quantum optimization. Participants are eligible to receive investment from three prominent venture capital firms, office space in downtown Toronto, and intensive technical training from industry and academic leaders in quantum computing and machine learning.

“As someone who walks the line between academia and entrepreneurship, the Lab was very useful as a means to keep Xanadu on track, achieving necessary milestones we needed to derisk the company for our first round. For that I am truly indebted…Overall, the Lab has been fundamental to Xanadu’s success.”

Christian Weedbrook

Founder & CEO, Xanadu


Who Should Apply?

Ideal Quantum Incubator Stream candidates are creative, intelligent, and ambitious individuals with technical competency in machine learning, computational science, physics, math, statistics, or engineering; business acumen and experience in technology startups; or relevant industry experience or expertise. The Incubator Stream’s focus is on early-stage companies (pre-seed) or even projects (pre-incorporation); however, startups at all levels of maturity will be considered. All quantum programming and training is conducted in English and takes place in Toronto, Canada.

Example Innovation Areas:

  • Materials Discovery
  • Optimization and Logistics
  • Reinforcement and Unsupervised Machine Learning
  • Chemical Engineering
  • Genomics and Drug Discovery
  • Systems Design
  • Finance
  • Security

The list above is not exhaustive.

Contact to discuss the Incubator Stream with a Quantum team staff member.

Representative CDL Alumni

Our Mentors

CDL mentors include accomplished entrepreneurs, experienced operators, and active angel and venture investors. Mentors meet every eight weeks in Toronto to help founders set objectives over the program’s 10-month duration.

James Hardiman
Andrew Fursman
Maryanna Saenko
Alan Baratz

Full list of CDL-Toronto Fellows and Associates  

Our Scientists

Teams accepted to the CDL QML Incubator Stream benefit from extensive advising sessions and regular office hours with quantum physics, machine learning, and quantum computing experts. These scientists help to evaluate approaches to building technology, suggest improvements, and explore formal advising engagements.

Peter Wittek
Seth Lloyd
Roger Melko
Michele Mosca

Full list of CDL-Toronto Scientists  

Incubator Stream Features

The QML Incubator Stream offers a robust set of resources for new founders to launch and scale a startup.

  • Business Guidance and Investor Access – Objective-setting meetings with the CDL Fellows and Associates, a group of highly successful entrepreneurs and investors with expertise in scaling high-tech startups.
  • Capital – Pre-seed investment from three prominent venture capital firms:
  • Quantum Access – Quantum computing resources from our technology partners:
    • D-Wave – D-Wave Sampling Service, an interface to the D-Wave2000Q quantum computer and the D-Wave sampling servers
    • Rigetti – Rigetti Forest programming environment, with access to cloud-connected superconducting quantum processors and Quantum Virtual Machine (QVM);
    • Xanadu – Strawberry Fields, an open-source library for photonic quantum computing, with a suite of simulators for execution on CPU/GPU, and early private access to Xanadu’s cloud-based quantum photonic chips”.
  • Technical Education – QML Bootcamp lead by Professor Peter Wittek, author of the first textbook on quantum machine learning, with tutorials from other experts.
    • Click here to read Dr. Wittek’s latest co-authored review article on QML in Nature.
    • Click here to enroll in Dr. Wittek’s QML massive open online course
  • Business Support – Business development support from MBAs at Canada’s top business school, the Rotman School of Management at the University of Toronto.


The QML Incubator Stream operates one annual cohort at CDL-Toronto. Participating founders are strongly encouraged to relocate to Toronto, Canada in order to take advantage of the Incubator Stream features. For more information or to schedule an introduction meeting with the CDL team, email  




By 2022, the Quantum Incubator Stream will have produced more well- capitalized, revenue generating quantum software companies than the rest of the world combined. The majority of these will be based in Canada.  

Common Questions

What is quantum computing?

Quantum computers make direct use of the odd characteristics of quantum physics, such as superposition (a quantum bit (qubit) having multiple values at the same time) and entanglement (two qubits sharing and communicating certain characteristics despite large distances). While classical computation can make use of quantum effects (e.g. tunneling), quantum computers have a high degree of control over quantum states, as well as a mechanism to prevent the decoherence of the quantum states on reasonable time scales.

What is quantum machine learning? How is it different than what exists now?

Quantum machine learning uses quantum technologies to improve the speed and performance of learning algorithms. This may involve performing classical computation on data from quantum sensors or using a quantum computer to enhance machine learning on classical data. While scalable universal quantum computers are still a long way off, quantum machine learning may benefit from using current and near future quantum information processing devices. Further background information on QML can be found through the following articles: “Quantum Machine Learning” (technical) “Quantum Machine Learning: Path to a Better Artificial Intelligence?” (nontechnical)

What are the skills and knowledge prerequisites for the Incubator Stream?

For applicants coming from a computer science background, having a solid understanding of machine learning, probabilistic graphical models, statistics, and Monte Carlo methods is recommended, along with experience with distributed systems. For physicists, quantum computing, quantum many-body systems, and quantum information processing are the most relevant areas, and experience with large-scale numerical computations is a great advantage. Python and Tensorflow experience is required.

Do participants need to be in Toronto for the duration of the program?

Participants must be in Toronto for the technical bootcamp of the Incubator Stream during the month of July 2019 and for group sessions with CDL mentors in October 2019, December 2019, February 2020, April 2020, and June 2020. Participants are strongly encouraged to live in Toronto for the rest of the program to best make use of CDL resources, to work through problems with the technical team, to have rich interactions with the city’s AI ecosystem and because Toronto is a fantastic place to build a tech company.

How does the investment work?

Companies must decide whether to opt in or out of the pre-seed investment at the outset of the program. Those that opt in and obtain approval for their business proposals will receive investment. 

Who are the technology partners?

D-Wave Systems Founded in 1999, D-Wave Systems is the world’s first quantum computing company and the leader in the development and delivery of quantum computing systems and software. Its mission is to unlock the power of quantum computing to solve the world’s most challenging problems. D-Wave systems are being used by world-class organizations and institutions including Lockheed Martin, Google, NASA, USC, USRA and Los Alamos National Laboratory. D-Wave has been granted more than 140 US patents and has published over 90 peer-reviewed papers in leading scientific journals.

Rigetti Rigetti Computing is a full-stack quantum computing company that designs and manufactures superconducting quantum-integrated circuits. Rigetti packages and deploys those chips in a low-temperature environment, and builds control systems to perform quantum logic operations on them. Rigetti believes that the first useful quantum computers are within reach and that quantum computing has the potential to one day have an enormous positive impact on humanity. To help realize that vision, it is also developing new algorithms for quantum computing, with a focus on near-term applications in computational chemistry and machine learning. Forest is the world’s first full-stack programming and execution environment for quantum/classical computing and includes Quil (quantum instruction language), the Rigetti programming standard for quantum/classical computing.

Xanadu Xanadu is a light-based quantum computing company that creates silicon photonic chips to build a truly full-stack solution. Instead of using electrons to carry information and perform calculations, Xanadu uses photons. Unlike electrons, photons are very stable and are almost unaffected by random noise from heat. We use photonic chips to generate, control, and measure photons in ways that enable extremely fast computation. Strawberry Fields, Xanadu’s programming platform, is a library for simulation, optimization and quantum machine learning of continuous-variable circuits. The platform contains a Python API for quantum programming based on our user-friendly Blackbird language and a suite of virtual quantum computer backends built in NumPy and TensorFlow.

I have a background in machine learning or physics but don’t have a startup or team. Can you introduce me to others in the Incubator Stream?

Yes, we will accept individuals with strong technical backgrounds. Submit an application, and a CDL team member will contact you.

I’m not Canadian. Can I still apply?

Yes. Depending on your nationality, you may need a visa. If you are accepted, we can provide you access to support from a Canadian immigration law firm, which can help you obtain the necessary entry permits.

Can entrepreneurs without physics or ML experience still be involved?

Yes, particularly if they have specific industry expertise. The application is the same for those with technical and business backgrounds.

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