The Quantum Stream at CDL-Toronto brings together entrepreneurs, investors, leading scientists in quantum technologies, and quantum hardware vendors (D-Wave Systems, IBM Q, Rigetti Computing, and Xanadu) to build ventures in the nascent domain of quantum computing, machine learning, optimization, sensing and other applications of quantum technologies. Participants are eligible for office space in downtown Toronto, and an intensive 4-week technical quantum bootcamp 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.”
Founder & CEO, Xanadu
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.
Both individuals and early-stage companies are encouraged to apply.
Example Innovation Areas:
The list above is not exhaustive.
Contact email@example.com to discuss the Incubator Stream with a Quantum team member.
The Quantum Incubator Stream offers a robust set of resources for new founders to launch and scale a startup in the quantum ecosystem.
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.
Full list of CDL-Toronto Fellows and Associates
Teams accepted to the CDL Quantum 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.
Full list of CDL-Toronto Scientists
Peter Wittek, Founding Academic Director, CDL Quantum
In September of 2019, Rotman Assistant Professor Peter Wittek went missing during a mountaineering expedition in the Himalayas, after being caught in an avalanche. Peter was a valued member of the Rotman community and his loss is keenly felt.
The CDL Quantum program offers an intense 4-week bootcamp focused on helping would-be founders learn the necessary technical and business skills required to succeed in the Quantum startup space. You will gain free access to Quantum hardware, receive guidance from Quantum experts, and benefit from mentorship provided by leading business professionals and academics.
For the individual participants, there will be various activities and social events over the 4-week period, where they can meet potential co-founders and team members. In 2019, approximately 75% of our individual participants either formed or joined a venture over the course of the bootcamp.
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 decoherence of the quantum states on reasonable time scales.
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).
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.
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.
IBM Q IBM Q is an industry-first initiative to build commercial universal quantum systems for business and science applications. IBM Q will provide access and hands-on technical support for the public IBM Q Experience™ systems, and IBM’s open source quantum software platform, Qiskit™. IBM will provide ongoing support through a single point of contact coordinator.
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.
Yes, we will accept individuals with strong technical backgrounds. Submit an application, and a CDL team member will contact you.
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.
Yes, particularly if they have specific industry expertise. The application is the same for those with technical and business backgrounds.