The Institute for Quantum Computing (IQC) is a scientific research institute at the University of Waterloo. The research happening at IQC harnesses the quantum laws of nature in order to develop powerful new technologies and drive future economies.
Start with our Quantum computing 101 page. It's a quick start guide on quantum computing to help you understand some of the research that happens at IQC.
The Transformative Quantum Technologies (TQT) program at the University of Waterloo aims to advance the use of quantum mechanics from laboratory curiosity to an impactful device.
In his own words, Marc Morin is “addicted to the game.”
Morin is the CEO and co-founder at Auvik Networks, pronounced awe-vik, as in awesome. “It’s like having a child who does way better than you and it’s awesome,” Morin explained at the CryptoWorks21 Distinguished Lecture last fall. Elaborating on his evolving role as a CEO in a tech company, he shared lessons learned—the mistakes he made and the things he got right—during his personal journey as a serial technology entrepreneur.
Researchers at the Institute for Quantum Computing (IQC) in collaboration with researchers at the National Institute for Standards and Technology (NIST) have developed a highly robust method for structuring light and matter waves, enhancing the powerful probing ability of neutrons.
Quantum computers can solve a linear algebra problem faster than classical computers, according to a new study published in Science. The finding proves that constant-depth quantum circuits are more powerful than their classical counterparts, and provides a new sense of how quantum technology will be a key to more powerful computing.
Giovanni Fanchini, Western University
In this talk, we will review the use of thin films of organic polyradicals – organic polymers with one unpaired electron per monomer [1] – for memory devices and other applications. Although memory devices based on radical polymers have been often proposed, their stability was frequently limited to a few writing cycles, despite the excellent quality of the active layer.
Alexander Belovs, University of Latvia
This talk reflects on recent research in progress with Andras Gilyen. Over the years, there have been a number of papers dealing with quantum algorithms testing some properties of classical probability distributions. Our goal is to understand what is the right way for quantum algorithms to access the distribution. There is a number of possible models, and we analyse their mutual strength.
Frederic Magniez, Université Paris Diderot
We describe a new quantum paradigm, that we call Quantum Chebyshev’s inequality, to approximate with relative error the mean of any random variable with a number of quantum samples that is linear in the ratio of the square root of the variance to the mean. Classically the dependency is quadratic. To illustrate this method, we apply it to the approximation of frequency moments in the multi-pass streaming model, and to the approximation of the number of edges and triangles in the quantum graph query access model.
