News archive - 2020

Wednesday, December 16, 2020

Professor Crystal Senko awarded Canada Research Chair in Trapped Ion Quantum Computing

Crystal Senko adjusts optical components in her lab

It is with great pleasure that we congratulate Professor Crystal Senko from the Faculty of Science for being named a Canada Research Chair (CRC)!

Senko joins 15 other University of Waterloo Science Professors in this distinguished program, and is one of nine professors across Waterloo appointed in 2020.

Wednesday, November 25, 2020

NSERC honours Donna Strickland with a new prize for research excellence

Donna Strickland

The Natural Sciences and Engineering Research Council of Canada (NSERC) is honouring Canada’s most recent science Nobel laureates by launching prizes in their names that will highlight Canadian research excellence.

Tuesday, November 24, 2020

Q & A with the experts: The problem with herd immunity and COVID-19

The “herd immunity strategy” has been discussed and largely rejected by scientists as a strategy to combat COVID-19.

Monday, November 23, 2020

Professor David Hawthorn’s lab uses x-rays to see waves of electrons in superconductors

Although physicists understand the properties of metals, insulators and semiconductors extremely well, the basic physics of high-temperature superconductors has remained a great mystery for over 30 years.

A new study using cutting edge experimental techniques by University of Waterloo researchers has now shed some light on the properties of one class of superconductor, known as cuprate superconductors, which have copper oxide layers inside of the material.

Thursday, November 19, 2020

Training machine intelligence for quantum control

Nature Machine Intelligence cover, September 2020

Advanced simulations may one day be able to help us explore new frontiers in atomic physics, build new materials and discover new drugs. But first, researchers must find the best ways to control these simulations. New research featured on the September cover of Nature Machine Intelligence explores machine learning as a method for achieving optimal control.

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