June 5, 2022
STAQ Summer School 2022 is a go. This year's lecturers are Aram Harrow, Akimasa Miyake, Peter Love, Shelby Kimmel, Ken Brown, and Felix Leditzky. More information can be be found at https://staq.pratt.duke.edu/summer-school
July 15, 2021
Summer School 2021 was online again with a broader range of topics. Full details can be found here https://staq.pratt.duke.edu/summer-school Lecturers and topics Kenneth Brown, Duke, Quantum Error Correction Yufei Ding, UC Santa Barbara, Quantum Architecture Casey Duckering, U. Chicago Sophia [...]
July 2, 2020
The STAQ Summer School went virtual. The downside was missing all the great interactions with students. The upside is that all the material is recorded so that everyone can learn more quantum information. Materials are available here.
February 11, 2020
The 22nd Annual SQuInT workshop was held in Eugene, Oregon. Organized by STAQer Akimasa Miyake, University of New Mexico, with Brian Smith at the University of Oregon. STAQ presented one invited talk and three contributed talsk. Maya Berlin-Udi from the Haeffner group describes hardware efforts [...]
August 4, 2019
Members of the Brown lab at Duke and the Chong lab at U. Chicago presented at the 5th International conference on Quantum Error Correction. You can watch Dripto Debroy's talk on Stabilizer Slicing and Natalie Brown's talk on Leakage and Error Correction on YouTube.
June 21, 2019 | Duke Engineering News
A week-long summer school led by Duke ECE professor Kenneth Brown explored topics in quantum information for beginners and experts alike.
June 18, 2019
The inaugural STAQ Quantum Ideas School (#SummerSTAQ) is underway.
May 31, 2019
STAQ researchers at Chicago and Duke will present about their Asymptotic Improvements to Quantum Circuits via Qutrits at ISCA 2019.
December 5, 2018
STAQ Teams met at Duke University in December to launch the project.
August 7, 2017 | Duke Engineering News
Seven-university, five-year interdisciplinary collaboration is funded by the National Science Foundation’s largest quantum computing effort to date