Upcoming Talks

TBA

Mario Krenn studied Physics at the Technical University in Vienna, Austria, and did his PhD with Anton Zeilinger on quantum optics and entanglement until End of 2017. There he started to use computers to design new quantum experiments, several of which have been executed in laboratories. Afterwards, he went to Toronto, Canada, to the Lab of Alan Aspuru-Guzik to learn how Chemists and Material Scientists use Artificial Intelligence and Deep Learning for the design of new molecules. Since September 2021 started and leads the "Artificial Scientist Lab" at the Max Planck Institute for the Science of Light, Erlangen, Germany. His main research is on AI-based design of quantum experiments and discovery of new physical phenomena in that way. He is also interested in how to use AI and millions of scientific papers to suggest new scientific research directions.

Tremendous algorithmic and experimental progress has been made towards realizing the potential of quantum computing. On the one hand, quantum algorithms and their circuit implementations are being developed and put to the test on the current generation of noisy hardware. On the other hand, hardware devices continue to expand in scale and are increasingly capable of suppressing, detecting, and correcting errors. The next challenge is to develop the crucial systems architecture to perform various computational tasks on emerging hardware more robustly and more efficiently. In this talk, I will advocate for achieving a form of early fault tolerance based on application-specific error correction. My talk will focus on a few recent results from our group at Yale about tailoring quantum error correction or detection for a range of critical applications, spanning from state preparation, expectation value estimation, quantum random access memory (QRAM), magic state functional units, and more. I will discuss the several conceptual design stages that underpin the customized error correction schemes, including logical qubit encoding, logical gate synthesis, qubit placement, and routing. More broadly, I will highlight the intricate but rewarding process of designing quantum algorithm, software and architecture in tandem.

Yongshan Ding is an Assistant Professor of Computer Science at Yale University, with a secondary appointment in Applied Physics. He is a member of the Yale Quantum Institute (YQI) and is affiliated with the Computer Systems Lab (CSL). Ding completed his Ph.D. from the University of Chicago, receiving the William Rainey Harper Dissertation Fellowship, one of UChicago's highest honors. He is also a recipient of the Siebel Scholarship. Prior to that, he received his B.Sc. degrees in Computer Science and Physics from Carnegie Mellon University. Ding is also the lead author of a textbook, Quantum Computer Systems, in Springer Nature's Synthesis Lectures in Computer Architecture.