QSI Seminar: Richard Kueng, Johannes Kepler University Linz

The classical shadow formalism and (some) implications for quantum machine learning

SPEAKER: Dr Richard Kueng

AFFILIATION: Institute for Integrated Circuits, Johannes Kepler University Linz, Austria 

RESEARCH TOPIC: Quantum algorithms/QML/Tomography 

ABSTRACT:
Extracting important information from a quantum system as efficiently and tractably as possible is an important subroutine in most near-term applications of quantum hardware.
We present an efficient method for constructing an approximate classical description of a quantum state using very few measurements of the state. This description, called a classical shadow, can be used to predict many different properties. The required number of measurements is independent of the system size and saturates information-theoretic lower bounds.
If time permits, I will also illustrate how one can combine classical shadows with machine learning (ML). This combination showcases that training data obtained from quantum experiments can be very empowering for classical ML methods. 

This is joint work with Robert Huang and John Preskill (both Caltech).

HOSTED BY: Dr Mária Kieferová, Centre for Quantum Software and Information, University of Technology Sydney, Australia

BIO: RICHARD KUENG
Born and raised in the vicinity of Linz, Richard Kueng pursued his academic studies from 2007 to 2012 at ETH Zurich, Switzerland. After completing a BSc in Interdisciplinary Sciences and a MSc in Physics (top of his class), he started his doctoral studies at the University of Freiburg, Germany.
With an academic exchange at the University of Sydney in-between, he completed his doctorate at the University of Cologne in 2016 (summa cum laude). After brief postdoc appointments in Cologne and Berlin (Free University), Richard Kueng joined the California Institute of Technology. From 2017 to 2020, he held a joint research position at both the Institute for Quantum Information and Matter (IQIM) and the Department of Computing and Mathematical Sciences (CMS).
In 2020, Richard Kueng returned ``home” to Linz and is currently assistant professor (tenure track) at the Institute for Integrated Circuits at the Johannes Kepler University Linz.

Richard Kueng pursues an interdisciplinary research agenda at the interface between computer science (algorithms & computational complexity), physics (quantum information & quantum technologies) and applied math (convex geometry & high dimensional probability theory). Broadly speaking, he aspires to develop efficient and simple solutions for important algorithmic challenges that also come with rigorous performance guarantees. Concrete examples are efficient subroutines for quantum and classical data processing, as well as (convex) optimization. Applications in optics, wireless communication, the math of voting and electronic design automation are also within his portfolio.