Dr. Andreas Elben

My research lies at the intersection of quantum information theory, many-body physics, and quantum simulation. I develop methods to characterize, benchmark, and learn from quantum devices, with a particular focus on extracting reliable information from complex many-body experiments and on understanding when such devices can outperform classical simulation. I collaboate closely with experimental groups, including those at the ETHZ-PSI Quantum Computing Hub.

A central theme of my work is the development of randomized measurement and classical-shadow methods for probing quantum states and dynamics beyond standard observables. These tools enable scalable studies of entanglement, fidelity, many-body dynamics, and other nontrivial properties on near-term quantum platforms, in close connection with experiments. This also includes the development of open source software for the analysis and processing of data produced by quantum experiments.

Before joining PSI, I was a postdoctoral researcher at the Institute for Quantum Information and Matter at the California Institute of Technology and in the Simons Collaboration on Ultra-Quantum Matter, and obtained my PhD at the Institute for Quantum Optics and Quantum Information in Innsbruck.

For further information about me and my research, please feel free to get in touch or visit my personal website at andreaselben.github.io.

• Randomized measurements and classical shadows for many-body quantum systems
• Benchmarking and verification of quantum devices in regimes beyond exact classical simulation
• Quantum many-body dynamics, thermalization, and emergent randomness
• Digital-analog quantum simulation on near-term hardware, in particular using hybrid qubit-boson devices
• Classical complexity, learnability, and quantum advantage

Giuseppe Calabrese — PhD student

Research topic: learning hybrid qubit-boson quantum devices

Dimitri Lanier — PhD student

Research topic: large-scale quantum channel learning with tensor networks and error mitigation

• Google Scholar
• ORCID: 0000-0003-1444-6356
• RandomMeas.jl (GitHub) — open-source tools for randomized measurements