Rostock 2019 – scientific programme
Parts | Days | Selection | Search | Updates | Downloads | Help
Q: Fachverband Quantenoptik und Photonik
Q 3: Quantum Information (Quantum Computing) I
Q 3.1: Invited Talk
Monday, March 11, 2019, 10:30–11:00, S HS 001 Chemie
Quantum information scrambling and hybrid machine learning with trapped ions — •Norbert M. Linke1, Kevin A. Landsman1, Daiwei Zhu1, and Chris Monroe1,2 — 1Joint Quantum Institute, University of Maryland, College Park, MD 20742, USA — 2IonQ, Inc., College Park, MD 20740, USA
Trapped ions are a promising candidate system to realize a scalable quantum computer. We present a system comprised of a chain of 171Yb+ ions with individual Raman beam addressing and individual readout [1]. This fully connected processor can be configured to run any sequence of single- and two-qubit gates, making it in effect an arbitrarily programmable quantum computer.
We use this versatile system to perform a teleportation-based protocol to verify quantum information scrambling. This phenomenon describes the dispersal of local information into many-body quantum entanglements and correlations, and has recently been conjectured to shed light on the black-hole information paradox.
Quantum-classical hybrid systems offer a path towards the application of near-term quantum computers to different optimization tasks. We present several demonstrations relating to machine learning in such a hybrid approach, such as finding the ground state binding energy of the deuteron nucleus, the training of shallow circuits [3], and the preparation of quantum critical states using a quantum approximate optimization algorithm (QAOA) scheme. Recent results from these efforts, and concepts for scaling up the architecture will be discussed.
[1] Nature 563:63 (2016) [2] arXiv:1806.02807 [3] arXiv:1801.07686