Greenhorn Meeting 2026

Session

(Quantum) Mechanical Oscillators

6 Oct 2026, 10:30

Institute for Quantum Physics

Conveners

(Quantum) Mechanical Oscillators

• Hans Michel (Universität Hamburg)

13. Inter-Mode Correlations in a Quantum Optomechanical System

Sofiia Kokhanska (Institute of Spintronics and Quantum Information, Faculty of Physics and Astronomy, Adam Mickiewicz University)

06/10/2026, 10:30

Talk

Nonclassical correlations between different bosonic modes constitute one of the key signatures of quantum behavior in hybrid quantum systems and play an important role in quantum information processing, quantum communication, and quantum sensing. In particular, inter-mode quantum correlations provide valuable insight into the transfer and redistribution of quantum excitations in coupled...

28. Towards Remote Quantum Coherent Coupling of Atoms and a Mechanical Oscillator via Light

Andreas Weber (Department Physik, Universität Basel)

06/10/2026, 10:45

Talk

Hybrid quantum systems that combine complementary physical platforms offer a promising route toward devices capable of simultaneously storing, processing, and transmitting quantum information.[1] In our experiment, we combine a spin-polarized ultracold atomic ensemble and a membrane optomechanical system to realize such a hybrid platform. We engineer coherent interactions between the two...

29. Coherent feedback cooling of a mechanical oscillator

Alexandre Huot de Saint-Albin (Basel University)

06/10/2026, 11:00

Talk

Quantum feedback is a powerful technique for controlling quantum systems. The conventional strategy relies on quantum-limited measurements followed by classical processing and feedback actuation onto the system. However, quantum mechanics also allows coherent feedback of quantum signals. Such coherent feedback may exploit the information stored in non-commuting observables, while circumventing...

7. Implementation of a Simple Neural Network using a Neuromorphic Linear Wave-Scattering System

Paula Turkiewicz (Adam Mickiewicz University)

06/10/2026, 11:15

Talk

Neuromorphic computing aims to perform machine-learning tasks directly in physical hardware, exploiting the system's own dynamics instead of digital simulation. Wanjura and Marquardt recently proposed realizing neural networks in a physical system based on linear wave scattering, showing that a nonlinear activation function can emerge from purely linear optics [1]. Here, we test this idea by...