Optimal transport (OT) is an ubiquitous optimization problem in mathematics, machine learning, and natural sciences since it induces a family of geometrically intuitive, robust distances on the space of probability distributions. It is relevant for modern physics for two main reasons: First, many data samples can be represented as (probability) distributions on suitable feature spaces, such as histograms, point clouds, image densities, et cetera. In a more abstract way, whole datasets can be interpreted as distributions on sample space. OT distances provide the natural language for comparing and interpolating between data, for instance in the context of generative modelling. Second, OT directly emerges in physical modelling or approximations, for instance in density functional theory or in statistical physics in the form of the Schrödinger bridge problem. In this talk we give a gentle introduction to optimal transport, the induced distances, and its applications to physics.
Biological membranes undergo dramatic shape transformations during vesicle release, organelle division, and intracellular trafficking. At the microscopic level these events require a change in membrane topology: the transformation of one continuous membrane into two separate ones. Such transitions occur on nanometre length scales where lipids must rearrange into highly curved, non-bilayer structures while still preserving the membrane’s barrier function.
In cells, specialized proteins such as dynamin catalyze these topological transitions. In this talk I will show how theoretical modelling and simulations can reveal the mechanisms and the control knobs that make them fast, reliable, and sometimes leaky. Using self-consistent field theory, coarse-grained molecular simulations, and phenomenological models, we map the energy landscapes governing membrane fusion and fission and identify the transient intermediates that dominate them, including hemifusion diaphragms, stalks, rim pores, and worm-like micelles.
A central message is that small changes in membrane composition or membrane–protein interactions can strongly reshape the energy landscape, producing large changes in the free-energy barriers and therefore in the rates and outcomes of membrane division. I will also discuss how multiple-membrane geometries, such as mitochondria and endoplasmic-reticulum contact sites, open additional pathways to membrane fission through transient inter-membrane fusion events.
My lab exploits optical resonances — from thin-film cavities to microscopic lasers inside living cells — to build new tools for science and medicine. Here I present three recent developments.
First, by monitoring resonance shifts of deformable optical micro-cavities and microscopic lasers, we resolve cellular forces in the picoNewton range and record contraction-induced refractive index changes down to 10⁻⁵ refractive index units, providing a new window onto the mechanical activity of cells and tissue.
Second, I will show how we have optimised OLED (organic light-emitting diode) technology for biomedical implants. OLEDs — the technology of choice for modern smartphones and TVs — can be integrated on a much wider range of substrates than conventional LEDs, making them well suited for neurostimulation and optogenetics, that is light-based control of genetically engineered neurons).
Finally, by driving the interaction between molecular excited states and optical cavity modes into the strong coupling regime, we obtain a new set of parameters for cavity tuning. We exploit these to develop thin-film optical filters and LEDs with angle-independent emission spectra — a key requirement for example for compact fluorescence-based sensing devices.
Warum fällt vielen Studienanfänger*innen der Einstieg in die Physik so schwer – und wie lassen sich ihre Lernprozesse besser verstehen und gezielter unterstützen? Trotz bekannter Hürden in der Studieneingangsphase wird die universitäre Physiklehre in der deutschsprachigen fachdidaktischen Forschung bislang nur vereinzelt untersucht. Der Vortrag stellt ein Forschungsprogramm vor, das diese Lücke systematisch schließt. Im Mittelpunkt stehen Studien zum Verständnis physikalischer Repräsentationen – etwa von Vektorfeldern und vektoriellen Differentialoperatoren – sowie zu typischen Lernschwierigkeiten im Umgang mit diesen Konzepten. Eye-Tracking-Experimente erlauben dabei Einblicke in visuelle Aufmerksamkeitsmuster, Denkprozesse und Fehlvorstellungen. Die Ergebnisse fließen in die Entwicklung neuer, vorlesungsbegleitender Aufgabenformate ein, die in der Lehre erprobt und nach dem Prinzip der evidenzbasierten Medizin evaluiert werden. So entsteht ein enger Forschungs-Lehr-Zirkel, der zeigt: Hochschuldidaktik Physik ist kein Randthema, sondern ein Schlüssel zur Weiterentwicklung universitärer Lehre – vorausgesetzt, sie bekommt den Raum, den sie verdient.
