IMFUFA Seminarr?kke i efter?ret 2025
IMFUFA er sektionen/forskningsgruppen for matematik og fysik under Institut for Naturvidenskab og Milj?.
Alle seminarer afholdes i bygning 27, auditorium 27.1-089 ("Lokale 1") onsdage fra kl. 14 til 15 (med kaffepause og yderligere diskussion fra kl. 15 til 16).
10.09: Helle Astrid Kj?r (KU)
Unlocking the Secrets of Past Sea Ice Using Land Ice Cores
Ice cores extracted from land reveal critical insights to past climate: the isotopic composition of water in the ice reflects past temperatures, while the greenhouse gases directly trapped in ice bubbles allow us to place modern atmospheric conditions in the context of glacial and interglacial cycles.
Today, as climate change accelerates, the Arctic is experiencing transformations, with sea ice observed by satellites shrinking at an alarming rate. Sea ice plays a pivotal role in the Arctic's climate system by amplifying warming through feedback loops. To understand the scale of these changes knowing past sea ice variability in relation to climatic parameters such as temperature and CO2 is crucial for predicting future changes.
Traditionally, marine sediment records have been used to study past sea ice changes. However, sediment archives typically provide low temporal resolution records. Ice cores however offer an opportunity to study the intricate dynamics of past sea ice at a finer timescale.
Historically, sea salt (e.g., sodium [Na+] and chloride [Cl-]) and methanesulphonic acid (MSA-) have been used as proxies in land ice cores. However, these proxies have limitations: sea salt can also originate from the open ocean, and MSA- can diffuse in the ice with time.
Over the past decade, in collaboration with Italian colleagues, we have advanced the use of bromine and iodine in ice cores as innovative proxies for past sea ice conditions. In this presentation, we will discuss the significant progress made over the past ten years, and highlight the advantages, and share key findings with regards to past sea ice variability.
17.09: Cordula Reisch (IMFUFA)
Reaction diffusion equations in life science and ecology
Reaction diffusion equations are a powerful tool for describing processes in life science and ecology. I will give an overview of my research related to reaction diffusion equations.
The first example is the description of wildfire propagation in a spatially heterogeneous landscape. The propagation speed depends among others on the flammable biomass, the topography of the surface, and the wind velocity. Numerical simulations and mathematical analysis provide information on the spread of fire fronts.
In the second example, the interactions between immune cells and the virus during liver inflammation are modeled on a mesoscopic length scale. We abstract from single cells by describing them through densities, but keep some spatial structure of the tissue. The choice of the modeling frame and length scale leads to reaction diffusion equations with a spatial heterogeneous nonlocal term.
This term changes the system's behavior from describing chronic inflammation to healing infection courses and is therefore relevant for medical interventions.
The nonlocal term is analytically challenging when studying the instability of steady states. I will summarize results on the bifurcation properties supported by computer-assisted proofs.
As an outlook, I will present projects on the symbiosis of algae and corals, and multiphase models for tissue growth.
24.09: Tage Christensen (IMFUFA)
In, about and with the theories of relativity: The twin paradox revisited
22.10 Magnus Aspenberg (Lund U)
How antibiotic spectrum influences resistance evolution
In this talk I will outline some recent work together with E. Martens and K. Wollein Waldetoft, on the evolution of resistance in large microbal communitites. It is an important question in clinical treatment with antibiotics whether one should use broad or narrow spectrum of the antibiotics, i.e. if the antibiotics should target many (broad spectrum) or few (narrow spectrum) bacteria. Since the all the bacteria interact in a complex manner with each other it is not clear what the outcome is on a specific resistent bacteria, under the prescence of antibiotics. Given the interactions between bacteria, we build a mathematical model for the evolution of resistance in communities of bacteria, based on the generalised Lotka-Volterra equations.
05.11 Kaare Jensen (DTU)
Cutting mechanics of soft tissues: from natural stingers to paper cuts
12.11: Philipp Altrock (Kiel U)
Mathematical models of CAR T expansion integrating longitudinal data
19.11: Rok Cestnik (Lund U)
Inferring Dynamical Properties from Time Series Data
In this talk, I will present approaches for inferring dynamical properties directly from time series data. The main emphasis will be on oscillatory dynamics, with a theme of estimating phase dynamics from observations. I will first show methods that assume a phase description and fit it directly. Then I will move to machine learning approaches, where a model is trained to reproduce the system and can then be used to infer dynamical properties. I will highlight recent work with reservoir computing as a simple and versatile tool for modeling and inference.