Physics

Models of systems biology, climate change, ecology, complex instruments, and macroeconomics have parameters that are hard or impossible to measure directly. If we fit these unknown parameters, fiddling with them until they agree with past experiments, how much can we trust their predictions? We have found that predictions can be made despite huge uncertainties in the parameters – many parameter combinationsare mostly unimportant to the collective behavior. We will use ideas and methods from differential geometry and approximation theory to explain sloppiness as a ‘hyperribbon’ structure of the manifold of possible model predictions. We show that physics theories are also sloppy – that sloppiness may be the underlying reason why the world is comprehensible. We will present new methods for visualizing this model manifold for probabilistic systems – such as the space of possible universes as measured by the cosmic microwave background radiation.

It has been argued astronomy and astrophysics as a research field developed with the first telescope.  At the same time that Galileo observed the phases of Venus and the moons of Jupiter, European Powers will colonizing the Americas and other parts of the world.  This began a relationship between astronomy and colonization that continues today in terms of astronomers and nations building giant telescopes on Indigenous lands.  In the future as private actors develop a new space industry we will see the export of this colonialism to Space, to the Moon and one day even to Mars. We are already seeing this today with the development of satellite constellations, some of which are visible by the unaided eye and with the multinational Artemis Accords for lunar exploration.  In this talk I will review the relation between astronomy and colonization in the past, present, and future; and I will discuss steps educators and astronomers can take to address this in the classroom and how the field of astronomy and space exploration can be inclusive of Indigenous rights and voices.

Zoom link: https://pitp.zoom.us/j/95620288526?pwd=dW9ReW5FUVp3TWFmUVUxZjV5VFhNdz09

A large body of existing ecological theory relies on very strong and unrealistic assumptions about the way individuals move and get to interact with each other and with the environment. Specifically, several models assume that individuals behave like the molecules of an ideal gas: following completely random trajectories through the entire area occupied by the population and only interacting with each other when their trajectories intersect. In this presentation, I will first discuss how traditional population dynamics models emerge from ideal gas assumptions. Then, I will present our ongoing research to refine those models using more elaborated tools from random walk theory, spatially-extended nonlinear dynamical systems, and stochastic calculus. I will discuss examples covering both the development of new theory and its application ecological data.