Seminars and Colloquia at ESO Garching and on the campus

The SDSS-V Local Volume Mapper is a novel integral field spectrograph with an extremely wide field of view. It is currently conducting a survey of a large fraction of the Southern Milky Way plane and the Magellanic Clouds.
In this talk I will present the results of Early Science observations which target the massive globular cluster Omega Centauri.
Due to its brightness and large extent in the sky, this cluster provides a perfect benchmarking target for extragalactic stellar population studies. At the same time the wide LVM field of view allows study of the poorly constrained kinematics in the outer region of the cluster, providing a missing piece for dynamical modelling efforts.

From the integrated light we successfully measure the rotation curve of the cluster out to a radius of three half-light radii, significantly extending the range of our previous kinematic investigations based on resolved measurements with VLT MUSE. We can also recover the age and the metallicity of the cluster and provide detailed comparisons between different single stellar population models.

Artificial Intelligence (AI) has changed our way of assessing, processing, and distributing information, and Large Language Models (LLMs) like Chat GPT, Gemini, Claude and others could be seen as a replacement of intellectual performance previously only available through human intelligence. In the scientific community, many of us have been using AI and LLMs to accelerate their scientific productivity. However, it is unclear whether LLMs are actually needed to do high-quality science or simply yield higher productivity without substantially extending knowledge? This informal discussion was triggered by a discussion I had with Jason at the ESO guest house in Chile in January. I would like to discuss whether science actually profits from LLMs or if these tools rather undermine novel, quality research by design.