New Carlsberg Foundation grants for three IFA researchers
The Carlsberg Foundation has just awarded 188 scientific activities including grants for Jesper Olsen, Søren Ulstrup and Anders Nygaard
Associate professor Jesper Olsen has received a 2.2 m DKK infrastructure grant for Accelerator mass spectrometry – a tool for interdisciplinary research (AMIR)
Accelerator mass spectrometry (AMS) is an interdisciplinary tool used to answer research questions like: What is the pulse of the Sun? When did the Viking Age start? When did humans migrate out of Africa? What is the temporal change of glaciers? by measuring the isotopes of 10Be, 14C and 26Al. Together with a diverse group of researchers we wish to strengthen the AMS facility at Aarhus University.
Associate professor Søren Ulstrup has received a 400,000 DKK infrastructure grant for Viewing electrons on nanometer length scales and femtosecond timescales
The properties of materials can be controlled using light pulses with a time duration on the order of femtoseconds (0.000000000000001 s). Light can switch an insulating material into a conductive one and even create order out of disorder on the atomic scale. Here, we will visualise such phase transitions by probing them on nanometer length scales and femtosecond timescales with a new experiment.
PhD student Anders Nygaard has received a 1.2 m DKK Internalisation fellowship grant for Optimising Cosmological Emulators: Enhanced Training Data Sampling for Efficient Inference
Cosmological inference aims to determine key properties of the Universe, like its expansion rate, using models based on physical laws. These models are computationally expensive, especially for complex N-body simulations, which track the movement of matter. Machine-learning models with the ability to emulate the results of these simulations can help reduce this computational burden significantly.
Understanding cosmology requires millions of model evaluations to compare theory with observations, but running full simulations is time-consuming and costly. Emulators allow researchers to achieve accurate results more efficiently, making large-scale projects, like mapping the Universe's structure, feasible within practical time limits.
Emulators are trained on a small set of full simulations using clever data selection methods. Instead of running expensive simulations repeatedly, the emulator learns to predict outcomes for new scenarios in milliseconds. For high-cost models like N-body simulations, this drastically reduces computation time, enabling quicker cosmological insights.