| Thursday 10 October 2024 | |
| Events for day: Wednesday 09 October 2024 |
| 11:00 - 12:00 Wednesday Weekly Seminar - Hybrid Format Extraction of Parton Distribution Functions Considering Measured Observables and Projected EIC Measurement Data School PARTICLES AND ACCELERATORS Abstract: The extraction of parton distribution functions (PDFs) and the strong coupling constant relies heavily on physical observables. Utilizing a variety of appropriate data significantly impacts proton PDFs. In this lecture I will first review the procedure for obtaining new PDF sets. Then, it will explain the constraints imposed by experimental data, such as W/Z boson production, Drell-Yan processes, and jet measurements, on various parton distributions. Finally, it will discuss how simulated data for future colliders can improve PDFs and the strong coupling constant. Link to Join Virtually: ... 13:30 - 15:00 Weekly Seminar Knocking at the Door of the Cosmic Microwave Background (CMB) School ASTRONOMY I will talk about the model-building approach to describe the very early universe, which can address the several unresolved puzzles of the hot Big Bang Cosmology. The formation of topological defects as a result of phase transition is another promising phenomenon to probe the unseen universe. I will briefly describe the formation of topological defects and the emission of the Stochastic Gravitational-Wave Background (SGWB). One of the topological defects, Cosmic Strings, may have an imprint on the CMB. I will briefly talk about how we can see their footprints in the CMB and constrain the cosmic string tension. Recently, (International Pulsar ... 14:00 - 15:00 Combinatorics and Computing Weekly Seminar Algorithmic Optimal Transport in High Dimensions School MATHEMATICS Optimal transport is the problem of moving a mass of objects from an initial mass distribution to a final mass distribution with minimum cost. The input to the problem is the initial and final distributions, as well as the distance metric or cost of transportation between each initial position and each final position. We should match points in the initial mass with points in the final mass so as to minimize the total cost. This problem was first proposed in the context of economics and recently in the context of machine learning to compare and transform probability distributions. I shall mainly talk about these applications. If I have ... |