Upcoming events

First Newsletter 2019

Further information will be given as soon as it is available.

Bethe Forum "Multihadron Dynamics in a box"

09.09.2019 – 13.09.2019
Poster Multihadron Dynamics
From September 9 - 13, 2019, the Bethe Forum "Multihadron Dynamics in a Box" will take place in the Bethe Center for Theoretical Physics in Bonn. The Forum is organized by M. Mai (Washington, DC), U.-G. Meißner (Bonn / Jülich), A. Rusetsky and C. Urbach (both Bonn).

For more information as well as the registration form please see the event webpage.

Recent years have witnessed a growing interest in the study of three-particle systems in lattice QCD. Substantial progress has been achieved both in the development of the methods that enable one to extract infinite-volume observables from lattice data produced on finite-size lattices, as well as in Monte-Carlo calculations of the three-particle systems, but important recent developments in the two-particle sector will also be addressed, since these questions are inherently related to each other.
In particular, it is planned to discuss the following questions:

  • What is the best strategy in the analysis of data in the three-particle sector?

  • What are the quantities to extract form the finite-volume sector?

  • How the further progress in the field looks like after the derivation of the quantization condition (analysis of the data on the Roper resonance, three-particle decay matrix elements, etc.)?

  • What are the present status and immediate perspectives of lattice simulations in the three-particle sector? For example, can one expect the calculation of the excited levels in the three-particle sector? Are the calculations in many-body (four and more) systems feasible in a forseeable future?

Lecture Series on "Machine Learning and its Applications"

07.10.2019 – 11.10.2019
Poster Machine Learning

Fabian Ruehle (CERN, Geneva) will give a Lecture Series on "Machine Learning and its Applications" from October 7 - 11, 2019, in the Bethe Center for Theoretical Physics in Bonn.

Abstract: Machine Learning techniques, in particular neural networks, have become an integral part of our lives. Due to their versatile nature, they are applied in the private and academic sector with tremendous success. In these lectures, I will first review the basic building blocks of neural networks and how they are trained. I will then discuss popular neural network architectures and how they are used in unsupervised, semi-supervised and supervised machine learning. I will also introduce other common machine learning techniques and present example applications to problems in Physics (ranging from Astrophysics and Cosmology to Particle Physics, Mathematical Physics and String Theory). In the exercises, I will use the techniques introduced in the lectures to solve simple problems in real time.

For more information please check the event webpage.

Further events will be announced as soon as possible.