DESY plays a significant role in the German national research data infrastructure, with the PUNCH4NFDI and DAPHNE4NFDI consortia both being led by DESY scientists, and with strong contributions to their science goals. The NFDI consortia are now half-way through their first funding period of five years, and deliberations and discussions are commencing on the future setup of PUNCH4NFDI and...
The Belle II experiment at the SuperKEKB accelerator aims at precision measurements in B, tau and charm physic sectors. Many such measurements rely on high precision vertexing and thus precise alignment of the detection elements. A global alignment method utilizing Millepede II software package will be presented, which determines around sixty thousand alignment parameters simultaneously....
The CMS Generative Machine Learning Group will showcase three distinct projects, each utilizing point cloud-based generative models to advance particle physics research. The first project, "Attention to Mean Fields for Particle Cloud Generation", features an attention-based generative model that adeptly processes complex collider data represented as point clouds, demonstrating effectiveness on...
Modern scientific experiments often generate large amounts of data, posing challenges for real-time processing and analysis. ASAPO, a high-performance streaming framework developed at DESY, addresses these challenges by providing a robust solution for online and offline data processing. Leveraging TCP/IP and RDMA over Ethernet and Infiniband, ASAPO facilitates high-bandwidth communication...
!!!Please place me into the Monday afternoon 4:30 pm - 6 pm session!!!
Neural Networks (NNs) can be used to solve Ordinary and Partial Differential Equations (ODEs and PDEs) by redefining the question as an optimization problem. The objective function to be optimized is the sum of the squares of the PDE to be solved and of the initial/boundary conditions. A feed forward NN is trained to...
Within the EU-Project RF2.0, DESY focus on sustainable scientific computing infrastructure splitted into more classical/obvious directions like, new architectures, longer system lifetimes, software efficiencies etc. and the model to operate a decent amount of compute resources with variable power consumption coupled to 'true RE power' availability at DESY location by steering the compute load...
We investigate the potential of quantum computers for pattern recognition in track reconstruction at LUXE, based on a quadratic unconstrained binary optimisation and a quantum graph neural network.
