8 papers
Dffusion: Capturing the Beam-Beam Physics of Collisions with Diffusion Models
Antonio Chahine, Mariarosaria D'Alfonso, Jan Eysermans +10
Beam-induced backgrounds at high-luminosity colliders, such as the FCC-ee, are dominated by incoherent pair creation (IPC), and require computationally expensive simulatio…
QUIVER: Quantum-Informed Views for Enhanced Representations in Large ML Models
Aritra Bal, Michael Binder, Markus Klute +2
Large machine learning models benefit substantially from multimodal inputs that provide a complementary view of the same example. We introduce QUIVER (QUantum-Informed Views for En…
Particle-Lund Multimodality in Jet Taggers
Loukas Gouskos, Benedikt Maier
The Lund plane offers a physics-motivated, hierarchical representation of QCD radiation within jets, while transformer-based taggers have reached state-of-the-art performance by le…
From Information Geometry to Jet Substructure: A Triality of Cumulant Tensors, Energy Correlators, and Hypergraphs
Aritra Bal, Markus Klute, Benedikt Maier +1
Pairwise Fisher graphs capture local covariance information, but they cannot distinguish an irreducible multi-observable radiation pattern from a collection of ordinary pairwise co…
Contrastive Metric Learning for Point Cloud Segmentation in Highly Granular Detectors
Max Marriott-Clarke, Lazar Novakovic, Elizabeth Ratzer +3
We propose a novel clustering approach for point-cloud segmentation based on supervised contrastive metric learning (CML). Rather than predicting cluster assignments or object-cent…
Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)
Julia Gonski, Jenni Ott, Shiva Abbaszadeh +118
The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environmen…