5 papers
Volumetric Benchmarking of Quantum Computing Noise Models
Tom Weber, Kerstin Borras, Karl Jansen +2
The main challenge of quantum computing on its way to scalability is the erroneous behaviour of current devices. Understanding and predicting their impact on computations is essent…
JetFlow: Generating Jets with Conditioned and Mass Constrained Normalising Flows
Benno Käch, Dirk Krücker, Isabell Melzer-Pellmann +3
Fast data generation based on Machine Learning has become a major research topic in particle physics. This is mainly because the Monte Carlo simulation approach is computationally…
Point Cloud Generation using Transformer Encoders and Normalising Flows
Benno Käch, Dirk Krücker, Isabell Melzer-Pellmann
Data generation based on Machine Learning has become a major research topic in particle physics. This is due to the current Monte Carlo simulation approach being computationally ch…
Snowmass White Paper: Quantum Computing Systems and Software for High-energy Physics Research
Travis S. Humble, Andrea Delgado, Raphael Pooser +23
Quantum computing offers a new paradigm for advancing high-energy physics research by enabling novel methods for representing and reasoning about fundamental quantum mechanical phe…
Direct optimisation of the discovery significance when training neural networks to search for new physics in particle colliders
Adam Elwood, Dirk Krücker
We introduce two new loss functions designed to directly optimise the statistical significance of the expected number of signal events when training neural networks to classify eve…