From the 4 of 234 papers with an AI index.
39 citations
- University of California, BerkeleyUS92 papers
- The Ohio State UniversityUS83 papers
- University of California SystemUS79 papers
- University College LondonGB65 papers
- University of MichiganUS64 papers
- Université Paris-SaclayFR61 papers
- Centre National de la Recherche ScientifiqueFR60 papers
- Brookhaven National LaboratoryUS59 papers
- Yale UniversityUS59 papers
- Michigan State UniversityUS56 papers
- SLAC National Accelerator LaboratoryUS55 papers
- Institució Catalana de Recerca i Estudis AvançatsES54 papers
21 papers · 1 filter
Graph theory inspired anomaly detection at the LHC
Jack Y. Araz, Dimitrios Athanasakos, Mateusz Ploskon +1
Designing model-independent anomaly detection algorithms for analyzing LHC data remains a central challenge in the search for new physics, due to the high dimensionality of collide…
Forecasting Generative Amplification
Henning Bahl, Sascha Diefenbacher, Nina Elmer +2
Generative networks are perfect tools to enhance the speed and precision of LHC simulations. Especially when generating events beyond the size of the training dataset, it is import…
Precise branching fractions
Vladimir V. Gligorov, Dean J. Robinson
Although discovered more than sixty years ago, direct measurement of the branching fractions is a formidable challenge that has not been attempted. Typically the…
On Focusing Statistical Power for Searches and Measurements in Particle Physics
James Carzon, Aishik Ghosh, Rafael Izbicki +3
Particle physics experiments rely on the (generalised) likelihood ratio test (LRT) for searches and measurements, which consist of composite hypothesis tests. However, this test is…
Sweeping the pion chimney for axion-like particles with KOTO
Reuven Balkin, Stefania Gori, Dean J. Robinson +1
We demonstrate that novel limits on prompt axion-like particles (ALPs) in the hard-to-probe mass range near the neutral pion - the so-called pion chimney - may be obtained from rec…
Pretrained Event Classification Model for High Energy Physics Analysis
Joshua Ho, Benjamin Ryan Roberts, Shuo Han +1
We introduce a foundation model for event classification in high-energy physics, built on a Graph Neural Network architecture and trained on 120 million simulated proton-proton col…