10 papers
Towards anomaly detection searches for new physics signatures including Higgs bosons with weakly supervised machine learning
Chi Lung Cheng, Julia Gonski, Runze Li +5
The Higgs boson, with its universal coupling to mass, provides a broadly applicable portal to sectors beyond the Standard Model and is therefore a natural anchor for anomaly detect…
Searching for Anomalies with Foundation Models
Vinicius Mikuni, Benjamin Nachman
Foundation models have the potential to extend the discovery reach for anomaly detection searches. When studying the large OmniLearned foundation model on data from the CMS experim…
Unfolding with a Wasserstein Loss
Katy Craig, Benjamin Faktor, Benjamin Nachman
Data unfolding -- the removal of noise or artifacts from measurements -- is a fundamental task across the experimental sciences. Of particular interest are applications in physics,…
FAIR Universe Weak Lensing ML Uncertainty Challenge: Handling Uncertainties and Distribution Shifts for Precision Cosmology
Biwei Dai, Po-Wen Chang, Wahid Bhimji +15
Weak gravitational lensing, the correlated distortion of background galaxy shapes by foreground structures, is a powerful probe of the matter distribution in our universe and allow…
Signal-Aware Contrastive Latent Spaces for Anomaly Detection
Runze Li, Benjamin Nachman, Dennis Noll
High-dimensional feature spaces in particle physics events pose a fundamental challenge to density-estimation-based weakly supervised anomaly detection, whose fidelity degrades rap…
Weakly Supervised Anomaly Detection in Events with a Higgs Boson and Exotic Physics
Chi Lung Cheng, Sarah Demers, Sascha Diefenbacher +3
We present a machine learning-based anomaly detection strategy designed to identify anomalous physics in events containing resonant Standard Model physics and demonstrate this meth…