Researchers have conducted a search for dark matter produced in association with a Z boson using CMS Run 2015D open data. The study employed Neural Spline Flows to model background and signal densities, reducing observational data into a 37-dimensional feature vector. While the analysis did not find evidence for dark matter, it established upper limits on signal-strength parameters for scalar, vector, and axial-vector mediators, noting that observed limits were weaker than expected due to a background modeling discrepancy. AI
IMPACT This research applies advanced machine learning techniques, specifically Neural Spline Flows, to particle physics data, potentially paving the way for more sophisticated analysis in complex scientific domains.
RANK_REASON The cluster contains an arXiv paper detailing a scientific research methodology and findings.
- arXiv
- Centers for Medicare and Medicaid Services
- CMS Run 2015D
- dark matter
- Hugging Face
- Metropolitan Museum of Art
- MINIAOD
- MINIAODSIM
- Neural Spline Flows
- Standard Model
- Z boson
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