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Dark Matter Search Uses Neural Spline Flows with CMS Data

By PulseAugur Editorial · [1 sources] ·

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, constructing a test statistic from the log-likelihood ratio. The analysis yielded observed 95% confidence level upper limits on the signal-strength parameter for scalar, vector, and axial-vector mediators, though these limits were weaker than expected due to a background modeling discrepancy rather than evidence of dark matter. AI

IMPACT This research demonstrates a novel application of Neural Spline Flows for complex data modeling in particle physics, potentially influencing future analytical techniques.

RANK_REASON The item is a scientific paper detailing a novel application of a statistical method to a physics search. [lever_c_demoted from research: ic=1 ai=0.4]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Dark Matter Search Uses Neural Spline Flows with CMS Data

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The item is a scientific paper detailing a novel application of a statistical method to a physics search. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Mono-Z Dark Matter Search with Neural Spline Flows Using CMS Run 2015D Open Data

    We report a search for dark matter (DM) produced in association with a leptonically decaying \(Z\) boson at \(\sqrt{s}=13\) TeV using CMS Run 2015D open data corresponding to an integrated luminosity of \(2.32\,\mathrm{fb}^{-1}\) together with simplified-model Monte Carlo simulat…

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