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

Hitesh Rasineni; Bhavishya Chebrolu

cs.LGJul 15, 2026

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

Authors: Hitesh Rasineni, Bhavishya Chebrolu

Organizations: VIT-AP University, Amaravati, India · 1VIT-AP University, Amaravati, 522241, India · Mohan Babu University, Tirupati, India · 2Mohan Babu University, Tirupati, 517102, India

Abstract

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 simulation. Events are selected in the mono- $Z\rightarrow\ell^+\ell^-$ final state in both the $μμ$ and $ee$ channels. Forty kinematic observables are extracted from MINIAOD and MINIAODSIM, cleaned with physics-motivated selections, and reduced to a 37-dimensional feature vector. Five Neural Spline Flows are trained independently to model Standard Model background and mediator-specific DM signal densities. The per-event test statistic is constructed from the log-likelihood ratio between the signal and background density estimates, providing sensitivity across the full kinematic phase space without requiring a hard upper $\mathrm{MET}$ threshold. A simultaneous profile-likelihood fit combining the two channels yields observed (expected) 95% confidence level upper limits on the signal-strength parameter of $μ<0.0177$ ( $0.0018$ ) for the scalar mediator, $μ<0.0362$ ( $0.0039$ ) for the vector mediator, and $μ<0.0498$ ( $0.0069$ ) for the axial-vector mediator. The observed limits are weaker than expected because of a residual high- $\mathrm{MET}$ background-modeling discrepancy rather than evidence for a DM signal. To our knowledge, this is the first application of Neural Spline Flow likelihood-ratio scoring to a mono- $Z$ dark matter search using CMS Run 2015D open data simultaneously in the $μμ$ and $ee$ channels.

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Abstract

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