Hadronic Mono-Z Dark Matter Sensitivity with Flow Matching on CMS Open Data

We present a projected sensitivity study for hadronic mono-Z dark-matter production using CMS Run~2015D HTMHT open data corresponding to 2.256382381~invfb, from which 1,439,523 events satisfy the hadronic mono-Z selection. Backgrounds are modelled with a conditional flow-matching continuous normalizing flow trained on the selected HTMHT events and evaluated on a held-out validation split reweighted to the full selected population. To mitigate artifacts from missing-object features and avoid in-sample scoring bias we apply sentinel imputation for undefined angular features, persist the train/validation split indices, and enforce a minimum reported background yield of 20 events when selecting the working point. A signal-side offline trigger proxy is applied to the simulated signal before scoring. Under this procedure the baseline analysis yields expected significances of 2.89σ, 7.62σ, and 7.41σ for three simplified-model benchmarks. An ablation study that removes the detailed extra-jet kinematics reduces the expected significance by 53--71%, indicating that extra-jet topology carries substantial discriminating power in the hadronic mono-Z channel. These results are projected sensitivities (no unblinding performed); the limitations and reproducibility of the study are discussed in Sections limitations and reproducibility.