arXiv subjects

Merna Abumusabh

Publications and source records attributed to Merna Abumusabh.

3 recordsLinked to original sources

arXiv2026

The $B^+ \to K^+ \nu \bar \nu$ decay as a QCD axion search: comparing reinterpretation approaches

Two recent independent analyses of Belle II $B^+ \! \to \! K^+\nu\bar\nu$ data yield limits on ${\mathcal B}(B^+ \! \to \! K^+ a)$ -- the two-body mode to a light invisible particle such as the QCD axion -- differing by a factor of roughly four; we trace this to the choice of kinematic variable space. The central figure of merit is the resolution in the reconstructed di-neutrino invariant mass $q^2_{\rm rec}$: fine-grained binning resolves the narrow axion signal, while coarse binning dilutes it into a background-dominated range. A BDT axis trained on $B^+ \! \to \! K^+\nu\bar\nu$ adds little discriminating power for $B^+ \! \to \! K^+ a$, as this axis is largely uncorrelated with $q^2$. These expectations are confirmed by a set of numerical tests. The subleading shape systematics omitted from our $q^2_{\rm rec}$-based approach {\em lower}, not raise, the $B^+ \! \to \! K^+ a$ limit: by better accommodating the $B^+ \! \to \! K^+\nu\bar\nu$ shape, they leave less room for the axion signal, making our $q^2_{\rm rec}$-based bound conservative, if anything. A dedicated reanalysis confirms that the kinematic-axes choice alone accounts for the factor-of-four sensitivity difference, and that the $B^+ \! \to \! K^+ a$ bound varies sizeably within the $q^2_{\rm rec}\times\eta({\rm BDT}_2)$ space, depending on the SM-likeness of $B^+ \! \to \! K^+\nu\bar\nu$, thus losing the dual-probe feature of our $q^2_{\rm rec}$-based approach. These results point to a broader consideration: likelihoods dominated by BDT variables are of limited use for reinterpretations when the signal shape differs appreciably from the BDT's training signal. We therefore advocate that experimental collaborations publish likelihood projections in physical variable spaces alongside BDT-based likelihoods, to maximise the reinterpretability of their measurements.

hep-ph↗

arXiv2025

The $B^+ \to K^+ \nu \bar \nu$ decay as a search for the QCD axion

We introduce a model-independent framework to reinterpret Belle II results using only public data, analytically reconstructing the mapping between true and reconstructed kinematic variables within the statistically dominant Inclusive Tagging Analysis. This enables rare-decay measurements to probe light invisible particles -- such as the QCD axion or axion-like particles, collectively denoted $a$ -- without relying on internal simulations. Applying the method to $B^+ \! \to \! K^+ \nu \bar\nu$ yields the strongest bound on the branching fraction for $B^+ \! \to \! K^+ a$, improving existing limits by about a factor of nine and constraining the axion's fundamental flavour-changing coupling to $b$ and $s$ quarks. The approach establishes $B^+ \! \to \! K^+ \nu \bar\nu$ as a dual probe -- simultaneously testing short-distance new physics and light invisible states, the two probes working independently to an excellent approximation -- and provides a general strategy for model-independent reinterpretation of collider data.

hep-ph↗

arXiv2025

Graph-based Full Event Interpretation: a graph neural network for event reconstruction in Belle II

In this work we present the Graph-based Full Event Interpretation (GraFEI), a machine learning model based on graph neural networks to inclusively reconstruct events in the Belle~II experiment. Belle~II is well suited to perform measurements of $B$ meson decays involving invisible particles (e.g. neutrinos) in the final state. The kinematical properties of such particles can be deduced from the energy-momentum imbalance obtained after reconstructing the companion $B$ meson produced in the event. This task is performed by reconstructing it either from all the particles in an event but the signal tracks, or using the Full Event Interpretation, an algorithm based on Boosted Decision Trees and limited to specific, hard-coded decay processes. A recent example involving the use of the aforementioned techniques is the search for the $B^+ \to K^+ \nu \bar \nu$ decay, that provided an evidence for this process at about 3 standard deviations. The GraFEI model is trained to predict the structure of the decay chain by exploiting the information from the detected final state particles only, without making use of any prior assumptions about the underlying event. By retaining only signal-like decay topologies, the model considerably reduces the amount of background while keeping a relatively high signal efficiency. The performances of the model when applied to the search for $B^+ \to K^+ \nu \bar \nu$ are presented.

hep-ex↗