# VBF Event Classification with Recurrent Neural Networks at ATLAS's LHC Experiment
## 6 Application to an ATLAS Search and Results  
This approach was validated using the data collected by the ATLAS experiment during the Run-2. A high-mass diboson semi-leptonic search was performed by the ATLAS collaboration [16] using the approach presented in this work to categorise data events in  
Figure 8: The fractions of signal events passing the VBF requirement on the RNN score as functions of the resonance mass for both VBF and GGF production in the 2-lepton channel. VBF and GGF/DY categories. Despite the lower decay rate, the VBF channel represents a promising signature since the amount of SM process is much more suppressed. The analyses of diboson events have a long history in the context of high-energy particle searches. Observation and characterisation of this kind of events represented a crucial test of the electro-weak (EW) and the Higgs sector of the SM. In particular, high-energy \(W_{L}W_{L}\) scattering was a key feature supporting the presence of a new scalar boson to complete the SM framework [24]. A new scalar boson was then discovered observing ZZ events in the so-called _golden channel_[25]; the new particle was proved to be consistent with the prediction of the [PERSON] boson. However, the [PERSON] boson discovery is not the end of the story; the cross section of very high-mass \(W_{L}W_{L}\) scattering has not been directly measured, so the diboson channel might still hide new physics. This channel is still one of the most promising channels to access and observe new physics. There are different theoretical models that foresee the presence of new high-mass resonances that may decay into diboson systems. All the possible final states are investigated. For the semi-leptonic search, a complex analysis selection was designed to enhance the signal sensitivity of these models in dedicated regions where a signal is expected to be found (Signal Regions, SRs). The first selection applied is the reconstruction of the vector boson which decays into leptons. Candidate events are selected according to the number of leptons (with a maximum of 2 leptons per event) and then assigned to 0, 1 or 2 lepton channels. After the leptonic selection, the VBF to GGF/DY categorisation is performed via the RNN score. Once categorisation has been applied, the identification of hadronically vector bosons is implemented. The complete analysis flow is shown in Figure 9. Multiple SRs are designed for each channel and category; the details of the applied selections can be found in [16]. There are many physical processes with final states similar to the interested signals. These events constitute the _background sources_ of an analysis. The impact of most relevant backgrounds can be estimated with proper methods. In this analysis, dedicated control regions (CRs) were designed: each CR was intended to estimate a specific source of  
Figure 9: Selection flow and signal region definitions of the \(X\to VV\to V_{\ell}V_{h}\) search. Here, \(\ell\) and \(h\) denote, respectively, a lepton and a hadronic decay. background, which is controlled by comparison to data samples. Finally, a statistical procedure based on a maximum likelihood fit was then performed in a combined CRs+SRs fit; the outcome of the procedure tests and the consistency between the observed data and the theory expectations revealed any deviation from the SM background processes. Examples of signal regions are shown in Figure 10; the distributions show the expected background coming from the standard model processes and the observed data for the final discriminating variable in 2-lepton and 1-lepton channels. In this search, the reconstructed transverse mass (\(m_{\tau}\)) of the diboson system for the 0-lepton channel and the diboson invariant mass for the 1-lepton (\(m_{\ell\
u jj}\)) and 2-lepton (\(m_{\ell\ell jj}\)) channels were used to extract possible new signals.