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CMS-PAS-SMP-22-011
Study of vector boson scattering in the semileptonic final state and search for anomalous quartic gauge couplings from proton-proton collisions at 13 TeV
Abstract: A measurement of the electroweak production of ZV (V = W, Z) boson pairs associated with two jets in proton-proton collisions at a center-of-mass energy of 13 TeV is presented. The analysis targets final states with two isolated electrons or muons from Z decays and three to four jets, depending on the momentum of the vector boson that decays into quarks. The data, corresponding to an integrated luminosity of 138 fb1, were collected at the CERN LHC with the CMS detector during the 2016--2018 data-taking period. The cross section is measured in a fiducial region characterized by a large invariant mass and pseudorapidity gap between the two forward jets. The electroweak production of ZV in association with two jets is measured with an observed (expected) significance of 1.3 (1.8) standard deviations. Constraints are also placed on effective field theory parameters that describe anomalous electroweak production of WW, WZ, and ZZ boson pair pairs in association with two jets, combining the ZV and WV semileptonic events. Stringent limits are set on anomalous quartic gauge couplings in terms of dimension-8 operators.
Figures & Tables Summary References CMS Publications
Figures

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Figure 1:
An illustrative Feynman diagram for the VBS process contributing to the EW production of events containing a vector boson that decays hadronically (V=W, Z), W or Z boson that decays into leptons, and two forward jets. New physics (represented by a black circle) in the EW sector can modify the VZ production.

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Figure 2:
Distributions of sub-leading VBS jet pT for the data, and the post-fit backgrounds (stacked histograms), in the SRs of for the ZV channel for the resolved b-tag (left) and the resolved b-veto (right) categories. The post-fit VBS EW ZV signal is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 2-a:
Distributions of sub-leading VBS jet pT for the data, and the post-fit backgrounds (stacked histograms), in the SRs of for the ZV channel for the resolved b-tag (left) and the resolved b-veto (right) categories. The post-fit VBS EW ZV signal is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 2-b:
Distributions of sub-leading VBS jet pT for the data, and the post-fit backgrounds (stacked histograms), in the SRs of for the ZV channel for the resolved b-tag (left) and the resolved b-veto (right) categories. The post-fit VBS EW ZV signal is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 3:
Distributions of DNN score for the data, and the post-fit backgrounds (stacked histograms), in the SRs of for the ZV channel for the b-tag (left) and the b-veto (right) channels, for the boosted (resolved) category in the first (second) row. The post-fit VBS EW ZV signal is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 3-a:
Distributions of DNN score for the data, and the post-fit backgrounds (stacked histograms), in the SRs of for the ZV channel for the b-tag (left) and the b-veto (right) channels, for the boosted (resolved) category in the first (second) row. The post-fit VBS EW ZV signal is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 3-b:
Distributions of DNN score for the data, and the post-fit backgrounds (stacked histograms), in the SRs of for the ZV channel for the b-tag (left) and the b-veto (right) channels, for the boosted (resolved) category in the first (second) row. The post-fit VBS EW ZV signal is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 3-c:
Distributions of DNN score for the data, and the post-fit backgrounds (stacked histograms), in the SRs of for the ZV channel for the b-tag (left) and the b-veto (right) channels, for the boosted (resolved) category in the first (second) row. The post-fit VBS EW ZV signal is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 3-d:
Distributions of DNN score for the data, and the post-fit backgrounds (stacked histograms), in the SRs of for the ZV channel for the b-tag (left) and the b-veto (right) channels, for the boosted (resolved) category in the first (second) row. The post-fit VBS EW ZV signal is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 4:
Distributions of MZV for the data, and the post-fit backgrounds (stacked histograms), in the SRs of the boosted b-tag (left) and the boosted b-veto (right) channels. The template for one signal hypothesis is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 4-a:
Distributions of MZV for the data, and the post-fit backgrounds (stacked histograms), in the SRs of the boosted b-tag (left) and the boosted b-veto (right) channels. The template for one signal hypothesis is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 4-b:
Distributions of MZV for the data, and the post-fit backgrounds (stacked histograms), in the SRs of the boosted b-tag (left) and the boosted b-veto (right) channels. The template for one signal hypothesis is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 5:
Distributions of MWV for the data, and the post-fit backgrounds (stacked histograms), in the SRs of the electron (left) and the muon (right) channels. The template for one signal hypothesis is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 5-a:
Distributions of MWV for the data, and the post-fit backgrounds (stacked histograms), in the SRs of the electron (left) and the muon (right) channels. The template for one signal hypothesis is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.

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Figure 5-b:
Distributions of MWV for the data, and the post-fit backgrounds (stacked histograms), in the SRs of the electron (left) and the muon (right) channels. The template for one signal hypothesis is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panel shows ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the middle panels indicates the systematic component of the post-fit background uncertainty.
Tables

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Table 1:
Definitions of the SRs and the CRs for the VBS ZV analysis for both resolved and boosted categories.

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Table 2:
Variables used as input to the DNN for the resolved and boosted models in the two b-tagged categories. The variables used in each category are labeled by a number representing their rank in the model quantified according to the SHAP algorithm [76].

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Table 3:
The impact of each systematic uncertainty, together with the impact of the data statistical uncertainty, on the signal strength μ, as extracted from the fit to measure the EW ZV VBS signal with the DNN output distributions. Upper and lower uncertainties are given for the various sources. The theory uncertainty includes contributions from both the signal and backgrounds.

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Table 4:
Observed and expected 95% CL intervals on the parameters on the parameters of the quartic operators in WV and ZV channels. The last two columns show the observed and expected limits for the combination of the WV and ZV channels.
Summary
A study of the electroweak production of ZV (V=W, Z) boson pairs in semi-leptonic decays in association with two jets in proton-proton collisions at 13 TeV is performed. The analysis uses a sample of proton-proton collisions recorded by the CMS experiment at the CERN LHC in 2106--2018, corresponding to an integrated luminosity of 138 fb1. The cross section is measured in a fiducial region characterized by large invariant mass and pseudorapidity gap of the two forward jets using feed-forward deep neural network (DNN) discriminators. The measured cross section for electroweak ZV VBS process is 0.63 +0.530.51 times the standard model prediction. The ZV and WV semi-leptonic events are combined and constraints are also reported on coefficients of new operators from an effective field theory sensitive to an anomalous electroweak production of WW, WZ, and ZZ boson pairs in association with two jets. Stringent limits are set on anomalous quartic gauge couplings in terms of dimension-8 operators.
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