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| CMS-PAS-SUS-23-018 | ||
| Search for DM in association with b-quark and lepton pairs | ||
| CMS Collaboration | ||
| 20 July 2024 | ||
| Abstract: A search is performed for dark matter produced in association with bottom quark and lepton pairs in data collected by the CMS detector at the LHC, corresponding to 138 fb$ ^{-1} $ of proton-proton collisions at a center-of-mass energy of 13 TeV. The analysis explores for the first time at the LHC the associated production of a bottom quark-antiquark pair and a new neutral Higgs boson that subsequently decays into a Z boson and a pseudoscalar, where the latter acts as dark matter mediator in the context of the 2HDM+$ a $ model. The analysis probes final states with a pair of same-flavor leptons arising in decays of Z bosons, which tend to be produced in opposite directions with respect to the dark matter particles that originate from the decay of the pseudoscalar. The resulting imbalance in transverse momentum in combination with observables related to the lepton pair is exploited in this search. Furthermore, we make use of novel multivariate techniques that target the wide range of kinematic scenarios occurring for the various mass configurations. | ||
| Links: CDS record (PDF) ; Physics Briefing ; CADI line (restricted) ; | ||
| Figures | |
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Figure 1:
Example graph for heavy pseudoscalar mediator production decaying into Dark Matter particles, in association with $ \mathrm{Z}(\to \mathrm{l}\bar{\mathrm{l}}) \mathrm{b}\overline{\mathrm{b}} $ |
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Figure 2:
Signal and control regions definition. All requirements are on top of the baseline selection. |
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Figure 3:
The distribution of the effective missing transverse momentum ($ p_{\mathrm{T}}^\text{miss} $) computed for each process as described in the text is shown for each CR defined. A comparison between the predicted shape in simulation and the observed distribution in data is presented for the DY (upper left), $ {\mathrm{t}\overline{\mathrm{t}}} $ (upper right), WZ (lower left), and ZZ (lower right) control regions after performing a B-only fit simultaneously across all CRs. With the exception of DY CR, where by definition a hard cut at $ p_{\mathrm{T}}^\text{miss} = $ 140 GeV exists, in all other cases the last bin includes the overflow. The lower panel shows the post-fit values and uncertainties of the ratio between the observed data and the predicted SM background. The various background processes are represented with color-filled histograms, with the color as indicated in the legend for each case. The data points are shown as black dots with vertical and horizontal error bars, in this case comprising the total collected data in Run 2. |
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Figure 3-a:
The distribution of the effective missing transverse momentum ($ p_{\mathrm{T}}^\text{miss} $) computed for each process as described in the text is shown for each CR defined. A comparison between the predicted shape in simulation and the observed distribution in data is presented for the DY (upper left), $ {\mathrm{t}\overline{\mathrm{t}}} $ (upper right), WZ (lower left), and ZZ (lower right) control regions after performing a B-only fit simultaneously across all CRs. With the exception of DY CR, where by definition a hard cut at $ p_{\mathrm{T}}^\text{miss} = $ 140 GeV exists, in all other cases the last bin includes the overflow. The lower panel shows the post-fit values and uncertainties of the ratio between the observed data and the predicted SM background. The various background processes are represented with color-filled histograms, with the color as indicated in the legend for each case. The data points are shown as black dots with vertical and horizontal error bars, in this case comprising the total collected data in Run 2. |
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Figure 3-b:
The distribution of the effective missing transverse momentum ($ p_{\mathrm{T}}^\text{miss} $) computed for each process as described in the text is shown for each CR defined. A comparison between the predicted shape in simulation and the observed distribution in data is presented for the DY (upper left), $ {\mathrm{t}\overline{\mathrm{t}}} $ (upper right), WZ (lower left), and ZZ (lower right) control regions after performing a B-only fit simultaneously across all CRs. With the exception of DY CR, where by definition a hard cut at $ p_{\mathrm{T}}^\text{miss} = $ 140 GeV exists, in all other cases the last bin includes the overflow. The lower panel shows the post-fit values and uncertainties of the ratio between the observed data and the predicted SM background. The various background processes are represented with color-filled histograms, with the color as indicated in the legend for each case. The data points are shown as black dots with vertical and horizontal error bars, in this case comprising the total collected data in Run 2. |
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Figure 3-c:
The distribution of the effective missing transverse momentum ($ p_{\mathrm{T}}^\text{miss} $) computed for each process as described in the text is shown for each CR defined. A comparison between the predicted shape in simulation and the observed distribution in data is presented for the DY (upper left), $ {\mathrm{t}\overline{\mathrm{t}}} $ (upper right), WZ (lower left), and ZZ (lower right) control regions after performing a B-only fit simultaneously across all CRs. With the exception of DY CR, where by definition a hard cut at $ p_{\mathrm{T}}^\text{miss} = $ 140 GeV exists, in all other cases the last bin includes the overflow. The lower panel shows the post-fit values and uncertainties of the ratio between the observed data and the predicted SM background. The various background processes are represented with color-filled histograms, with the color as indicated in the legend for each case. The data points are shown as black dots with vertical and horizontal error bars, in this case comprising the total collected data in Run 2. |
png pdf |
Figure 3-d:
The distribution of the effective missing transverse momentum ($ p_{\mathrm{T}}^\text{miss} $) computed for each process as described in the text is shown for each CR defined. A comparison between the predicted shape in simulation and the observed distribution in data is presented for the DY (upper left), $ {\mathrm{t}\overline{\mathrm{t}}} $ (upper right), WZ (lower left), and ZZ (lower right) control regions after performing a B-only fit simultaneously across all CRs. With the exception of DY CR, where by definition a hard cut at $ p_{\mathrm{T}}^\text{miss} = $ 140 GeV exists, in all other cases the last bin includes the overflow. The lower panel shows the post-fit values and uncertainties of the ratio between the observed data and the predicted SM background. The various background processes are represented with color-filled histograms, with the color as indicated in the legend for each case. The data points are shown as black dots with vertical and horizontal error bars, in this case comprising the total collected data in Run 2. |
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Figure 4:
The distribution of the MLP4 discriminator is shown for each CR defined. A comparison between the simulation prediction and the observed distribution in data is presented for the DY (upper left), $ {\mathrm{t}\overline{\mathrm{t}}} $ (upper right), WZ (lower left), and ZZ (lower right) control regions after performing a B-only fit simultaneously across all CRs. The X-axis labels indicate the range of bins from the intended SR definition (Section 5.3) that have been merged into a single bin for a given CR due to statistical considerations. The lower panel shows the post-fit values and uncertainties of the ratio between the observed data and the predicted SM background. The various background processes are represented with color-filled histograms, with the color as indicated in the legend for each case. The data points are shown as black dots with vertical and horizontal error bars, in this case comprising the total collected data in Run 2. |
png pdf |
Figure 4-a:
The distribution of the MLP4 discriminator is shown for each CR defined. A comparison between the simulation prediction and the observed distribution in data is presented for the DY (upper left), $ {\mathrm{t}\overline{\mathrm{t}}} $ (upper right), WZ (lower left), and ZZ (lower right) control regions after performing a B-only fit simultaneously across all CRs. The X-axis labels indicate the range of bins from the intended SR definition (Section 5.3) that have been merged into a single bin for a given CR due to statistical considerations. The lower panel shows the post-fit values and uncertainties of the ratio between the observed data and the predicted SM background. The various background processes are represented with color-filled histograms, with the color as indicated in the legend for each case. The data points are shown as black dots with vertical and horizontal error bars, in this case comprising the total collected data in Run 2. |
png pdf |
Figure 4-b:
The distribution of the MLP4 discriminator is shown for each CR defined. A comparison between the simulation prediction and the observed distribution in data is presented for the DY (upper left), $ {\mathrm{t}\overline{\mathrm{t}}} $ (upper right), WZ (lower left), and ZZ (lower right) control regions after performing a B-only fit simultaneously across all CRs. The X-axis labels indicate the range of bins from the intended SR definition (Section 5.3) that have been merged into a single bin for a given CR due to statistical considerations. The lower panel shows the post-fit values and uncertainties of the ratio between the observed data and the predicted SM background. The various background processes are represented with color-filled histograms, with the color as indicated in the legend for each case. The data points are shown as black dots with vertical and horizontal error bars, in this case comprising the total collected data in Run 2. |
png pdf |
Figure 4-c:
The distribution of the MLP4 discriminator is shown for each CR defined. A comparison between the simulation prediction and the observed distribution in data is presented for the DY (upper left), $ {\mathrm{t}\overline{\mathrm{t}}} $ (upper right), WZ (lower left), and ZZ (lower right) control regions after performing a B-only fit simultaneously across all CRs. The X-axis labels indicate the range of bins from the intended SR definition (Section 5.3) that have been merged into a single bin for a given CR due to statistical considerations. The lower panel shows the post-fit values and uncertainties of the ratio between the observed data and the predicted SM background. The various background processes are represented with color-filled histograms, with the color as indicated in the legend for each case. The data points are shown as black dots with vertical and horizontal error bars, in this case comprising the total collected data in Run 2. |
png pdf |
Figure 4-d:
The distribution of the MLP4 discriminator is shown for each CR defined. A comparison between the simulation prediction and the observed distribution in data is presented for the DY (upper left), $ {\mathrm{t}\overline{\mathrm{t}}} $ (upper right), WZ (lower left), and ZZ (lower right) control regions after performing a B-only fit simultaneously across all CRs. The X-axis labels indicate the range of bins from the intended SR definition (Section 5.3) that have been merged into a single bin for a given CR due to statistical considerations. The lower panel shows the post-fit values and uncertainties of the ratio between the observed data and the predicted SM background. The various background processes are represented with color-filled histograms, with the color as indicated in the legend for each case. The data points are shown as black dots with vertical and horizontal error bars, in this case comprising the total collected data in Run 2. |
png pdf |
Figure 5:
Main statistical discriminant of the analysis used to extract the signal. The left side of the upper panel (divided by a vertical greyish dotted line) shows the four CRs defined to estimate the normalization of the main background processes entering the signal region, whereas the right side of the upper panel shows the full MLP spectrum (seventeen bins) in the SR used to ultimately discriminate between signal and background. The lower panel shows the post-fit values and uncertainties of the ratio between the observed data and the predicted SM background. The various background processes are represented with color-filled histograms, with the color as indicated in the legend for each case. The data points are shown as black dots with vertical and horizontal error bars, while the signal scenarios under consideration are represented with a dashed-dotted line. The benchmark signal cross section is set to 0.05 pb for proper visualization purposes. The figure comprises the full combination of all search channels and categories for the total collected data in Run 2. |
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Figure 6:
Expected upper limits at 95% CL on the product of the cross section and branching fraction ($ \sigma \times B $) as specified in the text on the signal process here studied. The dependence of the limits on the pair $ (m_{\mathrm{H}},m_{\mathrm{a}}) $ has been accommodated into various 1D projections for a fixed value of $ m_{\mathrm{H}} $, where the corresponding limits have been scaled by an appropriate factor to easy the visualization of those. The y-axis contains the obtained cross section upper limit for the various combinations, whereas the x-axis exhibits the dependence on the mass of the pseudoscalar. The dashed line corresponds to the central expected limits, while the green and yellow bands indicate the regions that contain 68% and 95% of the distribution of the expected limits. |
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Figure 7:
Excluded regions on the parameter phase space for the 2HDM+$ a $ model. The solid blue line encompasses the central expected excluded region for all the various projections, while the red-dotted lines represent the 95% CL coverage of the central contour. Projections are presented for the $ m_{\mathrm{H}} $-vs-$ m_{\mathrm{a}} $ plane (upper left), $ m_{\mathrm{H}} $-vs-$ \tan\beta $ plane (upper right), $ m_{\mathrm{a}} $-vs-$ \sin\theta $ plane (lower left), and $ \tan\beta $-vs-$ \sin\theta $ plane (lower right), for fixed values of the corresponding non-varied parameters as in Eq. 1. The olive green band represents the allowed phase-space values for each projection as estimated by assuming $ \langle \sigma v \rangle = $ (2-4) $\times$ 10$^{-26}$ cm$^{3}$/$s$, which covers a range around the central value required by the observed DM relic. The cases where this curve is not visible in the figures correspond to the scenario where the preferable values of $ \tan\beta $ for this range of $ \langle \sigma v \rangle $ fall beyond the threshold ($ \tan\beta > $ 25) depicted in the projections. |
png pdf |
Figure 7-a:
Excluded regions on the parameter phase space for the 2HDM+$ a $ model. The solid blue line encompasses the central expected excluded region for all the various projections, while the red-dotted lines represent the 95% CL coverage of the central contour. Projections are presented for the $ m_{\mathrm{H}} $-vs-$ m_{\mathrm{a}} $ plane (upper left), $ m_{\mathrm{H}} $-vs-$ \tan\beta $ plane (upper right), $ m_{\mathrm{a}} $-vs-$ \sin\theta $ plane (lower left), and $ \tan\beta $-vs-$ \sin\theta $ plane (lower right), for fixed values of the corresponding non-varied parameters as in Eq. 1. The olive green band represents the allowed phase-space values for each projection as estimated by assuming $ \langle \sigma v \rangle = $ (2-4) $\times$ 10$^{-26}$ cm$^{3}$/$s$, which covers a range around the central value required by the observed DM relic. The cases where this curve is not visible in the figures correspond to the scenario where the preferable values of $ \tan\beta $ for this range of $ \langle \sigma v \rangle $ fall beyond the threshold ($ \tan\beta > $ 25) depicted in the projections. |
png pdf |
Figure 7-b:
Excluded regions on the parameter phase space for the 2HDM+$ a $ model. The solid blue line encompasses the central expected excluded region for all the various projections, while the red-dotted lines represent the 95% CL coverage of the central contour. Projections are presented for the $ m_{\mathrm{H}} $-vs-$ m_{\mathrm{a}} $ plane (upper left), $ m_{\mathrm{H}} $-vs-$ \tan\beta $ plane (upper right), $ m_{\mathrm{a}} $-vs-$ \sin\theta $ plane (lower left), and $ \tan\beta $-vs-$ \sin\theta $ plane (lower right), for fixed values of the corresponding non-varied parameters as in Eq. 1. The olive green band represents the allowed phase-space values for each projection as estimated by assuming $ \langle \sigma v \rangle = $ (2-4) $\times$ 10$^{-26}$ cm$^{3}$/$s$, which covers a range around the central value required by the observed DM relic. The cases where this curve is not visible in the figures correspond to the scenario where the preferable values of $ \tan\beta $ for this range of $ \langle \sigma v \rangle $ fall beyond the threshold ($ \tan\beta > $ 25) depicted in the projections. |
png pdf |
Figure 7-c:
Excluded regions on the parameter phase space for the 2HDM+$ a $ model. The solid blue line encompasses the central expected excluded region for all the various projections, while the red-dotted lines represent the 95% CL coverage of the central contour. Projections are presented for the $ m_{\mathrm{H}} $-vs-$ m_{\mathrm{a}} $ plane (upper left), $ m_{\mathrm{H}} $-vs-$ \tan\beta $ plane (upper right), $ m_{\mathrm{a}} $-vs-$ \sin\theta $ plane (lower left), and $ \tan\beta $-vs-$ \sin\theta $ plane (lower right), for fixed values of the corresponding non-varied parameters as in Eq. 1. The olive green band represents the allowed phase-space values for each projection as estimated by assuming $ \langle \sigma v \rangle = $ (2-4) $\times$ 10$^{-26}$ cm$^{3}$/$s$, which covers a range around the central value required by the observed DM relic. The cases where this curve is not visible in the figures correspond to the scenario where the preferable values of $ \tan\beta $ for this range of $ \langle \sigma v \rangle $ fall beyond the threshold ($ \tan\beta > $ 25) depicted in the projections. |
png pdf |
Figure 7-d:
Excluded regions on the parameter phase space for the 2HDM+$ a $ model. The solid blue line encompasses the central expected excluded region for all the various projections, while the red-dotted lines represent the 95% CL coverage of the central contour. Projections are presented for the $ m_{\mathrm{H}} $-vs-$ m_{\mathrm{a}} $ plane (upper left), $ m_{\mathrm{H}} $-vs-$ \tan\beta $ plane (upper right), $ m_{\mathrm{a}} $-vs-$ \sin\theta $ plane (lower left), and $ \tan\beta $-vs-$ \sin\theta $ plane (lower right), for fixed values of the corresponding non-varied parameters as in Eq. 1. The olive green band represents the allowed phase-space values for each projection as estimated by assuming $ \langle \sigma v \rangle = $ (2-4) $\times$ 10$^{-26}$ cm$^{3}$/$s$, which covers a range around the central value required by the observed DM relic. The cases where this curve is not visible in the figures correspond to the scenario where the preferable values of $ \tan\beta $ for this range of $ \langle \sigma v \rangle $ fall beyond the threshold ($ \tan\beta > $ 25) depicted in the projections. |
| Summary |
| The first dedicated DM search performed in the $ \mathrm{b}\overline{\mathrm{b}}\mathrm{H} \rightarrow \mathrm{Z}\mathrm{a} $ channel is presented. A data set of proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb$ ^{-1} $ is analyzed. The analysis is relevant in the context of non-minimal DM models such as the 2HDM+$ a $, where the mediator can couple to other scalar states in the sector and can be produced in decays of those. The presence of b jets makes this search suitable to probe those scenarios in which the production of scalar in association with b-quarks is enhanced. In the context of the 2HDM+$ a $, those scenarios are favored by cosmological observations, which could indicate a large amount of DM particles being annihilated through an s-channel process producing a substantial number of b-quarks. The analysis exploits the Z boson decay into a pair of muons or electrons, thus benefiting from a clean signature and high efficiency in the reconstruction of the main physics object and of the event triggering. A powerful statistical discriminator between the varied signal topologies and the predominant backgrounds is deployed by making use of sophisticated machine learning techniques. The multivariate classifier is trained to reach a high level of discrimination across a broad range of kinematic variations that arise from the different configurations in which the Z boson and the DM mediator are produced. In order to better estimate the normalization of the main SM processes entering the selection and thus contributing to the background events, a set of dedicated CRs has been devised. These CRs are fitted simultaneously with the SR, which allows, on top of correcting the normalization of the key backgrounds, to properly correlate and constrain the dominant systematic uncertainties. Aside from estimating the normalization using a data-driven approach, also the shape of the largest background is corrected using a subsidiary measurement to improve the modeling of one of the key variables. Moreover, state-of-the-art theoretical calculations are also included in the shape modeling of the second-largest background by making use of event-by-event reweighing techniques. The results are presented in terms of model-independent limits on the signal process cross section, assuming the validity of the narrow width approximation, and as constraints on the parameter phase space of the specific 2HDM+$ a $ case. Exclusion regions in the 2D planes formed by four relevant 2HDM+$ a $ parameters are shown, while at the same time, the results are compared with expectations for this model in the context of cosmological predictions. |
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