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| CMS-PAS-SUS-16-034 | ||
| Search for new physics in final states with two opposite-sign, same-flavor leptons, jets, and missing transverse momentum in pp collisions at $\sqrt{s}= $ 13 TeV | ||
| CMS Collaboration | ||
| March 2017 | ||
| Abstract: A search is presented for physics beyond the standard model in final states with two opposite-sign, same-flavor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 35.9 fb$^{-1}$ of proton-proton collisions at $\sqrt{s}= $ 13 TeV collected with the CMS detector at the LHC in 2016. The analysis uses the invariant mass of the lepton pair, searching for a kinematic edge or a resonant-like excess compatible with the Z boson mass. The search for a kinematic edge targets strong production while the resonance search targets both strongly and electroweakly produced new physics. Both search modes use several event categories, based on observables related to the lepton pair and the hadronic system, in order to increase the sensitivity to new physics. A fit is also employed to search for a possible kinematic edge position in the strong, non-resonant search. The observations in all signal regions are consistent with the expectations from the standard model, and the results are interpreted in the context of simplified models of supersymmetry. | ||
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Links:
CDS record (PDF) ;
inSPIRE record ;
CADI line (restricted) ;
These preliminary results are superseded in this paper, JHEP 03 (2018) 076. The superseded preliminary plots can be found here. |
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| Figures & Tables | Summary | Additional Figures & Tables | References | CMS Publications |
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Additional information on efficiencies needed for reinterpretation of these results are available here.
Additional technical material for CMS speakers can be found here. |
| Figures | |
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Figure 1:
Diagrams for models with decays containing at least one dilepton pair stemming from a Z decay are shown. The gluino GMSB model targeted by the strong on-Z search is shown in the left. The right diagram shows the chargino-neutralino production model resulting in a final state with a Z boson, a W boson, and two LSPs. In the gluino GMSB model, $\tilde{\mathrm {G}}$ denotes the massless gravitino. |
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Figure 1-a:
Diagram for the gluino GMSB model targeted by the strong on-Z search, where $\tilde{\mathrm {G}}$ denotes the massless gravitino. |
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Figure 1-b:
The diagram shows the chargino-neutralino production model resulting in a final state with a Z boson, a W boson, and two LSPs. |
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Figure 2:
A diagram showing a model in which bottom squarks are pair produced with subsequent decays that contain at least one dilepton pair. This model features a characteristic edge in the ${m_{\ell \ell }}$ spectrum given approximately by the mass difference of the ${{\tilde{\chi }^0_2}}$ and ${{\tilde{\chi }^0_1}} $. |
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Figure 3:
The ${E_{\mathrm {T}}^{\text {miss}}} $ distribution is shown for data compared to the background prediction in the strong on-Z signal regions with $ {N_{\text {b-jets}}} = $ 0 (left) and $ {N_{\text {b-jets}}} \geq $ 1 (right). The rows show SRA (top), SRB (middle), and SRC (bottom). The $ {E_{\mathrm {T}}^{\text {miss}}} $ template prediction for each signal region is normalized to the first bin of each distribution, and therefore the prediction agrees with the data by construction. |
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Figure 3-a:
The ${E_{\mathrm {T}}^{\text {miss}}} $ distribution is shown for data compared to the background prediction in the strong on-Z signal regions with $ {N_{\text {b-jets}}} = $ 0 for SRA. The $ {E_{\mathrm {T}}^{\text {miss}}} $ template prediction for each signal region is normalized to the first bin of each distribution, and therefore the prediction agrees with the data by construction. |
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Figure 3-b:
The ${E_{\mathrm {T}}^{\text {miss}}} $ distribution is shown for data compared to the background prediction in the strong on-Z signal regions with $ {N_{\text {b-jets}}} \geq $ 1 for SRA. The $ {E_{\mathrm {T}}^{\text {miss}}} $ template prediction for each signal region is normalized to the first bin of each distribution, and therefore the prediction agrees with the data by construction. |
png pdf |
Figure 3-c:
The ${E_{\mathrm {T}}^{\text {miss}}} $ distribution is shown for data compared to the background prediction in the strong on-Z signal regions with $ {N_{\text {b-jets}}} = $ 0 for SRB. The $ {E_{\mathrm {T}}^{\text {miss}}} $ template prediction for each signal region is normalized to the first bin of each distribution, and therefore the prediction agrees with the data by construction. |
png pdf |
Figure 3-d:
The ${E_{\mathrm {T}}^{\text {miss}}} $ distribution is shown for data compared to the background prediction in the strong on-Z signal regions with $ {N_{\text {b-jets}}} \geq $ 1 for SRB. The $ {E_{\mathrm {T}}^{\text {miss}}} $ template prediction for each signal region is normalized to the first bin of each distribution, and therefore the prediction agrees with the data by construction. |
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Figure 3-e:
The ${E_{\mathrm {T}}^{\text {miss}}} $ distribution is shown for data compared to the background prediction in the strong on-Z signal regions with $ {N_{\text {b-jets}}} = $ 0 for SRC. The $ {E_{\mathrm {T}}^{\text {miss}}} $ template prediction for each signal region is normalized to the first bin of each distribution, and therefore the prediction agrees with the data by construction. |
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Figure 3-f:
The ${E_{\mathrm {T}}^{\text {miss}}} $ distribution is shown for data compared to the background prediction in the strong on-Z signal regions with $ {N_{\text {b-jets}}} \geq $ 1 for SRC. The $ {E_{\mathrm {T}}^{\text {miss}}} $ template prediction for each signal region is normalized to the first bin of each distribution, and therefore the prediction agrees with the data by construction. |
png pdf |
Figure 4:
The $ {E_{\mathrm {T}}^{\text {miss}}} $ distribution is shown for data compared to the background prediction in the electroweak on-Z WZ/ZZ (left), and HZ (right) signal regions. The $ {E_{\mathrm {T}}^{\text {miss}}} $ template prediction for each signal region is normalized to the first bin of each distribution, and therefore the prediction agrees with the data by construction. |
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Figure 4-a:
The $ {E_{\mathrm {T}}^{\text {miss}}} $ distribution is shown for data compared to the background prediction in the electroweak on-Z WZ/ZZ signal region. The $ {E_{\mathrm {T}}^{\text {miss}}} $ template prediction for each signal region is normalized to the first bin of each distribution, and therefore the prediction agrees with the data by construction. |
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Figure 4-b:
The $ {E_{\mathrm {T}}^{\text {miss}}} $ distribution is shown for data compared to the background prediction in the electroweak HZ signal region. The $ {E_{\mathrm {T}}^{\text {miss}}} $ template prediction for each signal region is normalized to the first bin of each distribution, and therefore the prediction agrees with the data by construction. |
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Figure 5:
Results of the counting experiment of the edge search. For each signal region, the number of observed events, shown as black data points, is compared to the total background estimate, shown as a blue line with a blue uncertainty band. The non flavor symmetric background component from instrumental $E_{\text {T}}^{\text {miss}}$ is indicated as a green area while the non flavor symmetric background with neutrinos is shown as a violet area. |
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Figure 6:
Fit of the dilepton mass distributions to the signal-plus-background hypothesis in the baseline signal region, projected on the same-flavor (left) and opposite-flavor (right) event samples. The fit shape is shown as a blue, solid line. The individual fit components are indicated by dashed lines. The flavor-symmetric (FS) background is shown with a black dashed line. The Drell-Yan (DY) background is displayed with a purple dashed line. The extracted signal component is displayed with a red dashed line. |
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Figure 6-a:
Fit of the dilepton mass distributions to the signal-plus-background hypothesis in the baseline signal region, projected on the same-flavor event sample. The fit shape is shown as a blue, solid line. The individual fit components are indicated by dashed lines. The flavor-symmetric (FS) background is shown with a black dashed line. The Drell-Yan (DY) background is displayed with a purple dashed line. The extracted signal component is displayed with a red dashed line. |
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Figure 6-b:
Fit of the dilepton mass distributions to the signal-plus-background hypothesis in the baseline signal region, projected on the opposite-flavor event sample. The fit shape is shown as a blue, solid line. |
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Figure 7:
Cross section upper limits and exclusions contours at 95% CL obtained from the results of the on-Z search interpreted in the gluino GMSB model. The region to the left of the red dotted (black solid) line shows the masses which are excluded by the expected (observed) limit. |
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Figure 8:
Cross section upper limits and exclusions contours at 95% CL obtained from the results of the on-Z search interpreted in the electroweak WZ model. The region to the left of the red dotted (black solid) line shows the masses which are excluded by the expected (observed) limit. |
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Figure 9:
Cross section upper limits and exclusion contours at 95% CL obtained from the results of the edge search interpreted in the slepton-edge model. The region to the left of the red dotted (black solid) line shows the masses which are excluded by the expected (observed) limit. |
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Figure 10:
The covariance (left) and correlation (right) matrices for the background predictions in the on-Z strong signal regions. Within each signal region, the individual $ {E_{\mathrm {T}}^{\text {miss}}} $ bins are shown in increasing order starting from 100 GeV. |
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Figure 10-a:
The covariance matrix for the background predictions in the on-Z strong signal regions. Within each signal region, the individual $ {E_{\mathrm {T}}^{\text {miss}}} $ bins are shown in increasing order starting from 100 GeV. |
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Figure 10-b:
The correlation matrix for the background predictions in the on-Z strong signal regions. Within each signal region, the individual $ {E_{\mathrm {T}}^{\text {miss}}} $ bins are shown in increasing order starting from 100 GeV. |
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Figure 11:
The covariance (left) and correlation (right) matrices for the background predictions in the on-Z electroweak signal regions. Within each signal region, the individual $ {E_{\mathrm {T}}^{\text {miss}}} $ bins are shown in increasing order starting from 100 GeV. |
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Figure 11-a:
The covariance matrix for the background predictions in the on-Z electroweak signal regions. Within each signal region, the individual $ {E_{\mathrm {T}}^{\text {miss}}} $ bins are shown in increasing order starting from 100 GeV. |
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Figure 11-b:
The correlation matrix for the background predictions in the on-Z electroweak signal regions. Within each signal region, the individual $ {E_{\mathrm {T}}^{\text {miss}}} $ bins are shown in increasing order starting from 100 GeV. |
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Figure 12:
The covariance (left) and correlation (right) matrices for the background predictions in the edge strong signal regions. |
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Figure 12-a:
The correlation matrix for the background predictions in the edge strong signal regions. |
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Figure 12-b:
The covariance matrix for the background predictions in the edge strong signal regions. |
| Tables | |
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Table 1:
Summary of all signal region selections. |
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Table 2:
Predicted and observed event yields are shown for the strong on-Z signal regions, for each region and ${E_{\mathrm {T}}^{\text {miss}}} $ bin defined in Table 1. The uncertainties shown include both statistical and systematic errors. |
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Table 3:
Predicted and observed event yields are shown for the electroweak on-Z signal regions, for each region and $ {E_{\mathrm {T}}^{\text {miss}}} $ bin defined in Table 1. The uncertainties shown include both statistical and systematic errors. |
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Table 4:
Results of the edge-search counting experiment for event yields in the signal regions. The statistical and systematic uncertainties are added in quadrature. |
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Table 5:
Results of the unbinned maximum likelihood fit for event yields in the signal region, including the DY and FS background components, along with the fitted signal contribution and edge position. The fitted value for $R_{\mathrm {SF/OF}}$ and the local and global signal significances are also given. The quoted uncertainties account for both statistical and systematic sources. |
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Table 6:
Systematic uncertainties taken into account for the signal yields and their typical values. |
| Summary |
|
A search for physics beyond the standard model has been presented in the opposite-sign, same-flavor lepton; jets; and $E_{\mathrm{T}}^{\text{miss}}$ final state using a data sample of pp collisions collected with the CMS detector in 2016 at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb$^{-1}$. Searches are performed for signals that either produce a kinematic edge in the dilepton invariant mass, or use dilepton systems whose invariant mass is compatible with the decay of a Z boson. Comparing the observation to estimates for SM backgrounds obtained from data control samples, and no statistically significant evidence for a signal has been observed. The search for strongly produced new physics containing an on-shell Z boson is interpreted in a model of gauge-mediated supersymmetry breaking, where the Z bosons are produced in decay chains initiated through gluino pair production. Gluino masses below 1500-1770 GeV have been excluded, depending on the neutralino mass, extending the previous exclusion limits derived from the previous CMS publication by almost 500 GeV. The electroweak on-Z search has been interpreted in a simplified model of chargino-neutralino production where the neutralino decays to a Z boson and the LSP, and the chargino decays to a W boson and the LSP. In this model, we probe chargino masses in the range 160-610 GeV. The search for a kinematic edge in the ${m_{\ell\ell}} $ distribution is interpreted in a simplified model based on bottom squark pair production, where dilepton mass edges are produced in decay chains containing the two lightest neutralinos and a slepton, where the branching ratios have been fixed to produce the desired topology. Bottom squark masses below 980 to 1200 GeV have been excluded, depending on the ${{\tilde{\chi}^0_2}} $ mass. These limits extend previous exclusion limits by 400-600 GeV depending also on the ${{\tilde{\chi}^0_2}} $ mass. |
| Additional Figures | |
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Additional Figure 1:
PDFs for the four input variables to the likelihood discriminant: ${E_{\mathrm {T}}^{\text {miss}}}$ (a), di-lepton ${p_{\mathrm {T}}}$ (b), $|\Delta \phi |$ between the leptons (c), and $\Sigma m_{\ell \text {b}}$ (d) for data in the OF region. |
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Additional Figure 1-a:
PDFs for one of the four input variables to the likelihood discriminant: ${E_{\mathrm {T}}^{\text {miss}}}$ for data in the OF region. |
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Additional Figure 1-b:
PDFs for one of the four input variables to the likelihood discriminant: di-lepton ${p_{\mathrm {T}}}$ for data in the OF region. |
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Additional Figure 1-c:
PDFs for one of the four input variables to the likelihood discriminant: $|\Delta \phi |$ between the leptons for data in the OF region. |
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Additional Figure 1-d:
PDFs for one of the four input variables to the likelihood discriminant: $\Sigma m_{\ell \text {b}}$ for data in the OF region. |
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Additional Figure 2:
Fitted shape for backgrounds containing a Z boson for dielectron events (a) and dimuon events (b). The fitted shape consists of an exponential (green) and a Breit-wigner convolved with a double-sided Crystal-Ball (red), whose sum (blue) describes the backgrounds containing a Z boson. |
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Additional Figure 2-a:
Fitted shape for backgrounds containing a Z boson for dielectron events. The fitted shape consists of an exponential (green) and a Breit-wigner convolved with a double-sided Crystal-Ball (red), whose sum (blue) describes the backgrounds containing a Z boson. |
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Additional Figure 2-b:
Fitted shape for backgrounds containing a Z boson for dimuon events. The fitted shape consists of an exponential (green) and a Breit-wigner convolved with a double-sided Crystal-Ball (red), whose sum (blue) describes the backgrounds containing a Z boson. |
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Additional Figure 3:
Result of fit in signal region for same-flavor (a) and opposite-flavor (b) events for data evaluating the null hypothesis. |
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Additional Figure 3-a:
Result of fit in signal region for same-flavor events for data evaluating the null hypothesis. |
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Additional Figure 3-b:
Result of fit in signal region for opposite-flavor events for data evaluating the null hypothesis. |
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Additional Figure 4:
${m_{\ell \ell }}$ distribution in the ${\mathrm{ t } {}\mathrm{ \bar{t} } }$ like (a) and non ${\mathrm{ t } {}\mathrm{ \bar{t} } }$ like (b) edge signal regions.The number of observed events, shown as black data points, is compared to the total background estimate, shown as a blue line with a blue uncertainty band. The non flavor symmetric background component from instrumental $E_{\text {T}}^{\text {miss}}$ is indicated as a green area while the non flavor symmetric background with neutrinos is shown as a violet area. |
png pdf |
Additional Figure 4-a:
${m_{\ell \ell }}$ distribution in the ${\mathrm{ t } {}\mathrm{ \bar{t} } }$ like (a) and non ${\mathrm{ t } {}\mathrm{ \bar{t} } }$ like (b) edge signal regions.The number of observed events, shown as black data points, is compared to the total background estimate, shown as a blue line with a blue uncertainty band. The non flavor symmetric background component from instrumental $E_{\text {T}}^{\text {miss}}$ is indicated as a green area while the non flavor symmetric background with neutrinos is shown as a violet area. |
png pdf |
Additional Figure 4-b:
${m_{\ell \ell }}$ distribution in the ${\mathrm{ t } {}\mathrm{ \bar{t} } }$ like (a) and non ${\mathrm{ t } {}\mathrm{ \bar{t} } }$ like (b) edge signal regions.The number of observed events, shown as black data points, is compared to the total background estimate, shown as a blue line with a blue uncertainty band. The non flavor symmetric background component from instrumental $E_{\text {T}}^{\text {miss}}$ is indicated as a green area while the non flavor symmetric background with neutrinos is shown as a violet area. |
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Additional Figure 5:
Two-dimensional distribution of the observed significances in the slepton-edge signal model. |
| Additional Tables | |
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Additional Table 1:
Cut flow table for the edge signal model for a mass point at $m_{\tilde{b}}=$ 900 GeV and $m_{\tilde{\chi }_{2}^{0}}=$ 150 GeV. Expected dilepton events refers to luminosity$\times $cross section$\times $branching ratio. |
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Additional Table 2:
Cut flow table for the edge signal model for a mass point at $m_{\tilde{b}}=$ 900 GeV and $m_{\tilde{\chi }_{2}^{0}}=$ 500 GeV. Expected dilepton events refers to luminosity$\times $cross section$\times $branching ratio. |
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Additional Table 3:
Cut flow table for the edge signal model for a mass point at $m_{\tilde{b}}=$ 1000 GeV and $m_{\tilde{\chi }_{2}^{0}}=$ 300 GeV. Expected dilepton events refers to luminosity$\times $cross section$\times $branching ratio. |
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Additional Table 4:
Cut flow table for the edge signal model for a mass point at $m_{\tilde{b}}=$ 1200 GeV and $m_{\tilde{\chi }_{2}^{0}}=$ 200 GeV. Expected dilepton events refers to luminosity$\times $cross section$\times $branching ratio. |
png pdf |
Additional Table 5:
Cut flow table for the edge signal model for a mass point at $m_{\tilde{b}}=$ 1200 GeV and $m_{\tilde{\chi }_{2}^{0}}=$ 1000 GeV. Expected dilepton events refers to luminosity$\times $cross section$\times $branching ratio. |
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Additional Table 6:
Cut flow table for the strong on-Z signal region selections for the gluino GMSB signal model with the mass of the gluino and the $\tilde{\chi }_{1}^{0}$ equal to 1400 and 700 GeV, respectively. The theoretical cross section for this signal is 25.3 fb and at least one Z boson was required to decay leptonically, for a branching fraction of 0.192. |
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Additional Table 7:
Cut flow table for the electroweak on-Z signal region selections for the WZ signal model with the mass of the chargino and the LSP equal to 550 and 200 GeV, respectively. The theoretical cross section for this signal is 30.2 fb and the Z boson was required to decay leptonically, for a branching fraction of 0.10. |
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The code for calculating the MT2 variable can be found here.
A macro for calculating the nll variable and the RooWorkSpace with the fitted pdfs used for the calculation is available here. |
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