CMS-PAS-B2G-24-015

CMS-PAS-B2G-24-015
Search for resonances decaying to a Higgs boson in the bb final state and an anomalous jet
CMS Collaboration
28 March 2025

Abstract: This note presents an analysis searching for new physics through the process where a new massive particle, X, decays into a Higgs boson and a second particle, Y. The Higgs boson subsequently decays into a pair of b-quarks and the decay products of Y are assumed to produce a non-QCD-like, e.g. anomalous, jet. In the benchmark process, Y decays into $\text W^+ \text W^-$ forming one large-area jet. A second benchmark process is also considered, where Y is a hadronically decaying top quark, originating from a vector-like quark decaying into a top quark and a Higgs boson. CMS data recorded at a centre-of-mass energy of 13 TeV in 2016-2018 and corresponding to 138 fb $^{-1}$ are analysed. In this analysis, the identification of the Y particle is enhanced by computing the anomaly score of its candidate jet using an autoencoder, allowing the simultaneous search for multiple Y decay modes with a single analysis. No significant excesses are observed and upper limits on the signal cross section for various masses of X and Y, at 95% confidence level, are placed.
Links: CDS record (PDF) ; CADI line (restricted) ;

Figures	Summary	References	CMS Publications

Figures
png pdf	Figure 1: An illustration showing the signal targeted by this analysis. The final state consists of a boosted jet originated from H decaying to $\mathrm{b} \overline{\mathrm{b}}$ and another boosted jet originating from the decay of a second particle, $\mathrm{Y}$ .
png pdf	Figure 2: The $M_\mathrm{jj}$ (left) and $M_\mathrm{j}^{\mathrm{Y}}$ (right) projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the CR. Pass (upper) and fail (lower) control region categories are shown. The high level of agreement between the model and the data in the fail region is due to the nature of the background estimate. The lower panels show the ``Pull'' defined as (observed events $-$ expected events) $/\sqrt{\smash[b]{\sigma_{\text{obs}}^{2} + \sigma_{\text{exp}}^{2}}}$ , where $\sigma_{\text{obs}}$ and $\sigma_{\text{exp}}$ are the total uncertainties in the observation and the background estimation, respectively.
png pdf	Figure 2-a: The $M_\mathrm{jj}$ (left) and $M_\mathrm{j}^{\mathrm{Y}}$ (right) projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the CR. Pass (upper) and fail (lower) control region categories are shown. The high level of agreement between the model and the data in the fail region is due to the nature of the background estimate. The lower panels show the ``Pull'' defined as (observed events $-$ expected events) $/\sqrt{\smash[b]{\sigma_{\text{obs}}^{2} + \sigma_{\text{exp}}^{2}}}$ , where $\sigma_{\text{obs}}$ and $\sigma_{\text{exp}}$ are the total uncertainties in the observation and the background estimation, respectively.
png pdf	Figure 2-b: The $M_\mathrm{jj}$ (left) and $M_\mathrm{j}^{\mathrm{Y}}$ (right) projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the CR. Pass (upper) and fail (lower) control region categories are shown. The high level of agreement between the model and the data in the fail region is due to the nature of the background estimate. The lower panels show the ``Pull'' defined as (observed events $-$ expected events) $/\sqrt{\smash[b]{\sigma_{\text{obs}}^{2} + \sigma_{\text{exp}}^{2}}}$ , where $\sigma_{\text{obs}}$ and $\sigma_{\text{exp}}$ are the total uncertainties in the observation and the background estimation, respectively.
png pdf	Figure 2-c: The $M_\mathrm{jj}$ (left) and $M_\mathrm{j}^{\mathrm{Y}}$ (right) projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the CR. Pass (upper) and fail (lower) control region categories are shown. The high level of agreement between the model and the data in the fail region is due to the nature of the background estimate. The lower panels show the ``Pull'' defined as (observed events $-$ expected events) $/\sqrt{\smash[b]{\sigma_{\text{obs}}^{2} + \sigma_{\text{exp}}^{2}}}$ , where $\sigma_{\text{obs}}$ and $\sigma_{\text{exp}}$ are the total uncertainties in the observation and the background estimation, respectively.
png pdf	Figure 2-d: The $M_\mathrm{jj}$ (left) and $M_\mathrm{j}^{\mathrm{Y}}$ (right) projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the CR. Pass (upper) and fail (lower) control region categories are shown. The high level of agreement between the model and the data in the fail region is due to the nature of the background estimate. The lower panels show the ``Pull'' defined as (observed events $-$ expected events) $/\sqrt{\smash[b]{\sigma_{\text{obs}}^{2} + \sigma_{\text{exp}}^{2}}}$ , where $\sigma_{\text{obs}}$ and $\sigma_{\text{exp}}$ are the total uncertainties in the observation and the background estimation, respectively.
png pdf	Figure 3: The $M_\mathrm{jj}$ (left) and $M_\mathrm{j}^{\mathrm{Y}}$ (right) projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the SR. Pass (upper) and fail (lower) control region categories are shown. The high level of agreement between the model and the data in the fail region is due to the nature of the background estimate.
png pdf	Figure 3-a: The $M_\mathrm{jj}$ (left) and $M_\mathrm{j}^{\mathrm{Y}}$ (right) projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the SR. Pass (upper) and fail (lower) control region categories are shown. The high level of agreement between the model and the data in the fail region is due to the nature of the background estimate.
png pdf	Figure 3-b: The $M_\mathrm{jj}$ (left) and $M_\mathrm{j}^{\mathrm{Y}}$ (right) projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the SR. Pass (upper) and fail (lower) control region categories are shown. The high level of agreement between the model and the data in the fail region is due to the nature of the background estimate.
png pdf	Figure 3-c: The $M_\mathrm{jj}$ (left) and $M_\mathrm{j}^{\mathrm{Y}}$ (right) projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the SR. Pass (upper) and fail (lower) control region categories are shown. The high level of agreement between the model and the data in the fail region is due to the nature of the background estimate.
png pdf	Figure 3-d: The $M_\mathrm{jj}$ (left) and $M_\mathrm{j}^{\mathrm{Y}}$ (right) projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the SR. Pass (upper) and fail (lower) control region categories are shown. The high level of agreement between the model and the data in the fail region is due to the nature of the background estimate.
png pdf	Figure 4: The expected (upper) and observed (lower) 95% confidence level upper limits on $\sigma(\mathrm{p}\mathrm{p} \to {\mathrm{X}\to(\mathrm{H}\to\mathrm{b} \overline{\mathrm{b}})(\mathrm{Y}\to\mathrm{W}\mathrm{W}\to4\mathrm{q})})$ for different values of $\mathrm{M}_\mathrm{X}$ and $\mathrm{M}_\mathrm{Y}$ . The limits have been evaluated in discrete steps corresponding to the centers of the boxes. The numbers in the boxes are given in fb.
png pdf	Figure 4-a: The expected (upper) and observed (lower) 95% confidence level upper limits on $\sigma(\mathrm{p}\mathrm{p} \to {\mathrm{X}\to(\mathrm{H}\to\mathrm{b} \overline{\mathrm{b}})(\mathrm{Y}\to\mathrm{W}\mathrm{W}\to4\mathrm{q})})$ for different values of $\mathrm{M}_\mathrm{X}$ and $\mathrm{M}_\mathrm{Y}$ . The limits have been evaluated in discrete steps corresponding to the centers of the boxes. The numbers in the boxes are given in fb.
png pdf	Figure 4-b: The expected (upper) and observed (lower) 95% confidence level upper limits on $\sigma(\mathrm{p}\mathrm{p} \to {\mathrm{X}\to(\mathrm{H}\to\mathrm{b} \overline{\mathrm{b}})(\mathrm{Y}\to\mathrm{W}\mathrm{W}\to4\mathrm{q})})$ for different values of $\mathrm{M}_\mathrm{X}$ and $\mathrm{M}_\mathrm{Y}$ . The limits have been evaluated in discrete steps corresponding to the centers of the boxes. The numbers in the boxes are given in fb.
png pdf	Figure 5: The median expected (dashed line) and observed (solid line) 95% confidence level upper limits on $\sigma(\mathrm{p}\mathrm{p} \to {\mathrm{X}\to(\mathrm{H}\to\mathrm{b} \overline{\mathrm{b}})(\mathrm{Y}\to\mathrm{b} \mathrm{q} \overline{\mathrm{q}})})$ for different values of $\mathrm{M}_\mathrm{X}$ . The inner (green) band and the outer (yellow) band indicate the regions containing 68% and 95%, respectively, of the distribution of limits expected under the background-only hypothesis.

Summary

A search for new physics through the process where a resonant particle decays into a Higgs boson and an additional particle

$\mathrm{Y}$ is presented. The Higgs boson subsequently decays into a pair of b-quarks, and both resultant particles are reconstructed as large-area jets in the Lorentz-boosted regime. H candidate jets are tagged using the ParticleNet tagger that is designed to recognize jets originating from a decay of a massive particle into

$\mathrm{b} \overline{\mathrm{b}}$ . The identification of the second particle is enhanced by computing the anomaly score of its candidate jet using an autoencoder, allowing the simultaneous search for multiple Y decay modes with a single analysis. The analysis considers two benchmark models. The main benchmark assumes

$\mathrm{Y} \to \mathrm{W}^+\mathrm{W}^-$ , with further hadronic decays of the W bosons. It is simulated for 42 different

$\mathrm{M}_\mathrm{X}$ and

$\mathrm{M}_\mathrm{Y}$ hypotheses. The largest local significance of 2.06

$\sigma$ is observed for

$\mathrm{M}_\mathrm{X}=$ 1600 GeV and

$\mathrm{M}_\mathrm{Y}=$ 90 GeV, with a

$p$ value of 0.019. This corresponds to a global significance of 0.13

$\sigma$ after accounting for the look-elsewhere effect. Exclusion limits, at 95% confidence level, are set in the 0.3--16 fb range, depending on the mass hypothesis. Exclusion limits are also placed on a second benchmark that assumes the

$\mathrm{Y} \to \mathrm{b} \mathrm{q} \overline{\mathrm{q}}$ decay mode, originating from a vector-like quark decaying into a top quark and a Higgs boson, with

$\mathrm{M}_\mathrm{X}$ ranging from 1400 to 3000 GeV while

$\mathrm{M}_\mathrm{Y}$ is set to the mass of the top quark.

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