CMS-PAS-TOP-22-007

CMS-PAS-TOP-22-007
Searches for violation of Lorentz invariance in $ \mathrm{t}\mathrm{\bar{t}} $ production using dilepton events in proton-proton collisions at $ \sqrt{s}= $ 13 TeV
CMS Collaboration
24 May 2023

Abstract: Violation of Lorentz invariance is searched for using top quark pair ($ \mathrm{t}\mathrm{\bar{t}} $) production in proton-proton collisions at the LHC, at a center-of-mass energy of $ \sqrt{s}= $ 13 TeV. Events containing one electron and one muon collected with the CMS detector are analyzed in a data sample corresponding to an integrated luminosity of 77.4 fb$ ^{-1} $. A measurement of the differential normalized cross section for $ \mathrm{t}\mathrm{\bar{t}} $ production as a function of sidereal time is performed. Potential violation of Lorentz invariance is introduced as an extension of the standard model (SM), with an effective field theory predicting the modulation of the $ \mathrm{t}\mathrm{\bar{t}} $ cross section with sidereal time. Bounds on Lorentz-violating couplings are extracted, and found to be compatible with Lorentz invariance with an absolute precision of 0.1 $ {-}$0.8%. This search can also be interpreted as a precision test of special relativity with top quarks, improving precision by two orders of magnitude over a previous such measurement.
Links: CDS record (PDF) ; CADI line (restricted) ;

Figures & Tables	Summary	Additional Figures	References	CMS Publications

Figures
png pdf	Figure 1: Distribution of the number of b jets in data and simulation, after the event selection, (left) in 2016 and (right) in 2017 samples. The error band includes statistical and systematic uncertainties of the predictions.
png pdf	Figure 1-a: Distribution of the number of b jets in data and simulation, after the event selection, (left) in 2016 and (right) in 2017 samples. The error band includes statistical and systematic uncertainties of the predictions.
png pdf	Figure 1-b: Distribution of the number of b jets in data and simulation, after the event selection, (left) in 2016 and (right) in 2017 samples. The error band includes statistical and systematic uncertainties of the predictions.
png pdf	Figure 2: Prefit (up) and postfit (down) distributions of the number of b jets in sidereal time bins, in 2016 and 2017 data. The uncertainty band reflects the statistical and systematic uncertainty in each bin, including correlations across bins.
png pdf	Figure 2-a: Prefit (up) and postfit (down) distributions of the number of b jets in sidereal time bins, in 2016 and 2017 data. The uncertainty band reflects the statistical and systematic uncertainty in each bin, including correlations across bins.
png pdf	Figure 2-b: Prefit (up) and postfit (down) distributions of the number of b jets in sidereal time bins, in 2016 and 2017 data. The uncertainty band reflects the statistical and systematic uncertainty in each bin, including correlations across bins.
png pdf	Figure 3: The $ \mathrm{t} \bar{\mathrm{t}} $ normalized differential cross section as a function of sidereal time, using combined 2016 and 2017 data.
png pdf	Figure 4: Uncertainty breakdown for the normalized differential cross section, by splitting according to the treatment of time dependence: uniform across sidereal time (flat luminosity component, background normalization, theory), correlated in sidereal time bins (trigger, luminosity stability and linearity, pileup, and MC statistics), systematics uncorrelated in sidereal time bins (other experimental systematics), and statistical uncertainty.
png pdf	Figure 5: Number of $ \mathrm{t} \bar{\mathrm{t}} $ events reconstructed in the SME hypothesis divided by the SM hypothesis, as a function of the number of b jets and sidereal time, here for the four directions of the $ c_L $ coefficients. The uncertainty band represents the MC statistical uncertainty in the sample used to compute the SME hypothesis.
png pdf	Figure 6: Fitted SME coefficients and their uncertainties measured in fits of single coefficients while the coefficients corresponding to the three other directions are left floating, within the $ c_L $, $ c_R $, $ c $, and $ d $ families. Fitting a single coefficient, while the others are fixed to the SM value, leads to negligible changes in the results.
png pdf	Figure 7: Uncertainty breakdown for SME fits of single coefficients in 2016+2017 data while the coefficients corresponding to the three other directions are left floating, by splitting according to the treatment of time-dependence: flat across sidereal time (flat luminosity component, background normalization, theory), correlated in sidereal time bins (trigger, luminosity stability and linearity, pileup, MC statistics, single top decay in the SME), systematics uncorrelated in sidereal time bins (other experimental systematics) and statistical uncertainty.

Tables
png pdf	Table 1: Event yield in data and MC simulation in 2016 and 2017, after selection.
png pdf	Table 2: Summary of the systematic uncertainties and their correlation scheme between 2016 and 2017 data sets, and between sidereal time bins. Sources marked with an asterisk are only included in the SME fits.
png pdf	Table 3: Expected and observed 1$ \sigma $ interval measured for the SME fits of single coefficients while the others are fixed to their SM value, and while coefficients for the three other directions are floating.

Summary

A search for violation of Lorentz invariance has been performed using top quark pairs ($ \mathrm{t} \bar{\mathrm{t}} $), requiring the presence of one muon and one electron in the events. Data collected in 2016 and 2017 at CMS is used with an integrated luminosity of 77.4 fb$ ^{-1} $. A measurement of the $ \mathrm{t} \bar{\mathrm{t}} $ yield as a function of sidereal time is performed. Lorentz invariance assumption is tested by measuring 16 sets of Wilson coefficients within the Standard Model Extension, an effective field theory predicting modulation of $ \mathrm{t} \bar{\mathrm{t}} $ cross section with sidereal time. Measurements of the Lorentz-violating couplings are found to be compatible with the SM hypothesis. The precision of the results ranges from less than 1 $ \times $ 10$^{-3} $ to 8 $ \times $ 10$^{-3} $ for the fits of the coefficients. This constitutes the most precise test of Lorentz invariance using top quarks at a hadron collider.

Additional Figures
png pdf	Additional Figure 1: Integrated luminosity as a function of the sidereal hour in 2016 and 2017. The uncertainty band represents the uncertainty in the luminosity estimate.
png pdf	Additional Figure 2: Uncertainties in the luminosity estimate as a function of the sidereal hour in 2016, splitted into three sources: uniform component as a function of sidereal time, cross-detector stability, and linearity of the luminometer responses.
png pdf	Additional Figure 3: Uncertainties in the luminosity estimate as a function of the sidereal hour in 2017, splitted into three sources: uniform component as a function of sidereal time, cross-detector stability, and linearity of the luminometer responses.
png pdf	Additional Figure 4: Nominal distribution of the number of pileup interactions with its uncertainty, and distributions of the number of pileup interactions in sidereal hour bins in 2016.
png pdf	Additional Figure 5: Nominal distribution of the number of pileup interactions with its uncertainty, and distributions of the number of pileup interactions in sidereal hour bins in 2017.
png pdf	Additional Figure 6: Efficiency of the dilepton trigger in data divided by the simulation as a function of the sidereal hour in 2016. The uncertainty bands represent the statistical uncertainty (red), and the statistical and stystematic uncertainties added in quadrature (blue).
png pdf	Additional Figure 7: Efficiency of the dilepton trigger in data divided by the simulation as a function of the sidereal hour in 2017. The uncertainty bands represent the statistical uncertainty (red), and the statistical and stystematic uncertainties added in quadrature (blue).
png pdf	Additional Figure 8: Prefit distribution integrated over the the number of b jets in sidereal time bins, in 2016 and 2017 data. The uncertainty band reflects the statistical and systematic uncertainty in each bin, including correlations across bins.
png pdf	Additional Figure 9: Postfit distribution integrated over the the number of b jets in sidereal time bins, in 2016 and 2017 data. The uncertainty band reflects the statistical and systematic uncertainty in each bin, including correlations across bins.
png pdf	Additional Figure 10: The $ \mathrm{t} \bar{\mathrm{t}} $ normalized differential cross section as a function of sidereal time, using 2016 data.
png pdf	Additional Figure 11: The $ \mathrm{t} \bar{\mathrm{t}} $ normalized differential cross section as a function of sidereal time, using 2017 data.
png pdf	Additional Figure 12: Uncertainty breakdown for the normalized differential cross section, by splitting according to the kind of uncertainties: experimental, theory, background normalization, luminosity, MC statistical uncertainty, and statistical uncertainty.
png pdf	Additional Figure 13: Uncertainty breakdown for the normalized differential cross section, by splitting according to the experimental uncertainties: electron, muon, pileup, b tagging, jet energy scale, ECAL prefiring, trigger, and statistical uncertainty.
png pdf	Additional Figure 14: Number of $ \mathrm{t} \bar{\mathrm{t}} $ events reconstructed in the SME hypothesis divided by the SM hypothesis, as a function of the number of b jets and sidereal time, here for the four directions of the $ c_R $ coefficients. The uncertainty band represents the MC statistical uncertainty in the sample used to compute the SME hypothesis.
png pdf	Additional Figure 15: Number of $ \mathrm{t} \bar{\mathrm{t}} $ events reconstructed in the SME hypothesis divided by the SM hypothesis, as a function of the number of b jets and sidereal time, here for the four directions of the $ c $ coefficients. The uncertainty band represents the MC statistical uncertainty in the sample used to compute the SME hypothesis.
png pdf	Additional Figure 16: Number of $ \mathrm{t} \bar{\mathrm{t}} $ events reconstructed in the SME hypothesis divided by the SM hypothesis, as a function of the number of b jets and sidereal time, here for the four directions of the $ d $ coefficients. The uncertainty band represents the MC statistical uncertainty in the sample used to compute the SME hypothesis.
png pdf	Additional Figure 17: Uncertainty breakdown for SME fits of single coefficients in 2016+2017 data while the coefficients corresponding to the three other directions are left floating, by splitting according to the kind of uncertainties: experimental, theory, background normalization, luminosity, MC statistical uncertainty, and statistical uncertainty.
png pdf	Additional Figure 18: Uncertainty breakdown for SME fits of single coefficients in 2016+2017 data while the coefficients corresponding to the three other directions are left floating, by splitting according to the experimental uncertainties: electron, muon, pileup, b tagging, jet energy scale, ECAL prefiring, trigger, and statistical uncertainty.
png pdf	Additional Figure 19: Uncertainty breakdown for SME fits of single coefficients in 2016+2017 data while the coefficients corresponding to the three other directions are left floating, by splitting according to the SME uncertainties in the single top quark process: in the XX, XY, XZ, YZ directions, and statistical uncertainty.

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