-- RehamAly - 2021-03-09

  • Final answers in green
  • In-progress answers in blue

MET+X Conveners Questions

#### General

Question: - You do not discuss the impact of the HEM effect on your analysis of the 2018 data set. Please document how you study / estimate / control this effect.

The following plots show the MET and MET phi distributions before (left) and after (right) applying the HEM veto in CR (side band of the m4l). To check how much the effect, the ratio of before (red) and after (black) applying HEM veto for 2018 MC samples is shown. We find no noticeable change in the above-mentioned distributions before and after applying the veto. We have also checked them for SR and no noticeable deviations have been observed. Since we find no noticeable change in the above-mentioned distributions before and after applying the HEM veto, we didn't add any uncertainties related to the HEM issue.

  • MET distribution in CR before (left) and after (right) applying HEM veto:

h_hLogLinXPFMETType1_7_XYcorr_4bins_CR_4l_13TeV_ratio_logXY_totalUnc.png h_HEM_MET_XYcorr_4bin_CR_4l_13TeV_ratio_logXY_totalUnc.png

* MET phi distribution in CR before (left) and after (right) applying HEM veto:

h_hpfmet_phi_7_XYcorr_CR_4l_13TeV_ratio_log.png h_HEM_MET_XYcorr_phi_CR_4l_13TeV_ratio_log.png

* ratio distribution in CR before (red) and after (black) applying HEM veto:

bkg_ZZ_HZZ_TTV_VVV_HEM_CR_2018.png bkg_ZZ_HZZ_TTV_VVV_HEM_METphi_CR_2018_2.png

* ratio distribution in SR before (red) and after (black) applying HEM veto:

bkg_ZZ_HZZ_TTV_VVV_HEM_SR_2018.png bkg_ZZ_HZZ_TTV_VVV_HEM_METphi_SR_2018_2.png

#### Introduction
Question: - L181+: You refer to EFT models being used for interpretation. I assume this is outdated?

Yes it is out of date ... We removed.

#### Signals

Question: - There is currently no mention of the Dark Higgs model. What is the plan/status here?

Still in progress

#### Datasets

Question: - L232+: Please clarify a bit more the generation settings for the signal. Is it LO or NLO? Are there additional jets in the matrix element / is jet multiplicity merging used?

The signal samples are NLO and No jet multiplicity have been used. The information has been added to the note.

Question: - L268: You say that all samples use NNPDF 3.0 NLO. Is that also true for 2017/2018? There, the CMS default is 3.1 NNLO (in line with tune CP5).

Indeed it is NNPDF3.1... fixed in the note.

Question: - Tab 8: IIUC, this table suggests that gg and qq initial states are produced separately. Based on the XS, it seems that qq is suppressed by 2-3 order of magnitude inclusively for tan beta =1. Does qq matter here or only for higher tan beta?

That is true, it doesn't matter the qq samples in the case of tan beta = 1 but it contribute in the case of the samples with high tan beta values.

#### Objects

Question: - sec 4.4.41: please compare your filters to the latest JME twiki [1]. It seems there is at least one filter missing from your list (Flag_eeBadScFilter) [1]https://mmm.cern.ch/owa/redir.aspx?C=IuNGg-mha1tMX52vcYoQ2Rpy52250ILG8V88myVlrJ5DkypayPLYCA..&URL=https%3a%2f%2ftwiki.cern.ch%2ftwiki%2fbin%2fviewauth%2fCMS%2fMissingETOptionalFiltersRun2

The filter is already included in the analysis for data. Fixed in the note.

Question: - sec 4.5: How big is the effect of the prefiring weight and how are the related ucnertainties treated?

The following plots show the MET distribution with (red) and without (black) the prefireing weight on signal sample in 2016 (left) and 2017 (right) signal sample (ratio would be the best). We find no noticeable change in the above-mentioned distributions before and after applying the preferring weights. We have also checked them for MC backgrounds and no large deviations have been observed. Since the effect is small, we didn't add uncertainties related to the prefireing weights.

prefire_sig400_2016_SR.png prefire_sig400_2017_SR.png

#### Selection

Question: - L445+: You say that events must pass a four-lepton selection and refer to [26]. It's not clear to me whether you mean that the selection described in the following (e.g. 5.3) is this selection or whether there is something else that is not described here?

All the 4l event selection is described in in the note in section 5 "Event Selection" . I just mentioned the refenece of the HZZ4l note.

Question: -Your selection does not mention any requirement on separation of jets and the met vector in the transverse plane. Do you apply such a requirement? This is usually a good way of rejecting fake met contanimation.

We didn't consider any requirement on separation of jets and the met vector, since we think that the fake MET have been cut with the applied MET filter. But for completeness we checked the delta phi (met, jet) for 2016 signal and different bkg under the Higgs peak but we found that the distribution is flat as shown in the following plot.


#### CUt-based selection

Question: You say that you have attempted optimizing cuts on various variables (whcih?), but only the cuts on m(4l) and ptmiss were useful. What quantitative improvement did the third-best cut give you?

On top of the cut on (m4l) we tried putting cuts on different variables such as (Delta phi (4l, MET) - Transverse mass (4l, MET) - DeltaR (Z1, Z2) - b tagged jet multiplicity - |MET- pT(4l)/ pT(4l)| ) and check the effect to of the cuts on the analysis sensitivity measured from the upper limit on the signal strength, moreover we check the effect of the cut on the different signal sample. But instead of doing rectangular cuts on those variable we injected the variables to the BDT.

#### BG esitmation

Question: - L551+: In multiple places, you mention "signal" and "background". What exactly does this refer to? Please clarify.

L 551 mention gg ZZ background modeling ... The sentence has been rephrased since we mean the Higgs sample and ggZZ sample .

Question: : - Eq 7: I do not quite understand the logic of having 3P1F and 2P2F regions in the same estimation method. You have previously explained, and write in the text, that the goal here is to include different types of prodction processes. However, I am fundamentally confused as to why that is necessary. Naively, I would have thought that the 3P1F region already includes a contibution that could be written as f/(1-f)*N2P2F. In that case, the formula in eq 7 is just double counting the 2P2F contribution tothe signal region. What am I missing?

The 2P2F control region contain the contribution coming from processes have 2 fake objects like Z+jets, tt while the 3P1F control region contain the contribution coming from processes have 1 fake obiect like WZ background, so need to include the contribution from both regions. As you mentioned that the 3P1F region already includes a contibution from 2P2F region that we subtract to not double count this contribution.

Question: -Fake rate: What fake rate value is used for met>last bin?

For the MET value > last bin we use the fake rate of the last bin.

Question: - Z+X BG in general: You quote the resulting expected yields of this process, but you do not show any shape information. How is the differential shape of this process estimated? Same question for uncertainty.

The estimation of Z+X background depend on the method described in the HZZ4l analysis, we are not using shapes uncertainties we use normalization. In the following plots we show an example of 2p2f and 3p1f CR in 2016.

h_hM4l_EEEE_AI_AI_2e2mu_13TeV_ratio.png h_hM4l_MMMM_AI_AI_2e2mu_13TeV_ratio.png

h_hM4l_MMEE_AI_AI_2e2mu_13TeV_ratio.png hM4l_EEMM_AI_AI_2e2mu_13TeV_ratio.png

h_hM4l_EEEE_3p1f_total_2e2mu_13TeV_ratio.png h_hM4l_MMMM_3p1f_total_2e2mu_13TeV_ratio.png

h_hM4l_MMEE_3p1f_total_2e2mu_13TeV_ratio.png h_hM4l_EEMM_3p1f_total_2e2mu_13TeV_ratio.png

Question: -Fig 15: Please rearrange the y-ordering of the ackgrounds so that small BGs (e.g. Z+x) are easier to see

h_hLogLinXPFMET_7_blind_4bins_4l_13TeV_ratio_logXY_totalUnc_2016.png h_hLogLinXPFMET_7_blind_4bins_4l_13TeV_ratio_logXY_totalUnc_2017.png.png

h_hLogLinXPFMET_7_blind_4bins_4l_13TeV_ratio_logXY_totalUnc_2018.png h_hLogLinXPFMET_7_blind_4bins_4l_RunII_ratio_logXY_totalUnc.png

#### Observables

Question: - General: You show signals with constant mA,ma in your plots and vary tan beta and sin theta. As you explained earlier, tan beta and sin theta do not alter the kinetmaics. Please show variations of the masses instead.

The signal with different MA values are shown in the previous question.

Question: - Fig 13: Do these plots already include the cut on m4l? If not, what do they look like after?

The plots on Figure 13 don't include the cut on m4l. Here are the MZ1 (left) and MZ2 (right) with the m4l cut.

h_hMZ1_window_4l_RunII_ratio_log.png h_hMZ2_window_4l_RunII_ratio_log.png

#### MVA

Question: - L734: is Z+X included?

Z+X background estimated from data not included in the MVA study but the MC background samples contributing to this background have been used in the study.

Question: - Fig 16: What sample is this? LM or HM?

I divided the MonoHiggs signal samples to two category depending on the mass of the heavy pesudoscalar A.

Low Mass region (LM) contain all the signal samples with mass of heavy pesudoscalar A of 200, 300, 400 whatever is the value of mass of light pseudoscalar or tan beta or sin theta.

High Mass region (HM): contain all the signal samples with mass of heavy pesudoscalar A of 500, 600, 700, 800 whatever is the value of mass of light pseudoscalar or tan beta or sin theta.

Question: - How does the shape of MZ1, MZ2 compare between the mono-H signals and the SM H samples?

The distribution of mZ1 and mZ2 are shown in Figure 13 in the AN. The shape of MZ1, MZ2 for the mono-H signals and the SM H samples should have the same distribution, where we reconstruct Z1 as the Z with mass closest to 90 GeV "on-shell" and the second Z as Z2 "off shell"

h_hMZ1_7_4l_RunII_ratio_log.png h_hMZ2_7_4l_RunII_ratio_log.png

Question: - Generally: If we use the MVA based method, we should take care to build confidence that the MVA does not introduce significant data/mc differences that might affect the analysis. As far as I can tell, you are currently doing this by a) showing some of the data/mc comparisons of the input distributions and b) showing a part of the MVA output distribution in the SR. In both cases, we can only take limited conclusions, given that the phase space in neither case really represents your most sensitive signal bins. Additionally, the MVA relies on the correlations between variables, whcih is not tested when looking at individual distributions. I would therefore like to encourage you to think about a more systematic approach to building confidence in the MVA model. Could we for example look at a validation region that is relatively similar to the SR? Off the top off my head, I would think that a mass sideband in m4l would at least allow to check the modeling in ZZ events, if not in SM H events directly, but that should already be instructive given that the sources of fake MET should be similar between the two.

The following plots shows the MVA input variables distributions in CR (side band of m4l) in different years if data taken:

1) 2016:

h_h4l_pt_CR_4l_13TeV_ratio_log_2016.png h_hMZ2_7_CR_4l_13TeV_ratio_log_2016.png h_hM4lmed_7_CR_4l_13TeV_ratio_2016.png h_hLogLinXPFMETType1_7_XYcorr_4bins_CR_4l_13TeV_ratio_logXY_totalUnc_2016.png h_DPHI_7_CR_4l_13TeV_ratio_log_2016.png h_h_DR_ZZ_7_CR_4l_13TeV_ratio_log_2016.png h_hM4l_T_4bins_CR_4l_13TeV_ratio_logXY_totalUn2016.png

2) 2017:

h_h4l_pt_CR_4l_13TeV_ratio_log_2017.png h_hMZ2_7_CR_4l_13TeV_ratio_log_2017.png h_hM4lmed_7_CR_4l_13TeV_ratio_2017.png h_hLogLinXPFMETType1_7_XYcorr_4bins_CR_4l_13TeV_ratio_logXY_totalUnc_2017.png h_DPHI_7_CR_4l_13TeV_ratio_log_2017.png h_h_DR_ZZ_7_CR_4l_13TeV_ratio_log_2017.png

3) 2018:

h_h4l_pt_CR_4l_13TeV_ratio_log_2018.png h_hMZ2_7_CR_4l_13TeV_ratio_log_2018.png h_hM4lmed_7_CR_4l_13TeV_ratio_2018.png h_hLogLinXPFMETType1_7_XYcorr_4bins_CR_4l_13TeV_ratio_logXY_totalUnc_2016.png h_DPHI_7_CR_4l_13TeV_ratio_log_2018.png h_h_DR_ZZ_7_CR_4l_13TeV_ratio_log_2018.png h_hM4l_T_4bins_CR_4l_13TeV_ratio_logXY_totalUn2018.png

#### Uncertainties

Question: Tab 20: Are the theory uncertainties shape or just normalization? If shape, please plot the variations. If not, please explain why shape not

All the theory uncertainties are normalization as provided by LHCHXSWG in https://twiki.cern.ch/twiki/bin/view/LHCPhysics/CERNHLHE2019 and HZZ4l note.

needed. Question: - Please show all variations for the ptmiss distirbution as well as for the BDT dist.

Al the variations for the ptmiss distribution are shown in Figure 23.

Question: - How is the uncertainty associated to the qqZZ electroweak correction evaluated? In EXO-19-003 (mono-Z(ll)), which also has ZZ as leading background, there is a significant amount uncertainty stemming from higher order corrections on ZZ (including also a rough estimate of mixed ewk-qcd corrections). There, the situation is different in the sense that EXO-19-003 directly probes the Z boson pt spectrum, while you are likely more sensitive to the pt of the di-Z system. Please clarify what is done and how it relates to what is done in EXO-19-003.

This analysis relay on HZZ4l analysis where the qqZZ background has been deeply studied since it is the main background of the Higgs analysis. We kept the same uncertainty values as SM HZZ4l analysis.

Question: - Fig 24: Same question that was asked in a previous presentation: The up and down variations for a number of sources go in the same directoin (e.g. bottom left), which seems pathological. Is there a physical reason for this behavior?

We checked the MET variations at early step of the analysis (before any selection cut) for main background samples separately. We found that the up and down variations changing for different binning (some bind the variations goes in opposite directions and some bins the variations in same direction). We are contacting MET group to check this behavior.

#### Statistiscal analysis

Question: - L804: You say you fit on both the BDT and ptmiss distribution. Judging from the rest of the text, I assume that you mean that these are two separate approached (you do not fit both at the same time). Suggest to write this more clearly

I mean that we used separate approaches, one approach use the MET distributions as input for the shape analysis and the second approach uses the BDT distributions as input for the shape analysis. rephrased in the note.

Question: - Fig 28: It seems that at high mA values, the BDT is worse than the ptmiss analysis. That seems pathological. What is the reason?

In the high MA region the loss in sensetivty is small as shown in the following values, this loss could be introduced since the statistics of signal sample is low compared to low MA region but since the analysis is not sensitive at high MA region this loss will not affect the final results.

MA = 600

Expected 2.5% Expected 16.0% Expected 50.0% Expected 84.0% Expected 97.5%

MET: r < 1.4032 r < 2.0580 r < 3.2656 r < 5.3223 r < 8.2383

BDT: r < 1.5917 r < 2.2606 r < 3.4531 r < 5.4077 r < 8.1530

MA = 800

Expected 2.5% Expected 16.0% Expected 50.0% Expected 84.0% Expected 97.5%

MET: r < 2.9758 r < 4.5203 r < 7.4688 r < 12.5298 r < 19.9273

BDT: r < 4.1052 r < 5.8306 r < 8.9062 r < 13.9828 r < 21.2491

Question: - Fig 29: Would be good to explain the y axis in the caption. Gain > 1 means BDT wins?

Yes If the gain is greater than 1 means that BDT wins. The definition of the Gain has been added to the caption.

Topic attachments
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PNGpng bkg_ZZ_HZZ_TTV_VVV_HEM_CR_2018.png r1 manage 13.4 K 2021-04-26 - 03:20 RehamAly  
PNGpng bkg_ZZ_HZZ_TTV_VVV_HEM_METphi_CR_2018.png r1 manage 10.3 K 2021-04-27 - 14:15 RehamAly  
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