Data scouting

Chapter V: The Compact Muon Solenoid experiment

5.8 Data scouting

2) invariant mass (GeV/c γ

0.08 0.1 0.12 0.14 γ0.16 0.18 0.2

2 pairs / 0.004 GeV/cγγ

0 50 100 150 200 250 300 350

400 Data

Signal + background Background only Preliminary

CMS 0.1 fb^-1 (13 TeV)

ECAL Barrel crystal

time

14h00 15h00 16h00 17h00 18h00 19h00 20h00 21h00

mass0πnormalized

0.92 0.94 0.96 0.98 1 1.02

CMS preliminary 2016

ECAL Barrel

FILL 4958 : 28 May 2016 With LM correction

Without LM correction

0 5 10 15 20 25 0.92 0.94 0.96 0.98 1 1.02

mean = 1.00 r.m.s = 0.07 %

mean = 0.94 r.m.s = 0.21 %

Figure 5.18: (Left) Invariant mass of photon pairs reconstructed in one crystal of the ECAL barrel, in the mass range of theπ⁰ meson, during the run 273730 taken in May 2016, corresponding to an integrated luminosity of approximately 100 pb⁻¹. (Right) The stability of the relative energy scale measured from the invariant mass distribution of π⁰ decays in the ECAL barrel for a typical LHC fill in 2016. The energy scale is measured by fit- ting the invariant mass distribution of approximately 200,000 photon pairs in the mass range of theπ⁰ meson. Each point is obtained from a fit to approximately 8 minutes of data taking. The error bars represent the statistical errors on the fitted peak position. The energy scale is plotted as a function of time, over a period of 8 hours for data recorded on May 28, 2016 during LHC fill 4958. The plot shows the data with (green points) and without (red points) light monitoring corrections applied. The right-hand panel shows the projected relative energy scales [147].

date (day/month) 19/04 19/05 18/06 18/07 17/08 16/09 16/10 15/11

Relative E/p scale

0.93 0.94 0.95 0.96 0.97 0.98 0.99 1 1.01 1.02

without laser monitoring correction with laser monitoring correction

CMS ECAL barrel

(8 TeV) 19.7 fb-1

0 100 200

Mean 1

RMS 0.0009 Mean 0.95 RMS 0.011

date (day/month) 17/09 24/09 01/10 08/10 15/10 22/10 29/10

Relative E/p scale

0.92 0.94 0.96 0.98 1 1.02

1.04 with laser monitoring correction

without laser monitoring correction CMS 2015 Preliminary

= 13 TeV, L = 2.5 fb-1

ECAL Barrel

Mean 1

RMS 0.001537

0 200 400 600

Mean 1

RMS 0.001537 Mean 0.9401 RMS 0.006944 Mean 0.9401 RMS 0.006944

Figure 5.19: Ratio of the energy measured by the ECAL over the momentum measured by the tracker, E/p, for electrons selected from W → ^eνe

and Z → ^e⁺^e⁻ decays, as a function of the date at which they were recorded [120,154]. The ratio is shown both before (red open circles) and af- ter (green filled circles) the application of transparency corrections obtained from the laser monitoring system, and for the ECAL barrel in 2012 at 8 TeV (upper plot) and in 2015 at 13 TeV (lower plot). Histograms of the values of the measured points, together with their mean and RMS values are shown beside the main plots.

Dustin Anderson 6 Aug. 2016

Scouting With Hadronic Events

17 PF Scouting

HT (GeV)

250 GeV 410 GeV 800 GeV

HT > 250 GeV: Scouting with calo-jets

• Rate: 3.7 kHz

Loosest HT trigger in standard HLT menu HT > 410 GeV:

Scouting with PF candidates

• Rate: 720 Hz

Calo Scouting

A.U.

(Not to scale)

Rates from 2016 data.

Luminosity = 1e34 cm^-2 s^-1 ¹⁷

Parking HT > 410 GeV: Parking

• Rate: 720 Hz

HT = Σ | jet pT |

Figure 5.20: HLT HT thresholds for Calo and PF scouting for 2015 (top) and 2016 (bottom) data-taking runs [155]. The rates for the 2015 (2016) are normalized to an instantaneous luminosity of 7×¹⁰³³ ^cm⁻²^s⁻¹⁽¹⁰³⁴ ^cm⁻² s⁻¹).

the corresponding event content [155]. Calo scouting, which selects events based only on Calo jets and records only calorimetric information, has a very small event size of ∼ 1.5 kilobyte (kB), allowing the rate to go as a high as 3.8 kHz. Meanwhile,PF scouting, which runs the full PF algorithm and records all PF-reconstructed information, including leptons, photons, and jets with b-tagging information, has a larger event size ∼10 kB. In or- der to stay within the HLT timing budget, the maximum permissible rate is 720 Hz. Simultaneously, thedata parkingstream sends the full raw events from PF scouting directly to tape without reconstruction. This multifaceted approach is advantageous in the case that a signal is seen in the scouting data that warrants more investigation.

Figure 5.21: The event content for PF scouting (left) consists of PF candidates, anti-k_T R = 0.4 PF jets, PF E^miss_T , reconstructed vertices, PF- reconstructed electrons, muons, photons, and the median energy density in an eventρ, which amounts to∼10 kB. The event content for Calo scouting (right), consists of anti-k_T R = 0.4 Calo jets, CaloE_T^miss, vertices (if another trigger reconstructed them for this event), and the median energy density in an eventρ, which amounts to∼1.5 kB [155].

Chapter 6

TOPOLOGICAL HLT DEVELOPMENT AT √

S = 13 TEV

Traditionally, trigger algorithms employed at hadron colliders consisted of selecting events based on the presence of specific particles, such as leptons or photons, above some energy threshold and isolated from the rest of the event. In other trigger algorithms, global event properties (such as “sum”

quantities like the hadronic transverse energyHT or the missing transverse energyE^miss_T ) were also used.

The event selection used in modern searches for BSM physics employ new techniques, such as kinematic variables likeM_Rand R², that no longer map on to these traditional trigger requirements. Fortunately, the flexibility of the software-based system allowed the development of dedicated trigger paths, based on sophisticated kinematic variables and specific event topologies.

To target a broad range of new physics possibilities, we designed four different types of triggers for use in√

s =13 TeV pp collisions:

• Dijet razor trigger with hyperbolic M_R and R²requirements targeting the squark pair production topology;

• Quadjet razor trigger with hyperbolicM_Rand R²requirements targeting top-squark or gluino pair production topologies;

• High-R² trigger targeting dijet+invisible topologies with large transverse momentum imbalance; and

• Razor H(bb)trigger targeting production of Higgs boson decaying to a bottom quark-antiquark pair (H →bb) in association with a jet and possibly some missing transverse energy, i.e. H(bb) +jet+invisible.

The dijet and quadjet razor triggers are broadly motivated by SUSY pair production and represent an update and incremental improvement of the razor triggers used in previous searches at √

s = 8 TeV [94]. Both sets of triggers are based on hyperbolic thresholds in the(M_R, R²)plane, with the

2015 updated thresholds shown in Fig 6.1. The 2015 hyperbolic contours follow the iso-probability contours(R²+0.25)(MR+300 GeV) =constant, derived from the background-only fit to the MultiJet category in the 8 TeV razor search performed using 2012 data. This implies that these hyperbolic contours efficiently reject background, while maintaining a large acceptance for SUSY signal models with a large characteristic mass scaleM_∆ &500 GeV and sufficient transverse momentum imbalance. Another update is that the 13 TeV razor triggers are based on PF-reconstructed objects rather than Calo jets and muons, which means that the online R²variable is much more cor- related with the offline R² variable, which is also PF-based. This leads to an improved trigger efficiency plateau of 97% for 2015 (compared to 95% in 2012), shown in Fig.6.2.

HM_R+300LHR²+0.25L=270

HM_R+300LHR²+0.25L=240 R²=0.09

MR=200

0 100 200 300 400 500 600 700 0.0

0.1 0.2 0.3 0.4 0.5

M

R

Figure 6.1: Hyperbolic and baseline thresholds in R² and MR used in the dijet and quadjet razor triggers [44]. The hyperbolic thresholds are of the form(R²+0.25)(M_R+300 GeV) =constant.

The high-R² trigger is motivated by the search for the direct production of dark matter (DM) particles at the LHC [159]. DM particles themselves would not leave a detectable signal in the detector, but if they were pro-

duced in association with high-energy quarks or gluons, they could produce signatures with jets and transverse momentum imbalance. The traditional approach, employed by both CMS and ATLAS, is to search in events with one high-pT jet and largeE_T^miss(so-called monojet searches) [160, 161].

A complementary approach is to search in events with at least two jets pass- ing a looser event selection using the razor variables. The sensitivity of these variables to direct DM production was suggested in Ref. [162], and the search carried out by CMS demonstrates that the resulting sensitivity is comparable to that of monojet searches [162, 163, 159]. The hallmark of many direct DM production models in the razor plane is a peaking behavior near R² & 0.8 and an exponentially falling MRdistribution with no special structure. For this reason, the high-R²trigger is designed with a threshold in R²but no requirement on MR to allow for greater DM signal acceptance.

Finally, the razor H(bb) trigger is motivated by an excess observed in Run 1 by CMS in events with a Higgs boson decaying to two photons (H→^γγ) plus at least one extra jet [164]. The excess, corresponding to a local sig- nificance of 2.9σ, consists of five events observed with 400 GeV < M_R <

1400 GeV, R² > 0.05, and m_γγ consistent with mH = 125 GeV in a high- resolution diphoton category, compared to less than one expected background event. The general idea is to search for a similar signature in the H → bb channel, which comes with a larger signal yield (90,000 times more assuming SM Higgs branching ratios), but a much larger background, resulting in a considerably worse signal-to-background ratio and a much larger background event rate. These final two features make the definition of an optimal trigger strategy much more challenging than in the H → ^γγ decay channel. Given this, the trigger requirements of three jets, two b-jets, MR >300 GeV, R² >0.02, andm_bbroughly consistent withmH =125 GeV are chosen to (a) maintain signal acceptance based on the observed features, (b) accept additional events outside of the mH window to permit a robust background estimation based on a fit, and (c) limit the rate and average CPU time of the trigger to an acceptable level.

For each trigger, we developed two different versions: a “main” version intended for 7×¹⁰³³ ^cm⁻² ^s⁻¹ and 20 average pileup interactions, and a

“backup” version, with tighter thresholds intended for 1.4×¹⁰³⁴ ^cm⁻²^s⁻¹ and 40 average pileup interactions. The correspondence between the pur-

pose of each trigger and its path name is shown in Tab. 6.1. Each trigger path name encodes the main selection criteria. For the dijet and quadjet triggers, “RsqMR240” denotes the hyperbolic threshold (R²+0.25)(MR+ 300 GeV) = 240 GeV, “Rsq0p09 MR200” denotes the baseline thresholds R² > 0.09 and MR > 200 GeV, and “4jet” denotes a four-jet requirement where the two leading (remaining) jets are required to have a minimum p_T of 50 GeV (40 GeV). For the H(bb) trigger, “TriPFJet80 60 40” denotes a three-jet requirement where the leading, subleading, and remaining jet is required have a minimium p_T of 80 GeV, 60 GeV, and 40 GeV, respectively, “DoublePFBTagCSV0p7 0p4” denotes a two q_b-tagged jet requirement, with CSV discriminator values above 0.7 and 0.4, respectively, and

“Mbb60 200” denotes the 60<m_bb <200 GeV mass window.

Table 6.1: Correspondence between the purpose of each trigger and its path name.

Trigger path Purpose

HLT RsqMR240 Rsq0p09 MR200 main dijet trigger HLT RsqMR270 Rsq0p09 MR200 backup dijet trigger HLT RsqMR240 Rsq0p09 MR200 4jet main quadjet trigger HLT RsqMR270 Rsq0p09 MR200 4jet backup quadjet trigger

HLT Rsq0p25 main high-R² trigger

HLT Rsq0p30 backup high-R² trigger

HLT Rsq0p02 MR300 TriPFJet80 60 40

main H

(

)

trigger DoublePFBTagCSV0p7 0p4 Mbb60 200

HLT Rsq0p02 MR300 TriPFJet80 60 40DoublePFBTagCSV0p7 Mbb60 200 backup H

(

)

trigger

6.1 HLT path design

The design of the four main HLT paths in terms of producers (in purple) and filters (in blue) is shown in Fig. 6.3. The first step is always a filter, which rejects events with no hadronic activity above a certain threshold reconstructed by the L1 trigger. As detailed in Sec.5.6, there are two main techni- cal constraints an HLT path must satisfy: (a) the average CPU time required must be small enough so that the entire HLT menu fits within the timing budget of∼160 ms per event and (b) the rate must be small enough so that the entire HLT menu fits within the maximum allowable rate of ∼ ^{1 kHz.}

To satisfy the timing requirement, all the paths are outfitted with calori-

metric prefilters. The aim of these prefilters is to reject events based only on information from the calorimeters, whose reconstruction algorithms are much faster than the PF algorithm. In other words, to keep the timing of the paths manageable, it is necessary to limit the input rate to the PF algorithm.

Thus, all four triggers have a prefilter based on calorimeter-based versions of the razor variables.

6.2 HLT rate and average CPU time

The HLT rates and average CPU time consumed per event for the both the main and backup razor triggers, as measured in data collected in 2015, are presented in Tab.6.2. The thresholds on the razor variables, jetp_T, and b-tag discriminator values, and were all optimized to achieve an acceptable level of added rate and added CPU time per event with respect to the rest of HLT menu (taking into account overlapping events and reused algorithms) for the full suite of razor triggers.

Table 6.2: HLT rates and average CPU time consumed for the main and backup razor triggers under different running conditions in 2015. Run 260627 had 5×¹⁰³³ ^cm⁻² ^s⁻¹ peak instantaneous luminosity with 17 average pileup interactions, while run 259721 had 1.5×¹⁰³³ ^cm⁻² ^s⁻¹ ^peak instantaneous luminosity with 23 average pileup interactions.

Trigger path

Data rate [Hz] CPU time [ms]

Run 260627 Run 259721 5×¹⁰³³^cm⁻²^s⁻¹ ^1.5×¹⁰³³^cm⁻²^s⁻¹

17 PU 23 PU

HLT RsqMR240 Rsq0p09 MR200 7.7 27

HLT RsqMR270 Rsq0p09 MR200 2.3 17

HLT RsqMR240 Rsq0p09 MR200 4jet 1.2 20

HLT RsqMR270 Rsq0p09 MR200 4jet 0.5 15

HLT Rsq0p25 0.7 14

HLT Rsq0p30 0.4 14

HLT Rsq0p02 MR300 TriPFJet80 60 40DoublePFBTagCSV0p7 0p4 Mbb60 200 16.0 34 HLT Rsq0p02 MR300 TriPFJet80 60 40DoublePFBTagCSV0p7 Mbb60 200 8.0 26

6.3 Pileup dependence of HLT rate

The HLT rate, normalized by the number of colliding bunches, as a function of the number of pileup interactions for each razor trigger and for different data runs collected in 2015 is shown in Figures6.5and 6.6. Nominally, the dependence of the normalized HLT rate on pileup is expected to be linear,

as is the case for single-object triggers. In contrast, triggers based on sum quantities (such asHT orE_T^miss) and multi-object triggers often demonstrate a nonlinear dependence on pileup, not due to a physical increase in the cross section of the selected physics processes, but rather due to the effects of pileup contamination [165]. To illustrate this, consider the case of a QCD dijet event with no trueE^miss_T . Normally such an event would be rejected by E_T^misstriggers that requireE_T^missabove some threshold, but if some jets from pileup interactions are misinterpreted as part of the event-of-interest then the HLT-reconstructed~p_T^misswill be−∑j∈pileup~p_T^j, which may not perfectly balance to zero as illustrated in Fig.6.4.

As the razor triggers are both based on sum quantities and multiple objects, they also exhibit some nonlinear dependence on pileup. This implies that as the pileup increases at the LHC in 2016 and beyond, either trigger thresholds will need to rise dramatically or more sophisticated methods to deal with pileup contamination will need to implemented. One such method is delineated in Ch.9.

0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55

efficiency

0 0.2 0.4 0.6 0.8 1 1.2

CMS preliminary 13 TeV (2.3 fb^-1)

> 500 MR

signal: HLT_RsqMR240_Rsq0p09_MR200 || HLT_RsqMR240_Rsq0p09_MR200_4jet || HLT_Rsq0p25 reference: HLT_Ele27_eta2p1_WPLoose_Gsf

[GeV]

400 600 800 1000 1200

efficiency

0 0.2 0.4 0.6 0.8 1 1.2

/ ndf

χ2 1.033 / 5

p0 0.957 ± 0.01021 p1 217.9 ± 11.04 p2 99.83 ± 10.69

/ ndf

χ2 1.033 / 5

p0 0.957 ± 0.01021 p1 217.9 ± 11.04 p2 99.83 ± 10.69

CMS preliminary 13 TeV (2.3 fb^-1)

> 0.25 R2

signal: HLT_RsqMR240_Rsq0p09_MR200 || HLT_RsqMR240_Rsq0p09_MR200_4jet || HLT_Rsq0p25 reference: HLT_Ele27_eta2p1_WPLoose_Gsf

0.3 0.44 0.6 0.75 0.8 0.83 0.85 0.92

0.55 0.67 0.78 0.87 0.92 0.93 0.95 0.96

0.7 0.77 0.83 0.88 0.95 0.96 0.94 0.89

0.7 0.73 0.81 0.89 0.91 0.95 0.93 1

0.65 0.67 0.68 0.79 0.87 0.95 1 1

[GeV]

400 500 600 700 800 900 1000

0.2 0.3 0.4 0.5

efficiency

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

CMS preliminary 13 TeV (2.3 fb^-1)

signal: HLT_RsqMR240_Rsq0p09_MR200 || HLT_RsqMR240_Rsq0p09_MR200_4jet || HLT_Rsq0p25 reference: HLT_Ele27_eta2p1_WPLoose_Gsf

Figure 6.2: Trigger efficiency of the boolean “or” of the dijet, quadjet and high-R² triggers as used in the search of Ch.8, measured in a data sample of single-electron events as a function of R² (top), MR (middle), and as a function of(M_R, R²)(bottom) [44].

Razor Dijet Trigger Design

2 calo jets,   pT > (70,60)

2 PF jets,  pT > 80 Calo jet

sequence L1 HTT* or SingleJet*

or DoubleJetC*  

or QuadJetC*

Calo MET sequence

Calo R² > 0.02, MR > 100,  (MR +300)(R²+0.25) > 200

PF R² > 0.09, MR > 200,  (MR +300)(R²+0.25) > 240

PF jet sequence

PF MET producer

(a) HLT RsqMR240 Rsq0p09 MR200

Calo R² > 0.02, MR > 100,  (MR +300)(R²+0.25) > 200

PF jet sequence

Razor Quadjet Trigger Design

4 calo jets,   pT>(40,40,30,30)

4 PF jets,  pT>(50,50,40,40) Calo jet

sequence L1 HTT* or SingleJet*

or DoubleJetC*  

or QuadJetC*

Calo MET sequence

PF MET producer

PF R² > 0.09, MR > 200,  (MR +300)(R²+0.25) > 240

(b) HLT RsqMR240 Rsq0p09 MR200 4jet

Calo MET sequence

High-R ² Trigger Design

2 PF jets,  pT > 80

Calo   R² > 0.16 Calo jet

sequence L1 HTT* or SingleJet*

or DoubleJetC*  

or QuadJetC*

PF   R² > 0.25 2 calo jets,   pT > (70,60) PF jet

sequence

PF MET producer

PF R² > 0.02,   MR > 300

Calo MET sequence

PF MET producer

Razor H→bb Trigger Design

3 calo jets, pT>(70,50,30)

2 L3 b-tag   CSV > (0.4, 0.2)

Calo   MR > 200

3 PF jets   pT>(80,60,40) PF jet

sequence Calo jet

sequence

2 PF b-tag   CSV > (0.7,0.4)

PF   60 < mbb < 200, 

pTb > (50,30) L1 HTT* or SingleJet*

or DoubleJetC*  

or QuadJetC*

PF b-tag sequence L3 b-tag

sequence

(d) HLT Rsq0p02 MR300 TriPFJet80 60 40 DoublePFBTagCSV0p7 0p4 Mbb60 200

Figure 6.3: Flow of the producer steps (in purple) and filter steps (in blue) in the razor triggers [44].

Many Challenges with Pileup

Si Xie 9

Jets from pileup interactions may be mis-interpreted as part of the main interaction event

Jet from Primary interaction Jet from pileup

Figure 6.4: Pileup jet misinterpreted as part of the main interaction event [44].

< PU >

0 2 4 6 8 10 12 14 16 18 20 22 24

unprescaled rate / num colliding bx [Hz]

0 0.002 0.004 0.006 0.008 0.01 0.012 0.014

f(x) = -0.00280 + x*0.00047

CMS

Rate Monitoring

36 runs:

259637 (1596 b) 259683 (1813 b) 259685 (1813 b) 259686 (1813 b) 259721 (517 b) 259809 (1813 b) 259810 (1813 b) 259811 (1813 b) 259813 (1813 b) 259817 (1813 b) 259818 (1813 b) 259820 (1813 b) 259821 (1813 b) 259822 (1813 b) 259861 (1813 b) 259862 (1813 b) 259884 (1813 b) 259890 (1813 b) 259891 (1813 b) 260373 (589 b) 260424 (2232 b) 260425 (2232 b) 260426 (2232 b) 260427 (2232 b) 260431 (2232 b) 260532 (2232 b) 260533 (2232 b) 260534 (2232 b) 260536 (2232 b) 260538 (2232 b) 260541 (2232 b) 260575 (2232 b) 260576 (2232 b) 260577 (2232 b) 260593 (2232 b) 260627 (2232 b)

(a) HLT RsqMR240 Rsq0p09 MR200

< PU >

0 2 4 6 8 10 12 14 16 18 20 22 24

unprescaled rate / num colliding bx [Hz]

0 0.0005 0.001 0.0015 0.002 0.0025 0.003

f(x) = -0.00041 + x*0.00007

CMS

Rate Monitoring

36 runs:

(b) HLT RsqMR240 Rsq0p09 MR200 4jet

Figure 6.5: Pileup dependence of the dijet (a) and quadjet (b) razor triggers throughout 2015 [44]. Each data point corresponds to a different luminosity section (23.3 seconds of data-taking). The legend denotes the run number and number of colliding bunches in each run.

< PU >

0 2 4 6 8 10 12 14 16 18 20 22 24

unprescaled rate / num colliding bx [Hz]

0 0.0005 0.001 0.0015 0.002 0.0025

f(x) = -0.00034 + x*0.00005

CMS

Rate Monitoring

36 runs:

< PU >

0 2 4 6 8 10 12 14 16 18 20 22 24

unprescaled rate / num colliding bx [Hz]

0 0.005 0.01 0.015 0.02 0.025

f(x) = -0.00296 + x*0.00080

CMS

Rate Monitoring

36 runs:

(d) HLT Rsq0p02 MR300 TriPFJet80 60 40 DoublePFBTagCSV0p7 0p4 Mbb60 200

Figure 6.6: Pileup dependence of the high-R² (c) and H(bb)(d) razor triggers [44]. A detailed description of the graphs is given in Fig.6.5

Part III

Searches for new physics at the LHC

Chapter 7

SEARCHES FOR SUPERSYMMETRY AT √

S = 8 TEV

As discussed in Sec.3.8, models of SUSY predict additional, undiscovered fundamental particles which correspond to the heavy superpartners of SM particles. Of particular interest is the production of top squarks, bottom squarks, and gluinos due to their role in taming the quadric divergence of the Higgs mass in the SM (see Sec. 3.5). The residual fine-tuning inherent in these models is dependent on the masses of these superpartners, with a preference for smaller masses to avoid large fine-tuning. These consid- erations have motivated searches for the lightest allowed top and bottom squarks, as well as gluinos that may couple to top/bottom squarks, whose decays would produce final states enriched in b-jets. Moreover, due to the possible presence of top quarks that produce leptons∼ 30% of the time in the decay chain, the presence of electrons or muons may be used as part of the event selection to enhance the signal-to-background ratio. We exploit both of these features (b-jets and leptons) in the event classification.

We classify events into different “boxes,” or data categories, based on the jet multiplicity, b-jet multiplicity, and lepton (e orµ) multiplicity (see Fig.7.1).

The advantages of this classification are (i) by isolating different SM background processes, like tt, we can better model them individually, and (ii) in the event of a discovery, we may be able to infer the values of certain SUSY branching fractions based on the boxes where the signal is present. The like- lihood functions of the different boxes are statistically combined to exclude or discover particular SUSY models. In the following, this classification and statistical combination is referred to as the razor box approach.

In this chapter, we present an inclusive search for gluinos and top squarks¹ using pp collision data collected by CMS at√

s=8 TeV in the context of the minimal natural SUSY spectrum outlined in Sec.3.8[94]. Previous searches for natural SUSY by CMS [102, 103, 104, 105, 106] and ATLAS [97, 98, 99, 100, 101] at √

s = 7 and 8 TeV have probed gluino masses up to 1.3 TeV

1Though we don’t explicitly interpret our results in the context of bottom squark production, many of the conclusions regarding top squark production carry over.

Dalam dokumen Naturalness Confronts Nature: Searches for Supersymmetry with the CMS Detector in pp Collisions at √s = 8 and 13 TeV (Halaman 103-110)

Chapter V: The Compact Muon Solenoid experiment

5.8 Data scouting

Scouting With Hadronic Events

TOPOLOGICAL HLT DEVELOPMENT AT √

S = 13 TEV

0 100 200 300 400 500 600 700 0.0

0.1 0.2 0.3 0.4 0.5

M

R

(

)

(

)

Razor Dijet Trigger Design

Razor Quadjet Trigger Design

High-R 2 Trigger Design

Razor H→bb Trigger Design

Many Challenges with Pileup

Part III

Searches for new physics at the LHC

SEARCHES FOR SUPERSYMMETRY AT √

S = 8 TEV

High-R ² Trigger Design