1

Theory uncertainties at HL-LHC

Osamu Jinnouchi(TokyoTech)
Beyond the BSM (The 4th Kavli IPMU-Durham IPPP-KEK-KIAS workshop)
2018 Oct 1 - 4

2

HL-LHC plan & statistical impact- 4000

Most of thecurrent papers

x 5 stat.
availablein next springx 10 stat.
full LHC

x 100 stat.
full HL-LHC

3miss▪ ET▪
▪ keep the performance on tracking

threshold tuning, algorithm improvement▪ b-tagging:▪ owing to the Inner tracker replacement,b-tagging keeps its performance, even better
than Run-2▪ Trigger▪ increase the overall budget 10kHz (Run-2:1kHz)▪ improve the BG rejection new hard/software

to cope with high rate while keeping the lowthreshold

160
140

Phase-II upgrade scoping document
CERN-LHCC-2015-020|ηsoft track|<4.0, |ηR |<4.0, Reference|η

soft track100|<3.2, |η

pT

RpT|<3.2, Middle

PowhegPythia tt
RpT>0.1|ηsoft track|<2.7, |ηR |<2.7, Low
pT

8060

 !
≃ 25
Run-2tt ⟨μ⟩≃25
 
arXiv: 1802.08168 |η|<4.040
2000500 1000 1500 2000 2500 3000 3500 4000 4500

ITk Pixel TDR
CERN-LHCC-2017-021
ATLAS Simulation
s=14 TeV, tt, <µ>=200
104

MV2HL-LHC103

Σ ET [GeV]|η|<11<|η|<22<|η|<33<|η|<4|η|<2.5
Run 2 (|η|<2.5)102

10major deterioration in performancenot foreseen in HL-LHC

s=14 TeV, µ =190-210

ATLAS Simulation120

u-jet rejection▪ Pile-up <μ>(2018) ≃50 → <μ>(HL-LHC)≃>200

RMS Emiss[GeV]x,y

Performance of the key objects

Inclined Duals
50*50 μm2Run2

10.55

0.6 0.65

0.7 0.75

0.8 0.85

0.9 0.95

1b-jet efficiency

Introduction▪ HL-LHC▪ with 100 times statistics, things look different▪ needs for even higher order corrections▪ can discuss on the detailed shape of the distribution tail▪ can deal with very rare events▪ uncertainties not a big concern so far, become major contributions▪ “theory uncertainties” could be the one! we should start thinking about
reducing them, with the help of huge stats from LHC

disclaimer : I consulted with the following documents
ATL-PHYS-PUB-2018-010: impact of theory uncertainties related toHiggs boson production in the H→ZZ*→4l and the ttH channels withthe ATLAS detector at the HL-LHC“QCD issues in searches for New Physics with the ATLAS detector”
Mattias Saimpert, QCD@LHC2018 presentation
JPS 2018 fall : Yuji Yamazaki (Kobe U.) review talk4

5

Important Physics topics at HL-LHC
ATL-PHYS-PUB-2017-001[1] Higgs physics at HL-LHC▪ Understanding of the Higgs potential▪ Discovery & measurement of the Higgs
trilinear self-coupling to explore theshape of the Higgs potential▪ promising channels:

HH → bb + bb, bb + γγ , bb + τ +τ −▪ Extremely rare, very challenging▪ Yukawa-couplings for lighter (2nd)generations need to be covered[2] Searches of the BSM▪ Precisions on the background & signal
estimations are vital▪ Severe environment at HL-LHC
Theoretical uncertainties are the key for thesuccess of HL-LHC

ATL-CONF-2018-031

6[1] Theory Uncertainties
in Higgs physics

7

Theory uncertainties▪ Normalization and modeling▪ both for signal & backgrounds
Ex) Higgs related analysis
topicchannelreference
BSM
A/H tautau JHEP 01 (2018) 055
Combination Couplings ATLAS-CONF-2018-031
arXiv: 1808.09054
DiBosonhWW
arXiv:1808.08238
yukawa
VHbb
ATLAS-CONF-2018-021
yukawaHtautauarXiv: 1804.06174
HH4b
PRL119(2017)0418002
μ yukawa
Hmumu
PRD97 (2018) 072003
top yukawa ttH

dominant theoretical systematics
Tau fake estimates, embedding of Z
Signal modelings
WW modelingV+jets modeling
H pT modelingmulti-jet shape
Drell-yan modelingtt+V modeling▪ For the HL-LHC physics projections, the 1/2 of Run-2 estimation is used
▪ improvements in higher-order corrections, resummation▪ inputs from experiments would improve the modeling▪ PDF reduction expected with the help from theory community (?)

8Uncertainties in Yukawa coupling measurements
Projection at 2014 (ATLAS-PHYS-PUB-2014-016)

ttH → multi − leptons
−0.1

−0.05

ATL-PHYS-PUB-2018-010
∆µttH

00.05

0.1

ttH cross section (scale variations)ttH cross section(scale variation)
ttZ modeling(generator)

τhad identification
ttZ modeling (generator)
Jet energy scale (flavor comp. 2LSS)

ttH modeling(parton shower)

ttH modeling (parton shower)
Jet energy scale (pileup subtraction)

Run-236 fb-1
Run-1
25 fb-1

four top production cross section
Non-prompt stat. in 4th bin of 3L SR

ttH cross section(PDF)

ttH cross section (PDF)
ttZ cross section (scale variations)
Luminosity

ttZ cross section(scale variation)

pileup reweighing
rare top decay cross section
ttH modeling (shower tune)
ttZ modeling (shower tune)

Run-2
80 fb-1
arXiv:1808.08238

electron identification

theoryuncertainty
ranking

Non-prompt stat. in 3rd bin of 3L SR
Diboson modeling
Non-prompt stat. in 5th bin of 2LSS SR
Jet energy scale variation 1Pull
1 standard deviation
Prefit Impact on µttH

Postfit Impact on µttH

ATLAS Simulation
Preliminarys = 14 TeV, 3000 fb-1
−1.5
8 −6−1−4−0.5−2 00.5 4 1 6 1.528(θ - θ0)/∆θ▪ Due to unexpectedly rapid progress in analyses, e.g. multi-variates,optimizations in analysis/performance, or conservative prospects (?) in 2014,
some of them are already reached by the current precisions▪ More accurate treatments of systematics will be available, after we obtain
good amount of statistics from HL-LHC9σsys projection in ttH(→multi-leptons)▪ signal strength measurement▪ σtheory has direct impact on the resultµ=σ signal
σ theory∝ yf

ATL-PHYS-PUB-2018-010

ttH model (inclusive)
affects σ(theory)- missing HO calc.
- αs- PDF
fake objects
ttH model (acceptance)
affects σ(signal)- parton shower model
Stats no longer an issueat HL-LHC

10LHC PDFs & towards HL-LHCxf

LHC measurements for PDF fits

1ATLAS Preliminary
0.8

0.6

Q2 = 10 GeV2ATLASepWZtop18 NNLO
uncertainties:
experimental
modelparameterisation

xuv

epWZ

xg (! 0.05)
xdv

0.4

0.2

10-3

10-2

10-1

F. Giuli (Oxford)

In HL-LHC, high-x PDF are important▪ high-x gluon PDF▪ jet and top pair production data are inputs▪ NNLO+NNLL for tt▪ high-x quark PDF▪ high mass DY: NNLO pQCD+NLO EW

1x

ATL-PHYS-PUB-2018-017
A new ATLAS PDF set:
ATLASepWZTop18
Based on the NNLO analyses of W/Z,
top, ep data from HERA11[2] Theory Uncertainties
in BSM searches(from Run-2 analyses)

12

QCD process backgrounds

0.50.45ATLAS Simulation Preliminary

0.4Jets
η=0.0|η|=2.0|η|=4.5

0.35
0.3

CB µ (φ=0)η=0.0|η|=2.0Electrons
η=0.0|η|=2.0N.C. γ
η=0.0|η|=2.0Hadr. τ
1p0n
3pXn

0.25

fake signal topology from combinatorics
Phys. Lett. B 785 (2018) 136
Fraction of entries

Relative resolution σ/pT

fake MET through jet resolution effects
ATLAS-CONF-2018-038

s = 13 TeV, 36.1 fb-1
ATLAS

0.3

Data

0.25

Multijet (Pythia8)
Multijet (Herwig++)

0.2

Multijet (Sherpa)
m~g = 1000 GeV, m∼ = 450 GeV

0.15

χ

0.2m~g = 2000 GeV, m∼ = 450 GeV
χ0.1

0.15
0.1

0.05

0.05
010102103
p [GeV]
T000.5

1

1.5

2

2.5

33.5

4|Δη |121) Uncertainties from fakes (above plots)2) Uncertainties in Signal & background predictions▪ matrix element : QCD order, Nparton▪ parton shower model, ISR/FSR tune
Impact all LHC physics▪ PDF/αs variations, flavor scheme, etc

Background estimation strategy in non-resonant searches
1) Define control regions (CR)▪ background dominate regions▪ corresponds to background source

13

Eur. Phys. J. C75 (2015) 153

2) Normalize MC background prediction in the CR▪ simultaneous fit to data in all CR▪ normalization uncertainties ~ data stats3) Cross-check extrapolation quality in validation
region (VR)4) Extrapolate to signal region (SR) normalized by Transfer Factor (TF)
Big impact from QCD modeling uncertainties on MC• highest order MC available is used for prediction• evaluated by varying ME, PS, ISR/FSR tune, PDF/αs, flavor scheme

14(I) Jet smearing method▪ [ fundamental assumption ] high MET arise fromfluctuations in the detector response to jets

▪ Method:1) multi-jet event selection with good jets
(low MET events)
2) generate pT response function (RF) basedon MC as a starter4) generate variables based on final RFEvents / π/32

3) jet pT smeared according to expected pT
response, generate pseudo-events,
compared to data, modify RF, repeat thisMultijet validation region
SUSY strong 0-lepton analysis
Phys. Rev. D 87, 012008 (2013)104310∫L dt ~4.7 fbData 2011 ( s= 7 TeV)
Pseudo-data + non-QCD MC
Pseudo-data
W+jetsZ+jetstt and single topmultijet-1ATLAS
SR-C Loose102▪ Method limitations in future use▪ non-gaussian tail (large uncertainties)▪ fake MET from pileup jet removal algorithm

110-1
Data/Estimate

inefficiency, not implemented

10

2.50
2
1.5
1
0.5
00

0.5

1

1.5

0.5

1

1.5

2

2.5

2

2.5

3

3

miss

Δφ (jet,PT )min[rad.]15(II) large-R jet substructure uncertainties
L. Skinnari

R=1.0 anti-kT jet to reconstruct high pT W, top• QCD modeling crucial : energy scale, substructure, etc
•

4540
3530

ATLAS Preliminary-1
s = 13 TeV, 36.7 fb
Trimmed anti-k t R =1.0
Dijet Selection
Top tagger (∈sig = 80%): τ32 + d23

Data - Sig.
Pythia8 dijet
Herwig++ dijet
Stat. uncert.
Stat. ⊕ syst. uncert.

25
20

sys. > stat.

15
105

1.5500

1000

Data
MC

1.25

1500
2000
2500
Leading large-R Jet p T [GeV]

10.05
0.04
0.03
0.02

1000

1500
2000
2500
Leading large-R Jet p T [GeV]QCD jet rejection in Top tagger

ATLAS
s = 13 TeV, 36.2 fb-1, Z +jet
Trimmed anti-k t R =1.0 (LCW+JES+JMS)|η | < 0.8
JetStat. ⊕ Syst.

e E -resolution

e E -scale

Pile-up (JVT)

MC modellingµ E -resolution IDµ E -resolution MSµ E -scale (charge) residualµ E -scale (charge)µ E -scale

Pile-up (NPV shift)

StatisticalSub-leading jet veto

Δφ

0.01
0.00

0.75
0.5500arXiv:1807.09477
Fractional JES uncertainty

Background rejection (1/ ∈bkg)

ATLAS-CONF-2017-064

200300400 500 600
Large-R jet p [GeV]
Tlarge-R jet Energy scale calibration
uncertainties16a) Impact on Stop 0L search (low Δm)compressed region:
top mass cannot be reconstructed
hard ISR jet required

direct stop pair production
JHEP 12 (2017) 085mχ∼0 [GeV]

900

ATLAS

SUSY

Observed limit (±1 σtheory)
Expected limit (±1 σexp)

1800~(*) ∼0Top squark pair production, B(t1 → t χ) = 100%1700

s=13 TeV, 36.1 fb-1

ATLAS 20 fb-1, s=8 TeVLimits at 95% CLm

t +SRA+SRB+SRC+SRD+SRE1mχ∼ 0600bdominant systematics from theory

t1m~<300W +mm+4001m

χ∼ 0t1m~<500200
1000200

400600800

1000
1200m~t [GeV]1▪ dominant systematics from▪ ISR modeling in tt events→ difference btw MCs▪ multi-jet background

RISR :

0.3-0.4 0.4-0.5

a) Impact on Stop 0L search (high Δm)mχ∼0 [GeV]900~(*) ∼0Top squark pair production, B(t1 → t χ) = 100%
1ATLASSUSY

Observed limit (±1 σtheory)
Expected limit (±1 σexp)

1800
700

17s=13 TeV, 36.1 fb-1ATLAS 20 fb-1, s=8 TeVLimits at 95% CL

mt +SRA+SRB+SRC+SRD+SRE1mχ∼ 0600

t1m~<5001mχ∼ 0bbt̃

Wt

χ̃01

t

1m~

<300p

W +mm+400200t̃

1000p
200

400

600

800

1000
1200m~t [GeV]1▪ dominant systematics from▪ tt events modeling▪ JER, JES, b-tagging

χ̃01t

Wb

direct stop pair production
JHEP 12 (2017) 085

18b) multi large-R jets
Search for massive supersymmetric particles in multi-jet final statesqqpg̃

g̃p

˜0100˜0100qq

RPV SUSY gluino scenarios
qqq

fully hadronic, no MET requirement
many jets (≥ 4/5 large-R jets, b-tag categories)

qqq

total jet mass as main discriminant

Fraction of entries

Phys. Lett. B 785 (2018) 136
0.35

s = 13 TeV, 36.1 fb-1
ATLAS

0.3

Data

0.25

Multijet (Pythia8)
Multijet (Herwig++)

0.2

Multijet (Sherpa)
m~g = 1000 GeV, m∼ = 450 GeVχ

0.15

m~g = 2000 GeV, m∼ = 450 GeV
χ0.1→ fully data-driven estimates(next page)

0.05
00

main background : multi-jet,combinatorics → huge uncertainties

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.82

M ΣJ [TeV]19b) multi large-R jets

▪ the SM mass template obtained in CR ( JHEP 05 (2014) 005 )▪ estimate uncertainties by varying CR definition▪ background estimate uncertainties, ~20%, have a large impact
on the final results

background estimates in SR
EventsPhys. Lett. B 785 (2018) 136

10−1

data
bkg pred ±1 σ
Syst. ±1 σ
m~g = 2000 GeVm∼χ0 = 50 GeV
m~g1= 1900 GeVm∼χ0 = 1050 GeV10236.1 fb-1

10−310−4

Pythia8 non-matched
Pythia8 b-matched
Data non-matched
Data b-matched

10−5600 GeV < p < 644 GeV
T0.5 < |η| < 1.0

10−7

s = 13 TeV, 36.1 fb-1

ATLAS
s = 13 TeV,

10−2ATLAS

5jSR

103

−6−5−4−3−2−10log (m/ p )101N jet ≥ 5|Δη| < 1.4SR1T

Data/bkg pred

Fraction of Entries

jet mass template data vs. MC

104

200.2

0.4

0.6

0.8

11.2

1.4

1.6

1.8

20.2

0.4

0.6

0.8

11.21.4

1.6

1.82

1.5
10.500M ΣJ [TeV]c) displaced vertex search▪ Search for the long-lived gluinos (Split-SUSY scenarios)
Cut and count analysis- Missing ET > 250 GeV- >= 1 Displaced vertex- mDV>10GeV- ntrack>=5- No SM irreducible background expected- Experimental (detector) backgrounds

Phys. Rev. D97 (2018) 052012

non-standard reconstruction

detailed material map needs to be known
to suppress hadronic interaction BG2021c) displaced vertex search▪ data driven background estimaterandom crossing BG estimation

CRmerged vertex

hadronic interaction(low mass region)

however dominant bg comesfrom the hadronic interaction

VRSR

random crossing(high mass region)

there are gases in the detector
gap regions

5-track(4+1)-track
SR Background
prediction

prediction in SR is extrapolated
from low mass region, expo
shape assumed → -100 ~ 300%

need to revisit BG modelings

Personal Remark (request for theory community)▪ Towards HL-LHC, people in experimentalists currently work very
hard on the hardware upgrades and physics prospects analyses▪ Due to the lack of hints/evidences of the new physics yet, we wouldforesee a hard time in keeping the strong momentum during thelifetime of HL-LHC (budget, attracting younger generation…)▪ Precision measurements of Higgs couplings, searches of SUSY ineven higher mass regime (>2TeV) are important and just fine,
but we need something more

▪ I think, we (experimentalists) are desperate for new theoreticalframework (like “SUSY” before the start of LHC) which guide us toa new paradigm in HL-LHC regime22

Summary▪ Theory uncertainties will be major systematics in HL-LHC▪ systematics on signal/background predictions▪ estimation of the fake backgrounds▪ These affect measurements (eg. Higgs) type analyses,
as well as search (eg. BSM) type analyses▪ Need to tackle this: looking for the new higher order
predictions, new methods/modelings to have better
descriptions of data with the simulations▪ Cooperation between experiments and theorists is vital23