di-higgs, gravitational waves, and lhc · outline 1 why bbvv (v = ;w)? 2 non-resonant sm di-higgs...

Di-Higgs, Gravitational Waves, and LHC

Tathagata Ghosh

University of Hawaii at Manoa

A. Alves, T.G., K. Sinha, Phys. Rev. D96 035022 [arXiv:1704.07395]A. Alves, T.G., H. Guo, K. Sinha, arXiv:1808.08974

A. Alves, T.G., H. Guo, K. Sinha, [In progress]

Double Higgs Production at Colliders Workshop

FermilabSeptember 6, 2018

Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 1 / 32

Outline

1 Why bbVV (V = γ,W )?

2 Non-resonant SM di-Higgs in bbγγ channel

3 EWPT: Di-Higgs and Gravitational Wave

4 Resonant di-Higgs in bbγγ channel @ GW BMs

5 Resonant di-Higgs in bbWW channel @ GW BMs


LEFT = −κλλvh3 − mtv

(v + κth + c2

v hh)tt + αs

12

(cgh − cgg

2v hh)G aµνG

aµν

Trilinear coupling only: κt = 1, c2 = cg = cgg = 0

• hh→ bbbb: largest BR, ∼ 34%, large QCD backgrounds

• hh→ bbW+W−: decent BR, but tt is a tough background to beat

• hh→ bbτ+τ−: promising with efficient τ, b-tagging

• hh→ bbγγ: BR ∼ 0.14%, but it’s very clean!

• bbγγ has the best prospects, around 1.5 σ @ 13TeV HL-LHC

How to beat challenging backgrounds in bbVV channel?


Non-resonant SM di-Higgs in bbγγ channel

Backgrounds:

• Continuum bbγγ: Irreducible one, εb = εγ ∼ 0.7

• Higgs backgrounds: tth, bbh, Z (bb)h

• jjγγ: p(j → b) = 0.015 Azatov et. al.[1502.00539]

• ccγγ: p(c → b) = 0.3

• bbγj : p(j → γ) ∼ 10−4

• hadronic ttγ ATLAS [ATL-PHYS-PUB-2014-019]

Simulation:

• We simulate signal with MadGraph5 aMC@NLO at LO with full mt

effect

We use NNLO K-factor of 2.27 to start with production cross-sectionof 36.8 fb de Florian and Mazzitelli [1305.5206]


Important kinematic variables

pT (b), pT (γ)

Mbb,Mγγ

pT (bb), pT (γγ)

Mbbγγ

∆R(bb),∆R(γγ),∆R(bγ)

A combination of these variables were used by previous studies

All previous studies point towards . 2σ significance @ 14 TeV LHC with 3 ab−1

luminosity using the same BG normalizations (first 5 BGs used)

Baur et. al. [0310056], Baglio et. al. [1212.5581], Wagner et. al. [1512.00068] Azatov et. al. [1502.00539],ATLAS [ATL-PHYS-PUB-2014-019]


How to get better prospects?

• Expensive solution: a bigger machine, 27, 100 TeV

• Multivariate Statistical Analysis

• Combine many search channels

• Machine Learning: BDT, Deep Learning, etc

• Alves, Ghosh, Sinha approach: Optimized cuts+BDT [1704.07395]


Cut-and-count, an art?

• Most widely employed technique by phenomenologists

• How is it exactly done? By eye! Huge waste of data ??

200 300 400 500 600 700 800 900 1000Mbbγγ [GeV]

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

∆R

(γ,γ

)

continuum bbγγ

100

101

102

103

200 300 400 500 600 700 800 900 1000Mbbγγ [GeV]

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

∆R

(γ,γ

)

hh→bbγγ

100

101

102

103


Cut-and-count should be a science!Tuning cut thresholds

• Simple idea: let’s tune the cut thresholds!

• Problem :( prohibitively large grids, O(1014) points

• Solution ;) let’s ask data scientists

• Random search

1.0 1.5 2.0 2.5Signal Significance (σ)

0

20

40

60

80

100

120

140

Freq

uenc

y

best

man

ual s

earc

h

No BDT Classification, Random search1000 trials

• Amazing! Human tuning is not better than average randomsearch!


Tuning cut thresholds – better than Random Search

• Bayesian Optimization to find maximum Significance(~x)

• TPE =⇒ HyperOpt

• The objective is to optimize some significance metric Ω(x)

• TPE models the objective function by a probabilistic surrogate function

• With more trials the algorithm better models the objective function learnigfrom past trials

∼33% improvement compared to generic cut and count result!


Using BDTs: Cuts+ML

• AI algorithms like BDT and DNN improve event classification

• BDTs are faster and easier to train, used by LHC collaborations

• Many tools are in the market, TMVA, Sklearn, XGBoost

• Using ML after only basic object identification cuts left us with toosmall a S/B

• Some kinematic cuts are needed to clean the sample of BG

• Why not optimize cuts and ML tool at the same time?


Cuts+ML

• Tuning cut thresholds and ML hyperparameters

• Another huge improvement in significance!

Taking systematic uncertainties into account

• If S/B is small, systematics become important

• HyperOpt selects a different cut-strategy to increase S/B....softeningthe effect of systematics

With 10% systematics we get ∼ 3.5σ


Resonant di-Higgs: EWPTxSM: SM + Singlet Scalar

V (φ, S) = −µ2H†H + λ(H†H)2 +a1

2H†HS

+a2

2H†HS2 +

b2

2S2 +

b3

3S3 +

b4

4S4

Huang et. al. [1701.04442]

Large SNR for LISA found for BM5, BM7, BM8 and BM9


xSM: Gravitational Waves

The total GW energy spectrum

ΩGWh2 ' Ωcolh2 + Ωswh

2 + Ωturbh2

We address several subtle issuespertaining to the bubble wallvelocity and the hydrodynamics ofthe plasma, in particular thetension between requiring bubblewall velocities small enough toproduce a net baryon numberthrough the sphaleron process, andlarge enough to obtain appreciablegravitational wave production.

We obtain GW inspired BMs forcollider study

10-5

10-4

0.001 0.010 0.100 110

-19

10-16

10-13

10-10

10-7

f(Hz)

ΩGWh2

UDECIGO

soundwaves

turbulence

BM5

500 600 700 8000.01

10

104

mh2(GeV)

SNR

LISA

TaijiTianQin

DECIGO

UDECIGO

BBO


Collider Analysis

• Jointly tuning cuts+BDT

While BM5 can be discovered, evidence of BM7 can be found@ 14TeV LHC with 3 ab−1!


Resonant di-Higgs in bbWW channel @ GW BMs

• For Mh2 > 600 GeV significance in bbγγ channel looses sensitivity

• We plan to use bbWW channel for higher mass BMs to exploit thetwo largest BRs of the 125 GeV Higgs

tt is an irreducible background – hard to beat

Due to the presence of νs in the final state it is difficult toreconstruct h2 mass

Preliminary results:

• For BM5 we have 1.7σ with 10% systematics

Need to use new kinematic variables like Heavy Mass Estimator toreconstruct h2 mass better Huang et. al. [1701.04442]


Further research

A full scan of xSM to find optimal benchmarks to showcomplementarity between bbWW channel and Gravitational Waves

Implement full Higgs EFT in our non-resonant analysis framework


In progress: OptCut

Introducing OptCut... until a better name comes

• A Python package to optimize cut-and-count analysis


Thank You!!!


Measure its properties like spin and couplings

Determine its total width and observe all the decay channels

Study its self-interactions vacuum stability, electro-weak phasetransition, BSM

V (|H|2) = −µ2|H|2 +1

2λ|H|4 (H → h(x) + v)

= V0 + m2hh

2 + λhhhhhh + λhhhhhhhh


SM Double Higgs Production @ LHC

• Destructive interference between triangle and box diagrams in the SM


(v + κth + c2

v hh)tt + αs

12

(cgh − cgg

2v hh)G aµνG

aµν



Decay channels





• bbγγ has the best prospects, around 2σ @ 13TeV HL-LHC



(v + κth + c2

v hh)tt + αs

12

(cgh − cgg

2v hh)G aµνG

aµν






• bbγγ has the best prospects, around 2σ @ 13TeV HL-LHC

How to beat challenging backgrounds in bbVV channel?


Cut-flow for best set of optimized cuts


Variables used for BDT


Thresholds for joint optimization of cuts+ML


Thresholds for sequential optimization of cuts+ML


Non-resonant final result

• With cross-checked realistic background simulations

• Taking systematics into account

• Using better AMS metrics

• Jointly tuning cuts+BDT


Resonant best-cuts


xSM: EWPT

xSM: SM + Singlet Scalar

V (φ, S) = −µ2H†H + λ(H†H)2 +a1

2H†HS

+a2

2H†HS2 +

b2

2S2 +

b3

3S3 +

b4

4S4

iλh1h1h1= 6[λvc3

θ +1

4c2θsθ (2a2vs + a1) +

1

2a2vcθs

2θ

+1

3s3θ (3b4vs + b3)

],

iλh1h1h2=

1

2

[− 2cθs

2θ (2a2vs + a1 − 6b4vs − 2b3)

+4v (a2 − 3λ) c2θsθ + c3

θ (2a2vs + a1) − 2a2vs3θ

]

λh1XX = cθλSMh1XX

The gauge invariant effective potential is found to be:

V (h, s,T ) = −1

2[µ2 − Πh(T )]h2 −

1

2[−b2 − Πs (T )]s2

+1

4λh4 +

1

4a1h

2s +1

4a2h

2s2 +b3

3s3 +

b4

4s4,

The thermal masses are given by

Πh(T ) =

(2m2

W + m2Z + 2m2

t

4v2+λ

2+

a2

24

)T 2,

Πs (T ) =

(a2

6+

b4

4

)T 2

Independent parameters: vS ,mh2 , θ, b3, b4


Non-resonant kinematic distributions


Resonant kinematic distributions

200 300 400 500 600 700 800 900 1000Mbbγγ [GeV]

10-4

10-3

10-2

1/σdσ/dM

bbγγ [G

eV−

1]

BM5BM7bbγγ

Zh

tth


Significance Metrics


di-higgs, gravitational waves, and lhc · outline 1 why bbvv (v = ;w)? 2 non-resonant sm di-higgs...

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