di-higgs, gravitational waves, and lhc · outline 1 why bbvv (v = ;w)? 2 non-resonant sm di-higgs...
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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
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 2 / 32
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?
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 3 / 32
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]
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 4 / 32
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]
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 5 / 32
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]
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 6 / 32
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
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 7 / 32
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!
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 8 / 32
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!
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 9 / 32
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?
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 10 / 32
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
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 11 / 32
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
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 12 / 32
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
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 13 / 32
Collider Analysis
• Jointly tuning cuts+BDT
While BM5 can be discovered, evidence of BM7 can be found@ 14TeV LHC with 3 ab−1!
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 14 / 32
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]
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 15 / 32
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
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 16 / 32
In progress: OptCut
Introducing OptCut... until a better name comes
• A Python package to optimize cut-and-count analysis
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 17 / 32
Thank You!!!
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 18 / 32
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
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 19 / 32
SM Double Higgs Production @ LHC
• Destructive interference between triangle and box diagrams in the SM
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
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 20 / 32
Decay channels
• 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 2σ @ 13TeV HL-LHC
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 21 / 32
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 2σ @ 13TeV HL-LHC
How to beat challenging backgrounds in bbVV channel?
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 22 / 32
Cut-flow for best set of optimized cuts
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 23 / 32
Variables used for BDT
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 24 / 32
Thresholds for joint optimization of cuts+ML
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 25 / 32
Thresholds for sequential optimization of cuts+ML
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 26 / 32
Non-resonant final result
• With cross-checked realistic background simulations
• Taking systematics into account
• Using better AMS metrics
• Jointly tuning cuts+BDT
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 27 / 32
Resonant best-cuts
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 28 / 32
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
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 29 / 32
Non-resonant kinematic distributions
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 30 / 32
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
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 31 / 32
Significance Metrics
Tathagata Ghosh (UHM) Di-Higgs, Gravitational Waves, and LHC September 6, 2018 32 / 32
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