Higgs Measurements at a Muon Collider Higgs Factory [Preliminary] - - PowerPoint PPT Presentation

aconway@fnal.gov Muon Collider Detector Research and Desi gn 1

Higgs Measurements at a Muon Collider Higgs Factory

[Preliminary] Alexander Conway, UChicago Muon Collider Detector Research and Design Group

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Machine Parameters

• Average luminosity:
• Integrated luminosity: (4.2 fb^-1)
• Number of Higgs: 71264
• Beam spread: (0.004%)

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Higgs Parameters

• M_h = 125GeV
• Gamma_h = 4.07GeV

– Br(h->bb) = 0.577 – Br(h->WW*) = 0.215 – Br(h->ta+ta-) = 0.063

• (from LHC Higgs Cross Section Working Group -

arXiv:1201.3084v1)

• Initial state radiation reduces Higgs effective cross

section to 53%

– Cite Estia?

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Channels

• Bb

– ~80% efficiency (compare to ILC Z->bb tagging) – Background from gamma*/Z (do energy cuts? -do both)

• WW*

– H → WW* → l + nu + (l + nu or jj) (~ 54%) – No background

• Tau+tau-

– 100% efficiency? – Background from gamma*/Z (do cuts? - do both)

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Channels b-bbar

• Signal:

– Raw: 18.2pb – 53% ISR * 80% b-tag:

• 7.7pb (assume purity=1)

– 52% (Energy/event shape cuts)

• 4.0pb
• Background:

– Raw: 57.2pb – 80% b-tag

• 42.2pb

– 15% (Energy/event shape cuts)

• 6.3pb

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Channels WW* tau+ tau-

• Require lepton and neutrino with

– Two jets or – Lepton + neutrino

• 54% of WW* events
• h->WW* is

– Raw: 6.8pb – 53% (ISR) * 54% (Br)

• 1.9pb
• Background is

– Nothing (0.001pb because my

program requires non-zero background)

• Perfect tagging?
• h->tau+ tau- is

– Raw: 2.0pb – 53% (ISR):

• 1.1pb

– 80% (Energy/event shape cuts):

• 0.8pb
• Background is

– Raw: 12.8pb – 40% (Energy/event shape cuts):

• 5.1pb

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Channel Signal x-sect (pb) Background x- sect (pb) S/B S/sqrt(B) @ 4fb^-1 Bb – no cuts* 7.7 42.2 0.18 75 Bb - cuts** 4.0 6.3 0.63 101 WW* 1.9 0.001

• ta+ta- - no cuts

2.0 12.8 0.16 35.4 ta+ta- - cuts** 0.8 5.1 0.16 22.4

Cross Sections

*ISR correction and b-tagging applied **Energy and event shape cuts from report

• ISR reduces tau+tau- enough that no cuts is better.

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Data Simulation and Fitting

• Poisson statistics

– Generate random values from Poisson distribution

with expected value of (L/step)*(s+b).

– Error = sqrt(N)

• Data points separated by beam spread
• How many points to take?

– Try different numbers and use however many

• ptimize fit?

– How to quote #Higgs/yr if we are taking most data

• ff-peak?

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Data Simulation and Fitting

• Fit function:

– Breit-Wigner convoluted with Gaussian beam spread, multiplied by ISR

correction and branching fraction, plus background cross section, times integrated luminosity per point.

• Fitting algorithm:

– Residual: [(fit – data)/(data error)]^2

• Minimize residual (Pearson's cumulative chi-square test statistic) with MIGRAD

– Find errors in MIGRAD fit with MINOS

• Full non-parabolic error calculation
• Free Parameters:

– Higgs mass, Higgs width, branching fraction

• Given Parameters:

– Integrated luminosity, background cross section, signal efficiency, beam

spread, initial state radiation correction

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Data Simulation and Fitting Quality of Fit

• Simulate new data and

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B-bbar with cuts

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Channel Signal x- sect (pb) Background x-sect (pb) Fitted Mass (MeV) Fitted Width (MeV) Fitted Branching Fraction Bb – no cuts* 7.7 42.2 0.06+-0.3 3.9+-0.5 0.58+-0.01 Bb - cuts** 4.0 6.3 0.10+-0`.14 4.14+-0.3 0.583+-0.005 WW* 1.9 0.001 0.27+-0.02 ta+ta- - no cuts 2.0 12.8 ta+ta- - cuts** 0.8 5.1

Data Simulation and Fitting

*ISR correction and b-tagging applied **Energy and event shape cuts from report

• ISR reduces tau+tau- enough that no cuts is better.