Non-SM Higgs Search at DØ

Andy Haas

Columbia University
DØ Experiment

SUSY '05

Durham, UK

Going Beyond the SM Higgs

Hierarchy stability problem:

QFT predicts radiative corrections

How does mh stay << mpl ?

Can the gauge couplings unify?

Supersymmetry enriches the Higgs sector and provides new opportunities for discovery at the Tevatron

Higgs at high tan

Enhanced rare decays (h→)

Higgs Bosons in Supersymmetry

Higgs fields come in pairs (Hu and Hd)

5 Higgs bosons : h, H, A, H+, H-

tan = Hu / Hd

Cross-sections for pp→bbh grow like tan2!

The h is predicted to be light, <~135 GeV

LEP limits on Higgs mass ~ 92 GeV
(not the usual 114 GeV like in the SM...)

LEP limits are much looser (~50 GeV) if
CP-violation is allowed in the Higgs sector...
we assume a CP-conserving Higgs!

At high tan (>~20),
the A is nearly degenerate with the h/H:

BR(A,h/H→bb) =~ 90%
We have focused on bbh(→bb) so far
BR(A,h/H→) =~ 10%
Will be explored in h→ and bbh(→) soon

H

h

A

total

Higgs Mass (GeV)

tanB = 30

tan

A

Highly

degenerate
region

Signal at NLO in QCD

Cross-section (fb)

There are two ways to calculate the signal production at a ppbar collider:

ppbar->bbh (4-flavor scheme)

ppbar->bh (5-flavor scheme) : use b-PDF

Both methods now agree at NLO

Uncertainties from PDF are comparable in size

D0 has performed a measurement to test the predictions of the b-quark PDF calculations

Z+b / Z+j

Z+b is a probe of b-quark PDF 
(Z+b) / (Z+j) = 0.023  0.005
= 0.018 (CTEQ6 prediction)
(DØ – hep-ex/0410078) - PRL. 94, 161801 (2005).

bbh

bh

bbh(bb): Data / Triggering

Custom multi-jet triggers

Level 1:
Three towers with TOT ET > 5 GeV

Level 2:
Three clusters with ET > 8 GeV
and HT >50 GeV

Level 3:
Three jets with ET > 15 GeV with two above 25 GeV in |eta|< 3.0

260pb-1 of good data

87.5 Million events

Includes Run II data up to June 2004

Level 1 : CJT(3,5)

Simulation

Trigger efficiencies measured

using data:
> mu-based unbiased trigger for L1/L2
> special run for L3 study

68-80% efficient for mA of 90-150 GeV

b-Jet Identification

B

IP

Identify jets containing bottom hadrons

main weapon again the huge QCD background

b-hadrons travel ~3 mm before decaying

Their mass leads to an opening angle between tracks --- large IP significances

Additional large IP significance tracks may arise from daughter decays (charms, tau)

High-IP-significance tracks are used to find the secondary vertex(es)

Jets with a secondary vertex in ∆R<0.5 are “tagged” as b-jets

Backgrounds consist of:

mis-tags: poorly reconstructed tracks which randomly happen to form a vertex

long-lived strange / charm decays
or photon to e+e- conversions

“gluon splitting” into nearly collinear charm or bottom pairs

3 mm

b-Tagging Efficiency

The b-tagging efficiency is measured in data and compared to simulations

Very difficult!
(no pure b-jet data sample)

Use the fact that the pTrel spectrum of muons is different for b, c, light – jets

Compare vertex tags to muon tags and extract vertex tagging efficiencies

b-tag efficiency

b-tag efficiency

jet |eta|

jet pT (GeV)

pTrel

muon

bbh(bb): Analysis Method

Signal:

3 or more b-tagged jets

Invariant mass of leading jets is
peaked at mA

Backgrounds:

Determined from data!

Shape estimated from the
double b-tagged data sample
(taking into account the kinematic bias from requiring a 3rd b-tag)

Normalized outside the “signal region”

Also modeled in MC as a cross-check

“fakes”: all light-quark/gluon jets (measured from data)

“heavy flavor”: (ALPGEN)
bbj(j), ccj(j), bbcc, cccc, bbbb

“other”: tt, Z(→bb)+jets (Pythia)

Events with >=3
b-tagged jets

“Signal window”

Triple b-tagged Background

Full multi-jet

data sample

Calculate TRF

(ET & 3 regions of )

Apply TRF to
un-b-tagged jets

Triple b-tagged
background shape

Double b-tagged
data sample

Tag-rate-function (TRF)

Background is completely determined from data !

Triple b-tagged
background

Fit outside the
signal region to data

|eta|<1.1

Jet pT (GeV)

MC Cross-checks

Double b-tag

Triple b-tag

Di-jet mass of leading b-tagged jets (GeV)

Monte Carlo accurately predicts
many other distributions in the
double b-tagged data as well.

g->bb !

Monte Carlo predicts a background
shape and normalization in good
agreement with the triple b-tagged data.

Higgs Widths

Higgs bosons get wider, proportional to tan2

Widths are modeled with BW shape, weighted by cross-section

Not a large effect on sensitivity, for reasonable tan values, after considering kinematic criteria

No
cuts

Kine.
cuts

Kine.
cuts and
3 b-tags

tan=60

tan=30

tan=10

Detector resolution

Mass-splitting of the Higgses

Mass splitting, weighted by inverse
cross-section difference, of h and H

What about when all 3 Higgs are nearly degenerate?

What matters is the shape and height of the invariant mass peak

When cross-sections are significant, the mass-splitting is small compared to the detector resolution

H

h

A

total

Higgs Mass (GeV)

tanB = 30

Highly

degenerate
region

MSSM Beyond Tree-Level

Supersymmetric loop corrections are calculated using “CPSuperH”

Production doesn't scale like tan2... can be faster or slower depending on the supersymmetric model and its parameters

We set limits on tan vs. mA in two of the “benchmark scenarios”:

no mixing and maximal mixing in the stop-quark sector

bbh(→bb) is more sensitive for <0.

But still is still sensitive to >0.

Note: h(→) loses less sensitivity for
>0, since BR(h→) increases

MSSM Limits

Limits set using CLS method (from LEP)

For each mA, set a cross-section limit at 95% C.L.

Cross-section uncertainties are calculated by varying the factorization / renormalization scales, and the PDF sets (CTEQ6)

The current result excludes much more parameter space than our preliminary result from last year

Similar analysis, with more data

Much more rigorous

better reconstruction

improved theoretical understanding

PDF+scale
uncertainty

A Quadruple b-tagged Event

Future of the Analysis

With no analysis improvements, expect to exclude down to tan=40 with 4fb-1

But we also look forward to a much improved analysis with next year's data set (1fb-1)

Inclusion of more triggers

Better calorimeter and jet energy calibration / resolution

Improved b-tagging

Use quadruple b-tagged events

Neural network?

Combine with h() channels?

Combine with CDF?

Lum. (pb-1)

Expected tree-level tan limits

Improving the b-tagging

This analysis is very sensitive to the b-tagging efficiency and the background tagging rate

One obvious way to improve the b-tagging S/B is to use more information about the secondary vertex(es) in each jet

number of tracks on vertex

the 2

the “mass”

decay length significance

number of secondary vertices

... combine into neural network?

Initial studies show large gains in performance are possible

Improved Expectations

Use of a NN for b-tagging and
addition of silicon “Layer 0” for
Run IIb (this fall!)

About a 30% improvement in b-tagging efficiency at the same background rate

Can also decrease the systematic uncertainties by a factor of ~2

More statistics for measuring b-tagging efficiency

Smaller jet energy scale uncertainty

Exclude down to tanB~25

for low mA

Exclude up to mA~200 GeV

for tanB>~50

Some sensitivity up to mA~300 GeV
for very large tanB

Conclusions

A search has been completed for neutral Higgs bosons in the MSSM
using 260 pb-1 of DØ Run II data

Good agreement between heavy-flavor multijet simulations and data

Solid theoretical understanding of the bbh production and decay

hep-ex/0504018 : submitted to PRL!

Now that an initial analysis has been completed, we focus on improving it

Better b-tagging, advanced analysis techniques

New triggers / data – 1 fb-1 by this summer (now!), ~8 fb-1 by 2009!

We hope to make a discovery, or place impressive limits on tan vs. mA in the next few years, while preparing for the LHC era

Also, we are pursuing the tau channels: h→ and bbh(→)

Less loss of sensitivity for >0, complimentary search

Would provide very interesting constraints on MSSM if both the b and tau decays could be measured

Backup slides...

Fermilab Tevatron Accelerator – Run II

1 km radius p-pbar super-syncrotron

World's most powerful: 1.96 TeV

36 bunches of p and pbar

396 ns crossing period

25 cm RMS interaction region

One store every day or so...

DØ

Tevatron Performance

Run II began 4 years ago

Instantaneous luminosity has steadily increased

Last year was excellent, and this year is also right on track

Almost 1 fb-1 delivered so far

Should collect 4-8 fb-1 in the next few years

Current Detector Data / Efficiency

Data range for
this analysis:

260 pb-1 on
multi-jet trigger

The DØ Detector for Run II

Trigger System

Level 1

Calorimeter EM and TOT ET (.2x.2)(-)

Muon stubs

Central high-pT axial tracks

Level 2

Clustered calorimeter EM and TOT ET

Missing transverse calorimeter ET

Matched muon segments

Displaced high-pT axial tracks

Level 3 trigger algorithms:

Jets (no split/merge)

Central stereo tracks

Muons matched to central stereo tracks

Primary vertex

Jet lifetime b-tags

Level 1
2.5 MHz

Level 2

1.6 kHz

Level 3

1 kHz

Tape

50 Hz

Tracking Systems

Cross-check Using Double b-tagged Data

Full multi-jet

data sample

Calculate TRF

(ET & 3 regions of )

Apply TRF to
un-b-tagged jets

Double b-tagged
background

Full multi-jet

data sample

Double b-tagged

data sample

Compare

Contribution from “heavy-flavor” MC

Good agreement in shape.

Normalization of “heavy-flavor” MC agrees to within 10%.

TRF is iteratively corrected for “heavy-flavor”
in the un-b-tagged data sample

Monte Carlo Higgs Spectra

Our Monte Carlo uses Pythia, which is semi-leading-order

The events have been re-weighted, to mimic the NLO kinematics as closely as possible

Comparisons of the bh and bbh processes are in good agreement

bh

bbh

bh (dashed)
bbh (solid)

Comparison of bh
LO to NLO with Pythia

Systematic Uncertainties

Signal efficiency uncertainties
(total = 21%):
b-tagging efficiency (15%)
Trigger efficiency (9%)
Jet energy scale (8%)
Integrated luminosity (6.5%)
NLO kinematics (5%)
Jet reco/ID efficiency (4%)
Jet energy resolution (1%)

Background shape / normalization uncertainties (total = 3%):
TRF shape (2%)
Statistics outside signal window (1%)
Width of signal window (1%)

Events with >=3
b-tagged jets

“Signal window”

Andy Haas

2004-07-07T15:59:13