p17 ZH -> mumu bb Analysis
w/ Neural Net Event Selection

Andy Haas
Columbia University

Higgs Meeting

D0 Collaboration Week

March 8, 2007

Analysis Updates

Reprocessed full p17 dataset (900->1.1/fb,
by adding cable-swap, latest SAM definitions, etc.)

Using the "correction factors" for ALPGEN MC incl. samples (divide xs by 1.5)

Add more tt,ZZ,WZ MC – nearly 1M each now

Loosen some analysis cuts:

- Removed the Zpt>20 GeV cut

- Go down from 15->10 GeV for muons from the Z

Use 4-vector inv. mass calculation for jets

- 5-10% better resolution

- will be studied extensively in the near future

Use certified p17 b-ID TRFs

Run b-tagging on smeared MC jets

More Updates

Do Z pT re-weighting. A data/MC ZpT ratio is derived

in untagged Z+2jet (data - QCD) and MC

and applied back to the Z+Xlp MC samples

Recalculate QCD fractions in 0,1,2 b-tagged samples

- Use non-isolated Z's to get shapes of QCD backgrounds...

0 b-tags (qcd is 3.2%)

2 b-tags (qcd is 27%)

isolated

non-isolated

isolated

non-isolated

1 b-tags (qcd is 3.7%)

QCD Background Fractions

QCD

Z+bb

QCD is significant at large Mjj... interesting!

Mjj (GeV)

Zero b-Tagged Comparison

Mjj (GeV)

Double b-Tagged Channel

old

new

This is just with simple +-1.5 sigma cut on Mjj to set limits.

Improvement will be greater after NN, since we've loosened other cuts.

Mjj-Cut-Based Results

Exp./SM ratio

Single-tag

Combine results of VERTIGHT&&!2L4 with 2L4 tagging

-Find the probability for there to be a second loose tag in the event, given that exactly one jet has actually been tight-tagged:

secprob

- Overall probability for the event to be double loose-tagged is conserved:

ploose2b = p0b*X + p1b*secprob + pgte2b*1,

where p0b,p1b,pgte2b are the probabilities for the event to have 0,1,>=2 tight-tags

X is the probability for the event to have 2 loose-tags, given that it has 0 tight-tags.

X= (ploose2b-p1b*secprob-pgte2b*1)/p0b

Mjj (GeV)

Single-tag QCD

0 VERYTIGHT && !2 L4 b-tags (qcd is 3.4%)

isolated

non-isolated

isolated

non-isolated

1 VERYTIGHT && !2 L4 b-tags (qcd is 3.3%)

**small compared to 27% for 2 L4 tags**

Single-tag Mjj-Cut-Based Results

single-tight

&& !double-loose

b-tagged

double-loose

b-tagged

By combining with single-tag,

equivalent to adding ~1/(s/d)^2=~60--40% more luminosity!

For ZZ, Exp./SM~ 8.3 after s+d, ~5.8 after mu+e combination, ~4.9 after NN ...

M_bb

Inv. mass of two b-tagged jets

expect these to be the jets from the Higgs

Data: plot M of all b-tagged jet pair combinations
(normalized to one entry per event)

MC: plot M of all jet pair combinations, weighted by the probability for the pair to be b-tagged given that some pair is b-tagged, times the probability for the event to be double b-tagged

For the NN, have to sample these distributions and select only one M_bb value per event

M_bb

M_jj

M_bb vs. M_jj

Very little difference

in signal or di-jet

MC samples

(less high mass tail

in signal)

M_bb is shifted to

lower values in

bb+jet events in MC

Neural Net Event Selection

Semi-optimized variable set and NN training (#hidden / topology, iterations, method)

Variables:
M_bb, pt1, pt2,
zdr – dR between muons from Z
deta, dphi – angles between jets
zeta – centrality of Z
met, set – discriminate tt

Trained on MC, with QCD from data

Background events are weighted for training according to their probability to be in the double(single)-tagged event sample

Signal events are weighted for training such that the total signal == total background

1/2 of events are used for training, rest for testing (and eventually setting limits)

Events and weights are saved in a “simple” ntuple, which others can also use to test their own multivariate discriminators

NN output

Untagged

NN output

0VT&&!2L4

NN output

Single-tight-tagged

1VT&&!2L4

NN output

Double-loose tagged

2L4

Significance

Find an optimal cut on the NN that maximizes S/sqrt(B).

Measure the ratio of S/sqrt(B) for this cut, vs. only an Mjj cut of +-1.5 sigma.

single-tag

double-tag

Conclusions

Many technical improvements made

QCD shape measured in non-isolated data

Combined single-tight and double-loose b-tags - gain ~50% in luminosity

Develop M_bb variable – gain of ~13% in luminosity

NN working pretty well – gains of ~100% in luminosity

Limits will be about 2x better (4x luminosity!) than our preliminary results!

Limits on ZZ –> will need ~5 times the p17 sensitivity to see ZZ->llbb

Need to update the analysis note

Time to coordinate with electrons (Fu) and publish

Backup

Old, btagging->JSSR

New, JSSR->btagging

pT of second-leading jet (GeV)

pT of second-leading jet (GeV)

Fabrice pointed out that one really should be tagging the smeared MC jets,

because there's a taggability cut of pT>15 GeV in data and MC.

Only smeared jets are fair to compare to data.

What is the effect?

0 b-tags (L4)

Old, btagging->JSSR

New, JSSR->btagging

pT of second-leading jet (GeV)

1 b-tags (L4)

Old, btagging->JSSR

New, JSSR->btagging

Better agreement (at low pT) when tagging smeared MC jets...

pT of second-leading jet (GeV)

>=2 b-tags (L4)

Andy Haas

2004-07-07T15:59:13