pT Spectra

Jaiby Joseph04/18/2011

Method

Signal(1.82 < Mass < 1.92)

Bkg_Left1.75 < Mass ≤ 1.8

Bkg_Right1.94 ≤ Mass < 1.99

Subtract the background pT distribution (Sum of left and right) from the signal pT distribution in the above shown ranges. Normalize the background using the Background fitted function in the signal region

pT distribution of D0+D0bar

Log scale

Log scale

No normalization of B

Linear scale

1/pT(d2N/dpTdy) Vs pT1/pT(d2N/dpTdy) Vs pT

(d2N/dpTdy) Vs pT (d2N/dpTdy) Vs pT

Linear scale

€

1NEventspT

d2NdydpT

No normalization of B

pT spectra with B normalization

Normalization: To do the normalization

a) Count the number of entries under the B fit function from 1.82-1.92b) Get the histogram counts from 5 bins on Left+Right (1.75-1.8)+(1.94-1.99)c) Normalize the background pT distribution histo with (a/b)

1. I get 5095171 counts from the summed pT distribution of Left+Right of D0+D0bar2. I get 5227370 counts under the B fit function in the Inv Mass peak region of D0+D0bar3. Normalize (1) with (2).

0-10%

MinBias1. I get 8652207 counts from the summed pT distribution of Left+Right of D0+D0bar2. I get 8873550 counts under the B fit function in the Inv Mass peak region of D0+D0bar3. Normalize (1) with (2).

Unweighed pT Spectra of 0-10%

Before B normalization B Normalized

Weighed pT Spectra of 0-10%

Before B Normalization After B Normalization

Unweighed pT Spectra of MB

Before B Normalization After B Normalization

Weighed pT Spectra of MBBefore B Normalization After B Normalization

0-10%

MB

€

1NEventspT

d2NdydpT Done with Normalized Bkg

Back-UP

Raw Histograms of 0-10%, pT weighed spectra

pT weighed 0-10%D0_bkgLeftD0_bkgRight

D0bar_bkgLeft D0bar_bkgRight

Continued…

Subtracted (0-10%)

€

1pT

d2NdydpT

The subtracted counts (# of entries) should be 155867

Inv Mass for pT slices0.1 < PtD0 < 0.5

0.5 < PtD0 < 0.9

0.9 < PtD0 < 1.5

PtD0 > 1.5