Status of K s 3 0 analysis

Status of Status of KKss 3 3 0 0 analysis analysis

M. Martini, S. Miscetti

Summary of work in progress

Data-MC calibration of 22 and 2

3

New fit procedure for bkg

Systematics on bkg determination

time-scale for the paper

M. Martini, Kaon meeting November 23rd 2004 2

Summary of work in progress

• Almost all the questions posed by Matt have been attached

• The MC production 2004 have been successfully used after calibration of the energy scale as shown in the past meeting. We now refer as:

-- OLDMC the production AllPhys+NeuKaon 2003 -- NEWMC the poduction AllPhys+NeuKaon 2004

For a whole MC Luminosity of 450x2 pb-1. Considering the kcra (MC/data)= 50% vs 30% we gain another factor 5/3. Whole MC eff.Lumi 1500 pb-1

• We have modified/added some steps in our analysis to simplify and improve the procedure for the bkg calibration.

• We believe that the background studies is now COMPLETE

• Tomorrow we will have a private meeting with the referees to show in further details the analysis status and if we agree in all points we start immediately to update the memo.


DATA MC

DATA MC

M

EE

M

Calibration of 22 and 2

3

In the construction of the 2 we have used, up to now, the values ofE and M observed in a golden sample of KS20 events.

We have now modified this in the analysis using a different sigma for each sample. DATA and MC (OLDMC, NEWMC) (2001 ,2002 ).


New calibration procedure for fakes

One of the criticized step of our analysis is the determination of thequantity of fake KCRASH. Two questions were posed:

1) Quantify the statistical error connected to the calibration:

2) Evaluate the systematic on fake determination due to the range used for fit.

Instead of using our old standalone recipe we move to fittingthe 1D-plots with HMCMLL inserted in a standalone Minuit program.Statistics of data and MC sample are now considered in the fitting procedure and an error is assigned to the resulting fake content.

Instead of trying all possible cuts we decided to use a 2D-Fit. We have translated a 2d-Histogram of 20x40 bins in 1D-Histogram of 800 bins and used the standard HMCMLL procedure.


New fake-calibration procedure

In the new calibration we use 2D histogram with an

almost entire scale

Old SBox definition:

14<22<40

23<3.5

23

22


New Fake-Acci-Split calibration procedure

To better calibrate DATA and MC, we have also questioned how well the MC reproduces the amount of double shower fragments and double accidental clusters. To understand and calibrate this we have divided the MC Kcrash events into 2 further classes:

2A: events of Ks20 in overlap with 2 accidental (~ 60% )

2S: events of Ks20 with 2 splitted clusters or 1 accidental + 1 splitted cluster (~ 35%)

To do this, we perform a 3 components fit (2S, 2A and fake events)



23

22

23

23 2

3

22

22

22

ALL 2 S

2 A Fake



Bin Number Bin Number


ALL 2 S

2 A Fake



• Data

• FIT



We remind that the calibration is carried out separately for the different samples:

- NEW 2001- NEW 2002- OLD 2001- OLD 2002

For each sample we now have 3 weights with a wholecorrelation matrix



For a single sample this is a typical fit result

NEWMC 2001

Fact E fact 2s 2a fake

2s 0,409 0,011 2s 1 -0,313 -0,161

2a 0,551 0,01 2a -0,313 1 -0,062

fake 0,788 0,064 fake -0,161 -0,062 1

DATA data MC MC EV TOT tot EV 2s 2s EV 2a 2a EV fake fake

119 11 115 11,5 165 13 15 4 40 6 110 102647 51 2479 47,0 4919 70 1757 42 3083 56 79 9178 13 178 18,4 229 15 3 2 6 2 220 154534 67 4386 98,2 10042 100 8401 92 1444 38 197 14169 13 194 10,9 352 19 38 6 289 17 25 5

12595 112 12760 220,0 23756 154 2506 50 21119 145 131 11

sample Correlation matrix ijWeights Wi with errors Wi

Ndata with error

expected from MC

Events of each type Ni with errors Ni

2 2

,

2i iW i i N W i W j i j ij

i i i j

N W N N


Result of Fake-Acci-Split calibration

A good agreement is observed in each scatter plot region

DATA-- MC 2

2<14

22>402

2<40

ALL

23

23

23 2

3


DATA-MC comparison at beginning of ana

Summing up 2001-2002 for each MC, we can compare DATA with the two different MC productions.

DATA data MC MC

282 17 280 17,6

5037 71 4721 59,3

452 21 425 27,1

10132 101 9919 145,6

326 18 376 13,9

22309 149 22540 269,6

DATA data MC MC

282 17 282 18,9

5037 71 4829 61,5

452 21 411 26,9

10132 101 9879 146,9

326 18 378 14,2

22309 149 22432 266,8

NEW OLD

A reasonable data-MC comparison is found for both samples.

SboxCSbox

UPCup

Down

CDown


Result of Fake-Acci-Split calibration

UP CUP

CSbox

Cdown

Sbox

Down


E

Review of the analysis chain

Since we have observed a little difference on E between DATA and MC (and we have correct this effect into 2 definition), we have changed E_CUT into E_CUT/E.

E/E

E/ETrack Veto 2fit Sbox countingOptimiz

ECUTTrack Veto 2fit Sbox counting

optimization

OLD

NEW


Events rejected by Track veto

E/E

DATA-- MC


Events retained afterTrack veto

E/E

DATA-- MC


Optimization

The optimization is done with the usual technique with a factortwo improvement on the MC statistics thus reducing the Discretization problem.

In this case we obtain the best ratio between surviving background and signal efficiency with the following set of cuts:

2fit < 40.43

E/E > 1.69

23 < 4.64

22 < 60

In this way we have a signal efficiency sig = (24.8 ± 0.8stat )%

and we found 2 events with 3.1 ± 1.6stat expected by MC


Data-MC comparison after optimization

DATA-- MC

22<14

22<402

2<40

ALL

23 2

3

23

23


DATA data MC MCEV

TOT tot EV 2s 2s EV 2a 2a EV fake fake

2 1 3,125 1,6 17 4 14 4 2 1 1 1

520 23 446,5 20,1 2402 49 1763 42 634 25 5 2

0 0 0 0,0 0 0 0 0 0 0 0 0

4 2 3,2 1,6 17 4 17 4 0 0 0 0

3 2 2,45 1,6 11 3 5 2 5 2 1 1

326 18 388,5 19,2 1961 44 534 23 1424 38 3 2

Data-MC comparison after optimization

Comparison between DATA and MC after the optimization procedure.


Evaluation of Systematic errors on bkgTo evaluate systematic error, we perform our analysis changing the most relevant parameters

1) Increase E and M to E+E and M+M

2) Decrease E and M to E-E and M-M

3) We correct in the MC the little data-MC shift on the average MC values found in the control sample Ks20.

5) Use the fit parameters calculated including also the signal box

6) Use the fit parameters calculated not distinguishing between 2S - 2A


Evaluation of Systematic errors on bkg 2fit

From optimization we obtain:

2fit < 40.5

We search the value for MC cut which gives the some retain integral observed in DATA. We obtain a variation of +5%.

-- DATA

-- MC

2fit


Systematic errorWe have evaluated the events shift in each box:

type sbox sbox % csbox csbox % up up % cup cup % down dwn % cdown cdwn %

Ana 3,13 0,00 447 0,00 0 0,00 3,20 0,00 2,45 0,00 389 0,00

+ 3,33 6,56 441 -1,25 0 0,00 3,20 0,00 2,45 0,00 382 -1,83

– 3,19 1,92 452 1,12 0 0,00 3,40 6,25 2,65 8,16 397 2,06

mean 3,34 6,72 455 1,79 0 0,00 3,25 1,56 2,65 8,16 411 5,79

Sbox 3,14 0,48 444 -0,58 0 0,00 3,21 0,34 2,48 1,02 388 -0,23

2com 3,11 -0,40 480 7,43 0 0,00 3,88 21,38 2,35 -4,06 390 0,44

2 3,33 6,56 471 5,49 0 0,00 3,55 10,94 2,45 0,00 399 2,70

6,9812,2824,860,009,5711,63


Time scale for paper …

• From our side the evaluation of the bkg has been completed and all suggestions/critiques of referees have been taken into consideration. However, tomorrow we will have a long meeting to go much further in detail on each item with the referees.

• We have another week of work to do in addressing the questions related to the systematics on the efficiency for the signal and the normalization.

• We expect to complete the revision of the analysis for first week of December.

• next week we start updating the memo for the background side. and then we will give it back to the referees for final approval.

• Plan is to have a complete memo for mid-Dicember and a first PLB for x-mas


Conclusions

• We have successfully calibrated and used the whole new and old MC production so doubling the statistics for the BKG evaluation.

• Most of the referees comments on the bkg determination pushed us to improve and clean our technique which now seems to us to be very stable showing satisfactory data-MC comparisons.

• We have other two weeks of hard work to complete the syst. on the evaluation of signal efficiency and normalization

• Planning to have a paper as a x-mass gift.


OLD calibration procedure

Both calibration done excluding

signal box. We use the mean value of weights.

Normalization 1

with

Normalization 2

with

CKcraMC

Fake

CKcraMC

Fake

Documents

Status of K s 3 0 analysis