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Introduction Analysis Results Conclusions Frascati 12 March 2008 Status of analysis F. Ambrosino T. Capussela F. Perfetto Status of analysis.

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Presentation on theme: "Introduction Analysis Results Conclusions Frascati 12 March 2008 Status of analysis F. Ambrosino T. Capussela F. Perfetto Status of analysis."— Presentation transcript:

1 Introduction Analysis Results Conclusions Frascati 12 March 2008 Status of analysis F. Ambrosino T. Capussela F. Perfetto Status of analysis

2 Frascati 12 March 2008 Outline Repeat the analysis with mass constraint before photons pairing Review the correction to the photon efficiency Look at Data /MC comparison for min 2

3 Status of analysis Frascati 12 March 2008 Sample selection OLD approach : 7 and only 7 pnc with 21 ° 10 MeV > 18 ° Kin Fit with no mass constraint P( 2) > MeV < E rad < 400 MeV AFTER PHOTONS PAIRING Kinematic Fit with and mass constraints (on DATA M = MeV/c 2 ) NEW approach : 7 and only 7 pnc with 21 ° 10 MeV > 18 ° Kin Fit with mass constraint ( on DATA M = MeV/c2 ) P( 2) > MeV < E rad < 400 MeV AFTER PHOTONS PAIRING Kinematic Fit with mass constraint

4 Status of analysis Frascati 12 March 2008 OLD - NEW Using the same cuts on min and Pur 75.4% Pur 84.5% Pur 92% Pur 94.8% Pur 97.6% Pur 82.2% Pur 99% Pur 98% Pur 96.3% Pur 91% Low purity Medium I purity Medium II purity Medium III purity High purity

5 Status of analysis Frascati 12 March 2008 OLD - NEW The slope in the efficiency shapes 8% 14% 21% 25% 26% Low purity Medium I purity Medium II purity Medium III purity High purity 8% 14.6% 22.3% 25.3% 26%

6 Status of analysis Frascati 12 March 2008 OLD - NEW RMS = RMS =

7 Status of analysis Frascati 12 March 2008 Efficiency Correction to the photon efficiency is applied weighting the Montecarlo events for the Data/MC photon efficiency ratio 1 exp( E /8.1 )

8 Introduction Analysis Results Conclusions Status of analysis Frascati 12 March 2008 Efficiency (I) Correction to the photon efficiency is applied weighting the Montecarlo events for the Data/MC photon efficiency ratio 1 exp( E /8.1 ) Low purity Medium II purity High purity P1 = P1 = P1 = P1 = P1 = P1 =

9 Introduction Analysis Results Conclusions Status of analysis Frascati 12 March 2008 Photons pairing Recoil is the most energetic cluster. In order to match every couple of photon to the right 0 we build a 2 -like variable for each of the 15 combinations: With: is the invariant mass of i 0 for j-th combination = MeV is obtained as function of photon energies

10 Introduction Analysis Results Conclusions Status of analysis Frascati 12 March 2008 Energy resolution

11 Introduction Analysis Results Conclusions Status of analysis Frascati 12 March 2008 Data – MC RMS A data MC discrepancy at level of 1 2 % is observed. A further check can be done comparing the energies of the two photons in the pion rest frame as function of pion energy

12 Status of analysis Frascati 12 March 2008 Conclusions We are ready to fit and to evaluate the systematical errors in the NEW approach. We have to resolve the Data MC discrepancy on min 2

13 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio in chiral theory The decay occours primarily on account of the d-u quark mass differences and the result arising from lowest order chiral perturbation theory is well known: With : A good understanding of M(s,t,u) can in principle lead to a very accurate determination of Q: And, at l.o.

14 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 The dynamics of the decay can be studied analysing the Dalitz plot distribution. The Dalitz plot density ( |A| 2 ) is specified by a single quadratic slope : |A| z with: E i = Energy of the i-th pion in the rest frame. = Distance to the center of Dalitz plot. max = Maximun value of. Z [ 0, 1 ] Dalitz plot expansion

15 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Dalitz plot expansion

16 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Dalitz expansion: theory vs experiment Calculation Tree One-loop[1] Dispersive[2] Tree dispersive Absolute dispersive Unitary[3] [1] Gasser,J. and Leutwyler, H., Nucl. Phys. B 250, 539 (1985) [2] Kambor, J., Wiesendanger, C. and Wyler, D., Nucl. Phys. B 465, 215 (1996) [3] Borosoy B., Niler R. hep-ph/ v2 (2005) Alde (1984) ± Crystal Barrel (1998) ± Crystal Ball (2001) ± 0.004

17 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Sample selection The cuts used to select: are: 7 and only 7 prompt neutral clusters with 21 ° < < 159 ° and E > 10 MeV Opening angle between each couple of photons > 18 ° Kinematic Fit with no mass constraint P( 2) > MeV < E rad < 400 MeV (after kin fit) The overall common selection efficiency (trigger, reconstruction, EVCL) is = ( )% With these cuts the expected contribution from events other than the signal is < 0.1%

18 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Sample selection

19 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Photons pairing Recoil is the most energetic cluster. In order to match every couple of photon to the right 0 we build a 2 -like variable for each of the 15 combinations: With: is the invariant mass of i 0 for j-th combination = MeV is obtained as function of photon energies

20 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Energy resolution

21 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Matching to s Cutting on: Minimum 2 value 2 between best and second combination One can obtain samples with different purity-efficiency Purity = Fraction of events with all photons correctly matched to 0 s

22 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Samples Pur 84.5% Eff 22 % Pur 92 % Eff 13.6 % Pur 94.8% Eff 9.2 % Pur 97.6% Eff 4.3 % Low purity High purity Medium purity III Medium purity II Pur 75.4% Eff 30.3 % Medium purity I 2 < 10 2 > < 5 2 > 3 2 < 3 2 > 4 2 < 2 2 > 7 No cut on 2 and 2

23 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Efficiency Low purity

24 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Efficiency Medium II purity

25 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Efficiency High purity

26 Reconstructed Phase space Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 The problem of resolution Low PurityHigh Purity

27 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Second kinematic fit Once a combination has been selected, one can do a second kinematic fit imposing 0 mass for each couple of photons.

28 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Fit procedure We obtain an extimate by minimizing The fit is done using a binned likelihood approach Where: n i = recostructed events i = for each MC event (according pure phase space): Evaluate its z true and its z rec (if any!) Enter an histogram with the value of z rec Weight the entry with z true Weight the event with the fraction of combinatorial background, for the signal (bkg) if it has correct (wrong) pairing

29 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Results on MC We have tested the fit procedure on MC by generating samples with different values of the parameter and looking at the result of our fit for these samples:

30 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Results on MC (Low Pur) Fitted region (0,0.6) Fitted region (0,1) Fitted region (0,0.7) Fitted region (0,0.8)

31 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Results on MC (Medium II Pur) Fitted region (0,0.6) Fitted region (0,1) Fitted region (0,0.7) Fitted region (0,0.8)

32 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Results on MC (High Pur) Fitted region (0,0.6) Fitted region (0,1) Fitted region (0,0.7) Fitted region (0,0.8)

33 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Data sample We have analyzed L int = 418 pb 1 of e e collisions collected in the data taking period N 1 = Mevts Low purity N 2 = Mevts Medium I purity N 3 = Mevts Medium II purity N 4 = Mevts Medium III purity N 5 = Mevts High purity

34 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Analysis on data Trying some more systematics checks on the fitting range we got in BIG trouble… Range Low · 10 3 Medium I · 10 3 Medium II · 10 3 Medium III · 10 3 High Pur · 10 3 (0, 1) 18 ± 2 18 ± 3 11 ± 3 8 ± 4 (0, 0.7) 31 ± 3 30 ± 2 26 ± 3 18 ± 4 18 ± 6

35 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Linearity of DATA / MC ratio Check linearity of DATA/MC reco using for MC pure phase space… Nothing really high purity…

36 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Linearity of DATA / MC ratio (II) Idea: check linearity of DATA/MC reco using for MC pure phase space… low purity = High statistics…

37 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 A possible explanation_ The edge of the flat part of the phase space depends in the value of the eta mass. What if its value on data is larger than the nominal one ?

38 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 A toy MC To understand the effect we used a toy MC to generate events with different eta masses: Sample 1 : M = MeV Sample 2 : M = MeV We observe that when the input mass value is used to build z variable the phase space shape does not change. But if one uses M = MeV to build the z variable for sample 2 big deviations are observed…….. Z 2 (547.8)/Z 1 (547.3)

39 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 A toy MC To understand the effect we used a toy MC to generate events with different eta masses: Sample 1 : M = MeV Sample 2 : M = MeV We observe that when the input mass value is used to build z variable the phase space shape does not change. But if one uses M = MeV to build the z variable for sample 2 big deviations are observed…….. Z 2 (547.8)/Z 1 (547.3) Z 2 (547.3)/Z 1 (547.3)

40 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Linearity If the effect is given by the eta mass, correcting for it now all sample should exhibit good linearity for the ratio DATA/MC rec (phase Low purity

41 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Linearity (II) If the effect is given by the eta mass, correcting for it now all sample should exhibit good linearity for the ratio DATA/MC rec (phase High purity

42 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Results on data Let us look at what happens now… RangeLow · 10 3 Medium I · 10 3 Medium II · 10 3 Medium III · 10 3 High Pur · 10 3 (0, 1) 33 ± 2 35 ± 2 33 ± 3 28 ± 3 25 ± 4 (0, 0.7) 33 ± 3 35 ± 3 32 ± 4 26 ± 4 25 ± 6 …..we gained greater stability with respect to the range and purity.

43 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Third kinematic fit We performed a kinematic fit constraining the mass (M = MeV) Range Low · 10 3 Medium I · 10 3 Medium II · 10 3 Medium III · 10 3 High · 10 3 (0, 1) 30 ± 2 31 ± 2 31 ± 3 25 ± 3 26 ± 4 (0, 0.8) 26 ± 2 28 ± 2 28 ± 3 22 ± 4 22 ± 5 (0, 0.7) 26 ± 3 28 ± 3 27 ± 4 21 ± 4 23 ± 5 (0, 0.6) 30 ± 4 31 ± 4 24 ± 5 20 ± 6 Range Low · 10 3 Medium I · 10 3 Medium II · 10 3 Medium III · 10 3 High · 10 3 (0, 1) 30 ± 2 31 ± 2 31 ± 3 25 ± 3 26 ± 4 (0, 0.8) 26 ± 2 28 ± 2 28 ± 3 22 ± 4 22 ± 5 (0, 0.7) 26 ± 3 28 ± 3 27 ± 4 21 ± 4 23 ± 5 (0, 0.6) 30 ± 4 31 ± 4 24 ± 5 20 ± 6

44 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 The systematic check This procedure relies heavily on MC. The crucial checks for the analysis can be summarized in three main questions: I. Is MC correctly describing efficiencies ? II. Is MC correctly describing resolutions ? III. Is MC correctly estimating the background ?

45 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Efficiency (I) Correction to the photon efficiency is applied weighting the Montecarlo events for the Data/MC photon efficiency ratio 1 exp( E /8.1 )

46 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Efficiency (I) Correction to the photon efficiency is applied weighting the Montecarlo events for the Data/MC photon efficiency ratio 1 exp( E /8.1 ) Low purity Medium II purity High purity

47 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Efficiency (II) Further check is to look at the relative ratio between the different samples: N2/N1 exp. =.7263 ±.0002 N3/N1 exp. =.4497 ±.0002 N4/N1 exp. =.3048 ±.0002 N5/N1 exp. =.1431 ±.0001 N2/N1 obs =.7258 ± N3/N1 obs. =.4556 ± N4/N1 obs. =.3140 ± N5/N1 obs. =.1498 ±

48 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Efficiency (III)

49 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Resolution (I) A first check on resolution is from pion mass distribution

50 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Resolution (II) The center of Dalitz plot correspond to 3 pions with the same energy (E i = M /3 = MeV). A good check of the MC performance in evaluating the energy resolution of 0 comes from the distribution of E 0 E i for z = 0

51 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Resolution (III) A further check can be done comparing the energies of the two photons in the pion rest frame as function of pion energy Vs.

52 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Resolution (IV) A data MC discrepancy at level of 1 2 % is observed. Thus we fit filling a histo with: z rec = z gen + (z rec z gen ). A further check can be done comparing the energies of the two photons in the pion rest frame as function of pion energy

53 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Fitting the combinatorial background Idea, try to fit background composition on DATA. To check procedure, we fit background composition on MC: Background fraction (MC) = 15.5 % Background fraction (MC fit) = (15.5 ± 0.2) % Background fraction (MC) = 8.0 % Background fraction (MC fit) = (7.9 ± 0.3) % Background fraction (MC) = 5.2 % Background fraction (MC fit) = (5.2 ± 0.3) % Background fraction (MC) = 2.4 % Background fraction (MC fit) = (2.4 ± 0.4) % Background fraction (MC) = 24.6 % Background fraction (MC fit) = (24.6 ± 0.2) %

54 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Fitting the combinatorial background (II) On DATA: Background fraction (MC) = 15.5 % Background fraction (DATA) = (16.6 ± 0.28) % Background fraction (MC) = 8.0 % Background fraction (DATA) = (8.90 ± 0.37) % Background fraction (MC) = 5.2 % Background fraction (DATA) = (6.0 ± 0.45) % Background fraction (MC) = 2.4 % Background fraction (DATA) = (3.25 ± 1.00) % Background fraction (MC) = 24.6 % Background fraction (DATA) = (26.45 ± 0.26) %

55 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Background Background composition, Medium II purity sample

56 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Systematic uncertainties Effect Low · 10 3 Medium I · 10 3 Medium II · 10 3 Medium III · 10 3 High · 10 3 Res Low E Bkg M Range Purity Tot We take as milestone, for each sample, the fit in the range (0, 0.7)

57 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Results We give the final results for the slope parameter in corrispondence of the sample with 92% of purity: This result is compatible with the published Crystal Ball result: = ± And the calculations from the chiral unitary approach. = ± stat ± syst

58 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Fit residual 2 /ndf = / 17.

59 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Effect of mass constraint in fit Why did this effect not pop up in other experiments analyses? The reason is the effect is much less evident if you constrain in a kinematic fit the mass and then use the value you have constrainedd to build z….

60 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Conclusions If you bless this preliminary result we are ready to prepare a brief paper for LP07. Otherwise……. The MEMO is ready and Giorgio already gave us his comments (This talk is partially upgrade one.) Next step: to perform the kinematic fit imposing mass before the photon pairing, as asked by Giorgio. And then? ……THE END!!!!!!!

61 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Spare

62 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Efficiency I Medium I purity

63 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Efficiency Medium III purity

64 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Results on MC (Medium I Pur) Fitted region (0,0.6) Fitted region (0,1) Fitted region (0,0.7) Fitted region (0,0.8)

65 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Results on MC (Medium III Pur) Fitted region (0,0.6) Fitted region (0,1) Fitted region (0,0.7) Fitted region (0,0.8)

66 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 DATA MC comparison

67 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 DATA MC comparison

68 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Outline

69 Introduction Theoretical tools Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio 2007 Outline

70 Introduction Analysis Results Conclusions Dalitz plot analysis of with the KLOE experiment Frascati 19 Luglio KLOE At KLOE is produced in the process. N ( ) 17 Mevts. The final state for is 7, with almost no physical background. BR( ) =


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