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Introduction  b observation  b search Summary August 28th, 2008W&C Seminar1 August 28 th, 2008W&C Seminar at Fermilab1 Eduard De La Cruz Burelo CINVESTAV.

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Presentation on theme: "Introduction  b observation  b search Summary August 28th, 2008W&C Seminar1 August 28 th, 2008W&C Seminar at Fermilab1 Eduard De La Cruz Burelo CINVESTAV."— Presentation transcript:

1 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar1 August 28 th, 2008W&C Seminar at Fermilab1 Eduard De La Cruz Burelo CINVESTAV IPN Mexico On behalf of the D0 collaboration Observation of the doubly strangeb-baryon  - b Observation of the doubly strange b-baryon  - b Outline: Introduction  Introduction   b observation   b search  Summary

2 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar2 The  - (sss) discovery (1964) The Eightfold way SU3

3 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar3 What energies we will looking at? TeV MeV few GeV GeV Z’,W’,KK modes, etc. Z, W, top, Higgs? Do we miss something here?

4 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar4 What energies we will look at? TeV MeV few GeV GeV B Physics Bs Mixing, CKM, lifetimes, etc.

5 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar5 B baryons at the Tevatron Unique to Tevatron (not produced in B factories) B baryons expected to be produced copiously at the Tevatron Only  b was considered as observed back in 2001 ~20 events. Interesting mass predictions using different models. However, very challenging.  b (bud)  b 0 (bud)  b + (buu)  b - (bdd)  b 0 (bus)  b - (bds)  b - (bss) J=1/2, 1 b Not yet observed

6 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar6 When Tevatron Run II begun: NotationQuark contentJPJP SU(3)(I,I 3 )SMass b0b0 b[ud]1/2 + 3*(0,0)  1.2  1.2 MeV b0b0 b[su]1/2 + 3*(1/2,1/2)5.80 GeV b-b- b[sd]1/2 + 3*(1/2,-1/2)5.80 GeV b+b+ buu1/2 + 6(1,1)05.82 GeV b0b0 b{ud}1/2 + 6(1,0)05.82 GeV b-b- bdd1/2 + 6(1,-1)05.82 GeV b0’b0’ b{su}1/2 + 6(1/2,1/2)5.94 GeV b-’b-’ b{sd}1/2 + 6(1/2,-1/2)5.94 GeV b-b- bss1/2 + 6(0,0) GeV b*+b*+ buu3/2 + 6(1,1)05.84 GeV b*0b*0 bud3/2 + 6(1,0)05.84 GeV b*-b*- bdd3/2 + 6(1,-1)05.84 GeV b*0b*0 bus3/2 + 6(1/2,1/2)5.94 GeV b*-b*- bds3/2 + 6(1/2,-1/2)5.94 GeV b*-b*- bss3/2 + 6(0,0) GeV from hep-ph/

7 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar7  (*)- b in October 2006 CDF announced the observation of the  b ’s with 1.1 fb -1 PRL 99, (2007)

8 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar8  - b observation Last year:  - b observation Number of events: 15.2 ± 4.4 Mass: ± 0.011(stat) GeV Width: ± GeV Signal Significance: We also measured: PRL 99, (2007)

9 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar9  - b observation Last year:  - b observation Signal significance = 7.8  Also searched for in  b -  c 0  - M(  b - ) =  2.5 (stat)  1.7 (syst) MeV/c 2 PRL 99, (2007)

10 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar10 During Tevatron Run II NotationQuark contentJPJP SU(3)(I,I 3 )SMass b0b0 b[ud]1/2 + 3*(0,0)  1.6 MeV b0b0 b[su]1/2 + 3*(1/2,1/2)5.80 GeV b-b- b[sd]1/2 + 3*(1/2,-1/2)  3.0 MeV b+b+ buu1/2 + 6(1,1)  2.7 MeV b0b0 b{ud}1/2 + 6(1,0)05.82 GeV b-b- bdd1/2 + 6(1,-1)  2.0 MeV b0’b0’ b{su}1/2 + 6(1/2,1/2)5.94 GeV b-’b-’ b{sd}1/2 + 6(1/2,-1/2)5.94 GeV b-b- bss1/2 + 6(0,0) GeV  b *+ buu3/2+6(1,1)  3.4 MeV b*0b*0 bud3/2 + 6(1,0)05.84 GeV b*-b*- bdd3/2 + 6(1,-1)  2.8 MeV b*0b*0 bus3/2 + 6(1/2,1/2)5.94 GeV b*-b*- bds3/2 + 6(1/2,-1/2)5.94 GeV b*-b*- bss3/2 + 6(0,0) GeV

11 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar11 B hadron observation status Mesons: –B +, B 0, B s, B c + (before Tevatron RunII) –B* (before Tevatron RunII) –B d **(Tevatron RunII) –B s ** (Tevatron RunII) Baryons: –  b (before Tevatron RunII) –  b +, and  b *+ (Tevatron RunII) –  - b (Tevatron RunII)

12 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar12 Data In this analysis we use 1.3 fb -1 of data collected by DØ detector (RunIIa data). Thanks to the Fermilab Accelerator division for doing wonderful work. Muon and central tracker subdetectors are particularly important in this analysis

13 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar13 How did we look for the  - b ? ++ -- p -- -- --  -b-b ~5 cm  - b → J/  +  - ~0.7 mm

14 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar14 Data reprocessing   p  When tracks are reconstructed, a maximum impact parameter is required to increase the reconstruction speed and lower the rate of fake tracks. But for particles like the  b -, this requirement could result in missing the  and proton tracks from the  and  - decays  

15 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar15 Increase of reconstruction efficiency Opening up the IP cut: (Before) ( After ) GeV D0

16 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar16  b Reconstruction procedure Reconstruction procedure:  Reconstruct J/  →  +  -  Reconstruct  →p   Reconstruct  →  +   Combine J/  +   Improve mass resolution by using an event-by-event mass difference correction  The optimization: 1.  b →J/  decays in data 2. J/  +  (fake from  (p  - )  + ) 3. Monte Carlo simulation of  b - →J/  +  -  →p  decays: –p T (p)>0.7 GeV –p T (  )>0.3 GeV  - →  decays: –p T (  )>0.2 GeV –Transverse decay length>0.5 cm –Collinearity>0.99  - b particle: –Lifetime significance>2. ( Lifetime divided by its error ) Final  b selection cuts:

17 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar17 Search for the  - b (bss)  bss quarks combination  Mass is predicted to be GeV  M(  - b ) > M(  b )  Lifetime is predicted to be 0.83<  (  - b )<1.67 ps

18 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar18 How do we look for it? -b-b ++ -- --  p -- K- Similar ~3 cm ~5 cm ~?~?

19 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar19  - b vs  - b : differences  - b (bds)  - b (bss) Decay  b  J/  (  +  - )   (   )  b  J/  (  +  - )   (  K  ) Mass  GeV GeV [1] Lifetime 1.42  0.28 ps 0.84 – 1.69 ps. [2] Daughters:   (   ): Mass:  0.07 MeV c  =4.91 cm   (  K  ): Mass:  0.29 MeV c  =2.461 cm [1] Phys. Rev. D 77, (2008); arXiv: [hep-ph] (2007). [2] arXiv:hep-ph/

20 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar20  reconstruction a challenge  →p  decays: –p T (p)>0.7 GeV –p T (  )>0.3 GeV  - →  decays: –p T (  )>0.2 GeV –Transverse decay length>0.5 cm –Collinearity>0.99 In this analysis for the  reconstruction: D0

21 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar21 Analysis strategy Fix selection criteria and then apply them to J /  +  Event per event mass correction Combine J/  + (  K + ) Reconstruction of  →  + K Select  p  Events are reprocessed to increase reconstruction efficiency of long-lived particles. Select J/  candidates Yield is optimized by using proper decay length significance cuts. Optimize yield by using multivariate techniques Keep blinded J/  +  combinations and optimize on J/  + (  K + ) Improve mass resolution from 80 MeV to 34 MeV Perform as many test as possible in different background samples

22 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar22  optimization First we select a proper decay length significance cut to clean  signal ( decay length significance > 10)  +K will have huge combinatory background D0

23 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar23  reconstruction Minimum selection cuts: –  +K vertex reconstructed –Transverse decay length significance>4 –Proper decay length uncertainty<0.5 cm Wrong- sign events  +K + Right-sign events (  +K - ) D0 PDG mass value

24 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar24 Boosted Decision Trees (BDT) All variables are related to  - or its decay products. We use a total of 20 variables. For training we use MC signal and background from wrong-sign events (J/  (  K + )). Most important variables: –p T (K) –p T (p) –p T (  ) –  - transverse decay length

25 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar25  - after BDT selection Clean  - signal D0

26 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar26  -  - contamination This is a reflection contamination due to mistaken a pion as a kaon. It is easy to eliminate by requiring M(  )>1.34. D0

27 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar27  - after BDT selection Wrong-sign combination events     decays removed D0

28 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar28 Final optimization We want to further reduce background (based on level we observe in the wrong- sign combinations.) We use  - yield in MC signal verify that we maintain the highest possible signal efficiency.

29 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar29 Final optimization: p T (B)>6 GeV We compare MC signal vs wrong-sign background events p T distribution.

30 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar30 Final optimization:  ( )<0.03 cm Similarly, MC signal is compare with uncertainty from wrong-sign events. Uncertainty on L xy Primary vertex B decay Vertex

31 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar31 Wrong-sign combinations After optimization:   <0.03 cm  J/  and  in the same hemisphere  p T (J/  +  )>6 GeV We define mass as: Mass window for the search: GeV After optimization, we look at wrong-sign combination first

32 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar32 Other control sample We analyze candidates in the sidebands of  - signal D0

33 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar33 Other control sample We analyze candidates in the sidebands of  signal D0

34 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar34 Nothing where nothing should be No excess is observed in any control samples after selection criteria is applied to them. We check also high statistics MC samples

35 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar35 Looking at right-sign combinations Clear excess of events near 6.2 GeV

36 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar36 Mass measurement Fit:  Unbinned extended log-likelihood fit  Gaussian signal, flat background  Number of background/signal events are floating parameters Number of signal events: 17.8 ± 4.9 Mean of the Gaussian: ± 0.010(stat) GeV Width of the Gaussian fixed (MC): GeV

37 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar37 Significance of the peak Two likelihood fits are performed: 1.Signal + background hypothesis (L S+B ) 2.Only background hypothesis (L B ) We evaluate the significance: Significance of the observed signal: 5.4 

38 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar38 Consistency check: Increase p T (B) Significance >6

39 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar39 Consistency check: Look back plots D0

40 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar40 Consistency check: lifetime We compare to a MC sample with a lifetime of 1.54 ps (~460 microns).

41 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar41 Alternative Cuts Based Analysis (CBA) VariableBDTCBA p T (  ) (GeV) >0.2 and input to BDT >0.2 p T (p) (GeV) >0.2 and input to BDT >0.7 p T (K) (GeV) input to BDT >0.3  - collinearity input to BDT >0.99  - transverse decay length (cm) input to BDT >0.5 Proper decay length uncertainty (cm) <0.3 Variables selected based on relative importance in BDT performance

42 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar42 Cut Based Analysis fit Fit:  Unbinned extended log-likelihood fit  Gaussian signal, flat background  Number of background/signal events are floating parameters Number of signal events: 15.7 ± 5.3 Mean of the Gaussian: ± 0.015(stat) GeV Width of the Gaussian fixed (MC): GeV Signal significance: 3.9 

43 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar43 BDT or Cut Base Analysis   After we remove duplicate events, we observe 25.5 ± 6.5 events.  Significance: 5.4 

44 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar44 Signal confirmed without BDT BDT vs CBA –Consistent number of observed signal candidates –Consistent mass –Consistent reconstruction efficiencies –BDT has better background rejection power.

45 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar45 One example: Event display

46 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar46 One example: Event display

47 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar47 Systematic uncertainties on the mass Fitting models –Linear background instead of flat. Negligible. –Varying Gaussian width between 28 – 40 MeV, 3 MeV Momentum scale correction: –Fit to the  b mass peak in data, 4 MeV. Event selection: –Varying selection criteria and from the mass shift observed between the cut-based and BDT analysis, a 12 MeV variation is estimated.

48 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar48 Production rate The systematic uncertainty includes contributions from the signal yields as well as selection efficiencies

49 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar49 Production rate

50 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar50 Summary Number of signal events: 17.8 ± 4.9 (stat) ± 0.8(syst) Mass: ± 0.010(stat) ± 0.013(syst) GeV Significance= 5.4 

51 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar51 Summary Consistent with expectations

52 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar52 Submitted to PRL

53 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar53 B baryons at the Tevatron B baryons: If it decays to J/  it the Tevatron produces at reasonable rate, we will find it. Precision measurements will come with statistics. A legacy from the Tevatron  b (bud)  b 0 (bud)  b + (buu)  b - (bdd)  b 0 (bus)  b - (bds)  b - (bss) J=1/2, 1 b

54 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar54 Fermilab’s latest discovery b-baryon  - b (bss)

55 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar55 Backup slides

56 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar56 Example: Decision Trees S/B S 1,B 1 S 2,B 2 S 12 S 11,B 11 S 21,B 21 B 22 Splitting continue … A decision tree is a binary decision. Starting from the first node, between the variables the best split is selected. In the next nodes from the first split the operation is repeated. Splitting stops until you reach a given proportion of signal or background, or until no more splits can be done. We combine 100 DT by using the bagger technique

57 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar57 Boosted Decision Trees (BDT) All variables are on  - or its decay products. For training we use MC signal and background from wrong-sign events (J/  (  K + )).

58 Introduction  b observation  b search Summary August 28th, 2008W&C Seminar58 BDT output After training the BDT, it is applied to a validation sample: –Signal MC –Background from wrong-sign events We select BDT>0. –BDT +1: Signal-like –BDT -1: background- like.


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