First glance at B0'K0 time-dependent CPV analysislacaprar/talks/B2_B2GM_B0etap... · 2016. 2....

First glance at B0 → η′K 0 time-dependent CPV analysis

Stefano Lacaprara

INFN Padova

23rd B2GM, Physics sessionKEK, February 1st 2016

Stefano Lacaprara (INFN Padova) Hbb KEK 1/2/2016 1 / 38

Outline

1 Introduction and motivations

2 B0 → η′(→ ηγγπ+π−)(K 0S → π+π−)BackgroundB0 → η′(→ ηγγπ+π−)(K 0S → π0π0)

3 B0 → η′(→ η3ππ+π−)(K 0S → π+π−)BackgroundB0 → η′(→ η3ππ+π−)(K 0S → π0π0)

4 Summary and outlook


Outline






Introduction and motivations

A sensitivity study for Time-Dependent CP violation analysis in theB0 → η′K 0channel, a charmless b → sqq̄ decay

CP asymmetry from time-dependent decay rateinto CP eigenstates;

Sη′K0 = sin 2φeff1 tightly related to sin 2φ1

I identical if only penguin diagram were present;I QCD factorization ∆Sη′K 0 ∈ [−0.03, 0.03]I new physics can enter in the loop, shifting ∆Sη′K 0

more than SM expectationη′ K

0 S

CP

HF

AG

Mo

rio

nd

20

14

0.5 0.6 0.7 0.8

BaBar

PRD 79 (2009) 052003

0.57 ± 0.08 ± 0.02

Belle

JHEP 1410 (2014) 165

0.68 ± 0.07 ± 0.03

Average

HFAG correlated average

0.63 ± 0.06

H F A GH F A GMoriond 2014

PRELIMINARYSimilar to B0 → φK 0, see work by A. GazI more complex final state;I η′ is a pseudo-scalar (φ a vector);I large BR: ∼ 6.6 · 10−5 (∼ 10xBR(B0 → φK 0))[CLEO(1998)]

F constructive interference between penguin diagramsI actual uncertainties σstat = 0.07, σsyst = 0.03

[Belle(2014)]

I projected for 50 ab−1 σstat = 0.008, σsyst = 0.008[Urquijo(2015)]

I no competition from LHCb (neutrals);


Status

Channel have been analyzed in B-factory[BABAR(2009), Belle(2007), Belle(2014)];

uncertainties are mostly statistical (∼ 3500 events for all final states);quasi-two body approach;

many decay channels available B0 → η′K 0SI η′ → ρ(→ π+π−)γ; BR:29% not yet: Hulya Atmacan (METU) is interested in working on thisI η′ → ηπ+π−; BR:43%ηγγ : η → γγ ; BR:40%η3π: η → π+π−π0 ; BR:23%

I K 0S → π+π−, K 0S → π0π0,I Total BR(B0 → η′(→ηγγ/η3ππ+π−)K 0S ) = 27% today

B0 → η′K 0L not yet studiedComplex final state, neutrals, large combinatorics;

Release used rel-00-05-03

Signal: MC5 BGx0 (some private production); Background MC5 BGx1


Outline






Selections ηγγ

B0 → η′(→ ηγγπ+π−)(K 0S → π+π−)

skim at least one decay chain have been reconstructedI w/o vertex or mass fit and with loose selections (as for the background)I Using the same skim for all decay channels: run only once on background

pre-selection N ≥ 1 decay chain, with vertex/mass constraintselection cuts on reconstructed quantities

good candidate selection:I Mbc > 5.25 GeV;

I |∆E | < 0.1 GeV;I M(ηγγ) ∈ [0.45, 0.57] GeV;I M(η′) ∈ [0.93, 0.98] GeV;I M(K 0S → π+π−) ∈ [0.48, 0.52] GeV;

I PIDπ(π±) > 0.2; Should use L-ratio instead

I d0(π±) < 0.08mm;

I z0(π±) < 0.1mm;

I N hitsPXD (π±) > 1

I P-valuevtx (B0, η′,K 0S ) > 1 · 10−5

Best candidate

if Ncands > 1, select candidate with highest P-valuevtx (B0, η′, η,K 0S )


Distributions: all/good candidates

bcM5.25 5.255 5.26 5.265 5.27 5.275 5.28 5.285 5.290

10000

20000

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40000

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70000

Mbc

All cands

MC match

Good cands

" MC match

Mbc

E∆0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.20

10000

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ηM0.4 0.45 0.5 0.55 0.6 0.65 0.70

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'ηM0.85 0.9 0.95 1 1.05 1.1 1.150

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10×

S0

KM

0.45 0.46 0.47 0.48 0.49 0.5 0.51 0.52 0.53 0.54 0.551

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410

510

πPID0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 11

10

210

310

410

510

)-π+π(S

0) K-π+π) γγ(η'( η→0B

combinatoricssmall

some true cand lost(mostly due to PID(π) and

N hitsPXD (π±) > 1);

almost all goodcandidate(s) aretrue;

Mη has a lowertail;


Distributions: best candidate

bcM5.25 5.255 5.26 5.265 5.27 5.275 5.28 5.285 5.290

5000

10000

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20000

25000

30000

35000

40000

Mbc

Best cands

" MC match

" SXF

Mbc

E∆0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.20

5000

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ηM0.4 0.45 0.5 0.55 0.6 0.65 0.70

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'ηM0.85 0.9 0.95 1 1.05 1.1 1.150

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310×

S0

KM

0.45 0.46 0.47 0.48 0.49 0.5 0.51 0.52 0.53 0.54 0.551

10

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410

510

πPID0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 11

10

210

310

410

510

)-π+π(S

0) K-π+π) γγ(η'( η→0B

All best candidates are true: SXF is negligible


Efficiency and ∆t resolution

Cands multiplicity

N candidates0 2 4 6 8 10 12 14 16 18 20

0

100

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310×

All cands multiplicity: 1.89

N good candidates0 2 4 6 8 10 12 14 16 18 20

0

100

200

300

400

500

600

310×

Good cands multiplicity: 1.06

: 0.330∈Best cands

: 0.318∈Best cands MC true

: 0.012∈Best cands MC false

)-π+π(S

0) K-π+π) γγ(η'( η→0B

t (ps)∆20− 15− 10− 5− 0 5 10 15 200

5000

10000

15000

20000

25000

30000

35000

40000

45000

/ ndf 2χ 698 / 91

Prob 0

norm 1.04e+02± 4.56e+04

CBias 0.0065± 0.0362 Cσ 0.01± 1.36

T

Bias 0.0071± 0.0432

Tσ 0.0± 3

OBias 0.035± 0.086 Oσ 0.04± 7.48

Cf 0.002± 0.523

Tf 0.003± 0.444

Fit

Core

Tail

Outlier

t>: 2.29 ps∆<

)-π+π(S

0) K-π+π) γγ(η'( η→0B

Efficiency %skim 57.1preselection 48.1good cands 33.1MC true 31.9SXF 1.2

t (ps)∆10− 8− 6− 4− 2− 0 2 4 6 8 100

10000

20000

30000

40000

50000Flavour

0B0B

t (ps)∆10− 8− 6− 4− 2− 0 2 4 6 8 10

Asy

mm

etry

1−

0

1

)-π+π(S

0) K-π+π) γγ(η'( η→0B

Flavour tagging is random,with �(1− 2w)2 = 32% dilution


Background reduction

B0 → η′(→ ηγγπ+π−)(K 0S → π+π−)Background MC sample BGx1, single skim for all channels;

Using only a fraction: L=30 fb−1;I need to process the full MC5 dataset to increase # of selected events;I Need to reduce the skim output!

NB No cut (yet) on continuum discriminating variableI still learning how to use itI Alessandro showed some issue in B0 → φK 0presentation on 2015/12/11

Sample # Ev (M) Skim (M) �skim pre-sel sel �seluū 48.15 1.023 2.13 · 10−2 8196 93 1.96 · 10−6dd̄ 13.03 0.274 2.27 · 10−2 2333 37 2.84 · 10−6ss̄ 11.49 0.238 2.07 · 10−2 2334 18 1.57 · 10−6cc̄ 38.87 1.127 2.90 · 10−2 9911 123 1.09 · 10−6total 111.54 2.662 2.39 · 10−2 22774 271 2.43 · 10−6


Background distribution at preselection level

5.25 5.255 5.26 5.265 5.27 5.275 5.28 5.285 5.290

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uuddsscc

0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.20

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450

E∆0.4 0.45 0.5 0.55 0.6 0.65 0.70

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ηM

0.85 0.9 0.95 1 1.05 1.1 1.150

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'ηM0.45 0.46 0.47 0.48 0.49 0.5 0.51 0.52 0.53 0.54 0.550

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S

0K

M0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

10

210

310

410

πPID

)-π+π(S

0) K-π+π) γγ(η'( η→0B


B0 → η′(→ ηγγπ+π−)(K 0S → π0π0)

Similar selection as in K 0S → π+π−case, taking into account the moredifficult π0 reconstructionI ∆E ∈ [−0.15, 0.25] GeV; (< 0.1 for K0S → π+π−)I M(π0) ∈ [0.1, 0.15] GeV;I M(K 0S → π0π0) ∈ [0.42, 0.52] GeV;I (full list in backup)

bcM5.25 5.255 5.26 5.265 5.27 5.275 5.28 5.285 5.290

10000

20000

30000

40000

50000

60000

70000

80000

90000

Mbc

All cands

MC match

Good cands

" MC match

Mbc

E∆0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.2 0.25 0.30

5000

10000

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ηM0.4 0.45 0.5 0.55 0.6 0.65 0.70

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310×

'ηM0.85 0.9 0.95 1 1.05 1.1 1.150

100

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500

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310×

0πM0.08 0.1 0.12 0.14 0.16 0.18 0.21

10

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410

510

S0

KM

0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.71

10

210

310

410

510

)0π0π(S

0) K-π+π) γγ(η'( η→0B combinatorics larger but stillmanageable (∼ 5 cands/ev)lower tails for Mπ0,K0

S,η;

SXF still small

Efficiency %skim 40.5preselection 36.1good cands 15.6MC true 13.5SXF 2.2

�(K 00S ) ∼ 1/2 �(K+−S )Stefano Lacaprara (INFN Padova) Hbb KEK 1/2/2016 13 / 38

Outline






B0 → η′(→ η3ππ+π−)(K 0S → π+π−)

Selections η3π

skim, preselection as for the ηγγchannel

good candidate selection:

Mbc > 5.25 GeV;

∆E ∈ [−0.15, 0.15] GeV;

M(η3π) ∈ [0.52, 0.57] GeV;

M(η′) ∈ [0.93, 0.98] GeV;

M(π0) ∈ [0.1, 0.15] GeV;

M(K 0S → π+π−) ∈ [0.48, 0.52] GeV;

PIDπ(π±) > 0.2;

d0(π±) < 0.08mm;

z0(π±) < 0.15mm;

N hitsPXD(π±) > 1

P-valuevtx (B0, η′, η,K 0S ) > 1 ·10−5

Best candidate




bcM5.25 5.255 5.26 5.265 5.27 5.275 5.28 5.285 5.291

10

210

310

410

510

Mbc

All cands

MC match

Good cands

" MC match

Mbc

E∆0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.21

10

210

310

410

510

ηM0.4 0.45 0.5 0.55 0.6 0.65 0.71

10

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510

'ηM0.85 0.9 0.95 1 1.05 1.1 1.151

10

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510

0πM0.08 0.1 0.12 0.14 0.16 0.18 0.21

10

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510

S0

KM

0.45 0.46 0.47 0.48 0.49 0.5 0.51 0.52 0.53 0.54 0.551

10

210

310

410

510

610

)-π+π(S

0) K-π+π) 0π-π+π(η'( η→0B Combinatoricsis huge (6π±);

same problemwith π0;

η′ and η3π wellreconstructedfor goodcandidates

non negligibletails for MCtrue π0, η′ andη3π

some 20% ofgoodcandidates arefalse



bcM5.25 5.255 5.26 5.265 5.27 5.275 5.28 5.285 5.291

10

210

310

Mbc

Best cands

" MC match

" SXF

Mbc

E∆0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.21

10

210

310

410

ηM0.4 0.45 0.5 0.55 0.6 0.65 0.71

10

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'ηM0.85 0.9 0.95 1 1.05 1.1 1.151

10

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0πM0.08 0.1 0.12 0.14 0.16 0.18 0.21

10

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S0

KM

0.45 0.46 0.47 0.48 0.49 0.5 0.51 0.52 0.53 0.54 0.551

10

210

310

410

)-π+π(S

0) K-π+π) 0π-π+π(η'( η→0B

Sizeable SXF ∼ 20%, is smarter best cand selection possible?



N candidates0 10 20 30 40 50 60 70 80 90 100

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000



0

10000

20000

30000

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)-π+π(S

0) K-π+π) 0π-π+π(η'( η→0B

t (ps)∆20− 15− 10− 5− 0 5 10 15 200

1000

2000

3000

4000

5000

6000

7000

/ ndf 2χ 115 / 91

Prob 0.0469

norm 4.8e+01± 6.9e+03 CBias 0.0166± 0.0934

C

σ 0.04± 1.16

TBias 0.01889±0.00613 −

Tσ 0.1± 2.5 OBias 0.087± 0.391

O

σ 0.13± 4.49 Cf 0.026± 0.508 Tf 0.021± 0.445

Fit

Core

Tail

Outlier

t>: 1.91 ps∆<

)-π+π(S

0) K-π+π) 0π-π+π(η'( η→0B

Better resolution (4π±)

Efficiency %skim 57.3preselection 54.8 (?)good cands 19.1MC true 15.3SXF 3.8

Lower efficiency: onlydue to π0?

pre-sel almost 100% onskim? Combinatorics?to be investigated

Got SWAP problem during

event selection on skims,

only fraction of skim

processed


Background reduction

B0 → η′(→ η3ππ+π−)(K 0S → π+π−)Background MC sample BGx1;

L=30 fb−1;

really need to process the full MC5 dataset to increment statistics ofselected events;I NB No cut (yet) on continuum discriminating variable

larger contribute from cc̄

reduction is larger (∼ 10x) than for ηγγchannel (but � as well)

Sample # Ev (M) Skim (M) �skim pre-sel sel �seluū 48.15 1.023 2.13 · 10−2 24037 14 2.91 · 10−7dd̄ 13.03 0.274 2.27 · 10−2 6552 6 1.25 · 10−7ss̄ 11.49 0.238 2.07 · 10−2 9686 5 1.04 · 10−7cc̄ 38.87 1.127 2.90 · 10−2 56653 40 8.31 · 10−7total 111.54 2.662 2.39 · 10−2 96928 271 1.35 · 10−7



5.25 5.255 5.26 5.265 5.27 5.275 5.28 5.285 5.290

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bcM

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4500

E∆0.4 0.45 0.5 0.55 0.6 0.65 0.70

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ηM

0.85 0.9 0.95 1 1.05 1.1 1.150

2000

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'ηM0.08 0.1 0.12 0.14 0.16 0.18 0.2

0

2000

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0πM0.45 0.46 0.47 0.48 0.49 0.5 0.51 0.52 0.53 0.54 0.550

10000

20000

30000

40000

50000

60000

70000

S

0K

M

)-π+π(S

0) K-π+π) 0π-π+π(η'( η→0B


B0 → η′(→ η3ππ+π−)(K 0S → π0π0)

Channel not used in Belle

Selection ∼ as beforeI ∆E ∈ [−0.15, 0.25] GeV; (< 0.15 for K0S → π+π−)I (full list in backup)

N candidates0 10 20 30 40 50 60 70 80 90 100

0

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10

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30

35



0

20

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)0π0π(S

0) K-π+π) 0π-π+π(η'( η→0B

bcM5.255.2555.265.2655.275.2755.285.2855.291

10

Best cands

" MC match

" SXF

E∆0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.21

10

ηM0.4 0.45 0.5 0.55 0.6 0.65 0.71

10

210

'ηM0.85 0.9 0.95 1 1.05 1.1 1.151

10

210

0πM0.08 0.1 0.12 0.14 0.16 0.18 0.21

10

210

S0

KM0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7

1

10

210

)0π0π(S

0) K-π+π) 0π-π+π(η'( η→0B

Private production

combinatorics is even larger(∼ 30 candidates per event)Sizeable SXF ∼ 30%,smarter best cand selectionis possible

�(K 00S ) ∼ 1/2 �(K+−S )

Efficiency %preselection 35.5good cands 10.1best cand 5.96SXF 3.8


Outline






Channels summary

With some comparison to B0 → φK 0(A.Gaz) and J/ψ(→ 2µ)K 0S channels

BR Eff. SXF Bgnd.? ∆tB0 →

10−5 sel. % % ·10−6 reso31.9 K+−

S1.2 2.43

η′(→ ηγγπ+π−)K 0S 1.1 13.1 K00S 2.1 1.252.25 ps

12.5 K+−S

3.5 0.58η′(→ η3ππ+π−)K 0S 0.6 6.0 K00S 3.8 −†

1.90 ps

35.2 K+−S

∼ 20φ(→ K+K−)K 0S 0.6 13.7 K00S ∼ 4

2.11 ps

φ(→ 2π)K 0S 0.07 28.3 K+−S ∼ 700 1.42 psJ/ψ(→ 2µ)K 0S 52 - - - 0.92 ps

? NB. w/o continuum suppression cut!†: bug found in background skimming


Outlook

Study is still very preliminary

So far only looked at signal η′ → ηπ+π−, with ηγγ and η3π;I ργ final state not yet addressed;I K 0L not yet looked at, too;I selection still to be optimized, but first attempt is good enough to start

with;

first look at continuum background (from MC5 campaign);I No continuum suppression yet

need to look at peaking background;

signal extraction and fit to be implementI synergies with B0 → φK 0analysis;Still long road toward a full scale sensitivity exercise, took first steps


Additional stuff

Additional or backup slides


Technicalities

Release used rel-00-05-03

code in GIT https://github.com/lacaprara/b2pd analysis

data used:I Privately produced signal;I MC5 for signal (BGx0) (still partially);I MC5 BGx1 sample for continuum background;

F Still only a fraction of produced dataset;F Skim (with loose selection) on large dataset;F Full selection on skimmed events;F trying to produce a single skim for all channels, not finalized yetF got problem (memory and crash in mixed and charged, respectively):

to be investigated;


https://github.com/lacaprara/b2pd_analysis

Background

Background selection done in two steps:1 Skim: require a reconstructed decay chain, in any of the four channels,

w/ loose selection and w/o vertex fit and constraint (for speed);I Trying to run skim on continuum background once for all channels;

2 Selection: apply all selection cuts2.1 Pre-selection: re-reconstruct the proper decay chain (exclusive) w/ vertex

and mass constraint2.2 Final: apply all selection cuts

I NB No cut (yet) on continuum discriminating variableI still learning how to use itI Alessandro showed some issue in B0 → φK 0presentation on 2015/12/11


Selections

B0 → η′(→ ηγγπ+π−)(K 0S → π0π0)

preselection at least one decay chain have been reconstructed

good candidate selection:I Mbc > 5.25 GeV;I ∆E ∈ [−0.15, 0.25] GeV; (< 0.1 for K0S → π+π−)I M(ηγγ) ∈ [0.45, 0.57] GeV;I M(η′) ∈ [0.93, 0.98] GeV;I M(π0) ∈ [0.1, 0.15] GeV;I M(K 0S → π0π0) ∈ [0.42, 0.52] GeV;I PIDπ(π

±) > 0.2;I d0(π

±) < 0.08mm;I z0(π

±) < 0.15mm;I N hitsPXD(π

±) > 1I P-valuevtx (B0, η

′, η,K 0S ) > 1 · 10−5




bcM5.25 5.255 5.26 5.265 5.27 5.275 5.28 5.285 5.290

10000

20000

30000

40000

50000

60000

70000

80000

90000

Mbc

All cands

MC match

Good cands

" MC match

Mbc

E∆0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.2 0.25 0.30

5000

10000

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45000

ηM0.4 0.45 0.5 0.55 0.6 0.65 0.70

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310×

'ηM0.85 0.9 0.95 1 1.05 1.1 1.150

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310×

0πM0.08 0.1 0.12 0.14 0.16 0.18 0.21

10

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310

410

510

S0

KM

0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.71

10

210

310

410

510

)0π0π(S

0) K-π+π) γγ(η'( η→0B

combinatoricslarger but stillmanageable

lower tails forMπ0,K0

S,η;

still most of allgoodcandidate(s)are true;



bcM5.25 5.255 5.26 5.265 5.27 5.275 5.28 5.285 5.290

2000

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Mbc

Best cands

" MC match

" SXF

Mbc

E∆0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.2 0.25 0.30

1000

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ηM0.4 0.45 0.5 0.55 0.6 0.65 0.70

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'ηM0.85 0.9 0.95 1 1.05 1.1 1.150

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310×

0πM0.08 0.1 0.12 0.14 0.16 0.18 0.21

10

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S0

KM

0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.71

10

210

310

410

)0π0π(S

0) K-π+π) γγ(η'( η→0B

Most best candidates are true: SXF is small ∼ 2%



N candidates0 2 4 6 8 10 12 14 16 18 20

0

20

40

60

80

100

120

310×



0

50

100

150

200

250

310×





)0π0π(S

0) K-π+π) γγ(η'( η→0B

t (ps)∆20− 15− 10− 5− 0 5 10 15 200

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

22000

/ ndf 2χ 358 / 91

Prob 33− 2.55e

norm 7.12e+01± 2.15e+04

CBias 0.0096± 0.0285 Cσ 0.01± 1.37

T

Bias 0.0103± 0.0468

Tσ 0.0± 3

OBias 0.051± 0.232 Oσ 0.1± 7.5

Cf 0.003± 0.522

Tf 0.004± 0.445

Fit

Core

Tail

Outlier

t>: 2.30 ps∆<

)0π0π(S

0) K-π+π) γγ(η'( η→0B

Efficiency %preselection 38.2good cands 15.3best cand 13.1

�(K 0S → π0π0) ∼ 0.5 �(K 0S → π+π−)

t (ps)∆10− 8− 6− 4− 2− 0 2 4 6 8 100

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

22000

24000 Flavour0B0B

t (ps)∆10− 8− 6− 4− 2− 0 2 4 6 8 10

Asy

mm

etry

1−

0

1

)0π0π(S

0) K-π+π) γγ(η'( η→0B

Flavour tagging is random,with �(1− 2w)2) = 32% diluition



5.25 5.255 5.26 5.265 5.27 5.275 5.28 5.285 5.290

200

400

600

800

1000

1200

1400

1600

1800

2000

2200

bcM

uuddsscc

0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.2 0.25 0.30

1000

2000

3000

4000

5000

6000

E∆0.4 0.45 0.5 0.55 0.6 0.65 0.70

2000

4000

6000

8000

10000

12000

14000

16000

ηM

0.85 0.9 0.95 1 1.05 1.1 1.150

5000

10000

15000

20000

25000

'ηM0.08 0.1 0.12 0.14 0.16 0.18 0.2

0

10000

20000

30000

40000

50000

0πM0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.70

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

22000

S

0K

M

)0π0π(S

0) K-π+π) γγ(η'( η→0B


Selections

B0 → η′(→ η3ππ+π−)(K 0S → π0π0)

preselection at least one decay chain have been reconstructed

good candidate selection:I Mbc > 5.25 GeV;I ∆E ∈ [−0.15, 0.25] GeV;I M(η3π) ∈ [0.52, 0.57] GeV;I M(η′) ∈ [0.93, 0.98] GeV;I M(π0) ∈ [0.1, 0.15] GeV;I M(K 0S → π0π0) ∈ [0.4, 0.52] GeV;I PIDπ(π

±) > 0.2;I d0(π

±) < 0.08mm;I z0(π

±) < 0.15mm;I N hitsPXD(π

±) > 1I P-valuevtx (B0, η

′, η) > 1 · 10−5




bcM5.255.2555.265.2655.275.2755.285.2855.291

10

210

310

All cands

MC match

Good cands

" MC match

E∆0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.21

10

210

310

ηM0.4 0.45 0.5 0.55 0.6 0.65 0.71

10

210

310

410

'ηM0.85 0.9 0.95 1 1.05 1.1 1.151

10

210

310

410

0πM0.08 0.1 0.12 0.14 0.16 0.18 0.21

10

210

310

410

S0

KM0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7

1

10

210

310

410

)0π0π(S

0) K-π+π) 0π-π+π(η'( η→0B

NB: channelnot used inBelle

combinatoricsis huge

η and η′

reconstructionis good



bcM5.255.2555.265.2655.275.2755.285.2855.291

10

Best cands

" MC match

" SXF

E∆0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.21

10

ηM0.4 0.45 0.5 0.55 0.6 0.65 0.71

10

210

'ηM0.85 0.9 0.95 1 1.05 1.1 1.151

10

210

0πM0.08 0.1 0.12 0.14 0.16 0.18 0.21

10

210

S0

KM0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7

1

10

210

)0π0π(S

0) K-π+π) 0π-π+π(η'( η→0B

Sizeable SXF ∼ 30%, smarter best cand selection is possibleStefano Lacaprara (INFN Padova) Hbb KEK 1/2/2016 35 / 38


N candidates0 10 20 30 40 50 60 70 80 90 100

0

5

10

15

20

25

30

35



0

20

40

60

80

100

120





)0π0π(S

0) K-π+π) 0π-π+π(η'( η→0B

t (ps)∆20− 15− 10− 5− 0 5 10 15 200

20

40

60

80

100

/ ndf 2χ 44.5 / 91

norm 0.9± 83.6

CBias 3.8± 2

C

σ 0.894± 0.108

T

Bias 0.0335±0.0191 −

Tσ 0.02± 1.25

OBias 0.048± 0.307

O

σ 0.03± 3.05

Cf 01− 5.05e±09 − 3.59e

Tf 0.008± 0.661

Fit

Core

Tail

Outlier

t>: 1.86 ps∆<

)0π0π(S

0) K-π+π) 0π-π+π(η'( η→0B

Private production

Efficiency %preselection 35.5good cands 10.1best cand 5.96SXF 3.8

�(K 0S → π0π0) ∼ 0.5 �(K 0S → π+π−)

t (ps)∆10− 8− 6− 4− 2− 0 2 4 6 8 100

10

20

30

40

50

60

70Flavour

0B

0B

t (ps)∆10− 8− 6− 4− 2− 0 2 4 6 8 10

Asy

mm

etry

1−

0

1

)0π0π(S

0) K-π+π) 0π-π+π(η'( η→0B



5.25 5.255 5.26 5.265 5.27 5.275 5.28 5.285 5.290

200

400

600

800

1000

1200

1400

1600

1800

2000

2200

bcM

uuddsscc

0.2− 0.15− 0.1− 0.05− 0 0.05 0.1 0.15 0.20

500

1000

1500

2000

2500

3000

3500

4000

4500

E∆0.4 0.45 0.5 0.55 0.6 0.65 0.70

2000

4000

6000

8000

10000

12000

14000

16000

ηM

0.85 0.9 0.95 1 1.05 1.1 1.150

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

22000

'ηM0.08 0.1 0.12 0.14 0.16 0.18 0.2

0

2000

4000

6000

8000

10000

12000

14000

16000

0πM0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.70

5000

10000

15000

20000

25000

S

0K

M

)0π0π(S

0) K-π+π) 0π-π+π(η'( η→0B


Bibliography I

[CLEO(1998)] CLEO. Observation of high momentum η′ production in B decays. PRL, 81:1786, 1998. doi:10.1103/PhysRevLett.81.1786. URL http://link.aps.org/doi/10.1103/PhysRevLett.81.1786.

[Urquijo(2015)] Phillip Urquijo. Comparison between belle ii and lhcb physics projections. Technical ReportBELLE2-NOTE-PH-2015-004, Apr 2015.

[BABAR(2009)] BABAR. Measurement of time dependent cp asymmetry parameters in B0 meson decays to ωK0S , η′

K0, and

π0K0S . PRD, 79:052003, 2009. doi: 10.1103/PhysRevD.79.052003. URLhttp://link.aps.org/doi/10.1103/PhysRevD.79.052003.

[Belle(2007)] Belle. Observation of time-dependent cp violation in B0 → η′

K0 decays and improved measurements of cp

asymmetries in B0 → ϕK0, K0S K0S K

0S and B

0 → j/ψK0 decays. PRL, 98:031802, 2007. doi:10.1103/PhysRevLett.98.031802. URL http://link.aps.org/doi/10.1103/PhysRevLett.98.031802.

[Belle(2014)] Belle. Measurement of time-dependent cp violation in b0 → η′k0 decays. Journal of High Energy Physics, 2014(10):165, 2014. doi: 10.1007/JHEP10(2014)165. URL http://dx.doi.org/10.1007/JHEP10%282014%29165.


http://link.aps.org/doi/10.1103/PhysRevLett.81.1786http://link.aps.org/doi/10.1103/PhysRevD.79.052003http://link.aps.org/doi/10.1103/PhysRevLett.98.031802http://dx.doi.org/10.1007/JHEP10%282014%29165

Introduction and motivationsB0'(+-)(K0S+-)BackgroundB0'(+-)(K0S00)

B0'(3+-)(K0S+-)BackgroundB0'(3+-)(K0S00)

Summary and outlook

First glance at B0'K0 time-dependent CPV analysislacaprar/talks/B2_B2GM_B0etap... · 2016. 2....

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