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Soutenance de thèse

Olga Kochebina

19 September, 2014

1

Standard Model and motivation for rare charm decays

The LHCb detector

Potential of LHCb for 4-body rare charm decays

D0 K- π+ µ+µ-

D0 K- K+ µ+µ-

D0 π- π+ µ+µ-

D0 K+ π- µ+µ-

Measurement of D0 K- π+ ρ/ω(µ+µ-)

also used as a normalization mode

Tests of electronic board for the LHCb Calorimeter Upgrade

Systematic uncertainties D+(s)π+ µ+µ- analysis (not shown today) 2

6 quarks

6 leptons

4 gauge bosons

1 scalar boson, Higgs

26 free parameters:

12 quark and lepton masses

3+3 mixing quark and neutrino angles

1+1 quark and neutrino CPV phase

3 factors of the gauge group (αs, αem, sinθw)

2 for the shape of the Higgs potential

1 (QCD) vacuum phase implicated in the

strong CP problem

SU(3)3 SU(2)

L U(1)

Y

3

The SM is a very successful theory

Many of its predictions were spectacularly verified experimentally

However, it leaves a lot of questions open. Examples:

• Dark Matter and Dark Energy

• Hierarchy problem

• Large differences between the fermion masses

• CP violation too weak to explain the dominance of matter over antimatter

• Does not include Gravitation

→ The SM is the low-energy description of a more

fundamental theory (> 1 TeV)

4

Searches in quark sector

Couplings are possible between:

uu via Z0

ud via W+

Couplings are forbidden:

uc, ct, ut for up-type quarks

ds, sb, db for down-type quarks

c q=+2/3e u q=+2/3e

Trees - forbidden

5

Searches in quark sector

Couplings are possible between:

uu via Z0

ud via W+

Couplings are forbidden:

uc, ct, ut for up-type quarks

ds, sb, db for down-type quarks

c q=+2/3e u q=+2/3e

Trees - forbidden Loops - allowed

c q=+2/3e u q=+2/3e

Flavour changing Neutral Currents (FCNC) are very suppressed in the SM.

They are easily modified by NP: good probe 6

Rare charm decays are … “very rare” GIM suppression in up-type quark: mass of the quarks in loops

are more similar than in K and B decays, mb-m

d << m

t-m

u

GIM: s

If mb=ms=md complete annihilation !

d VV* VV* VV*

CP violation is very small Charm decays dominated by transitions between the first 2

families, thus no weak phases.

→ Any signal can be New Physics! + Small signal could be observed at the LHC (large s(cc)LHCb, 7TeV=(1419±154)µb)

7

8

BFSM

VMD

9

BFSM

VMD

Studied at LHCb

10

BFSM

VMD

Addressed today

4 body rare charm decays

D0 K- π+ µ+µ-

D0 K- K+ µ+µ-

D0 π - π+ µ+µ-

D0 K+ π- µ+µ-

Short Distance (SD): sensitive to NP

BFSD(DXu e+e- ) = 3.7 10-9, slightly smaller for DXu µ+µ-

For exclusive modes BFSD~ O(10-10)

SD by far dominated by Long Distance (LD)

BF (D0π- π+µ+µ-)~ 10-6

BF (D0K+K-µ+µ- )~ 10-7

BF (D0K+π-µ+µ- )~ 10-8

L.Cappiello et al. arXiv:1209.4235v3

Via resonances

In SM:

11

In SM:

A. Paul et al., arXiv:1101.6053

m(µ+µ-), GeV/c2

Plan A: BF’s in regions away from resonances

Plan B: asymmetries in the full spectrum (interference between SD and LD)

• CP

• Forward backward

• T-odd

A=| ALD + ASD

|2 ~ | ALD |2 + 2Re(ALD ASD

*)

SD is very small compared to LD,

especially in the resonant zone.

12

SM

NP?

Can be generated by the interference between amplitudes with

CP violation: Different weak and strong phases

Forward-Backward asymmetry: amplitudes with different chiralities interfere

Asymmetry of m+to be emitted in

forward or backward

T-odd asymmetry

Angular asymmetry in the diplane angle ϕ (T-odd variable)

13

In helicity frame

AFBCP = A

FB (D) - A

FB(D)

Can be generated by the interference between amplitudes with

CP violation: Different weak and strong phases

Forward-Backward asymmetry: amplitudes with different chiralities interfere

Asymmetry of m+to be emitted in

forward or backward

AFBCP = A

FB (D) - A

FB(D)

T-odd asymmetry

Angular asymmetry in the diplane angle ϕ (T-odd variable)

14

In helicity frame

In the SM: all these asymmetries ~ 0

Tree level FCNC

(Beak GIM supp.) Loop-mediated FCNCs

Z-enhanced model

(ex: Extra-vector like quarks) Leptoquark models

SUSY

Schematically: Most models have a moderate effect on Banching Ratios

Asymmetries reach O(1%), some models predict >~10%

BSD up to a few 10-9 ( SM: O(10-10) )

15

[1]E791, PRL 86, 3969 (2001)

Exp Theory (total BF)

Cabibbo Favoured D0K- π+ µ+µ- <3.6×10-4[1] 6.2×10-6

Singly Cabibbo Suppressed D0K- K+ µ+µ- <3.3×10-5[1] 1.1×10-7

Singly Cabibbo Suppressed D0π- π+µ+µ- <5.5×10-7[2] 1.3×10-6

Doubly Cabibbo Suppressed D0K+ π- µ+µ- - 1.7×10-8

Upper limits of B, @90% CL

E791

No asymmetries studied yet!

LHCb is unique opportunity to measure BF and asymmetries in:

D0 K- π+ µ+µ-

D0 K- K+ µ+µ-

D0 π - π+ µ+µ-

D0 K+ π- µ+µ-

16

[2] LHCb, PLB728, 234-243 (2014)

17

Not enough data to measure asymmetries

Measure BF to constrain NP and predict potential of future datasets

Measure BF(D0K-+ /(m+m-))

essential normalization for the other 4 body

modes

Prediction of the potential of future datasets

D0K-+ m+m-

m(µ+µ-), MeV/c2

φ ρ

ω Data Loose cuts..

/: window in m(m+m-) of [675;875] MeV/c2

Designed for precise study of

CP-violation and flavor-physics:

• forward geometry

• precise momentum and mass

reconstruction

• precise vertex reconstruction,

• lifetime reconstruction

• Adapted and highly configurable

trigger system

• identification: π, K, μ

B(D) hadrons are

producing in high rapidity

LHCb delivered 2.0 fb-1 in 2012, 1.1 fb-1 in 2010-2011

2 < η < 5 (15 – 300 mrad)

Design luminosity 2×10³² cm-2 s-1

pp 18 ×1013

cc 59 ×1011

bb 26 ×1010 19

Large cross-section!

interaction point

Tracking Particle ID

RICH system

K, π, p ID HCAL, ECAL, Preshower /SPD

Trigger+ e/γ energy and ID

Muon chambers

Trigger, µ ID VELO

Precise vertexing

Tracking stations

momentum

20

Energy and position measurements

Hardware trigger decision (L0Hadron)

Particle identification (elections, hadrons)

ECAL

Shashlik (Pb-scint.)

6016 cells

HCAL

Tiles (Iron-scint.)

1488 cells

No hits in Scintillator Pad Detector (SPD)

+Shower in ECAL

Hits in SPD + Shower in ECAL

Hits in SPD + Shower in HCAL

Resolution:

21

Muon Chambers System

5 Muon stations interleaved with iron absorbers

Basic identification (trigger, preselection):

number of stations traversed as function of p

Sophisticated identification:

Distance between extrapolated tracks and hits in

muon system.

PIDmu (likelihood ratio),

ProbNNmu (neural network)

Additional information from RICH and Calo

22

Muon Chambers System

5 Muon stations interleaved with iron absorbers

Basic identification (trigger, preselection):

number of stations traversed as function of p

Sophisticated identification:

Distance between extrapolated tracks and hits in

muon system.

• muon-ID (mm) ~95%, mis-ID rate(m)~0.5%

PIDmu (likelihood ratio),

ProbNNmu (neural network)

Addition info from RICH and Calo

23

L0 Hardware Trigger 40 MHz1 MHz

Search for high pt, µ, e, γ, hadron candidates

CALO pt > 3.6 GeV, MUON pt >1.4 GeV

High Level Software Trigger Farm

HLT1: Add Impact parameter cuts

HLT2: Global event reconstruction.

Exclusive or inclusive offline-like selection

(lines)

Adaptation to

physics priorities

variation of beam conditions

24

L0 Hardware Trigger 40 MHz1 MHz

Search for high pt, µ, e, γ, hadron candidates

CALO pt > 3.6 GeV, MUON pt >1.4 GeV

Very important point of the analysis presented

today:

L0Hadron line use HCAL, ECAL

L0Muon line use muon stations

25

D0 K- π+ µ+µ-

D0 K- K+ µ+µ-

D0 π - π+ µ+µ-

D0 K+ π- µ+µ-

26

Also useful for flavour tagging:

D0 K- π+ µ+µ-

D0 K+ π- µ+µ-

Rare decay: Priority is to reduce the background

Use D* tag, D0h- h’+µ+µ- from D*D0+

Sophisticated selection for maximal use of decay discriminative features

Keeping systematic uncertainties low: normalization mode

𝐵𝐹(𝑠𝑖𝑔𝑛𝑎𝑙) = 𝐵𝐹(𝑛𝑜𝑟𝑚) 𝜀(𝑛𝑜𝑟𝑚)

𝜀(𝑠𝑖𝑔𝑛𝑎𝑙) 𝑁(𝑠𝑖𝑔𝑛𝑎𝑙)

𝑁(𝑛𝑜𝑟𝑚)

Δm=m(D*+) - m(D0)

Efficiency ratio cancel most of systematics (σ, Luminosity, reco, acceptance, etc.)

p, pT, IP(D),

FD, PID(m)

27

140 144 148 152 Δm, MeV/c2

1200

800

400

0

D0K-+ m+m-

m(µ+µ-), MeV/c2

φ ρ

ω

Motivation

Similar final state as signal decays

BF~4.9∙10-6

Not measured yet!

28

Data Loose cuts

m(m+m-) in [675;875] MeV/c2

Strategy

D0K-+ + - – normalization:

Similar kinematics

BF=(8.3±0.2)%, with 2.5% precision

Not the same final state

D0K-+ m+m-

m(µ+µ-), MeV/c2

φ ρ

ω

Motivation


BF~4.9∙10-6

Not measured yet!

29

Data Loose cuts

m(m+m-) in [675;875] MeV/c2

Strategy


Similar kinematics



D0K-+ m+m-

m(µ+µ-), MeV/c2

φ ρ

ω

Motivation


BF~4.9∙10-6

Not measured yet!

30

Data Loose cuts

m(m+m-) in [675;875] MeV/c2

Strategy


Similar kinematics



Obtained in MC

Obtained in data

2 fb -1, 8 TeV

2012 data

31

L0 trigger

HLT1 trigger

HLT2 trigger

Stripping

MVA+MuonID

Online

Offline

32

L0 trigger

Natural choice for L0 trigger

• D0K-+ + - : hadron line (use HCAL,ECAL)

• D0K-+ (/m+m-) : muon line (use Muon stations)

D0

D

signal

rest of event Two categories of trigger

decision:

TOS: There is at least one

trigger object which

is a part of the signal

TIS: There is at least one

trigger object which is

independent of the signal

L0 Hadron TIS:

Efficiencies do not cancel in ratio Problematic for systematics

• εL0TIS DKmm , ε L0TIS

DK should very similar as the rest of event is similar

• HadronTIS is the most efficient among TIS

• Measurement is still possible

33

L0 trigger

HLT1 trigger

HLT2 trigger

Stripping

MVA+Muon ID

Online

Offline

We developed dedicated cut-

based lines

Scan the level of cuts to find the

optimal and that respect:

- impact retention rate and CPU

- maximize signal significance

HLT2 and Stripping lines are

based on similar cuts

34

Daughter particles

Momentum, p Transverse momentum, pt

Impact parameter (IP) χ2 Track χ2

35

Signal from MC

Background from data

(sideband, after stripping)

D meson

Transverse momentum, pt Vertex χ2

Distance Of Closest Approach Impact parameter (IP) χ2

36

Signal from MC



D meson

Transverse momentum, pt Vertex χ2

DIRection Angle Flight Distance (FD) χ2

37

Signal from MC



20%

sel.

optimiz

ation

78%

measurement

D0K-+m+m- sample:

2% BDT training

L0HadronTOS|| L0MuonTOS

Control sample

50% for

measurement

50% control

sample

D0K- ++- sample:

Sample for BDT training

K-+m+m-: 3M events

Sample for efficiencies and systematics:

K-+m+m-: 4M events

K- ++-: 2M events

K- ++-: 2M events, more realistic

resonant model

2012 data, 2 fb-1 , 8 TeV, untagged sample (from PV)

38

D0K-+m+m- control sample:

L0 trigger

HLT1 trigger

HLT2 trigger

Stripping

MVA +MuonID

Online

Offline

39

Correlation between variables

Decision Tree Boosted Decision Tree

α1 +α2

+αn …

Performant classifier

Only one variable (BDT)

40

Boosted Decision Tree combines variables shown before

Training + testing samples

Signal proxy: MC (3M)

Background proxy: 2% upper sideband of D0K-+/(m+m-) sample

41

Optimal cut on BDT and ProbNNmu Fit yields for each cut on BDT and ProbNNmu

Find the point of the best significance

50

25

0

50

25

0

1800 1850 1900

1800 1850 1900 m(D0), MeV/c2

m(D0), MeV/c2

1800 1850 1900 m(D0), MeV/c2

50

25

0

1800 1850 1900 m(D0), MeV/c2

50

25

0

BDT > 0.2, ProbNNmu>0.3

20% signal sample

42

Signal: Cruijff function

20% signal sample

mD0

σ

αL αR

44

Signal: Cruijff function

Combinatorial background: 1st order polynomial

20% signal sample

mD0

σ

αL αR

45

Peaking background: 2 non-parametric PDF

20% signal sample

mD0

σ

αL αR

D0K- ++- , higher PT

D0K- ++- , lower PT

D0K- ++- D0

K-+m+m-

Just 20 MeV/c2 below

Decays in flight µν (single and double) create

a tail easily misfitted as combinatorial background

46

Not enough statisitcs in our MC for double decays in flight

zoom

If we apply ProbNNmu on 1 or 2 pions

MC2012, Stripping level

m(D0), MeV/c2 m(D0), MeV/c2

m(D0), MeV/c2 m(D0), MeV/c2

Single misID Double misID

47

Before the neutrino loss

𝑝

Not enough statistics in MC for double decays in flight:

It is rare to have decays before the end of the tracking stations

This sample of events can be used to

characterize the effect on the p of the losing

neutrino

Distributions of 𝜹𝒑 as a function of

(𝒑, charge)

After the neutrino loss

𝑝 − 𝜹𝒑

48


𝑝





neutrino


(𝒑, charge)


𝑝 − 𝜹𝒑

49

Smear (𝒑) in D0K- ++- MC full sample to reproduce the effect of energy

losing due to decays in flight, recalculate the mass


𝑝





neutrino


(𝒑, charge)


𝑝 − 𝜹𝒑

50

Smear (𝒑) in D0K- ++- MC full sample to reproduce the effect of energy

losing due to decays in flight, recalculate the mass

High PT Low PT

Forms

Fit fractions in the data control sample D0K-+(/ m+m-), selected with

(D_L0Hadron_TOS || D_L0Muon_TOS)

High PT

51 Forms

Low PT

52

Fit fractions in the data control sample D0K-+(/ m+m-), selected with

(D_L0Hadron_TOS || D_L0Muon_TOS)

78% signal

sample, used

for

measurement

53

N(D0K-+ /(m+m-)) = 2453 ± 60

Most of the efficiencies are from MC

From

Data

55

From real data with PIDCalib: a tag-and-probe technique using J/ψµµ

unbiased sample to get efficiency in bins of (P,η,nTracks)

For each µ-track from D0K-+m+m-

efficiency from J/ψµµ

Looked for an optimal binning:

Fine enough to be sensitive to efficiency variation inside a

kinematical bin

Coarse enough to have enough statistic in each bin

Details in backup

Obtained efficiency (75.7 ± 0.4)% 56

Necessary to assign systematics uncertainties

57

Fine

Muons from D0K-+m+m- and J/ψµµ

Compare three binnings: Fine, Default, Coarse

nTracks

59

nTracks



Default

nTracks

60

nTracks



Coarse

61

Comparison of results from three binnings (fine, default and coarse)

Systematic uncertainty: 2.5%



62

Efficiency ratio: difference between data and MC

Uncertainty on the BDT cut : < 2%

The variables used in the selection are not perfectly described by MC

Data/MC comparison helps to evaluate this effect

BDT combines all these variables

63

D0K-+ /(m+m-)

L0HadronTOS||L0MuonTOS)

D0K-+ + -

-1 -0.6 -0.2 0.2 0.6 1 BDT

-1 -0.6 -0.2 0.2 0.6 1 BDT

500

400

300

200

100

0

2500

2000

1500

1000

500

0

Data

MC

Data

MC

L0 Hadron TIS efficiencies should be similar at first order for D0K-+m+m- and

D0K- ++- as the rest of event is similar

Overlap of the clusters in HCAL has the different effect?

D0K- ++- has 3 ’s higher TIS efficiency?

TIS cluster

Signal cluster

64

Compare two TIS efficiencies involving two very different detectors

L0HadronTIS (use HCAL, ECAL)

L0MuonTIS (use Muon stations)



(D

0

K-

+m

+m

- )/

(D0

K-

+

+

- ) MuonTIS

HadronTIS

MC

65

No such effect seen in MC

Very similar!



(D

0

K-

+m

+m

- )/

(D0

K-

+

+

- ) MuonTIS

HadronTIS

MC

66

No such effect seen in MC

Very similar!

A look at the data is necessary!

Check the difference in data

One conservative way:

Compare measured BF on HadronTIS, MuonTIS

Not precise test!

Uncertainty on the comparison is 7.7%

Can be quoted as a conservative systematic uncertainty

This is too conservative. Work continues to find a better approach

67

BF L0HadronTIS = (4.37 ± 0.19) × 10-6

BF L0MuonTIS = (4.66 ± 0.28) × 10-6

ΔBF = (0.29 ± 0.34) × 10-6

Highest uncertainty is due to L0:

No physical reasons to be that high

Too conservative

New tests are ongoing

68

First measurement of:

Overall uncertainty: 12.5%

Can now be used as suitable normalization mode for the next step:

the measurement of total and partial BFs’ of other D0h- h’+µ+µ- decays

69

Our ultimate goals: Branching ratios and Asymmetries in

D0 K- π+ µ+µ-

D0 K- K+ µ+µ-

D0 π - π+ µ+µ-

D0 K+ π- µ+µ-

Can we find NP here ??

Test sensitivities with

Run I (2012, 2fb-1 at √s = 8 TeV)

Run II (5 fb-1 at √s = 13 TeV)

Upgrade (50 fb-1, √s =14 TeV)

First step is to design an optimal selection

What we already have: Stripping, HLT2

To finalize: we tested several Multivariate methods (BDT, ANN)

71

Study of the performances of different Multivariate methods in order to

find the best!

2 training methods:

- Boosted Decision Tree (BDT)

- Artificial Neural Network (ANN)

2 boosting methods:

- Gradient (GradBoost)

- Adaptive (AdaBoost)

7 sets of variables

2 MVA packages:

- TMVA (Root)

- MutliBoost (AppStat@LAL)

11 approaches in total

72

Find best significance

1800 1850 1900

1800 1850 1900

m(D0),

MeV/c2

1800 1850 1900

1800 1850 1900 m(D0),

MeV/c2

50

25

0

50

25

0

Find the best possible performance with this method is looked for

Each method is first trained Sample:

Signal: MC 2012, generated 2M

BKG: K- π+ µ+ µ sideband 10% of the data

Then it is tested for overtraining

ΔM

=M(D

*)-M

(D0),

Me

V/c

2

M(D0), MeV/c2

73

40% of the K- π+ µ+ µ- sample

50

25

0

50

25

0

Results: Signal significance from 11 methods:

MVA performs better than rectangular cuts

Properties of data are such that all methods perform similarly

Confirmed by fast convergence of tested approaches

Test sensitivities with

need other variables?

Work before the trigger and stripping?

Choose newVarB as the working hypothesis for the rest of the studies

Le

arn

ing

err

or

Number of trees

74

Study the sensitivity to

Asymmetries

Total Branching fractions

Branching fractions that would be a clear sign of NP

D0 K+ π- µ+µ- : (BF~5 ∙10-9) at low m(µ+µ-)

D0 K- K+ µ+µ- (BF~10-8) at low m(µ+µ-)

Tot. BF (Theory)

D0K- π+ µ+µ- 6.2×10-6.

D0K- K+ µ+µ- 1.1×10-7

D0π- π+µ+µ- 1.3×10-6

D0K+ π- µ+µ- 1.7×10-8

Consider three dataset Run I (2012, 2fb-1 at Vs = 8 TeV)

Run II (5 fb-1 at Vs = 13 TeV)

Upgrade (50 fb-1, Vs =14 TeV)

Extrapolate Signal and Background yields Signal: D* π+ D0(K- π+ µ+µ-) peak from

Background: sideband data

Re-scaled: BF, luminosity, cross section, MC

efficiencies.

76

1800 1850 1900

1800 1850 1900

m(D0),

MeV/c2

1800 1850 1900

1800 1850 1900 m(D0),

MeV/c2

50

25

0

50

25

0

50

25

0

50

25

0

D0 K+ π- µ+µ-

For D0 K- K+ µ+µ- (B~10-7-10-8)

D0 K- K+ µ+µ-

Branching fractions

Measurement

Possible observation

Asymmetries

In D0 K- π+ µ+µ-: asymmetry O(5%) measurable in Run II

In D0 K- K+ µ+µ-: measuring 5% takes the upgrade + an improved selection

(100% efficient trigger)

77

D0 K+ π- µ+µ-

For D0 K- K+ µ+µ- (B~10-7-10-8)

D0 K- K+ µ+µ-

Branching fractions

Measurement

Possible observation

Asymmetries

In D0 K- π+ µ+µ-: asymmetry O(5%) measurable in Run II

In D0 K- K+ µ+µ-: measuring 5% takes the upgrade + an improved selection

(100% efficient trigger)

78

Reminder: Most models predict asymmetries ~ 1%

Some models >~ 10%

New data taking period at 14 TeV with 40MHz beam

Change of the trigger strategy will allow to benefit from new luminosity

Changes in detector:

a 40MHz readout electronics for all subsystems

Calorimeter reviewed

the VELO, tracking stations will be upgraded completely

the PS, SPD sub-detectors, M1 muon station, aerogel in RICH1 will be removed

Low Level Trigger:

Hardware trigger L0 is

replaced by LLT, that

will be used at the

beginning, for testing

During data taking

runs readout detector

information at 40MHz

Decision is taken with

software at PC-farms

L=2×1033 cm-2 s-1

80

Requirements

Energy/position measurement

Identification of γ, electrons, hadrons

High sensitivity

Fast response (40MHz)

Clean sampling in 25ns (no spill-over)

L0 trigger input (present detector)

81

Prototypes of the analog/digital parts of the electronics have been redesigned

The PMT gain reduction is compensated by the gain of electronics

Needed the same performances as for the present electronics

Key parameters to look at: noise, linearity, full integration of the signal pulse in

the 25ns interval

A test beam is necessary for tests in realistic conditions

The amplification and integration of the signal in 25 ns 2 alternated integrators running at 20MHz

One integrates during 25ns

The other is readout, present result to ADC and reset

83

ECAL

module

e

Electron beam at 50 GeV, 100GeV,

125GeV

ECAL module

2 parallel acquisitions tested FE board with fast integration

Lecroy board with a long time interval

integrator

The time arrival of the particles is

asynchronous with respect to the clock of

the electronics Two scintillators provide the trigger

acquision and give the measurement of

the time arrival of the particles

84

ECAL module

e1

e2

Trigger

Time arrival

Noise at the level of ~1 ADC (=2.5 MeV) is negligible

1.6 ADC counts

OK

Linearity, dependence on energy of electrons, should be < 1%

< 1%

OK 50GeV

100GeV

125GeV

85

Spill-over should be < 1%

If pulse is too broad, part of the signal remains in the next 25ns sample

Need to check if signal pulse is

fully integrated during 25ns

> 1% !

Too broad pulse

86

1600 2000 2400

2500

1500

500

TDC t, ns

FE

AD

C

-2 -1 0 1 2 Δt(TDC), ns

1.4

1

0.6

0.2

Δ A

DC

, %

Plateau should be stable over 4 ns (<1%)

0

± 1ns, 2ns

Linearity and noise level are acceptable

Solution: filter pole-zero removes some frequencies and improves shape this

way

Plateau and spill over are too large

Signal pulse is too Broad or tail is too long

87

88

Not shown today: work on HLT2, stripping and 3 body rare charm decays

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