# Presentation: 124446

## EbE Vertexing for Mixing (CDF-7673)Ds* and other “reflections”

- EbE Vertexing for Mixing (CDF-7673)Ds* and other “reflections”

- _Alessandro Cerri_, Marjorie Shapiro
- Aart Heijboer, Joe Kroll
- UPenn

## Two Talks in One

- EbE vertexing and ct scale factor:
- We preblessed and didn’t bless, why?
- Where are we
- Conclusions and plans
- Partially reconstructed Bs modes:
- Why bother?
- How to improve the naïve approach
- Is it feasible?
- Plans

## Plan

- Measure PV scale factor from V1-V2

- Data

- MC

- Consistency

- PV scale factor from V1-V2 on data

- Measure “N-1” Lxy and d0

- Data

- MC

- Consistency,
- Validate MC

- PV scale factor from V-truth on Monte Carlo

- Measure d0(B):
- Beam, TrackbasedEbE, BeamconstrainedEbE

- Relevance of beam resolution on Lxy

- Beam  scale factor not necessary

- Primary Vertex

- Secondary Vertex

- Beamline

## Problems after preblessing

- It was pointed out that our statistics is significantly lower than the standard analyses
- We identified the cuts responsible for that and relaxed them

## The samples (after relaxing cuts)

**B****d********D****+******
**~5500**

**B****+********D****0******
**~6800**

**B****0********J/********K****+**
**~****5500**

**B****0********J/********K*****+**
**~****3500**

**(non-prompt)**
**D****+********K****+******
**~****99500**

******’********J/******
**~****16000**

- ~22000 fully reco’d B, ~100000 Fully reco’d D+, ~16000 fully reco’d ’
- Montecarlo: mostly BGEN (basically all of the above+Bs), using Pythia if possible

## This comes with a price though!

|  | J/K+
BGEN | J/K+
Pythia | J/K+
Data | J/K*+
MC | J/K*+
Data | K+
MC | K+
Data | J/
MC | J/
Data |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| N-1 Lxy Pull | 1.180.02
0.4 | 1.240.016
0.12 | 1.350.017
0.4 | 1.180.02
0.3 | 1.560.02
0.2 | 1.140.009
0.02 | 1.220.004
0.03 | 1.160.02
0.1 | 1.210.01
0.2 |
| N-1 d0 Pull | 0.970.02
0.3 | 1.130.014
0.07 | 1.190.014
0.4 | 0.991.3
0.2 | 1.310.02
0.2 | 1.080.008
0.02 | 1.020.003
0.03 | 1.040.02
0.1 | 1.110.008
0.3 |
| MC XSV pull | 1.300.02
0.01 |  |  | 1.230.02
0.01 |  | 1.130.01
0.15 |  | 1.210.02
0.04 |  |
| MC YSV pull | 1.250.02
0.2 |  |  | 1.280.02
0.09 |  | 1.140.01
0.2 |  | 1.270.02
0.15 |  |
| MC ZSV pull | 1.170.02
0.03 |  |  | 1.150.02
0.01 |  | 1.160.01
0.01 |  | 1.090.02
0.07 |  |
| MC Lxy Pull | 1.150.02
0.04 |  |  | 1.180.02
0.04 |  | 1.170.01
0.15 |  | 1.200.02
0.01 |  |

- Large systematic uncertainties (up to 30%) and data/mc disagreement

- <1
- <2
- <3

## Differences with Preblessing

- We gain in statistics: consistent signal yield with CCKM analyses
- Looser cuts  secondary vertex pulls in general get larger
- Pay another price: larger pull discrepancy between data and MC
- The main source of  1) and 2) seems to be the 2 cut:

- N-1 Lxy Pull vs 23D

- N-1 Lxy Pll vs 2xy

- -Data
- -MC

- -Data
- -MC

- This does not quite explain 3), since agreement between data and MC seems pretty good!

- Old cut

- New cut

## Data-MC disgreement

- Disagreement is as large as O(30%)
- Can’t be neglected
- A difference in the distributions? (kinematics, geometry, chi2 etc.)
- 23D is not well reproduced, but we moved to 2xy
- Other discrepancies? No evident single-variable ones:

- -Data
- -MC

- 23D

- 2xy

- We compare systematically all the distributions and pull behaviors for the various samples, against MC

## Bottomline

- With larger statistics, relaxed cuts:
- No more dependence on ct/Lxy
- Kinematics MC and data differ significantly
- However Pulls don’t seem to depend on those (individually)
- Pulls do depend on 2 but this is expected since 2 can be expressed as a linear function of the pulls themselves!
- Pulls generally larger but far from the ‘7500 numbers (~1.3)
- We are re-generating MC samples as close as possible to the data kinematics

## Reproducing the ‘7500 approach

- We are able to roughly reproduce the ‘7500 quantity (Lxy of ‘fake’ B)
- We spent some time figuring out the discrepancies in our samples: skimming is in progress with selections as close as we can to the blessed result
- Remember this is a quantity which is DIFFERENT from what we usually use in our study
- For this sample there are reasons to believe that several variables (e.g. 2, isolation etc.) shouldn’t have the same distributions as the data:
- Presence of D+  and/or pions from secondaries will make it larger than in signal!
- Trigger confirmation different (D daughters only vs all B daughters)
- Lxy pull is bound to grow indefinitely with 2 for “background”!
- Larger 2  wider pull

- In any approach: a tight cut on 2 (and any sensitive selection variable) will reflect in a modification of the expected Lxy pull, no matter what the definition is!

## Conclusions on scale factors

- Changing cuts changes the scale factor
- Changing fit model changes the scale factor
- The scale factor is not really a “scale factor”: hidden dependencies
- A scale factor of 1.4 for the current analyses is “conservative” in terms of the limit we obtain
- For the future We know we can improve things!
- In progress:
- Cross check of blessed result: final word on reproducing the ‘7500 numbers
- MC generation to improve systematic uncertainty on PV and SV scale factors
- What is the best way of correcting the 2  dependence?

## Ds* & co.:anything below Ds containing useful information([Ds], Dsl, Ds, Ds...)

## A closer look at the MC mass distribution

- Ds
- DsK
- Ds
- Ds

- All histograms BGEN 5.3.1 with lum.avg. full simulation
- Below Main peak:
- Photon background nastier than the rest: leaks in!
- Larger uncertainty and correlation in the fit
- Extend to Bs to use detailed fit developed by Hung-Chung for B0 decays
- Different backgrounds overlap in the ‘satellite’ region
- Mass cut should help rendering K factors similar

- Once you get below the fully reco’d peak, you have to bite the bullet and deal with all the modes leaking in!

## Yields from mass fit

- Fit analogous to CCKM: same sample, similar results
- Fit systematics are a problem, especially for non-fully reco’d stuff:
- Combinatorial background could be a problem: d0(EbE) helps!
- BDK has 200% uncertainty until we measure the BR!
- Photon leak-in depends on detector resolution (can probably be controlled looking at the B0 edge)
- Keeping under control inter-mode correlations will be crucial!

## Ds* (..and Ds, and partially reconstructed more in general)

- Take this as an example: it is inevitable to have to deal with all the different modes at once!
- Interesting ‘cheap’ way of doubling our hadronic statistics
- BsDs*[Ds]
- Small q for in Ds* decay (analogous to D*D)
- Photon ~parallel to Ds
- What is the loss in momentum (ct) resolution?
- Negligible: happy hadronic-style analysis
- Not Negligible: mixed semileptonic-like approach
- K factor
- There are interesting differences and analogies (focus of this talk)

## Naïve approach

- K factor (MBs/Pt) distr.
- from realistic MC:
- ~10% uncertainty
- On B momentum
- Much better than
- Semileptonics
- Still NOT negligible
- Technically, Bs mixing on this sample is like measurement on the semileptonics:
- Better momentum resolution
- Nastier background:
- Oscillating
- Many hard to disentangle components (,Ds*,/e,DsK,?), each with (at least in principle) different K factor

- Ds
- DsK
- Ds
- Ds
- Ds m>5

## Improving the ct resolution

- Different strategies can be applied to ‘recover’ information on the missing momentum:
- BsDs K: use the right mass assumption/don’t use M in the K factor!
- BsDs X [4 unknowns]
- Impose Bs invariant mass (1 constr.)
- BsDs, Ds [3 unknowns]
- Ds* (or ) invariant mass (1 constr.)
- Ds* small q   ~parallel (<0.1 rad) to Ds (~2 constr.)
- Lxy/Lxy>7  reasonable lever arm for geometrical measurement of B direction
- Beamline / 2D EbE (1 constr.)
- 3D EbE (2 constr.)
- 2 Ways of applying each of this:
- Explicitly solve equation and derive quantity (easier)
- Refit topology (à la CTVMFT) with additional constraint(s) (more complicated)

## Ds* Mode

- Used as benchmark, once the technology is there it can easily be expanded to semileptonic and hadronic modes
- Today’s results based on explicit solution
- Feasibility of full refit under way
- We will explore the following cases:
- Bs mass and PPDs constraints (2+1)
- Ds*-Ds mass and PPDs constraints (2+1)
- Full 3D pointing constraint plus a combination of Bs and Ds*-Ds constraint (2+1)
- 2D pointing constraint using beamline plus full Bs and Ds*-Ds constraints (1+1+1)
- 2D pointing constraint using EbE plus full Bs and Ds*-Ds constraints (1+1+1)
- Result evaluated looking at the derived ‘K factor’

## Comparison of K factors

- Naïve derivation in several cases worse than upfront uncertainty
- Fully constrained refit is bound to be better, how much? (work in progress)

- Imposing PPDs yields overestimate of momentum, as expected
- 3D pointing alone is very poor constraint
- PPDs already improves K factor

| Constraints | Mean | RMS |
| --- | --- | --- |
| Default | 0.959 | 0.0276 |
| M(D*-D) | 1.027 | 0.0255 |
| M(Bs) | 1.013 | 0.0199 |
| ~3D | 0.996 | 0.147 |
| 2D (Beam) | 1.002 | 0.0317 |
| 2D (EbE) | 1 | 0.03202 |

## Conclusions

- Easiest inclusion of Ds* (& friends) is just a replica of the semileptonic approach
- Separation of modes and possible discrepancy in K factors could raise serious issues?
- Improvement on first-round is in principle possible:
- several constraints at hand
- Need lots of information (track parameters, covariances, vertices...)
- Aim:
- get the last word on how much we can improve before proceeding to a full-fledged analysis
- Reach a reasonable compromise between complication and improvement!
- We want to measure the Bs lifetime including all these modes:
- Important independent analysis
- Fundamental cross-check for partially reconstructed modes
- BR(BsDsK) Will come “for free” (piggyback on B+DK/)