# Presentation: 082766

## EbE Vertexing for Mixing

- Alex

## Status

- Increased sample’s statistics
- Full ~350 pb-1
- D0, D+, K+, K*, ’
- Primary Vertex:
- SF robustly sitting around 1.38
- Dependencies (Z,Pt,Si hits,Ntracks)
- Effect of hourglass
- G3X (no time to show today, but does not seem relevant with current statistics)
- Systematics
- Comparison of pulls and extraction of a common value:
- D0 vs Lxy
- Secondary Vertex:
- Dependencies (Z,,, Pt,Lxy,ct, ,R,Isolation,Si hits)
- Extraction of a common scale factor with systematics?

## Primary Vertex

## The tools

- Prompt peak
- V-truth
- V1-V2
- d0/

- B

- d0

- Lxy

## Scale Factor from V1-V2

- Fit two independent subsets of ‘primary’ [I.e. non-B] tracks
- Measure (x1,y1,z1) and (x2,y2,z2)
- Obtain / for x, y and z
- Fit core with single gaussian (central value)
- Repeat fit with two
- gaussians (‘syst.’)
- Still using 1.38
- For what follows

## Is the PVSF ‘universal’?

## Bottomline...

- Scale factor shows no strong dependence on variables probed
- Any other variable you want to see?
- We could be more accurate but remember that the statistics is limited!
- Focus on assessing systematics
- Inter-sample
- Vary fit model (just like the overall fit)
- Will try to improve a little more on statistics (K, D), but mostly aiming at improving systematics

## Impact Parameters

- PV scale factor is not the full story: when you bring down PV, the importance of SV increases
- Need to get the SV scale factor right!
- REM: **even if PVSF=SVSF, we cannot use one common LxySF**

- Apply 1.38x and beamline constraint, check what happens:
- For instance with D0: EbE: 1.351.15       EbE+SSvtx: 1.261.09

- We can use the B I.P. pulls as cross check of the Lxy resolution...

## Impact Parameters & scale factors

- 1.38x on SV

- 1.38x on PV

## Secondary Vertex

## Scale factor from B decays

- Example: BK+
- Fit  to a single vertex
- “point”  back to K
- Measure Lxy wrt B vertex
- Pull is a proxy for a “seconday vertex” pull!

- K

- 

- 

- B

- Primary Vertex

- “Two”

- “One”

## K

- K+
- Lxy(2)                  Pull

- K*
- Lxy(2)                 Pull

- Two gauss.          One Gaussian

## Charm...

- D+
- Lxy(2)                  Pull

- ’ “3-1”
- Lxy(2)                  Pull

- Two gauss.          One Gaussian

## ’ can be used in two different ways to probe SV

- Two gauss.          One Gaussian

- ’ “2-2”
- Lxy(2)                  Pull

- “3-1”

- “2-2”

## ..and can be used also to probe the PV scale factor

- 1.310.02

- 1.010.04

- “1.38”

- Prompt production
- Lxy wrt EbE is 0!

## Bottomline for SV

- Hidden dependencies!
- Detector acceptance?
- Kinematics?
- Multiplicity? (no: K*)
- Figure out which distributions are different
- Check dependency!

- ...results in the next pages

## Distributions

- Detector acceptance (z) pretty similar
- No clear difference in Si properties
- Kinematics differs ( R Pt)
- However...

**L****xy**** Pull**

**Z**

**Isol. (0.7)**

******R**

**#L00 tracks**

****

**Pt at ********<0.15**

**#stereo tracks**

**Pt at ********>0.15**

**Pt of two**

****** ****Of two**

**Ct of ‘one’**

**one’s Lxy**

****** ****Of two**

**Pt one’s tracks**

## Pulls vs variables in prev. page

- Comparing ’ to average of other samples in each bin
- Everything excluded except ct
- Why? I can think of possible reasons, but in terms of bugs mostly! WORK IN PROGRESS

**L****xy**** Pull**

**Z**

**Pt of two**

****** ****Of two**

**Isol. (0.7)**

******R**

**Ct of ‘one’**

**one’s Lxy**

****** ****Of two**

**#L00 tracks**

****

**Pt one’s tracks**

**Pt at ********<0.15**

**#stereo tracks**

**Pt at ********>0.15**

## Ct and Lxy

- Ct(one) distribution

- Lxy distribution

- Lxy(two) pulls vs Lxy(B)

- Lxy(two) pulls vs ct(B)

- The problem does not show up with prompt objects!

## D+ Montecarlo vs data

- Ct(one) distribution

- Lxy(one) distribution

- Lxy(two) pulls vs Lxy(B)

- Lxy(two) pulls vs ct(B)

- The problem does not show up in montecarlo!

## ’ data vs D+ MC

- They are compatible!
- The ‘bug’ affects non-prompt data only!!!

## Is it in (Lxy) or in Lxy?

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

- Lxy mean

- (Lxy) mean

- Lxy/(Lxy) mean

- Lxy width

- (Lxy) width

- Lxy/(Lxy) width

## Same plots for ’

- Same plots for ’

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

- Lxy mean

- (Lxy) mean

- Lxy/(Lxy) mean

- Lxy width

- (Lxy) width

- Lxy/(Lxy) width

## Same plots for MC D+

- Same plots for MC D+

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

**L****xy****(D****+****)**

- Lxy mean

- (Lxy) mean

- Lxy/(Lxy) mean

- Lxy width

- (Lxy) width

- Lxy/(Lxy) width

## Secondary Vertex Conclusions, so far

- We have enough statistics to study the SV scale factor
- Dependency on ct unexpected
- Problem shows up ‘only’ in long lived signal in data
- it’s a pity that’s what we want to use for our analyses ;)
- Semileptonic lifetime?
- Working on finding the cause
- Montecarlo: It works!
- Investigate other variables in data (Impact parameter?)
- Probe other samples (D0?)
- Possible candidates:
- Alignment
- Scale factors?
- This is the last pending big issue at the moment

## Moving along the plans for improvements!

- Understand beamline parameterization:
- Is it modeled correctly
- Is it measured correctly
-  Include our best knowledge of it!
- Are secondary vertex pulls ok?
- Check with montecarlo truth
- Use n-prong vertices (J/K, K+/0, K+/0)
- Investigate dependencies (Pt, z,multiplicity, ) with full statistics

## Plan

- PV shows a very consistent picture
- Finish up PV studies (~days):
- re-run some ntuples to get full statistics in all cases
- Including K, D
- Use also BK background to get a source of studies for prompt Lxy pulls?
- SV riddle to be solved!
- I am working full steam on this.
- Two more weeks according to schedule, to straighten everything out, document and insert in  the blessing pipeline.

## Backup

## Outline

- Current status
- What was used for the mixing results
- What is the current understanding of Ebe
- Plans for improvements
- How can we improve?

## Current status

- Hourglass

- EbE: itearative track selection/pruning algorithm to provide an unbiased estimate of the PV position on an Event-by-Event basis
- Hadronic analyses used a flat ~25um beamline!
- Possible improvements:
- Move to “hourglass”
- Move to EbE
- EbE + Hourglass
- One of the 1⁄2 leptonic
- analyses used this with
- fixed hourglass parameters

## What do we know about EbE?

- Unbiased estimator of PVTX

|  | Transverse | Z |
| --- | --- | --- |
| Data (V1-V2) | 1.330.035 | 1.370.035 |
| MC (V1-V2) | 1.1920.034 | 1.260.035 |
| MC (V-truth) | 1.240.036 | 1.230.032 |
| J/ Prompt Peak | 1.2360.024 | ~ND~ |
| J/ d0/ | 1.1760.019 | ~ND~ |

- Reasonable (~5%) control of systematics

## Cross checks using I.P.(B)

- Lxy involves three ingredients:
- EbE
- Secondary vertex
- Beamline (in beamline constrained fits)

- Z dep. Beamline improves pulls!

- Scale factors work!

- Something funny when beamline is used!

- B

- d0

- Lxy

## Time dependence of Hourglass parameters

- Implementing DB access of time-dependent parameters

## What do we gain?

- 15-20% In vertex resolution!
- Better control of systematics (hard to evaluate)
- Correct EbE resolution (it is not clear that it is correct now)

- Red arrow is the effect of 1. Only
- Point 2. Affects mostly the green area (tiny ?)
- Point 3. Has an effect qualitatively similar to 1., but hard to evaluate

- Euphemism

## Hadronic analysis systematics

- ct scale factor                        0.000   0.024   0.061   0.090  0.144

## Hourglass parameters from DBProfiles

## Relative PV/BV contribution to d0 and Lxy pulls

- B

- d0

- Lxy

- PV and BV are linear combinations of the same covariances (PV, SV), with different coefficients
- Lxy sensitive to the major axis of SV
- Relative weight of PV and SV covariances different for Lxy and d0
- Look at:

- w

- w

- Note: the two Lxy (or d0) pieces do not linearly add to 1!

## Relative PV/BV contribution to IP and Lxy pulls

- B

- d0

- Lxy

- Not Beam Constrained
- Beam constrained
- Beam constrained with run-dep. hourglass

## Bottomline:

- SV and PV enter very differently in Lxy and d0
- Relative contribution depends strongly on PV and SV scales
- Beam constraint squeezes the PV resolution significantly. Becomes second order on Lxy!
- We are in a regime where the SV scale factor is critical!
- ... now let’s get more quantitative!