1 / 27

# Update: Beam Parameters from Dimuons - PowerPoint PPT Presentation

Update: Beam Parameters from Dimuons. 26 July 2004 Josh Thompson Aaron Roodman SLAC. Overview. Quick summary of the initial analysis: goals and technique Details about problems that arose during the initial analysis and studies conducted since then Steps to move forward with the analysis

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.

Update: Beam Parameters from Dimuons

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

## Update: Beam Parameters from Dimuons

26 July 2004

Josh Thompson

Aaron Roodman

SLAC

### Overview

• Quick summary of the initial analysis: goals and technique

• Details about problems that arose during the initial analysis and studies conducted since then

• Steps to move forward with the analysis

• What changes are being implemented

• What will be implemented in the future

### Beam Parameters from Dimuons

• Goal: measure beam parameters epsilon_y and beta*_y (at the IP)

• Due to hourglass effect, sigma_y of the interaction region should have a parabolic shape as a function of z, with a central waist

• Technique is to fit for sigma_y as a function of z and use this to extract beam parameters

### Gregory Schott method

• Using whole data sample (selection cuts applied):

• Fit z0, sigmaz to Gaussian

• Fix z0, sigmaz; fit x0, sigmax, y0, sigmay, 3 tilts, constant background term with a PDF for the doca distribution

• In bins of z:

• Fit y0, sigmay (optionally x0, sigmax) with other params fixed from above fit

• Correct sigmay for resolution variation with z (use doca error vs z plot; details follow)

### (Details)

• Tracks in dimuon events are independent (not vertexed)

• Selection cuts:

• tan(lambda1) + tan(lambda2) > 0.5 (cut cosmics)

• |10.58 GeV - m_mm| < 0.3 GeV

• nDCH >= 20 && nSVT >= 5

• cos(phi1 – phi2) < -0.99

• cos(theta) < 0.75

### First some review

Is the error on the track doca (from the covariance matrix of the track fit) reliable?

Yes: The measured miss distance between the docas of the two tracks in an event does correlate nicely to the combined doca errors for tracks 1 and 2

I get the same slope as in GS’s thesis: 1.2 mm/mm

• So the doca error from the fit is likely a good measure of resolution

• We will come back to this correlation later

Width of miss distance distribution (cm)

sqrt((doca error 1)^2 + (doca error 2)^2) (cm)

(verticality cut applied)

Error on doca

phi

### Problem 1:Error on doca w.r.t. phi

• Why do we care?

• We need to understand all aspects of the resolution

• GS: Integral over a track distribution flat in phi is assumed in the PDF, so cuts must preserve that distributionthis plot means we can’t cut directly on track quality

• I had 2 issues with this distribution:

• ‘Good’ regions have ~15-20um resolution while ‘bad’ regions have ~20-25um resolution – regions are almost mutually exclusive in doca error

• phi distribution of ‘good’ and ‘bad’ regions is unintuitive  Next page

### Is SVT structure the problem?

• Naively: doca resolution dominated by inner SVT layers

• Best resolution comes when first hit is as close as possible to IP and track is at a right angle to the SVT plane

• Extra material (eg SVT support ribs) degrades resolution

Dimuon tracks

(same plot as prev. page but showing only events on “SVT” plot at right)

Color code by doca error: >20umred; <20umgreen

mm

### SVT structure (II)

Color code by doca error: >20umred; <20umgreen

• From this (partial and hand-drawn) picture of the SVT:

• Each of the 6 modules of the inner SVT layer is split between a green region and red region

• No obvious reason why there should be a large resolution shift in the middle of each module, or from one module to the next at the same phi

### Problem 1 solved

• For the phi side only of Layers 1 and 2 of the SVT:

• ~Half of each module has every SVT strip connected for readout

• The rest of each module has every other strip “floating” (ie not read out)

• known as skip bonding

• Looking at the info in the SvtHitOnTrk of the Layer 1 phi-side hit:

• Blue (solid) histo shows phi distrib of events with regular bonding

• Red (dashed) histo shows phi distrib of events with skip bonding

Events

doca error (backw)

phi (backw)

(forw)

### Problem 2:Resolution variation with z

doca err

• As GS observed, the doca error decreases with increasing z (true for miss distance as well)

• [doca error is a single track quantity, so more convenient for detector studies]

• GS thesis: slope = -0.385 mm/cm

• Here: slope (forw) = -0.42 mm/cm

• slope (backw) = -0.24 mm/cm

•  Look at doca error in bins of theta

z

(backw)

doca err

### Expanded resolution studies

• How does resolution vary as a function of z and theta together?

• Use doca error in bins of theta and z

• But this is a two-peaked distribution (due to bonding difference)

• Is the mean of the distribution adequate?

• Fit to 2 Gaussians

• Also look at material length in SVT

### Material Length

Total material seen by tracks in first 15cm (x-y) of flight (approx SVT radius)

cm

For simplicity, I will look at the mean of this distribution

Caveat: This study looks at detector material path length in cm—not g/cm^2. I will work on getting that additional information.

(info comes from pathLength() method of DetIntersection)

### Material Length (II)

Mean of distribution from last page, binned in cos(theta) v z

(cm)

(cm)

First 15 cm (x-y) of flight

First 6 cm (x-y) of flight

Profiles: Material Length v z

6 cm of flight

15 cm of flight

(note suppressed zeros on y axes)

15 cm of flight

cos(theta)>0.65

6 cm of flight

cos(theta)>0.65

### Material Length v z

• Conclusion: All show a negative slope, but very slight and consistent with zero within errors

• Material length is not causing the resolution variation w.r.t. z

• I need to look at mass thickness to confirm this conclusion

-1.2<z<0.93 (cm)

0.69<cos(t)<0.75

1.47<z<1.73 (cm)

0.69<cos(t)<0.75

Sample Fits

-1.2<z<0.93 (cm)

0.43<cos(t)<0.50

1.47<z<1.73 (cm)

0.43<cos(t)<0.50

cos(theta)

Lower mean of doca err distribution (cm)

z (cm)

### theta and z dependence of doca error

• In the forward direction, this plot shows the resolution getting better as z increases

• At lower cos(theta) this is less pronounced. (NB: transition from forw to backw tracks occurs at cos(theta)~0.5)

• Lower mean correlates well with higher mean—high mean plot looks similar (see extra slide)

Resolution correction as a function of z only is probably not sufficient

Possible band of lower resolution diagonally across plot?

Average number of SVT hits in Layers 1,2,3:

All strips

Phi strips only

### Diagonal Band?

(note expansion in z scale; outer bins statistically limited)

Fraction of tracks w/a phi side hit in Layer 1

cos(theta)

### Missing f hit in Layer 1

z (cm)

Plug in x-y flight length l = 3.2 cm (min. radius of L1):

zL1 = z0 + l*tan(l) = z0 + 3.2*tan(p/2 – q) ~ 2.5 cm across the band

### Where do we go from here?

• [GS correction: sy,corrected2 = sy,fit2 / (1+slopefit*z/interceptfit)2 ]

• Incorporate the resolution directly into the PDF:

• Replace sdoca2 = sx2*sin2(f) + sy2*cos2(f) with:

• sdoca2 = sx2*sin2(f) + sy2*cos2(f) + sresolution2

• sresolution is the doca error from the track fit adjusted by a resolution function

• Resolution function comes from miss distance v doca error

• To do: Study this function more completely (e.g. is the miss distance distribution really Gaussian?)

### Test New PDF

• First run simple toys on new PDF:

• Generate data samples (Gaussian distributions of the fit parameters)

• Make sure fit gives the expected results

• In progress now

• Next look at MC:

• Generate MC with various beam distributions to test if fits return expected results

### Summary

• Understand the resolution variation in phi and see that the variation in z is more complicated than just a simple change with z

• Strategy: Incorporate doca error directly into the fit (starting from GS’s original fit)  correct for resolution event-by-event

• (alternately, use RMS miss distance in bins of theta, phi, and z)

• First test in toys and MC, see if fit is stable and unbiased

• Then try on data

## Extras

### Track distribution in cos(theta) – z plane

(Note: there may be tracks in bins which show “0” (white) here. Only bins w/ more than a certain threshold of tracks (~50) were filled.)