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Precision Alignment & Measurement Tools for Collider Physics Experiments

This study focuses on utilizing beam collision data to accurately measure and align detectors, improving momentum measurement in collider physics, calculating beam profiles, and generating data for various physics analyses. Key methods include Impact Parameter, D-phi correlation fits, and data generation tools like Pythia, enabling precise measurements without disrupting the beam. The study concludes that such methods are essential for alignment, detector resolution measurements, and trigger inputs, offering valuable insights for future physics experiments.

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Precision Alignment & Measurement Tools for Collider Physics Experiments

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  1. When Bunches Collide USCMS Hans Wenzel and Nick Leioatts

  2. Terminology • Pt – momentum transverse to the beam axis • Pseudorapidity – angle of a particle relative to the beam axis • Rapidity – angle and momentum of a particle relative to the beam axis

  3. Background • Beam width 20um • Arbitrary detector coordinate system • Other methods of reconstruction • must interrupt beam

  4. Purpose (Beam Position) • Find the origin of collisions without having to reconstruct the primary vertex • Align/Measure Resolution of Detectors • Important Input for many physics analyses • B lifetime • Improvement of momentum measurement (beam constrained track fit) • Input for the trigger • (SVT, HLT)

  5. Purpose (Beam Profile) • Useful feedback for the accelerator group (Measurement of beta-function) • Used for alignment of the Detector • Important resolution input for physics analyses

  6. Methods • Impact Parameter: D – closest approach of track to (0,0) • Phi(φ) – angle at minimum approach • Z0 – Z value at minimum approach

  7. D-φ Correlation D(φ0,Z0) = x0(sinφ0) + ax(sinφ0 )(Z0) – y0(cosφ0) - ay(cosφ0 )(Z0) ax, ay : x and y slope of beam • X0, Y0 : position of beam at Z = 0

  8. How many tracks? 1000 tracks needed for 1 micron precision

  9. (longer luminous region) 1000 tracks give 0.5 micron/cm precision

  10. β function • Width of the beam given Z • “Hourglass Effect” • Negligible in LHC

  11. Reconstruction Fit Beam Position D-phi fit Adjust track parameters to fitted beam position Fit Beta Function and longitudinal beam distribution Data Generation • Generation (MC) • Pythia generated minimum bias events • Pt filter (1.5 GeV/c) • Distribute according to betafunction • Calculate track parameters • Smear track parameters with resolution function • Displace beam • Generation (Accelerator) • Not done yet

  12. Rapidity and Pt of Pythia MC events • Pseudorapidity : η = -ln(tan(θ/2)) • Rapidity : y = (ln/2)*((E+pz)/(E-pz)) • Pt = √(ρx2+ρy2)

  13. Beam Profile

  14. Average abs(D0) vs Z correlation closest impact parameter (D0) given various errors in z

  15. What are we fitting? Fit Parameters: ε: Emittance β* Z0: Longitudinal beam Displacement σz: width of Longitudinal beam distribution

  16. σDtr(Pt) = 10μm + (10/Pt) 10000 tracks give 2cm (6%) precision

  17. Conclusions • Beam properties can be reconstructed from their tracks (no vertex fitting necessary) • This allows position and width to be measured without disrupting the beam • Important input for various physics analysis • Measurement tool for aligning and checking the alignment of tracking detectors and measuring the tracking IP resolution function.

  18. Future • Create accurate models of SVX and CMS detectors for analysis (Acceptance) • Apply to actual data (CDF)

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