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Forward Proton Detector

Forward Proton Detector. Nine independent spectrometers each consisting of two detectors. Scattered antiprotons. Scattered Protons. A UP Spectrometer. P UP Spectrometer. Dipole Magnets. Quadrupole Magnets. Quadrupole Magnets. Separator. Separator. z [m]. Dipole Spectrometer. IP.

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Forward Proton Detector

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  1. Forward Proton Detector Nine independent spectrometers each consisting of two detectors Scattered antiprotons Scattered Protons AUP Spectrometer PUP Spectrometer Dipole Magnets Quadrupole Magnets Quadrupole Magnets Separator Separator z [m] Dipole Spectrometer IP ADOWN Spectrometer PDOWN Spectrometer 109 nsec 78 nsec 78 nsec 109 nsec 200 nsec  Reconstruct particle tracks from detector (scintillating fiber) hits Dipole SpectrometerQuadrupole Spectrometers |t| ~ 0.0 GeV2 |t| > 0.8 GeV2 x > 0.04 x > 0.0  18 Pots integrated into DØ readout and inserted every store from Jan 2004 to Feb 2006 DOE Review Nov. 14, 2008 Arlington

  2. Low Luminosity Proposal Proposal I: Run with injection tune (*=1.6m), 1 p on 4 pbar (originally 2x4 but CDF not interested), no low  squeeze, collisions by ramping down separator voltages. This particular configuration is required to minimize setup time and extra collisions. (1x1 actually achieved)

  3. pot position integ. luminosity Elastic t Distribution estimated t range accessible with injection tune

  4. Some pots less than 4 mm from beam, limited by rate or in-limit switch

  5. Error propagation Elastic d/dt Main sources of error: - Uncertainty in pot positions=300 mm - Uncertainty in beam divergence=5mrad - Uncertainty in efficiencies - Uncertainty in Luminosity - Uncertainty in Ansatz function used in MC Luminosity is determined by comparing # jets from run IIA and High b store: Lumi = 30.6 ± 4.0 nb-1 Systematic errors included Statistical Errors only

  6. Elastic d/dt average DØ PRELIMINARY Carlos Avila (Bogota) main analyst Brandt editing physics note/paper

  7. Inclusive Double Pomeron Strategy • Use prescaled single arm triggers to model background • by randomly combining a p and a pbar event; compare to • DPOM trigger which should include the background + correlated • ppbar events. • Backgrounds include (SD, halo, ELAS(1), DPOM(1)) in various • combinations. • We can measure t distributions of SD (one side LM on and one • side off), halo (flag with TDC), ELAS(1) (from Elastic samples), • assume DPOM(1)= DPOM(2), and fit for fraction that are • DPOM-like, which should be higher in DPOM trigger. • Apply cuts (halo rejection, primary vertex), and refit, should get • higher DPOM fraction

  8. Inclusive Double Pomeron After vertex cut, fake background appears to have a higher ELAS(1) component. Vlastaabandonned analysis, Arnab has taken over, working on DØ low pT tracking <t>=0.63 <t>=0.99 DPOM trigger Fake Background Work in progress to validate and quantify

  9. Inclusive Double Pomeron

  10. DØ Summary • Thanks to hard work of Carlos we finally now have a preliminary measurement of elastic d/dt in the range 0.2<|t|<1.3 (Gev/c)2. • The delay in the analysis is finding the trigger efficiencies and the hit reco efficiencies which are correlated given the fact that they come from the same source: THE FIBERS. • Publishing this paper will be a great relief and will pave the way for future publications, such as inclusive double pomeron (Arnab) • I’ve taken over the editing of the hardware paper which was stalled, and expecttopublishthison similar timescale in NIM or J Inst. • Arnab isdoing tracking shifts, my only DØ involvementistryingtogetoutpapers

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