Home » Blogs » hl60's blog

Dijet Sivers Analysis - requrest for preliminary results

Updated on Wed, 2020-04-01 17:36. Originally created by hl60 on 2019-09-30 14:01.

Comment:
The deltaZeta plot has been approved for DNP2019.
The kT plot is pending approval(originally for DIS2020).

===============================================================================
Title: Measurement of transverse single-spin asymmetries for di-jet production in polarized p+p collisions at √ s = 200 GeV at STAR 
   
PAs: Huanzhao Liu, Scott Wissink, Will Jacobs

Abstract (submitted for DIS2020):
Our understanding of the origin of the nucleon spin remains incomplete. Determining the partonic orbital angular momentum (OAM) contributions is particularly challenging experimentally. One possible handle on the partonic OAM would be detection of a non-zero Sivers effect, which characterizes the correlation between the transverse momentum of a parton (kT) and the transverse spin (S) of its proton, moving in the longitudinal (p) direction. Experimentally, the Sivers function can be accessed by searching for a spindependent preference in di-jet transverse opening angle, which reverses direction when the beam polarization direction is flipped. A previous effort by STAR using 1 pb−1 of p+p data taken in 2006 at √ s = 200 GeV did not find a significant effect due to limited statistics. In 2012 and 2015, STAR accumulated much larger datasets (∼33 times the di-jets after event selection) at √ s = 200 GeV. Moreover, a new technique has been implemented to tag the flavor of the fragmenting partons, to avoid cancellation between u and d quark effects, which are expected to have opposite signs. The current status of the measurement of Sivers asymmetries using STAR 2012 and 2015 p+p data at √ s = 200 GeV will be reported.

Plots:

1. The deltaZeta plot (approved for DNP2019)


deltaZeta - Plus-Tagging Results (Black Points)
eta1+eta2 -2.80±0.08 -1.97±0.13 -1.09±0.07 -0.38±0.08 0.38±0.08 1.09±0.07 1.95±0.13 2.80±0.08 Average
deltaZeta [deg] -0.231±0.175  0.020±0.049 0.010±0.031 0.037±0.024 0.028±0.023 0.094±0.030 0.092±0.049 0.221±0.194 0.042±0.012
deltaZeta - Minus-Tagging Results (RedPoints)
eta1+eta2 -2.80±0.08 -1.96±0.13 -1.09±0.07 -0.38±0.08 0.38±0.08 1.09±0.07 1.94±0.13 2.80±0.08 Average
deltaZeta
[deg]		 -0.241±0.196  -0.003±0.055 -0.068±0.035 -0.041±0.027 -0.043±0.027 -0.067±0.035 -0.078±0.058 -0.099±0.230 -0.051±0.014
deltaZeta - Zero-Tagging Results (Green Points)
eta1+eta2 -2.81±0.08 -1.95±0.13 -1.09±0.07 -0.38±0.08 0.38±0.08 1.09±0.07 1.97±0.13 2.81±0.08 Average
deltaZeta
[deg]		 -0.218±0.119  -0.007±0.032 0.001±0.020 -0.046±0.015 0.012±0.015 0.009±0.020 -0.013±0.030 0.057±0.105 -0.010±0.008


2.The kT plot (pending approval)


<kT> - Plus-Tagging Results (Black Points)
eta1+eta2 -2.80±0.08 -1.97±0.13 -1.09±0.07 -0.38±0.08 0.38±0.08 1.09±0.07 1.95±0.13 2.80±0.08 Average
<kT> [MeV/c] -34.13±25.93  3.17±7.57 1.51±4.83 5.75±3.72 4.34±3.61 14.57±4.59 14.25±7.57 32.73±28.67 6.49±1.90
<kT> - Minus-Tagging Results (RedPoints)
eta1+eta2 -2.80±0.08 -1.96±0.13 -1.09±0.07 -0.38±0.08 0.38±0.08 1.09±0.07 1.94±0.13 2.80±0.08 Average
<kT> [MeV/c] -35.66±28.97 -0.50±8.46 -10.52±5.39 -6.32±4.19 -6.70±4.17 -10.29±5.42 -12.06±9.00 -14.70±34.06 -7.90±2.18
<kT> - Zero-Tagging Results (Green Points)
eta1+eta2 -2.81±0.08 -1.95±0.13 -1.09±0.07 -0.38±0.08 0.38±0.08 1.09±0.07 1.97±0.13 2.81±0.08 Average
<kT> [MeV/c] -32.23±17.65 -1.08±5.02 0.10±3.06 -7.10±2.37 1.80±2.38 1.34±3.02 -2.00±4.68 8.41±15.47 -1.49±1.23

Summary:
<1> Dataset
  The dijet Sivers analysis uses the STAR 2012 & 2015 pp200 data. List of runs can be found in the attachment. The official 2012 pp200 embedding is used for the analysis.
<2> Jet Reconstruction
  The jets are reconstructed using Anti-kT algorithm with standard STAR configuration. Jet radius is chosen to be 0.6.
<3> Selection
  1) every jet in the event is required to have -0.8 < jet eta < 1.8 and -0.7 < jet detector eta < 1.7

  2) |VertexZ| < 90 cm
  3) number of jets in highest rank vertex = 2
  4) high-pT jet pT > 6 GeV/c, low-pT jet pT > 4 GeV/c
  5) dijet deltaPhi >120 deg
  6) 2/3 < ratio of the two jet pT <3/2 (apply only when any jet has tracks with pT>30 GeV/c)
<4> Method
  1) beam-jet association: blue beam is associated with more forward jets, yellow beam is associated with more backward jets.
  2) flavor-tagging: Tagging is based on Q = sum of track_z*track_charge within a jet, where tracks have to have pT > 0.8 GeV/c. Plus-tagging has Q > 0.25, Minus-tagging has Q < -0.25, and Zero-tagging has -0.25 < Q < 0.25.
  3) Asymmetry is extracted as the Zeta centroid shift between spin-up and spin-down states.
  4) deltaZeta-<kT> correlation is figured out using data to convert deltaZeta to <kT>.
<5> Systematic Uncertainties
  Estimation of the Systematic uncertainties is based on run12 pp200 embedding for run12 data, and run12 embedding with ADC threshold lowered by 3 units for run15 data. Systematic uncertainties are not included in the preliminary result. Current list of the systematic uncertainties to be presented in the final results are:

    1) Dilution to parton level <kT>: estimated to be ~5%.
    2) Physics Modeling: parton purities are deduced from Pythia simulation. The uncertainty due to the limited precision of Pythia is estimated to be ~10%-15% on average.
    3) Physics Selection: uncertainty from association and flavor-tagging due to the limited precision of Pythia:
        a) Beam-jet association: up to 1%
        b) Flavor-tagging: up to 4%
    4) Polarization uncertainty: 3.4% scale uncertainty

Presentation:
Spin PWG 04-01-2020: https://drupal.star.bnl.gov/STAR/system/files/DijetSivers_SpinPWG_040120.pdf
Spin PWG 02-26-2020: https://drupal.star.bnl.gov/STAR/system/files/DijetSivers_SpinPWG_022620.pdf

»