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This update discusses the analysis of unidentified charged tracks in the muon arms of the PPG experiment, highlighting the fitting method used to extract jet yield. Two scenarios in d+Au and p+p collisions are examined, particularly with respect to away side width considerations. A detailed yield comparison between unidentified and identified hadrons is presented, alongside various correlation functions for different centrality classes in d+Au. Next steps include data presentation strategies and potential discussions with theorists regarding PYTHIA simulations.
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What is new • Unidentified charged tracks in muon arms are analyzed. Results are compared with Identified hadrons. • Fitting method is used to extract jet yield. There are two details, • 1.) In d+Au, the away side width is fixed by p+p. • 2.) In d+Au, the away side width is not fixed. • Comparison between fitting method and counting method.
Selection of unidentified charged tracks • chi2 < 20 • depth > 0 • DG0 < 20 cm • nhits > 12 • angle between station1 hit position vector and station1 momentum • theta_xp < 0.03 radian.
Yield comparison between unidentified and identified hadrons
Yield comparison between unidentified and identified hadrons
North central correlation function in 0-40% d+Au with combined statistics and fixed width
North central correlation function in 40-88% d+Au with combined statistics and fixed width
South central correlation function in 0-40% d+Au with combined statistics and fixed width
South central correlation function in 40-88% d+Au with combined statistics and fixed width
North central correlation function in 0-40% d+Au with combined statistics and without fixing width
North central correlation function in 40-88% d+Au with combined statistics and without fixing width
South central correlation function in 0-40% d+Au with combined statistics and without fixing width
South central correlation function in 40-88% d+Au with combined statistics and without fixing width
Width from d+Au 0-40% 40-88% South-central North-central
What next • There is no more statistic! We have to finger out a way to present the data best. E.g. Do we use the fitting or counting( more robust)? do we need to split more bins in centrality and pt ? • PYTHIA, I will do it ASAP. • Draft ? Discussion with theorist has to be done.