Threshold resummation in direct photon production
Nobuo Sato
Florida State University In collaboration with:
- J. Owens
Threshold resummation in direct photon production Nobuo Sato - - PowerPoint PPT Presentation
Threshold resummation in direct photon production Nobuo Sato Florida State University In collaboration with: J. Owens Motivation: Parton distribution functions (PDFs) - essential ingredients for hadron colliders. PDFs cannot be
◮ Parton distribution functions (PDFs) - essential ingredients for
◮ PDFs cannot be computed from first principles - extracted from
◮ The uncertainties in the fitted PDFs are different among the parton
◮ In particular, gluon distribution is unconstrained at large x. ◮ Production of a state with mass m and rapidity y probes PDFs at
◮ In the past, the data was used to constrain gluon PDF at large
◮ It was removed from global fittings due to inconsistencies between
◮ Recently (1202.1762) d’Enterria and J. Rojo have included isolated
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WA70 √s = 23.0GeV pp CDF √s = 1800.0GeV p¯ p D0 √s = 1960.0GeV p¯ p E706 √s = 31.5GeV pp E706 √s = 38.7GeV pp PHENIX √s = 200.0GeV pp R110 √s = 63.0GeV pp R806 √s = 63.0GeV pp R807 √s = 63.0GeV pp UA6 √s = 24.3GeV pp UA6 √s = 24.3GeV p¯ p
◮ Catani, Mangano, Nason, Oleari, Vogelsang, hep-ph/9903436
◮ de Florian, Vogelsang, hep-ph/0506150
T
◮ Direct contribution: Dγ/γ = δ(1 − z) ◮ Jet fragmentation: Dγ/c ∼ αem/αS
T
sL4
sL3
sL2
sL
s L2n
s L2n−1
s L2n−2
T ) “Threshold logs” ◮ Resummation: technique to find the exponential representation of
T
x2
T
x2 T xa
xT √xaxb
T
xT z√xaxb ⊂ [xT , 1] ◮ Collider: CDF(√s = 1.8 TeV): xT ⊂ [0.03, 0.11]. ◮ Fixed Target: UA6(√s = 24 GeV): xT ⊂ [0.3, 0.6]. ◮ Threshold logs are more relevant for fixed target experiments. ◮ Due to PDFs, xa,b is small so that z → 1. This enhances the
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direct direct+fragment fragment direct+fragment
◮ Resummation is performed in “mellin space”:
c−i∞
◮ The invariant cross section in N-space:
T
◮ The resummed partonic cross section in N-space is given by:
N∆b N∆c NJd N
i,N
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◮ The current code of NLO+NLL is too slow to be used in global fits. ◮ An alternative to global fits exist: Bayesian reweighting technique.
◮ This technique is suitable for montecarlo based PDFs such as
◮ Watt and Thorne (1205.4024) proposed a way to apply the
◮ random PDFs:
◮ for each fk compute:
k =
◮ get weights as:
k)
1 2 (Npts−1) ∗ e− 1 2 χ2(k)
k)
1 2 (Npts−1) ∗ e− 1 2 χ2(k)
◮ observables are given as:
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k−th random PDF set best k−th random PDF set central cteq6mE UA6(pp)
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experimental xT range unweighted error band weighted error band
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experimental xT range unweighted error band weighted error band
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◮ High-x PDFs important for production of a state with mass m at
◮ Threshold resummation improves the theoretical prediction of direct
◮ Reweighting studies in other PDFs sets. ◮ Analysis of the global χ2 after reweighting. ◮ Develop a faster code for global fitting. ◮ Compare with scet techniques.