Quick search Find article
Quick search
Find article

Parton distribution functions suitable for Monte-Carlo event generators

John C. Collins1 and Xiaomin Zu1

Show affiliations


In the usual factorization theorems, which give predictions only for inclusive cross sections, there is considerable freedom in the choice of the scheme to define the parton distribution functions. These theorems do not directly apply to Monte-Carlo event generators, and more general factorization theorems which give predictions for fully exclusive cross sections are needed. It has been shown that appropriate parton distribution functions are uniquely defined by the showering algorithm. In this paper, we present results of calculations of the Monte-Carlo parton distribution functions in terms of the commonly used overlineMS parton distribution functions. At small x the differences are large, which demonstrates the importance of using the correct parton distribution functions in an event generator rather than overlineMS parton distribution functions. We present some simple approximations that enable an understanding of the sizes of the results to be obtained.


Keywords

QCD

NLO Computations

 

E-print Number: hep-ph/0204127

Cited: by |

Refers: to

PACS

12.38.Aw General properties of QCD (dynamics, confinement, etc.)

02.50.Ng Distribution theory and Monte Carlo studies

12.39.St Factorization

Subjects

Computational physics

Particle physics and field theory

Dates

Issue 06 (June 2002)

Received 17 April 2002, accepted for publication 10 June 2002

Published 18 June 2002



Related review articles

What's this?
View review articles related to this research to gain an insight into the key trends in this subject area. Related review articles are selected based on PACS/MSC codes, and are no more than three years old.

  1. The quark–gluon medium
  2. The phase diagram of dense QCD
  3. Exotic charmonium
More

View by subject




Export








Please login to access our web services, or create an account if you don't yet have one.

You must have cookies enabled in your web browser to be able to login.

Username
Password

Forgotten your password? Get a new one here.