Cookies

We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.


Durham Research Online
You are in:

Calculations for deep inelastic scattering using fast interpolation grid techniques at NNLO in QCD and the extraction of αs from HERA data.

Britzger, D. and Currie, J. and Ridder, A. Gehrmann-De and Gehrmann, T. and Glover, E. W. N. and Gwenlan, C. and Huss, A. and Morgan, T. and Niehues, J. and Pires, J. and Rabbertz, K. and Sutton, M. R. (2019) 'Calculations for deep inelastic scattering using fast interpolation grid techniques at NNLO in QCD and the extraction of αs from HERA data.', The European physical journal C., 79 (10). p. 845.

Abstract

The extension of interpolation-grid frameworks for perturbative QCD calculations at next-to-next-to-leading order (NNLO) is presented for deep inelastic scattering (DIS) processes. A fast and flexible evaluation of higher-order predictions for any a posteriori choice of parton distribution functions (PDFs) or value of the strong coupling constant is essential in iterative fitting procedures to extract PDFs and Standard Model parameters as well as for a detailed study of the scale dependence. The APPLfast project, described here, provides a generic interface between the parton-level Monte Carlo program NNLOjet and both the APPLgrid and fastNLO libraries for the production of interpolation grids at NNLO accuracy. Details of the interface for DIS processes are presented together with the required interpolation grids at NNLO, which are made available. They cover numerous inclusive jet measurements by the H1 and ZEUS experiments at HERA. An extraction of the strong coupling constant is performed as an application of the use of such grids and a best-fit value of αs(MZ)=0.1170(15)exp(25)th is obtained using the HERA inclusive jet cross section data.

Item Type:Article
Full text:(VoR) Version of Record
Available under License - Creative Commons Attribution.
Download PDF
(1270Kb)
Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1140/epjc/s10052-019-7351-x
Publisher statement:© The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Funded by SCOAP3
Date accepted:27 September 2019
Date deposited:18 October 2019
Date of first online publication:14 October 2019
Date first made open access:18 October 2019

Save or Share this output

Export:
Export
Look up in GoogleScholar