activity
19982002
most citedModelling generalized parton distributions to describe deeply virtual Compton scattering data

75 citations · 362 across the 7 of their papers we have counts for

collaborators

8 papers

hep-ph2002★ 75 cited

Modelling generalized parton distributions to describe deeply virtual Compton scattering data

A. Freund, M. McDermott, M. Strikman

We present a new model for generalized parton distributions (GPDs), based on the aligned jet model, which successfully describes the deeply virtual Compton scattering (DVCS) data f…

hep-ph2002★ 52 cited

Nuclear shadowing in deep inelastic scattering on nuclei: leading twist versus eikonal approaches

L. Frankfurt, V. Guzey, M. McDermott +1

We use several diverse parameterizations of diffractive parton distributions, extracted in leading twist QCD analyses of the HERA diffractive deep inelastic scattering (DIS) data,…

hep-ph2001★ 65 cited

A detailed next-to-leading order QCD analysis of deeply virtual Compton scattering observables

Andreas Freund, Martin McDermott

We present a detailed next-to-leading order (NLO) leading twist QCD analysis of deeply virtual Compton scattering (DVCS) observables, for several different input scenarios, in the…

hep-ph2001★ 33 cited

Colour dipoles and virtual Compton scattering

M. McDermott, R. Sandapen, G. Shaw

An analysis of Deeply Virtual Compton Scattering (DVCS) is made within the colour dipole model. We compare and contrast two models for the dipole cross-section which have been succ…

hep-ph2001★ 58 cited

A next-to-leading order QCD analysis of deeply virtual Compton scattering amplitudes

A. Freund, M. F. McDermott

We present a next-to-leading order (NLO) QCD analysis of unpolarized and polarized deeply virtual Compton scattering (DVCS) amplitudes, for two different input scenarios, in the $\…

hep-ph2001★ 28 cited

Next-to-leading order evolution of generalized parton distributions for HERA and HERMES

A. Freund, M. F. McDermott

The QCD evolution of both unpolarized and polarized generalized parton distributions (GPDs) to next-to-leading order (NLO) accuracy is presented, in both the DGLAP and ERBL regions…