Measurement of the cross section for prompt isolated diphoton production in pp̄ collisions at √s=1.96TeV

T. Aaltonen, Helsingin Yliopisto
B. Álvarez González, Universidad de Cantabria
S. Amerio, Istituto Nazionale Di Fisica Nucleare, Sezione di Padova
D. Amidei, University of Michigan, Ann Arbor
A. Anastassov, Northwestern University
A. Annovi, INFN, Laboratori Nazionali Di Frascati
J. Antos, Univerzita Komenského v Bratislave
G. Apollinari, Fermi National Accelerator Laboratory
J. A. Appel, Fermi National Accelerator Laboratory
A. Apresyan, Purdue University
T. Arisawa, Waseda University
A. Artikov, Joint Institute for Nuclear Research, Dubna
J. Asaadi, Texas A&M University
W. Ashmanskas, Fermi National Accelerator Laboratory
B. Auerbach, Yale University
A. Aurisano, Texas A&M University
F. Azfar, University of Oxford
W. Badgett, Fermi National Accelerator Laboratory
A. Barbaro-Galtieri, Lawrence Berkeley National Laboratory
V. E. Barnes, Purdue University
B. A. Barnett, Johns Hopkins University
P. Barria, Istituto Nazionale di Fisica Nucleare, Sezione di Pisa
P. Bartos, Univerzita Komenského v Bratislave
M. Bauce, Istituto Nazionale Di Fisica Nucleare, Sezione di Padova
G. Bauer, Massachusetts Institute of Technology
F. Bedeschi, Istituto Nazionale di Fisica Nucleare, Sezione di Pisa
D. Beecher, University College London
S. Behari, Johns Hopkins University

Abstract

This Letter reports a measurement of the cross section of prompt isolated photon pair production in pp̄ collisions at a total energy √s=1.96TeV using data of 5.36fb-1 integrated luminosity collected with the CDF II detector at the Fermilab Tevatron. The measured cross section, differential in basic kinematic variables, is compared with three perturbative QCD predictions, a leading order parton shower calculation and two next-to-leading order calculations. The next-to-leading order calculations reproduce most aspects of the data. By including photon radiation from quarks before and after hard scattering, the parton shower prediction becomes competitive with the next-to-leading order predictions.