Measurement of the isolated diphoton cross-section in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

TL;DR

This ATLAS study measures the isolated diphoton production cross-section in $pp$ collisions at $\sqrt{s}=7$ TeV using 2010 data corresponding to $37.2\;\mathrm{pb}^{-1}$. Photon candidates are selected with tight identification and isolation, and backgrounds from jets and electrons are estimated with fully data-driven techniques and subtracted. Differential cross-sections in $m_{\gamma\gamma}$, $p_{T,\gamma\gamma}$, and $\Delta\phi_{\gamma\gamma}$ are extracted and compared to NLO predictions from DIPHOX and ResBos; while $d\sigma/dm_{\gamma\gamma}$ and $d\sigma/dp_{T,\gamma\gamma}$ are broadly consistent, the observed $d\sigma/d\Delta\phi_{\gamma\gamma}$ distribution is significantly broader than theory, highlighting the role of fragmentation and soft-gluon effects. The results provide a data-driven benchmark for QCD modelling of diphoton processes and have implications for Higgs and beyond-the-Standard-Model searches that rely on photon final states.

Abstract

The ATLAS experiment has measured the production cross-section of events with two isolated photons in the final state, in proton-proton collisions at sqrt(s) = 7 TeV. The full data set acquired in 2010 is used, corresponding to an integrated luminosity of 37 pb^-1. The background, consisting of hadronic jets and isolated electrons, is estimated with fully data-driven techniques and subtracted. The differential cross-sections, as functions of the di-photon mass, total transverse momentum and azimuthal separation, are presented and compared to the predictions of next-to-leading-order QCD.

Figures (9)

• Figure 1: Extraction of the isolation energy ($E_{\mathrm{T}}^{\mathrm{iso}}$) distributions, for signal and background. The plots are made with a "di-jet-like" Monte Carlo sample: the "signal" and "background" classifications are based on the Monte Carlo information. (a) Normalized $E_{\mathrm{T}}^{\mathrm{iso}}$ distribution for the background and for the non-tight sample. (b) $E_{\mathrm{T}}^{\mathrm{iso}}$ distribution, for the tight and the non-tight samples: the latter is scaled as explained in the text. (c) Normalized $E_{\mathrm{T}}^{\mathrm{iso}}$ distribution for the signal and for the tight sample, after subtracting the scaled non-tight sample. In (a,c) the vertical line shows the isolation cut $E_{\mathrm{T}}^{\mathrm{iso}}<3$ GeV.
• Figure 2: Data-driven signal isolation distributions for the leading (top) and sub-leading (bottom) photons obtained using the photon candidates (solid circles) or extrapolated from electrons (continuous lines).
• Figure 3: Differential ${\gamma\gamma}$ yields in the $\mathbf{T}$$\mathbf{I}$$\mathbf{T}$$\mathbf{I}$ sample ($N^{\mathbf{T}\mathbf{I}\mathbf{T}\mathbf{I}}_{\gamma\gamma}$), as a function of the three observables $m_{\gamma\gamma}$, $p_{\mathrm{T},{\gamma\gamma}}$, $\Delta\phi_{\gamma\gamma}$, obtained with the three methods. In each bin, the yield is divided by the bin width. The vertical error bars display the total errors, accounting for both the statistical uncertainties and the systematic effects. The points are artificially shifted horizontally, to better display the three results.
• Figure 4: Projections of the 2-dimensional PDF fit on transverse isolation energies of the two photon candidates: leading photon (top) and sub-leading photon (bottom). Solid circles represent the observed data. The continuous curve is the fit result, while the dashed-dotted curve shows the ${\gamma\gamma}$ component. The dashed line represents the background component of the leading and sub-leading photon sample, respectively
• Figure 5: Schematic representation of the two-dimensional sideband method. The top plane displays the isolation ($x$-axis) and tight identification ($y$-axis) criteria for the classification of the leading photon candidate. When the leading photon belongs to region $A$, the same classification is applied to the sub-leading photon, as described by the bottom plane.