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Precise predictions for V+jets dark matter backgrounds. V + jets dark matter backgrounds

Lindert, J. M. and Pozzorini, S. and Boughezal, R. and Campbell, J. M. and Denner, A. and Dittmaier, S. and Gehrmann-De Ridder, A. and Gehrmann, T. and Glover, N. and Huss, A. and Kallweit, S. and Maierhöfer, P. and Mangano, M. L. and Morgan, T. A. and Mück, A. and Petriello, F. and Salam, G. P. and Schönherr, M. and Williams, C. (2017) 'Precise predictions for V+jets dark matter backgrounds. V + jets dark matter backgrounds.', The European physical journal C., 77 (12). p. 829.


High-energy jets recoiling against missing transverse energy (MET) are powerful probes of dark matter at the LHC. Searches based on large MET signatures require a precise control of the Z(νν¯)+Z(νν¯)+ jet background in the signal region. This can be achieved by taking accurate data in control regions dominated by Z(ℓ+ℓ−)+Z(ℓ+ℓ−)+ jet, W(ℓν)+W(ℓν)+ jet and γ+γ+ jet production, and extrapolating to the Z(νν¯)+Z(νν¯)+ jet background by means of precise theoretical predictions. In this context, recent advances in perturbative calculations open the door to significant sensitivity improvements in dark matter searches. In this spirit, we present a combination of state-of-the-art calculations for all relevant V+V+ jets processes, including throughout NNLO QCD corrections and NLO electroweak corrections supplemented by Sudakov logarithms at two loops. Predictions at parton level are provided together with detailed recommendations for their usage in experimental analyses based on the reweighting of Monte Carlo samples. Particular attention is devoted to the estimate of theoretical uncertainties in the framework of dark matter searches, where subtle aspects such as correlations across different V+V+ jet processes play a key role. The anticipated theoretical uncertainty in the Z(νν¯)+Z(νν¯)+ jet background is at the few percent level up to the TeV range.

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Publisher statement:© The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, 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.
Date accepted:15 November 2017
Date deposited:05 January 2018
Date of first online publication:05 December 2017
Date first made open access:No date available

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