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Dijet invariant mass distribution near threshold

  • Original Paper - Particles and Nuclei
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Abstract

In this paper, using soft-collinear effective theory, we study the invariant mass distribution for dijet production in \(e^+e^-\)-annihilation. Near threshold, where the dijet takes most of the energy, there arise the large threshold logarithms, which are sensitive to soft gluon radiations. To systematically resum the logarithms, we factorize the scattering cross-section into the hard, the collinear, and the soft parts. And we additionally factorize the original soft part into the global soft function and the two collinear-soft functions, where the latter can be combined with the collinear parts to form the fragmentation functions to jet (FFJs). The factorization theorem derived here can be easily applicable to other processes near threshold. Using the factorized result, we show the resummed result for the dijet invariant mass to the accuracy of next-to-leading logarithms. We have also obtained the result in the case of the heavy quark dijet and compared it with the case of the light quark.

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Notes

  1. Interestingly, like the FFJ, the FF to a heavy hadron can be additionally factorized as the collinear (\(\mu _c \sim m\)) and the csoft (\(\mu _{cs} \sim m(1-z)\)) functions [34, 35]

  2. If we consider the dijet production at the LHC, the relevant global soft function can be obtained by subtracting the csoft contributions to the parton distribution functions as well as to the FFJs in the final states [11].

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Acknowledgements

This study was supported by the Research Program funded by Seoul National University of Science and Technology.

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  1. Institute of Convergence Fundamental Studies and School of Natural Sciences, Seoul National University of Science and Technology, Seoul, 01811, Korea

    Chul Kim & Taehyun Kwon

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  1. Chul Kim
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Correspondence to Chul Kim or Taehyun Kwon.

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Kim, C., Kwon, T. Dijet invariant mass distribution near threshold. J. Korean Phys. Soc. (2024). https://doi.org/10.1007/s40042-024-01075-x

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