Scholarlink

<p>Higgs boson production through gluon fusion in association with two jets is an irreducible background to Higgs boson production through vector boson fusion, one of the most important channels for analyzing and understanding the Higgs boson properties at the Large Hadron Collider. Despite a range of available simulation tools, precise predictions for the corresponding final states are notoriously hard to achieve. Using state-of-the-art fixed-order calculations as the baseline for a comparison, we perform a detailed study of similarities and differences in existing event generators. We provide consistent setups for the simulations that can be used to obtain identical parametric precision in various programs used by experiments. We find that NLO calculations for the two-jet final state are essential to achieve reliable predictions.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Theory uncertainties of the irreducible background to VBF Higgs production

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月22日

查看全文
  • Xuan Chen,
  • Silvia Ferrario Ravasio,
  • Yacine Haddad,
  • Stefan Höche,
  • Joey Huston,
  • Tomáš Ježo,
  • Jia-Sheng Liu,
  • Christian T. Preuss,
  • Ahmed Tarek,
  • Jan Winter

摘要

Higgs boson production through gluon fusion in association with two jets is an irreducible background to Higgs boson production through vector boson fusion, one of the most important channels for analyzing and understanding the Higgs boson properties at the Large Hadron Collider. Despite a range of available simulation tools, precise predictions for the corresponding final states are notoriously hard to achieve. Using state-of-the-art fixed-order calculations as the baseline for a comparison, we perform a detailed study of similarities and differences in existing event generators. We provide consistent setups for the simulations that can be used to obtain identical parametric precision in various programs used by experiments. We find that NLO calculations for the two-jet final state are essential to achieve reliable predictions.