Diphoton production in association with two bottom jets

Fäh, David; Greiner, Nicolas

doi:10.1140/epjc/s10052-017-5296-5

Cited by 7 publications

(6 citation statements)

References 81 publications

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“…For the bbγγ background, the k-factor is taken from the ratio between NLO and LO total cross-sections as given in ref. [28]. New topologies of VBF-like contribution that are not included in this work arise as NLO-EW effects.…”

Section: Jhep04(2021)139mentioning

confidence: 98%

Resurrecting $$ b\overline{b}h $$ with kinematic shapes

Grojean

Paul

Qian

2021

J. High Energ. Phys.

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The associated production of a $$ b\overline{b} $$ b b ¯ pair with a Higgs boson could provide an important probe to both the size and the phase of the bottom-quark Yukawa coupling, yb. However, the signal is shrouded by several background processes including the irreducible Zh, Z →$$ b\overline{b} $$ b b ¯ background. We show that the analysis of kinematic shapes provides us with a concrete prescription for separating the yb-sensitive production modes from both the irreducible and the QCD-QED backgrounds using the $$ b\overline{b}\gamma \gamma $$ b b ¯ γγ final state. We draw a page from game theory and use Shapley values to make Boosted Decision Trees interpretable in terms of kinematic measurables and provide physics insights into the variances in the kinematic shapes of the different channels that help us complete this feat. Adding interpretability to the machine learning algorithm opens up the black-box and allows us to cherry-pick only those kinematic variables that matter most in the analysis. We resurrect the hope of constraining the size and, possibly, the phase of yb using kinematic shape studies of $$ b\overline{b}h $$ b b ¯ h production with the full HL-LHC data and at FCC-hh.

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Section: Jhep04(2021)139mentioning

confidence: 98%

Resurrecting $$ b\overline{b}h $$ with kinematic shapes

Grojean

Paul

Qian

2021

J. High Energ. Phys.

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“…The events are generated at leading order (LO) and then scaled to NLO by K-factors, defined as the ratio of higher order cross section over its LO counterpart. The K-factors are taken from the corresponding literature for t th [69], b bγγ [70], Zh [71] and the remaining part of the b bh processes from [72]. The Higgs particles are further decayed to γγ following the Higgs cross-section working group recommendations [73].…”

Section: Events Simulation For Hl-lhc and Fcc-hhmentioning

confidence: 99%

Machine learning the trilinear and light-quark Yukawa couplings from Higgs pair kinematic shapes

Alasfar

Gröber

Grojean

et al. 2022

J. High Energ. Phys.

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Revealing the Higgs pair production process is the next big challenge in high energy physics. In this work, we explore the use of interpretable machine learning and cooperative game theory for extraction of the trilinear Higgs self-coupling in Higgs pair production. In particular, we show how a topological decomposition of the gluon-gluon fusion Higgs pair production process can be used to simplify the machine learning analysis flow. Furthermore, we extend the analysis to include $$ q\overline{q} $$ q q ¯ → hh production, which is strongly suppressed in the Standard Model, to extract the trilinear Higgs coupling and to bound large deviations of the light-quark Yukawa couplings from the Standard Model values. The constraints on the rescaling of the trilinear Higgs self-coupling, κλ, and the rescaling of light-quark Yukawa couplings, κu and κd, at HL-LHC (FCC-hh) from single parameter fits are:$$ {\displaystyle \begin{array}{c}{\kappa}_{\lambda }=\left[0.53,1.7\right]\ \left(\left[0.97,1.03\right]\right)\\ {}{\kappa}_u=\left[-470,430\right]\ \left(\left[-58,55\right]\right)\\ {}{\kappa}_d=\left[-360,360\right]\ \left(\left[-26,28\right]\right)\end{array}} $$ κ λ = 0.53 1.7 0.97 1.03 κ u = − 470 430 − 58 55 κ d = − 360 360 − 26 28 We show that the simultaneous modification of the Yukawa couplings can dilute the constraints on the trilinear coupling significantly. We perform similar analyses for FCC-hh. We discuss some motivated flavourful new physics scenarios where such an analysis prevails.

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“…For the b bγγ background, the k-factor is taken from the ratio between NLO and LO total cross-sections as given in Ref. [26]. New topologies of VBF-like contribution that are not included in this work arise as NLO-EW effects.…”

Section: Events Simulation For Hl-lhc and Fcc-hhmentioning

confidence: 99%

Resurrecting $b\bar{b}h$ with kinematic shapes

Grojean¹,

Paul²,

Qian³

2020

Preprint

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The associated production of a b b pair with a Higgs boson could provide an important probe to both the size and the phase of the bottom-quark Yukawa coupling, y b . However, the signal is shrouded by several background processes including the irreducible Zh, Z → b b background. We show that the analysis of kinematic shapes provides us with a concrete prescription for separating the y b -sensitive production modes from both the irreducible and the QCD-QED backgrounds using the b bγγ final state. We draw a page from game theory and use Shapley values to make Boosted Decisions Trees interpretable in terms of kinematic measurables and provide physics insights into the variances in the kinematic shapes of the different channels that help us complete this feat. Adding interpretability to the machine learning algorithm opens up the black-box and allows us to cherry-pick only those kinematic variables that matter most in the analysis. We resurrect the hope of constraining the size and, possibly, the phase of y b using kinematic shape studies of b bh production with the full HL-LHC data and FCC-hh.

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Diphoton production in association with two bottom jets

Cited by 7 publications

References 81 publications

Resurrecting $$ b\overline{b}h $$ with kinematic shapes

Resurrecting $$ b\overline{b}h $$ with kinematic shapes

Machine learning the trilinear and light-quark Yukawa couplings from Higgs pair kinematic shapes

Resurrecting $b\bar{b}h$ with kinematic shapes

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