%0 Journal Article
%A Amacker, Jacob
%A Balunas, William
%A Beresford, Lydia
%A Bortoletto, Daniela
%A Frost, James
%A Issever, Cigdem
%A Liu, Jesse
%A McKee, James
%A Micheli, Alessandro
%A Paredes Saenz, Santiago
%A Spannowsky, Michael
%A Stanislaus, Beojan
%T Higgs self-coupling measurements using deep learning in the  b―bb―b  final state
%J Journal of high energy physics
%V 12
%N 12
%@ 1029-8479
%C [Trieste]
%I SISSA
%M PUBDB-2021-00149
%M arXiv:2004.04240
%M IPPP/20/11
%P 115
%D 2020
%X Measuring the Higgs trilinear self-coupling λ<sub>hhh</sub> is experimentally demanding but fundamental for understanding the shape of the Higgs potential. We present a comprehensive analysis strategy for the HL-LHC using di-Higgs events in the four b-quark channel (hh → 4b), extending current methods in several directions. We perform deep learning to suppress the formidable multijet background with dedicated optimisation for BSM λ<sub>hhh</sub> scenarios. We compare the λ<sub>hhh</sub> constraining power of events using different multiplicities of large radius jets with a two-prong structure that reconstruct boosted h → bb decays. We show that current uncertainties in the SM top Yukawa coupling y<sub>t</sub> can modify λ<sub>hhh</sub> constraints by ∼ 20
%K CERN LHC Coll: upgrade (INSPIRE)
%K potential: Higgs (INSPIRE)
%K multiplicity: difference (INSPIRE)
%K jet: multiple production (INSPIRE)
%K coupling: Yukawa (INSPIRE)
%K structure (INSPIRE)
%K background (INSPIRE)
%K Higgs Physics (autogen)
%K Beyond Standard Model (autogen)
%F PUB:(DE-HGF)16
%9 Journal Article
%U <Go to ISI:>//WOS:000601400500001
%R 10.1007/JHEP12(2020)115
%U https://bib-pubdb1.desy.de/record/453758