LEADER 03208nam 2200529 450 001 9910678250403321 005 20230524044417.0 010 $a9783031250910$b(electronic bk.) 010 $z9783031250903 024 7 $a10.1007/978-3-031-25091-0 035 $a(MiAaPQ)EBC7209146 035 $a(Au-PeEL)EBL7209146 035 $a(CKB)26192075200041 035 $a(DE-He213)978-3-031-25091-0 035 $a(PPN)26909461X 035 $a(EXLCZ)9926192075200041 100 $a20230524d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSearch for exotic Higgs boson decays to merged diphotons $ea novel CMS analysis using end-to-end deep learning /$fMichael Andrews 205 $a1st ed. 2023. 210 1$aBerlin, Germany :$cSpringer,$d[2023] 210 4$dİ2023 215 $a1 online resource (193 pages) 225 1 $aSpringer Theses, Recognizing Outstanding Ph.D. Research,$x2190-5061 311 08$aPrint version: Andrews, Michael Search for Exotic Higgs Boson Decays to Merged Diphotons Cham : Springer,c2023 9783031250903 320 $aIncludes bibliographical references. 327 $aIntroduction -- The LHC and the CMS detector -- Theory & phenomenology -- Analysis strategy -- Data sets -- Signal selection -- a mass regression -- Analysis -- Results -- Conclusions -- Supplementary studies. 330 $aThis book describes the first application at CMS of deep learning algorithms trained directly on low-level, ?raw? detector data, or so-called end-to-end physics reconstruction. Growing interest in searches for exotic new physics in the CMS collaboration at the Large Hadron Collider at CERN has highlighted the need for a new generation of particle reconstruction algorithms. For many exotic physics searches, sensitivity is constrained not by the ability to extract information from particle-level data but by inefficiencies in the reconstruction of the particle-level quantities themselves. The technique achieves a breakthrough in the reconstruction of highly merged photon pairs that are completely unresolved in the CMS detector. This newfound ability is used to perform the first direct search for exotic Higgs boson decays to a pair of hypothetical light scalar particles H?aa, each subsequently decaying to a pair of highly merged photons a?yy, an analysis once thought impossible to perform. The book concludes with an outlook on potential new exotic searches made accessible by this new reconstruction paradigm. 410 0$aSpringer Theses, Recognizing Outstanding Ph.D. Research,$x2190-5061 606 $aDeep learning (Machine learning) 606 $aHiggs bosons 606 $aParticles (Nuclear physics)$xDiffraction 615 0$aDeep learning (Machine learning) 615 0$aHiggs bosons. 615 0$aParticles (Nuclear physics)$xDiffraction. 676 $a006.31 700 $aAndrews$b Michael$f1835-1917,$01359230 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910678250403321 996 $aSearch for exotic Higgs boson decays to merged diphotons$93373324 997 $aUNINA