PT Journal
AU ATLAS Collaboration (Aad, Gea
   Amos, KR
   Aparisi Pozo, JA
   Bailey, AJ
   Cabrera Urban, S
   Cantero, J
   Cardillo, F
   Castillo Gimenez, V
   Costa, MJ
   Didenko
   Escobar, C
   Fiorini, L
   Fullana Torregrosa, E
   Fuster, J
   Garcia, C
   Garcia Navarro, JE
   Gomez Delegido, AJ
   Gonzalez de la Hoz, S
   Gonzalvo Rodriguez, GR
   Guerrero Rojas, JGR
   Higon-Rodriguez, E
   Lacasta, C
   Lozano Bahilo, JJ
   Marti-Garcia, S
   Martinez Agullo, P
   Miralles Lopez, M
   Mitsou, VA
   Monsonis Romero, L
   Moreno Llacer, M
   Munoz Perez, D
   Navarro-Gonzalez, J
   Poveda, J
   Prades Ibañez, A
   Rubio Jimenez, A
   Ruiz-Martinez, A
   Sabatini, P
   Salt, J
   Sanchez Sebastian, V
   Sayago Galvan, I
   Senthilkumar, V
   Soldevila, U
   Sanchez, J
   Torro Pastor, E
   Valero, A
   Valls Ferrer, JA
   Varriale, L
   Villaplana Perez, M
   Vos, M
TI Anomaly detection search for new resonances decaying into a Higgs boson and a generic new particle X in hadronic final states using √s=13 TeV pp collisions with the ATLAS detector
SO Physical Review D
JI Phys. Rev. D
PY 2023
BP 052009
EP 33pp
VL 108
IS 5
DI 10.1103/PhysRevD.108.052009
LA English
AB A search is presented for a heavy resonance Y decaying into a Standard Model Higgs boson H and a new particle X in a fully hadronic final state. The full Large Hadron Collider run 2 dataset of proton-proton collisions at root s =13 TeV collected by the ATLAS detector from 2015 to 2018 is used and corresponds to an integrated luminosity of 139 fb(-1). The search targets the high Y-mass region, where the H and X have a significant Lorentz boost in the laboratory frame. A novel application of anomaly detection is used to define a general signal region, where events are selected solely because of their incompatibility with a learned background-only model. It is constructed using a jet-level tagger for signal-model-independent selection of the boosted X particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark X decay into two quarks, covering topologies where the X is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into bb, and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section sigma(pp -> Y -> XH -> qqbb) for signals with m(Y) between 1.5 and 6 TeV and m(X) between 65 and 3000 GeV.
ER