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J. A. Murillo Quijada

Publications and source records attributed to J. A. Murillo Quijada.

3 recordsLinked to original sources

$t\bar{t}$ spin correlations from toponium production scenarios to non-relativistic resummation beyond the standard perturbative baseline

$t\bar{t}$ spin correlations originating from theoretical models assuming on one side toponium bound state formation in proton-proton collisions at 13 TeV are compared against predictions from non-relativistic QCD ressumation effects via Green's function formalism that go beyond the perturbative $t\bar{t}$ baseline with no bound state but could justify extra yield of events in the $t\bar{t}$ mass spectrum recently observed by ATLAS and CMS Collaborations, still awaiting an explanation. Toponium production comprises two scenarios, a simplified Effective Field Theory (EFT) with $η_t\rightarrow t\bar{t}$ decays and an additional model with scalar and vector toponium states with $η_t\rightarrow HZ$ and $J_t\rightarrow ZW^+W^-$ decays. Experimental measurements on $t\bar{t}$ system are added to the comparisons. Fitted diagonal spin correlation $C_{kk}$, $C_{rr}$, $C_{nn}$ matrix terms show a relative increase in value ranging from 200%-2330% for toponium $t\bar{t}$ decays with respect the perturbative NLO baseline. Relative contribution from resummation effect ranges from 0.6% to 10.4% and its combination with perturbative baseline improves agreement with Data distributions, with $χ^2/N_\mathrm{dof}$ value reduced by $\sim$4.5%-60.0% . Equivalent fitted cross-section for resummation effect $σ_{res}$, ranges from 7.3 to 9.1 pb in consistency with excess yield reported by LHC experiments. $σ_{res}$ $>$ 50 pb range is excluded at 95% C.L. A classifier performing at detector level achieves a ROC curve area of $0.91$ leading to toponium signal to background significances over 55. These results indicate that efficient isolation of observed $t\bar{t}$ excess events from background is feasible and a characterisation via spin correlation measurements would reveal their consistency with either toponium production or non-relativistic effects beyond the perturbative baseline.

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Impact of soft QCD effects over intrajet azimuthal anisotropies

Observations of collective signatures within jets of particles have been recently reported by measurements at the Large Hadron Collider at CERN laboratory, providing insights on the minimum conditions required for forming a Quark Gluon Plasma state. A quantitative comparison with data measurements on intrajet azimuthal anisotropies and predictions from PYTHIA event generator soft QCD model parameter tunes: Monash, CP5, and QCD-scheme CR is presented. Energetic jets with transverse momentum over 550 GeV from proton-proton collisions at 13 TeV are reconstructed. Results from predictions using the standard E-scheme (ES) and jet axis choice are compared with those from the Winner-Take-All (WTA) frame. Significant differences are present between predictions from WTA and ES frames at the lowest and highest intrajet charged particles multiplicities ($N_{\mathrm{ch}}$), with the QCD-scheme CR tune showing the smallest variation between frames. Predictions for $v_2$ at the highest $N_{\mathrm{ch}}$ are consistent with the data measurements at a 2.3$σ$ uncertainty level. These results set new guidance towards the search for intrajet collective effects and understanding of nonperturbative QCD dynamics originated from a single parton.

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Impact of neutral fluxes and signal significance optimization on semi-exclusive $pp \to t\bar{t}$ production via deep learning training

Photon flux benchmark models and recent experimental estimates of pomeron energy fluxes and structure functions are implemented in Monte Carlo simulations to assess their impact on physical observables and signal strength uncertainty for the yet-to-be-observed semi-exclusive $t\bar{t}$ production in proton-proton ($pp$) collisions at Large Hadron Collider (LHC) and Future Circular Collider (FCC) energies. The expected cross sections increase by factors of approximately 50 and 22 for pomeron-induced and photon-induced processes, respectively, from LHC to FCC energies. TensorFlow deep neural networks discriminate semi-exclusive processes from the non-peripheral $t\bar{t}X$ background, achieving a test area under the receiver operating characteristic curve (AUC) of $0.9917 \pm 0.0002$ for the photon-induced signal. At detector level, using the CMS detector geometry at CERN, the minimum Hadronic Forward energy observable is identified as the most effective discriminator against this background. For low-pileup $pp$ data, an Asimov dataset analysis incorporating statistical uncertainties and systematic contributions from pomeron and photon schemes predicts a significance of $5σ$ for pomeron-induced and photon-induced $t\bar{t}$ production with integrated luminosities of 1 and 4.7 $\mathrm{fb}^{-1}$, respectively. The systematic contributions to the total uncertainty are 25.1% and 7.6%, respectively. These results highlight the potential for experimental observation using Run 2 and Run 3 LHC data and for further studies within the LHC forward physics program.

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