Can the 750-GeV diphoton resonance be the singlet Higgs boson of custodial Higgs triplet model?

The observation of diphoton excess around the mass of 750 GeV in LHC Run-II motivates us to consider whether the singlet Higgs boson in the custodial Higgs triplet model can serve as a good candidate because an earlier study of comprehensive parameter scan shows that it can have the right mass in the viable mass spectra. By assuming the singlet Higgs mass at 750 GeV, its total width less than 50 GeV and imposing constraints from the LHC 8-TeV data, we identify an approximately linear region on the $(v_\Delta, \alpha)$ plane along which the exotic Higgs boson masses satisfy a specific hierarchy and have lower possible spectra, where $v_\Delta$ denotes the triplet vacuum expectation value and $\alpha$ is the mixing angle between the singlet Higgs boson and the standard model-like Higgs boson. Although the diphoton decay rate can be enhanced by charged Higgs bosons running in the loop in this region, it is mostly orders of magnitude smaller than that required for the observed production rate, except for the small $v_\Delta$ region when the diphoton fusion production mechanism becomes dominant. Nonetheless, this part of parameter space suffers from the problems of breakdown of perturbativity and large uncertainties in the photon parton distribution function of proton.Comment: 14 pages, 2 figures, and 2 tables; bugs in numerical calculations fixed, and discussions and conclusions changed; typo corrected; 16 pages, expanded with more detailed discussions, updated figures and tables, version to appear in the journa

Radiative corrections to Higgs couplings with weak gauge bosons in custodial multi-Higgs models

We calculate 1-loop radiative corrections to the $hZZ$ and $hWW$ couplings in models with next--to--simplest Higgs sectors satisfying the electroweak $\rho$ parameter equal to 1 at tree level: the Higgs singlet model, the two-Higgs doublet models, and the Georgi-Machacek model. Under theoretical and current experimental constraints, the three models have different correlations between the deviations in the $hZZ$ and $hWW$ couplings from the standard model predictions. In particular, we find for each model predictions with no overlap with the other two models.Comment: 5 pages, 1 figur

Applying mobile augmented reality (AR) to teach interior design students in layout plans: Evaluation of learning effectiveness based on the ARCS model of learning motivation theory

In this paper we present a mobile augmented reality (MAR) application supporting teaching activities in interior design. The application supports students in learning interior layout design, interior design symbols, and the effects of different design layout decisions. Utilizing the latest AR technology, users can place 3D models of virtual objects as e.g., chairs or tables on top of a design layout plan and interact with these on their mobile devices. Students can experience alternative design decision in real-time and increases the special perception of interior designs. Our system fully supports the import of interior deployment layouts and the generation of 3D models based on design artefacts based on typical design layout plan design symbols and allows the user to investigate different design alternatives. We applied John Keller’s Attention, Relevance, Confidence, and Satisfaction (ARCS) learning motivation model to validate our solution to examine the students’ willingness and verify the ability of students to improve learning through MAR technology. We compared a sample experimental group of N = 52 test-subjects with a sample of N = 48 candidates in a control group. Learning indicators as learning interest, confidence, satisfaction and effective have been utilized to assess the students’ learning motivation through the use of MAR technology. The learning results have been determined by the independent sample t testing. The significance of the post-test had a p-value \u3c 0.05 difference. The result of the study clearly shows that the reference group utilizing MAR technology as a learning aid show a higher learning effectiveness as the control group. Thus, we conclude that MAR technology does enhance students’ learning ability for interior design and making appropriate design decisions