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We combine the notion of asymptotic safety (AS) with conformal invariance in a hidden sector beyond the Standard Model. We use the renormalization group (RG) equations as a bridge to connect UV boundary conditions and EW/TeV scale physics and furnish a detailed example in the context of a leptophobic $U(1)$ model. A broad selection of UV boundary conditions are formulated corresponding to differing AS scenarios, and we find an AS scenario with very strong predictive power, allowing unique determination of most of the parameters in the model. We obtain the interrelationships among the couplings, the transition scale of the fixed point $M_{UV}$ and the generations of quarks coupled to the $Z$, and especially the correlation between $M_{UV}$ and the top quark Yukawa coupling $Y_t$. Several phenomenological implications of our results are presented for selected $Z$ masses.
Interacting fixed points in four-dimensional gauge theories coupled to matter are investigated using perturbation theory up to three loop order. It is shown how fixed points, scaling exponents, and anomalous dimensions are obtained as a systematic po
We discuss the visibility of gamma lines from dark matter annihilation. We point out a class of theories for dark matter which predict the existence of gamma lines with striking features. In these theories, the final state radiation processes are hig
We explain how asymptotic safety arises in four-dimensional supersymmetric gauge theories. We provide asymptotically safe supersymmetric gauge theories together with their superconformal fixed points, R-charges, phase diagrams, and UV-IR connecting t
There is a growing appreciation that hidden sector dynamics may affect the supersymmetry breaking parameters in the visible sector (supersymmetric standard model), especially when the dynamics is strong and superconformal. We point out that there are
The measurements of the muon and electron anomalous magnetic moments hint at physics beyond the standard model. We show why and how models inspired by asymptotic safety can explain deviations from standard model predictions naturally. Our setup featu