Abstract: An updated global fit on the parameter-space of the aligned two-Higgs-doublet model is performed with the help of the open-source package HEPfit, assuming the Standard-Model Higgs to be the lightest scalar. No new sources of CP violation, other than the phase in the Cabibbo-Kobayashi-Maskawa matrix of the Standard Model, are considered. A similar global fit was previously performed by O. Eberhardt et al. [Global fits in the aligned two-Higgs-doublet model, J. High Energy Phys. 05 (2021) 005] with a slightly different set of parameters. Our updated fit incorporates improved analyses of the theoretical constraints required for the perturbative unitarity and boundedness of the scalar potential from below, additional flavor observables and updated data on direct searches for heavy scalars at the LHC, Higgs signal strengths, and electroweak precision observables. Although not included in the main fit, the implications of the CDF measurement of the W +/- mass are also discussed.

Abstract: Current measurements of the temperature and polarization anisotropy power spectra of the cosmic microwave background (CMB) seem to indicate that the naive expectation for the slow-roll hierarchy within the most simple inflationary paradigm may not be respected in nature. We show that a primordial power spectrum with localized features could in principle give rise to the observed slow-roll anarchy when fitted to a featureless power spectrum. From a model comparison perspective, and assuming that nature has chosen a featureless primordial power spectrum, we find that, while with mock Planck data there is only weak evidence against a model with localized features, upcoming CMB missions may provide compelling evidence against such a nonstandard primordial power spectrum. This evidence could be reinforced if a featureless primordial power spectrum is independently confirmed from bispectrum and/or galaxy clustering measurements.

Abstract: HEPfit is a flexible open-source tool which, given the Standard Model or any of its extensions, allows to (i) fit the model parameters to a given set of experimental observables; (ii) obtain predictions for observables. HEPfit can be used either in Monte Carlo mode, to perform a Bayesian Markov Chain Monte Carlo analysis of a given model, or as a library, to obtain predictions of observables for a given point in the parameter space of the model, allowing HEPfit to be used in any statistical framework. In the present version, around a thousand observables have been implemented in the Standard Model and in several new physics scenarios. In this paper, we describe the general structure of the code as well as models and observables implemented in the current release.