Dark Matter production during Warm Inflation via Freeze-In

We present a novel perspective on the role of inflation in the production of Dark Matter (DM). Specifically, we explore the DM production during Warm Inflation via ultraviolet Freeze-In (WIFI). We demonstrate that in a Warm Inflation (WI) setting the persistent thermal bath, sustained by the dissipative interactions with the inflaton field, can source a sizable DM abundance via the non-renormalizable interactions that connect the DM with the bath. Compared to the (conventional) radiation-dominated (RD) UV freeze-in scenario for the same reheat temperature (after inflation), the resulting DM yield in WIFI is always enhanced, showing a strongly positive dependence on the mass dimension of the non-renormalizable operator. Of particular interest, for a sufficiently large mass dimension of the operator, the entirety of the DM abundance of the Universe can be created during the inflationary phase. For the specific models we study, we find an enhancement in DM yield of up to 30 orders of magnitude relative to RD UV freeze-in for the same reheat temperature. Our findings also suggest a broader applicability for producing other cosmological relics, which may have a substantial impact on the evolution of the early Universe.Comment: 7 pages, 4 figure

Machine Learning-Based Estimation of Soil’s True Air-Entry Value from GSD Curves

The application of machine learning (ML) methods has proven to be promising in dealing with a wide range of geotechnical engineering problems in recent years. ML methods have already been used for the prediction of soil water retention curves (SWRC) and estimation of air-entry values (AEV). However, the reported works in the literature are generally based on limited data and conventional, less accurate approaches for AEV estimation. In this paper, a large database, known as UNsaturated SOil hydraulic DAtabase (UNSODA), is studied and the conventional and true AEVs of 790 soil samples are estimated based on determination methods reported in the literature. A ML approach is then employed for the development of a predictive model for the estimation of true AEV from water content-based SWRCs of a wide range of soil types taking into account the impact of bulk density and grain size distribution parameters. The obtained results reveal an enhanced accuracy in AEV determination, featuring R2 values of 0.964, 0.901 and 0.851 for training, validation, and testing data, respectively, which confirm the high-level performance of the developed ML model. Based on the results of a sensitivity analysis, the particle sizes of 50 and 250 µm are found to have the highest impact on the AEV estimation

Phenomenology of Neutrino Portal Dark Matter and Supersymmetry

In this thesis we investigate the neutrino portal dark matter which tries to explain non-baryonic dark matter and the neutrino masses at the same time. Bearing in mind that natural theories like the Minimal Supersymmetric Standard Model also provide a WIMP type candidate for dark matter, we also calculate the sensitivities of the High Luminosity (HL) and High Energy (HE) upgrades of the Large Hadron Collider to strong supersymmetry signals. Firstly, we study the feasibility of the indirect detection of dark matter in a simple model using the neutrino portal. We derive the existing constraints on this scenario from Planck cosmic microwave background measurements, Fermi dwarf spheroidal galaxies and Galactic Center gamma-rays observations, and AMS-02 antiprotons observations. Secondly, by modifying our simple model, we analyze the scenario in which a thermal dark matter annihilating to standard model neutrinos via the neutrino portal. We derive existing constraints and future projections from direct detection experiments, colliders, rare meson and tau decays, electroweak precision tests, and small scale structure observations. Finally, we evaluate the sensitivities of the High Luminosity (HL) and High Energy (HE) upgrades of the LHC to gluinos and stops, decaying through the simplified topologies. Our HL-LHC analyses improve on existing experimental projections by optimizing the acceptance of kinematic variables

Effect of Surface Roughness on the Rheology of Silica-Coated Styrene/Acrylic Acid Copolymer Suspensions

Hypothesis: Today, due to the widespread use of coarse particle suspensions in chemical industry, the tendency to study the rheological behaviour of suspensions has increased significantly. One of the most important research fields is the study on friction of particles between them and the shear thickening behavior of their suspensions. In high-filled suspensions, the viscosity and the thickness of shear are proportional to the thickness of the suspended particles. Methods: This research is based on the syntheses of smooth particles (styrene/acrylic acid copolymers) and rough particles (silica-coated styrene/acrylic acid copolymers), with a volume proportion of 20%, 34% and 49% in the ethanol/water solution. The initial critical shear rate of suspension thickening regions was obtained in different ratios of rough and smooth particles. In addition, experimental and semi-empiric models such as Herschel Barclay and Gopalakrishnan have been used to describe the relationship between suspension rheology and microstructure. Findings:  It was observed that with the increase in roughness of the composition of the same percentage of particles, a more severe shear thickening behavior occurs in smaller amounts of rough particles. It was also observed that hydro-clusters were formed in samples that contain the highest proportion of suspension composition and consist of 100% coarse particles with the lowest amount of Peclet.  An increase in the amount of rough particles leads the system to an increase in viscosity at lower shear rates. Furthermore, the adaptation of the Gopalakrishnan model to experimental data clearly shows that an increase in roughness leads to a reduction in the critical value of Pe at the beginning of the shear thickening zone and a stronger shear thickness behavior in the system

Recycled Dark Matter

We outline a new production mechanism for dark matter that we dub "recycling": dark sector particles are kinematically trapped in the false vacuum during a dark phase transition; the false pockets collapse into primordial black holes (PBHs), which ultimately evaporate before Big Bang Nucleosynthesis (BBN) to reproduce the dark sector particles. The requirement that all PBHs evaporate prior to BBN necessitates high scale phase transitions and hence high scale masses for the dark sector particles in the true vacuum. Our mechanism is therefore particularly suited for the production of ultra heavy dark matter (UHDM) with masses above $\sim 10^{12}\,{\rm GeV}$. The correct relic density of UHDM is obtained because of the exponential suppression of the false pocket number density. Recycled UHDM has several novel features: the dark sector today consists of multiple decoupled species that were once in thermal equilibrium and the PBH formation stage has extended mass functions whose shape can be controlled by IR operators coupling the dark and visible sectors.Comment: 23 pages, 7 figures; v2: Lifetime of scalar updated. Conclusions unchange