The noble elements, argon and xenon, are frequently employed as the target and event detector for weakly interacting particles such as neutrinos and Dark Matter. For such rare processes, background radiation must be carefully minimized. Radon provides one of the most significant contaminants since it is an inevitable product of trace amounts of natural uranium. To design a purification system for reducing such contamination, the adsorption characteristics of radon in nitrogen, argon, and xenon carrier gases on various types of charcoals with different adsorbing properties and intrinsic radioactive purities have been studied in the temperature range of 190-295 K at flow rates of 0.5 and 2 standard liters per minute. Essential performance parameters for the various charcoals include the average breakthrough times (τ), dynamic adsorption coefficients (k a ) and the number of theoretical stages (n). It is shown that the k a -values for radon in nitrogen, argon, and xenon increase as the temperature of the charcoal traps decreases, and that they are significantly larger in nitrogen and argon than in xenon gas due to adsorption saturation effects. It is found that, unlike in xenon, the dynamic adsorption coefficients for radon in nitrogen and argon strictly obey the Arrhenius law. The experimental results strongly indicate that nitric acid etched Saratech is the best candidate among all used charcoal brands. It allows reducing total radon concentration in the LZ liquid Xe detector to meet the ultimate goal in the search for Dark Matter.

We study stellar property statistics, including satellite galaxy occupation, of massive halo populations realized by three cosmological hydrodynamics simulations: BA-HAMAS + MACSIS, TNG300 of the IllustrisTNG suite, and Magneticum Pathfinder. The simulations incorporate independent sub-grid methods for astrophysical processes with spatial resolutions ranging from 1.5 to 6 kpc, and each generates samples of 1000 or more halos with M halo > 10 13.5 M at redshift z = 0. Applying localized, linear regression (LLR), we extract halo mass-conditioned statistics (normalizations, slopes, and intrinsic covariance) for a three-element stellar property vector consisting of: i) N sat , the number of satellite galaxies with stellar mass, M > 10 10 M within radius R 200c of the halo; ii) M ,tot , the total stellar mass within that radius, and; iii) M ,BCG , the gravitationally-bound stellar mass of the central galaxy within a 100 kpc radius. Scaling parameters for the three properties with halo mass show mild differences among the simulations, in part due to numerical resolution, but there is qualitative agreement on property correlations, with halos having smaller than average central galaxies tending to also have smaller total stellar mass and a larger number of satellite galaxies. Marginalizing over total halo mass, we find the satellite galaxy kernel, p(ln N sat | M halo , z) to be consistently skewed left, with skewness parameter γ = −0.91 ± 0.02, while that of ln M ,tot is closer to log-normal, in all three simulations. The highest resolution simulations find γ −0.8 for the z = 0 shape of p(ln M ,BCG | M halo , z) and also that the fractional scatter in total stellar mass is below 10 percent in halos more massive than 10 14.3 M . We provide a Gaussian mixture fit to the low redshift N sat kernel as well as LLR parameters tabulated for halos more massive than 10 13.5 M in all simulations.

In a purely cold dark matter (CDM) universe, the initial matter power spectrum and its subsequent gravitational growth contain no special mass- or time-scales, and so neither do the emergent population statistics of internal dark matter (DM) halo properties. Using 1.5 million haloes from three illustristng realizations of a ΛCDM universe, we show that galaxy formation physics drives non-monotonic features (‘wiggles’) into DM property statistics across six decades in halo mass, from dwarf galaxies to galaxy clusters. We characterize these features by extracting the halo mass-dependent statistics of five DM halo properties – velocity dispersion, NFW concentration, density- and velocity-space shapes, and formation time – using kernel-localized linear regression (Kllr). Comparing precise estimates of normalizations, slopes, and covariances between realizations with and without galaxy formation, we find systematic deviations across all mass-scales, with maximum deviations of 25 per cent at the Milky Way mass of $10^{12} \, {\rm M}_\odot$. The mass-dependence of the wiggles is set by the interplay between different cooling and feedback mechanisms, and we discuss its observational implications. The property covariances depend strongly on halo mass and physics treatment, but the correlations are mostly robust. Using multivariate Kllr and interpretable machine learning, we show the halo concentration and velocity-space shape are principal contributors, at different mass, to the velocity dispersion variance. Statistics of mass accretion rate and DM surface pressure energy are provided in an appendix. We publicly release halo property catalogues and kllr parameters for the TNG runs at 20 epochs up to z = 12.

We introduce Gizmo-Simba, a new suite of galaxy cluster simulations within The Three Hundred project. The Three Hundred consists of zoom re-simulations of 324 clusters with M200 ≳ 1014.8 M⊙ drawn from the MultiDark-Planck N-body simulation, run using several hydrodynamic and semi-analytic codes. The Gizmo-Simba suite adds a state-of-the-art galaxy formation model based on the highly successful Simba simulation, mildly re-calibrated to match z = 0 cluster stellar properties. Comparing to The Three Hundred zooms run with Gadget-X, we find intrinsic differences in the evolution of the stellar and gas mass fractions, BCG ages, and galaxy colour-magnitude diagrams, with Gizmo-Simba generally providing a good match to available data at z ≈ 0. Gizmo-Simba’s unique black hole growth and feedback model yields agreement with the observed BH scaling relations at the intermediate-mass range and predicts a slightly different slope at high masses where few observations currently lie. Gizmo-Simba provides a new and novel platform to elucidate the co-evolution of galaxies, gas, and black holes within the densest cosmic environments.