Jumping Sundogs, Cat’s Eye and Ferrofluids

We have explored some features of the complex fluids present in Earth’s atmosphere by the observation of some optical phenomena and compared them to the optical phenomena observed in gems and magnetic materials. The main feature of a complex fluid is that it contains polyatomic structures such as polymer molecules or colloidal grains. This paper includes some setups using tabletop experiments, which are intended to show concretely the principles discussed, giving a sense of how well the idealizations treated apply to the atmospheric systems. We have explored sundogs, light pillars, and the halo formation, which involve the existence of a certain structure in the atmospheric medium, resembling the structures observed in some types of gems and ferrofluids.

Predicting dark matter halo formation in N-body simulations with deep regression networks

ABSTRACT Dark matter haloes play a fundamental role in cosmological structure formation. The most common approach to model their assembly mechanisms is through N-body simulations. In this work, we present an innovative pathway to predict dark matter halo formation from the initial density field using a Deep Learning algorithm. We implement and train a Deep Convolutional Neural Network to solve the task of retrieving Lagrangian patches from which dark matter haloes will condense. The volumetric multilabel classification task is turned into a regression problem by means of the Euclidean distance transformation. The network is complemented by an adaptive version of the watershed algorithm to form the entire protohalo identification pipeline. We show that splitting the segmentation problem into two distinct subtasks allows for training smaller and faster networks, while the predictive power of the pipeline remains the same. The model is trained on synthetic data derived from a single full N-body simulation and achieves deviations of ∼10 per cent when reconstructing the dark matter halo mass function at z = 0. This approach represents a promising framework for learning highly non-linear relations in the primordial density field. As a practical application, our method can be used to produce mock dark matter halo catalogues directly from the initial conditions of N-body simulations.

The manifestation of secondary bias on the galaxy population from IllustrisTNG300

ABSTRACT We use the improved IllustrisTNG300 magnetohydrodynamical cosmological simulation to revisit the effect that secondary halo bias has on the clustering of the central galaxy population. With a side length of 205 h−1 Mpc and significant improvements on the subgrid model with respect to previous Illustris simulations, IllustrisTNG300 allows us to explore the dependencies of galaxy clustering over a large cosmological volume and halo mass range. We show at high statistical significance that the halo assembly bias signal (i.e. the secondary dependence of halo bias on halo formation redshift) manifests itself on the clustering of the galaxy population when this is split by stellar mass, colour, specific star formation rate, and surface density. A significant signal is also found for galaxy size: at fixed halo mass, larger galaxies are more tightly clustered than smaller galaxies. This effect, in contrast to the rest of the dependencies, seems to be uncorrelated with halo formation time, with some small correlation only detected for halo spin. We also explore the transmission of the spin bias signal, i.e. the secondary dependence of halo bias on halo spin. Although galaxy spin retains little information about the total halo spin, the correlation is enough to produce a significant galaxy spin bias signal. We discuss possible ways to probe this effect with observations.

Stars made in outflows may populate the stellar halo of the Milky Way

ABSTRACT We study stellar-halo formation using six Milky-Way-mass galaxies in FIRE-2 cosmological zoom simulations. We find that $5{-}40{{\ \rm per\ cent}}$ of the outer (50–300 kpc) stellar halo in each system consists of in-situ stars that were born in outflows from the main galaxy. Outflow stars originate from gas accelerated by superbubble winds, which can be compressed, cool, and form co-moving stars. The majority of these stars remain bound to the halo and fall back with orbital properties similar to the rest of the stellar halo at z = 0. In the outer halo, outflow stars are more spatially homogeneous, metal-rich, and alpha-element-enhanced than the accreted stellar halo. At the solar location, up to $\sim \!10 {{\ \rm per\ cent}}$ of our kinematically identified halo stars were born in outflows; the fraction rises to as high as $\sim \!40{{\ \rm per\ cent}}$ for the most metal-rich local halo stars ([Fe/H] >−0.5). Such stars can be retrograde and create features similar to the recently discovered Milky Way ‘Splash’ in phase space. We conclude that the Milky Way stellar halo could contain local counterparts to stars that are observed to form in molecular outflows in distant galaxies. Searches for such a population may provide a new, near-field approach to constraining feedback and outflow physics. A stellar halo contribution from outflows is a phase-reversal of the classic halo formation scenario of Eggen, Lynden-Bell & Sandange, who suggested that halo stars formed in rapidly infalling gas clouds. Stellar outflows may be observable in direct imaging of external galaxies and could provide a source for metal-rich, extreme-velocity stars in the Milky Way.

The three causes of low-mass assembly bias

ABSTRACT We present a detailed analysis of the physical processes that cause halo assembly bias – the dependence of halo clustering on proxies of halo formation time. We focus on the origin of assembly bias in the mass range corresponding to the hosts of typical galaxies and use halo concentration as our chief proxy of halo formation time. We also repeat our key analyses across a broad range of halo masses and for alternative formation time definitions. We show that splashback subhaloes are responsible for two-thirds of the assembly bias signal, but do not account for the entire effect. After splashback subhaloes have been removed, we find that the remaining assembly bias signal is due to a relatively small fraction ($\lesssim \!10{{\ \rm per\ cent}}$) of haloes in dense regions. We test a number of additional physical processes thought to contribute to assembly bias and demonstrate that the two key processes are the slowing of mass growth by large-scale tidal fields and by the high velocities of ambient matter in sheets and filaments. We also rule out several other proposed physical causes of halo assembly bias. Based on our results, we argue that there are three processes that modify the assembly bias of small-mass haloes arising from the properties of the primordial Gaussian field: large-scale tidal fields, gravitational heating due to the collapse of large-scale structures, and splashback subhaloes located outside the virial radius.

Frost Halo Dynamics on Superhydrophobic Surfaces

Understanding the frosting mechanisms on solid surfaces is crucial to a broad range of industrial sectors such as aerospace, power transmission, and refrigeration. During the last few decades, extensive studies have been conducted on fundamental frosting phenomena, including ice nucleation, growth, bridging, and frost propagation, with few studies focusing on frost halo formation which has been shown to affect frosting dynamics on hydrophilic substrates. The role of frost halo dynamics formation on superhydrophobic surface remains unclear due to limited characterization in the past. Here, in order to study frost propagation dynamics, particularly freezing-induced vapor diffusion and frost halo formation, condensation frosting on highly-reflective nanostructured superhydrophobic surfaces (θ ≈170º) was visualized using high-speed top-view optical microscopy. Condensation frosting was initiated by cooling the surface to -20 ± 0.5°C in atmospheric conditions (relative humidity ≈50% and air temperature ≈25°C). We show that the wave front reaches neighboring supercooled droplets along the path of frost propagation, resulting in supercooled droplet freezing within ~100 ms and numerous microscale (~1 µm) condensing droplets forming around the primary freezing droplet. The microscale droplets form a condensate halo stretching two times the freezing droplet radius. The condensate halo was formed by the rapid evaporation of the supercooled recalescent freezing droplet due to the fast (~100 ms) release of latent heat, resulting in the heating of the freezing droplet and thus outwards diffusion of vapor. Further diffusion of vapor led to the subsequent evaporation of the halo condensate droplets within ~4 s. Interestingly, accompanied by the freezing of the primary droplet and condensate halo formation, the neighboring satellite droplets in the halo zone were observed to oscillate directionally and dramatically, indicative of the presence of a strong flow field disturbance due to rapid vapor diffusion. The visualizations presented here not only help to quantify the physics of condensate halo formation during frost wave propagation on superhydrophobic surfaces, but also provide insights into the role of freezing-induced vapor diffusion during frost dynamics.