Topology and Sizes of HII Regions during Cosmic Reionization

We use the results of large-scale simulations of reionization to explore methods for characterizing the topology and sizes of HII regions during reionization. We use four independent methods for characterizing the sizes of ionized regions. Three of them give us a full size distribution: the friends-of-friends (FOF) method, the spherical average method (SPA) and the power spectrum (PS) of the ionized fraction. These latter three methods are complementary: While the FOF method captures the size distribution of the small scale H~II regions, which contribute only a small amount to the total ionization fraction, the spherical average method provides a smoothed measure for the average size of the H~II regions constituting the main contribution to the ionized fraction, and the power spectrum does the same while retaining more details on the size distribution. Our fourth method for characterizing the sizes of the H II regions is the average size which results if we divide the total volume of the H II regions by their total surface area, (i.e. 3V/A), computed in terms of the ratio of the corresponding Minkowski functionals of the ionized fraction field. To characterize the topology of the ionized regions, we calculate the evolution of the Euler Characteristic. We find that the evolution of the topology during the first half of reionization is consistent with inside-out reionization of a Gaussian density field. We use these techniques to investigate the dependence of size and topology on some basic source properties, such as the halo mass-to-light ratio, susceptibility of haloes to negative feedback from reionization, and the minimum halo mass for sources to form. We find that suppression of ionizing sources within ionized regions slows the growth of H~II regions, and also changes their size distribution. Additionally, the topology of simulations including suppression is more complex. (abridged

Electronic effects in high-energy radiation damage in iron

Electronic effects are believed to be important in high--energy radiation damage processes where high electronic temperature is expected, yet their effects are not currently understood. Here, we perform molecular dynamics simulations of high-energy collision cascades in $\alpha$-iron using the coupled two-temperature molecular dynamics (2T-MD) model that incorporates both effects of electronic stopping and electron-ion interaction. We subsequently compare it with the model employing the electronic stopping only, and find several interesting novel insights. The 2T-MD results in both decreased damage production in the thermal spike and faster relaxation of the damage at short times. Notably, the 2T-MD model gives a similar amount of the final damage at longer times, which we interpret to be the result of two competing effects: smaller amount of short-time damage and shorter time available for damage recovery.Comment: 8 pages, 6 figure

Competing Relaxation Channels in Continuously Polydisperse Fluids: A Mode-Coupling Study

Systems with a high degree of size polydispersity are becoming standard in the computational study of deeply supercooled liquids. In this work we perform a systematic analysis of continuously polydisperse fluids as a function of the degree of polydispersity within the framework of the Mode-Coupling Theory of the glass transition (MCT). Our results show that a high degree of polydispersity tends to stabilize the liquid phase against vitrification, the magnitude of which depends on the shape of the polydispersity distribution. Further, we report on a separation between the localization lengths of the smallest and largest particles. A diameter-resolved analysis of the intermediate scattering functions reveals that this separation significantly stretches the relaxation patterns, which we quantitatively study by an analysis of the dynamical exponents predicted by the theory. Our observations have strong implications for our understanding of the nature of dynamical heterogeneities and localization lengths in continuously polydisperse systems. These results suggest that the dynamics of the smallest particles is of central importance to understand structural relaxation of continuously size polydisperse fluids, already in the mildly supercooled regime where MCT is usually applicable.Comment: 12 pages, 10 figure

Polydispersity modifies relaxation mechanisms in glassy liquids

State-of-the-art techniques for simulating deeply supercooled liquids require a high degree of size polydispersity to be effective. While these techniques have enabled great insight into the microscopic dynamics near the glass transition, the effect of the artificially introduced polydispersity on the dynamics has remained largely unstudied. Here we show that a particle's size not only has a strong correlation with its mobility, but we also observe that, as the mode-coupling temperature is crossed and the system becomes more deeply supercooled, a dynamic separation between small mobile and larger quiescent particles emerges at timescales corresponding to cage escape. Our results suggest that the cage escape of this population of mobile particles facilitates the later structural relaxation of the quiescent particles. This indicates that it is of vital importance to account for particle size effects when generalizing results to other glass-forming systems

Fast dynamics and high effective dimensionality of liquid fluidity

Fluidity, the ability of liquids to flow, is the key property distinguishing liquids from solids. This fluidity is set by the mobile transit atoms moving from one quasi-equilibrium point to the next. The nature of this transit motion is unknown. Here, we show that flow-enabling transits form a dynamically distinct sub-ensemble where atoms move on average faster than the overall system, with a manifestly non-Maxwellian velocity distribution. This is in contrast to solids and gases where no distinction of different ensembles can be made and where the distribution is always Maxwellian. The non-Maxwellian distribution is described by an exponent $\alpha$ corresponding to high dimensionality of space. This is generally similar to extra synthetic dimensions in topological quantum matter, albeit higher dimensionality in liquids is not integer but is fractional. The dimensionality is close to 4 at melting and exceeds 4 at high temperature. $\alpha$ has a maximum as a function of temperature and pressure in liquid and supercritical states, returning to its Maxwell value in the solid and gas states.Comment: 6 pages, 4 figure

Kinematic Characterisation of Hexapods for Industry

International audiencePurpose-The aim of this paper is to propose two simple tools for the kinematic characterization of hexapods. The paper also aims to share the authors' experience with converting a popular commercial motion base (Stewart-Gough platform, hex-apod) to an industrial robot for use in heavy duty aerospace manufacturing processes. Design/methodology/approach-The complete workspace of a hexapod is a six-dimensional entity that is impossible to visualize. Thus, nearly all hexapod manufacturers simply state the extrema of each of the six dimensions, which is very misleading. As a compromise, we propose a special three-dimensional subset of the complete workspace, an approximation of which can be readily obtained using a CAD/CAM software suite, such as CATIA. While calibration techniques for serial robots are readily available, there is still no generally-agreed procedure for calibrating hexapods. We propose a simple calibration method that relies on the use of a laser tracker and requires no programming at all. Instead, the design parameters of the hexapod are directly and individually measured and the few computations involved are performed in a CAD/CAM software such as CATIA. Findings-The conventional octahedral hexapod design has a very limited workspace, though free of singularities. There are important deviations between the actual and the specified kinematic model in a commercial motion base. Practical implications-A commercial motion base can be used as a precision positioning device with its controller retrofit-ted with state-of-the-art motion control technology with accurate workspace and geometric characteristics. Originality/value-A novel geometric approach for obtaining meaningful measures of the workspace is proposed. A novel, systematic procedure for the calibration of a hexapod is outlined. Finally, experimental results are presented and discussed

A deep learning approach to the measurement of long-lived memory kernels from Generalised Langevin Dynamics

Memory effects are ubiquitous in a wide variety of complex physical phenomena, ranging from glassy dynamics and metamaterials to climate models. The Generalised Langevin Equation (GLE) provides a rigorous way to describe memory effects via the so-called memory kernel in an integro-differential equation. However, the memory kernel is often unknown, and accurately predicting or measuring it via e.g. a numerical inverse Laplace transform remains a herculean task. Here we describe a novel method using deep neural networks (DNNs) to measure memory kernels from dynamical data. As proof-of-principle, we focus on the notoriously long-lived memory effects of glassy systems, which have proved a major challenge to existing methods. Specifically, we learn a training set generated with the Mode-Coupling Theory (MCT) of hard spheres. Our DNNs are remarkably robust against noise, in contrast to conventional techniques which require ensemble averaging over many independent trajectories. Finally, we demonstrate that a network trained on data generated from analytic theory (hard-sphere MCT) generalises well to data from simulations of a different system (Brownian Weeks-Chandler-Andersen particles). We provide a general pipeline, KernelLearner, for training networks to extract memory kernels from any non-Markovian system described by a GLE. The success of our DNN method applied to glassy systems suggests deep learning can play an important role in the study of dynamical systems that exhibit memory effects

Dependence of the local reionization history on halo mass and environment: did Virgo reionize the Local Group?

The reionization of the Universe has profound effects on the way galaxies form and on their observed properties at later times. Of particular importance is the relative timing of the reionization history of a region and its halo assembly history, which can affect the nature of the first stars formed in that region, the properties and radial distribution of its stellar halo, globular cluster population and its satellite galaxies. We distinguish two basic cases for the reionization of a halo - internal reionization, whereby the stars forming in situ reionize their host galaxy, and external reionization, whereby the progenitor of a galaxy is reionized by external radiation before its own stars are able to form in sufficient numbers. We use a set of large-scale radiative transfer and structure formation simulations, based on cosmologies derived from both Wilkinson Microwave Anisotropy Probe (WMAP) one-year and WMAP three-year data, to evaluate the mean reionization redshifts and the probability of internal/external reionization for Local Group-like systems, galaxies in the field and central cD galaxies in clusters. We find that these probabilities are strongly dependent on the underlying cosmology and the efficiency of photon production, but also on the halo mass. There is a rapid transition between predominantly external and predominantly internal reionization at a mass scale of ∼1012 M⊙ (corresponding roughly to L* galaxies), with haloes less massive than this being reionized preferentially from distant sources. We provide a fit for the reionization redshift as a function of halo mass, which could be helpful to parametrize reionization in semi-analytical models of galaxy formation on cosmological scales. We find no statistical correlation between the reionization history of field galaxies and their environmen