Extending the Globular Cluster System-Halo Mass Relation to the Lowest Galaxy Masses

High mass galaxies, with halo masses $M_{200} \ge 10^{10} M_{\odot}$, reveal a remarkable near-linear relation between their globular cluster (GC) system mass and their host galaxy halo mass. Extending this relation to the mass range of dwarf galaxies has been problematic due to the difficulty in measuring independent halo masses. Here we derive new halo masses based on stellar and HI gas kinematics for a sample of nearby dwarf galaxies with GC systems. We find that the GC system mass--halo mass relation for galaxies populated by GCs holds from halo masses of $M_{200} \sim 10^{14} M_{\odot}$ down to below $M_{200}$ $\sim 10^9 M_{\odot}$, although there is a substantial increase in scatter towards low masses. In particular, three well-studied ultra diffuse galaxies, with dwarf-like stellar masses, reveal a wide range in their GC-to-halo mass ratios. We compare our GC system--halo mass relation to the recent model of El Badry et al., finding that their fiducial model does not reproduce our data in the low mass regime. This may suggest that GC formation needs to be more efficient than assumed in their model, or it may be due to the onset of stochastic GC occupation in low mass halos. Finally, we briefly discuss the stellar mass-halo mass relation for our low mass galaxies with GCs, and we suggest some nearby dwarf galaxies for which searches for GCs may be fruitful.Comment: 16 pages, 5 figures, accepted for publication in MNRA

Globular clusters as probes of dark matter cusp-core transformations

Bursty star formation in dwarf galaxies can slowly transform a steep dark matter cusp into a constant density core. We explore the possibility that globular clusters (GCs) retain a dynamical memory of this transformation. To test this, we use the nbody6df code to simulate the dynamical evolution of GCs, including stellar evolution, orbiting in static and time-varying potentials for a Hubble time. We find that GCs orbiting within a cored dark matter halo, or within a halo that has undergone a cusp-core transformation, grow to a size that is substantially larger ($R_{\rm eff} > 10$ pc) than those in a static cusped dark matter halo. They also produce much less tidal debris. We find that the cleanest signal of an historic cusp-core transformation is the presence of large GCs with tidal debris. However, the effect is small and will be challenging to observe in real galaxies. Finally, we qualitatively compare our simulated GCs with the observed GC populations in the Fornax, NGC 6822, IKN and Sagittarius dwarf galaxies. We find that the GCs in these dwarf galaxies are systematically larger ($\langle R_{\rm eff}\rangle \simeq 7.8$ pc), and have substantially more scatter in their sizes, than in-situ metal rich GCs in the Milky Way and young massive star clusters forming in M83 ($\langle R_{\rm eff} \rangle \simeq 2.5$ pc). We show that the size, scatter and survival of GCs in dwarf galaxies are all consistent with them having evolved in a constant density core, or a potential that has undergone a cusp-core transformation, but not in a dark matter cusp.Comment: 14 pages, 10 figure

Leukocyte Motility Models Assessed through Simulation and Multi-objective Optimization-Based Model Selection

The advent of two-photon microscopy now reveals unprecedented, detailed spatio-temporal data on cellular motility and interactions in vivo. Understanding cellular motility patterns is key to gaining insight into the development and possible manipulation of the immune response. Computational simulation has become an established technique for understanding immune processes and evaluating hypotheses in the context of experimental data, and there is clear scope to integrate microscopy-informed motility dynamics. However, determining which motility model best reflects in vivo motility is non-trivial: 3D motility is an intricate process requiring several metrics to characterize. This complicates model selection and parameterization, which must be performed against several metrics simultaneously. Here we evaluate Brownian motion, Lévy walk and several correlated random walks(CRWs) against the motility dynamics of neutrophils and lymph node T cells under inflammatory conditions by simultaneously considering cellular translational and turn speeds, and meandering indices. Heterogeneous cells exhibiting a continuum of inherent translational speeds and directionalities comprise both datasets, a feature significantly improving capture of in vivo motility when simulated as a CRW. Furthermore, translational and turn speeds are inversely correlated, and the corresponding CRW simulation again improves capture of our in vivo data, albeit to a lesser extent. In contrast, Brownian motion poorly reflects our data. Lévy walk is competitive in capturing some aspects of neutrophil motility, but T cell directional persistence only, therein highlighting the importance of evaluating models against several motility metrics simultaneously. This we achieve through novel application of multi-objective optimization, wherein each model is independently implemented and then parameterized to identify optimal trade-offs in performance against each metric. The resultant Pareto fronts of optimal solutions are directly contrasted to identify models best capturing in vivo dynamics, a technique that can aid model selection more generally. Our technique robustly determines our cell populations’ motility strategies, and paves the way for simulations that incorporate accurate immune cell motility dynamics

Automated multi-objective calibration of biological agent-based simulations

Computational agent-based simulation (ABS) is increasingly used to complement laboratory techniques in advancing our understanding of biological systems. Calibration, the identification of parameter values that align simulation with biological behaviours, becomes challenging as increasingly complex biological domains are simulated. Complex domains cannot be characterized by single metrics alone, rendering simulation calibration a fundamentally multi-metric optimization problem that typical calibration techniques cannot handle. Yet calibration is an essential activity in simulation-based science; the baseline calibration forms a control for subsequent experimentation and hence is fundamental in the interpretation of results. Here, we develop and showcase a method, built around multi-objective optimization, for calibrating ABSs against complex target behaviours requiring several metrics (termed objectives) to characterize. Multi-objective calibration (MOC) delivers those sets of parameter values representing optimal trade-offs in simulation performance against each metric, in the form of a Pareto front. We use MOC to calibrate a well-understood immunological simulation against both established a priori and previously unestablished target behaviours. Furthermore, we show that simulation-borne conclusions are broadly, but not entirely, robust to adopting baseline parameter values from different extremes of the Pareto front, highlighting the importance of MOC's identification of numerous calibration solutions. We devise a method for detecting overfitting in a multi-objective context, not previously possible, used to save computational effort by terminating MOC when no improved solutions will be found. MOC can significantly impact biological simulation, adding rigour to and speeding up an otherwise time-consuming calibration process and highlighting inappropriate biological capture by simulations that cannot be well calibrated. As such, it produces more accurate simulations that generate more informative biological predictions

Nonlinear Development and Observational Consequences of Wardle C-Shock Instabilities

We compute the nonlinear development of the instabilities in C-shocks first described by Wardle, using a version of the ZEUS code modified to include a semi-implicit treatment of ambipolar diffusion. We find that, in three dimensions, thin sheets parallel to the shock velocity and perpendicular to the magnetic field lines form. High resolution, two-dimensional models show that the sheets are confined by the Brandenburg & Zweibel ambipolar diffusion singularity, forcing them to numerically unresolvable thinness. Hot and cold regions form around these filaments, disrupting the uniform temperature structure characteristic of a steady-state C-shock. This filamentary region steadily grows as the shock progresses. We compare steady-state to unstable C-shocks, showing excitation diagrams, line ratios, and line profiles for molecular hydrogen lines visible in the K-band, with the Infrared Space Observatory, and with NICMOS on the Hubble Space Telescope.Comment: 24 pages, 18 figures, uses aaspp4.sty, submitted to ApJ, 26 March 1997 Larger figures are jpegs; original postscript is available from http://www.mpia-hd.mpg.de/MPIA/Projects/THEORY/maclow/papers/cshk/p2.htm

Daily College Student Drinking Patterns Across the First Year of College

Objective: Despite the long recognized importance and well-documented impact of drinking patterns on health and safety, college student drinking patterns are understudied. This study used a daily-level, academic-year-long, multisite sample to identify subpopulations of college student drinking patterns and to describe how these groups differ from one another before, during, and after their first year of college. Method: wo cohorts of first-year college students (n = 588; 59% female) reported daily drinking on a biweekly basis using web-based surveys and completed surveys before and after their first year of college. Results: Cluster analyses based on time series analysis estimates of within-person drinking differences (per weekday, semester, first 6 weeks) and other descriptors of day-to-day drinking identified five drinking patterns: two low (47% and 6%), two medium (24% and 15%), and one high (8%) drinking cluster. Multinomial logistic regression analyses examined cluster differences in pre-college characteristics (i.e., demographics, alcohol outcome expectancies, alcohol problems, depression, other substance use) and first-year college experiences (i.e., academic engagement, alcohol consequences, risky drinking practices, alcohol problems, drinking during academic breaks). Low-drinking students appeared to form a relatively homogeneous group, whereas two distinct patterns were found for medium-drinking students with different weekend and Thursday drinking rates. The Thursday drinking cluster showed lower academic engagement and greater participation in risky drinking practices. Conclusions: These findings highlight quantitative and qualitative differences in day-to-day drinking patterns and suggest a link between motivational differences and drinking patterns, which may be addressed in developing tailored interventional strategies

Modeling Elasticity in Crystal Growth

A new model of crystal growth is presented that describes the phenomena on atomic length and diffusive time scales. The former incorporates elastic and plastic deformation in a natural manner, and the latter enables access to times scales much larger than conventional atomic methods. The model is shown to be consistent with the predictions of Read and Shockley for grain boundary energy, and Matthews and Blakeslee for misfit dislocations in epitaxial growth.Comment: 4 pages, 10 figure

The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples

Shotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (~ 200 million reads per sample). Alongside this, we cultured single-colony isolates of Enterobacteriaceae from the same samples and used hybrid sequencing (short- and long-reads) to create high- quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open- source software pipeline, ‘ResPipe’

Haloes gone MAD: The Halo-Finder Comparison Project

[abridged] We present a detailed comparison of fundamental dark matter halo properties retrieved by a substantial number of different halo finders. These codes span a wide range of techniques including friends-of-friends (FOF), spherical-overdensity (SO) and phase-space based algorithms. We further introduce a robust (and publicly available) suite of test scenarios that allows halo finder developers to compare the performance of their codes against those presented here. This set includes mock haloes containing various levels and distributions of substructure at a range of resolutions as well as a cosmological simulation of the large-scale structure of the universe. All the halo finding codes tested could successfully recover the spatial location of our mock haloes. They further returned lists of particles (potentially) belonging to the object that led to coinciding values for the maximum of the circular velocity profile and the radius where it is reached. All the finders based in configuration space struggled to recover substructure that was located close to the centre of the host halo and the radial dependence of the mass recovered varies from finder to finder. Those finders based in phase space could resolve central substructure although they found difficulties in accurately recovering its properties. Via a resolution study we found that most of the finders could not reliably recover substructure containing fewer than 30-40 particles. However, also here the phase space finders excelled by resolving substructure down to 10-20 particles. By comparing the halo finders using a high resolution cosmological volume we found that they agree remarkably well on fundamental properties of astrophysical significance (e.g. mass, position, velocity, and peak of the rotation curve).Comment: 27 interesting pages, 20 beautiful figures, and 4 informative tables accepted for publication in MNRAS. The high-resolution version of the paper as well as all the test cases and analysis can be found at the web site http://popia.ft.uam.es/HaloesGoingMA