Vergleichsuntersuchungen zur faktoriellen Struktur der Farbigen Progressiven Matrizen (CPM) von Raven

Ziel der vorliegenden Untersuchung: die Faktorenstruktur der CPM an einem breiteren Altersbereich (Normbereich der CPM) zu überprüfen und diese Ergebnisse mit den Werten bisher vorliegender Studien zu vergleichen

Resolution criteria to avoid artificial clumping in Lagrangian hydrodynamic simulations with a multi-phase interstellar medium

Large-scale cosmological galaxy formation simulations typically prevent gas in the interstellar medium (ISM) from cooling below $\approx 10^4$ K. This has been motivated by the inability to resolve the Jeans mass in molecular gas (>>$10^5\,\mathrm{M}_{\odot}$) which would result in undesired artificial clumping. We show that the classical Jeans criteria derived for Newtonian gravity are not applicable in the simulated ISM if the spacing of resolution elements representing the dense ISM is below the gravitational force softening length and gravity is therefore softened and not Newtonian. We re-derive the Jeans criteria for softened gravity in Lagrangian codes and use them to analyse gravitational instabilities at and below the hydrodynamical resolution limit for simulations with adaptive and constant gravitational softening lengths. In addition, we define criteria for which a numerical runaway collapse of dense gas clumps can occur caused by over-smoothing of the hydrodynamical properties relative to the gravitational force resolution. This effect is illustrated using simulations of isolated disk galaxies with the smoothed particle hydrodynamics code Swift. We also demonstrate how to avoid the formation of artificial clumps in gas and stars by adjusting the gravitational and hydrodynamical force resolutions.Comment: 24 pages, 15 figures, accepted for publication in MNRAS, smaller updates to match published versio

Selbst- und Idealbilder von Studenten des ersten und zweiten Bildungsweges und ihre vermutete und reale Beurteilung durch Hochschullehrer

Professoren und Mittelbau sowie 458 Studenten der Universität Mannheim beurteilten den "durchschnittlichen", den "idealen" und den Studenten des zweiten Bildungsweges. Bei den Studenten wurden zusätzlich die vermuteten Beurteilungen dieser Konzepte durch den Lehrkörper sowie die Selbstbilder erhoben. Alle Gruppen zeigten ähnliche Beurteilungsdimensionen. Zwischen Geschlechtern und Fakultäten sowie Mittelbau und Professoren differierten die Beurteilungen nicht überzufällig; Studenten höherer Semester hatten jedoch negativere Selbstbilder und vermutete Beurteilungen des "durchschnittlichen" Studenten. Die realen Beurteilungen des Lehrkörpers wurden von Studenten recht genau vorhergesagt. Studenten des zweiten Bildungsweges wurden von allen Gruppen auf Skalen, die "Willensstärke" und "Reife" erfassen, signifikant positiver als der "Durchschnitt" eingestuft

Tests of subgrid models for star formation using simulations of isolated disk galaxies

We use smoothed-particle hydrodynamics simulations of isolated Milky Way-mass disk galaxies that include cold, interstellar gas to test subgrid prescriptions for star formation (SF). Our fiducial model combines a Schmidt law with a gravitational instability criterion, but we also test density thresholds and temperature ceilings. While SF histories are insensitive to the prescription for SF, the Kennicutt-Schmidt (KS) relations between SF rate and gas surface density can discriminate between models. We show that our fiducial model, with an SF efficiency per free-fall time of 1 per cent, agrees with spatially-resolved and azimuthally-averaged observed KS relations for neutral, atomic and molecular gas. Density thresholds do not perform as well. While temperature ceilings selecting cold, molecular gas can match the data for galaxies with solar metallicity, they are unsuitable for very low-metallicity gas and hence for cosmological simulations. We argue that SF criteria should be applied at the resolution limit rather than at a fixed physical scale, which means that we should aim for numerical convergence of observables rather than of the properties of gas labelled as star-forming. Our fiducial model yields good convergence when the mass resolution is varied by nearly 4 orders of magnitude, with the exception of the spatially-resolved molecular KS relation at low surface densities. For the gravitational instability criterion, we quantify the impact on the KS relations of gravitational softening, the SF efficiency, and the strength of supernova feedback, as well as of observable parameters such as the inclusion of ionized gas, the averaging scale, and the metallicity.Comment: Submitted to MNRAS, 23 pages, 20 figure

A thermal-kinetic subgrid model for supernova feedback in simulations of galaxy formation

We present a subgrid model for supernova feedback designed for simulations of galaxy formation. The model uses thermal and kinetic channels of energy injection, which are built upon the stochastic kinetic and thermal models for stellar feedback used in the OWLS and EAGLE simulations, respectively. In the thermal channel, the energy is distributed statistically isotropically and injected stochastically in large amounts per event, which minimizes spurious radiative energy losses. In the kinetic channel, we inject the energy in small portions by kicking gas particles in pairs in opposite directions. The implementation of kinetic feedback is designed to conserve energy, linear momentum and angular momentum, and is statistically isotropic. To test and validate the model, we run simulations of isolated Milky Way-mass and dwarf galaxies, in which the gas is allowed to cool down to 10 K. Using the thermal and kinetic channels together, we obtain smooth star formation histories and powerful galactic winds with realistic mass loading factors. Furthermore, the model produces spatially resolved star formation rates and velocity dispersions that are in agreement with observations. We vary the numerical resolution by several orders of magnitude and find excellent convergence of the global star formation rates and the mass loading of galactic winds. We show that large thermal-energy injections generate a hot phase of the interstellar medium (ISM) and modulate the star formation by ejecting gas from the disc, while the low-energy kicks increase the turbulent velocity dispersion in the neutral ISM, which in turn helps suppress star formation.Comment: 22 pages, 17 figures (including appendix); submitted to MNRA

The impact of stochastic modeling on the predictive power of galaxy formation simulations

All modern galaxy formation models employ stochastic elements in their sub-grid prescriptions to discretise continuous equations across the time domain. In this paper, we investigate how the stochastic nature of these models, notably star formation, black hole accretion, and their associated feedback, that act on small ($<$ kpc) scales, can back-react on macroscopic galaxy properties (e.g. stellar mass and size) across long ($>$ Gyr) timescales. We find that the scatter in scaling relations predicted by the EAGLE model implemented in the SWIFT code can be significantly impacted by random variability between re-simulations of the same object, even when galaxies are resolved by tens of thousands of particles. We then illustrate how re-simulations of the same object can be used to better understand the underlying model, by showing how correlations between galaxy stellar mass and black hole mass disappear at the highest black hole masses ($M_{\rm BH} > 10^8$ M$_\odot$), indicating that the feedback cycle may be interrupted by external processes. We find that although properties that are collected cumulatively over many objects are relatively robust against random variability (e.g. the median of a scaling relation), the properties of individual galaxies (such as galaxy stellar mass) can vary by up to 25\%, even far into the well-resolved regime, driven by bursty physics (black hole feedback) and mergers between galaxies. We suggest that studies of individual objects within cosmological simulations be treated with caution, and that any studies aiming to closely investigate such objects must account for random variability within their results.Comment: Accepted for publication in MNRA

The Effects of Stellar Rotation. I. Impact on the Ionizing Spectra and Integrated Properties of Stellar Populations

We present a sample of synthetic massive stellar populations created using the Starburst99 evolutionary synthesis code and new sets of stellar evolutionary tracks, including one set that adopts a detailed treatment of rotation. Using the outputs of the Starburst99 code, we compare the populations' integrated properties, including ionizing radiation fields, bolometric luminosities, and colors. With these comparisons we are able to probe the specific effects of rotation on the properties of a stellar population. We find that a population of rotating stars produces a much harder ionizing radiation field and a higher bolometric luminosity, changes that are primarily attributable to the effects of rotational mixing on the lifetimes, luminosities, effective temperatures, and mass loss rates of massive stars. We consider the implications of the profound effects that rotation can have on a stellar population, and discuss the importance of refining stellar evolutionary models for future work in the study of extragalactic, and particularly high-redshift, stellar populations.Comment: 13 pages, 8 figures; accepted for publication in the Astrophysical Journa

Tests of subgrid models for star formation using simulations of isolated disk galaxies

We use smoothed-particle hydrodynamics simulations of isolated Milky Way-mass disk galaxies that include cold, interstellar gas to test subgrid prescriptions for star formation (SF). Our fiducial model combines a Schmidt law with a gravitational instability criterion, but we also test density thresholds and temperature ceilings. While SF histories are insensitive to the prescription for SF, the Kennicutt-Schmidt (KS) relations between SF rate and gas surface density can discriminate between models. We show that our fiducial model, with an SF efficiency per free-fall time of 1 per cent, agrees with spatially-resolved and azimuthally-averaged observed KS relations for neutral, atomic and molecular gas. Density thresholds do not perform as well. While temperature ceilings selecting cold, molecular gas can match the data for galaxies with solar metallicity, they are unsuitable for very low-metallicity gas and hence for cosmological simulations. We argue that SF criteria should be applied at the resolution limit rather than at a fixed physical scale, which means that we should aim for numerical convergence of observables rather than of the properties of gas labelled as star-forming. Our fiducial model yields good convergence when the mass resolution is varied by nearly 4 orders of magnitude, with the exception of the spatially-resolved molecular KS relation at low surface densities. For the gravitational instability criterion, we quantify the impact on the KS relations of gravitational softening, the SF efficiency, and the strength of supernova feedback, as well as of observable parameters such as the inclusion of ionized gas, the averaging scale, and the metallicity

Swift: A modern highly-parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications

Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and algorithms is thus crucial. In this paper, we introduce the fully open-source highly-parallel, versatile, and modular coupled hydrodynamics, gravity, cosmology, and galaxy-formation code Swift. The software package exploits hybrid shared- and distributed-memory task-based parallelism, asynchronous communications, and domain-decomposition algorithms based on balancing the workload, rather than the data, to efficiently exploit modern high-performance computing cluster architectures. Gravity is solved for using a fast-multipole-method, optionally coupled to a particle mesh solver in Fourier space to handle periodic volumes. For gas evolution, multiple modern flavours of Smoothed Particle Hydrodynamics are implemented. Swiftalso evolves neutrinos using a state-of-the-art particle-based method. Two complementary networks of sub-grid models for galaxy formation as well as extensions to simulate planetary physics are also released as part of the code. An extensive set of output options, including snapshots, light-cones, power spectra, and a coupling to structure finders are also included. We describe the overall code architecture, summarise the consistency and accuracy tests that were performed, and demonstrate the excellent weak-scaling performance of the code using a representative cosmological hydrodynamical problem with ≈300 billion particles. The code is released to the community alongside extensive documentation for both users and developers, a large selection of example test problems, and a suite of tools to aid in the analysis of large simulations run with Swift

Swift: A modern highly-parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications

Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and algorithms is thus crucial. In this paper, we introduce the fully open-source highly-parallel, versatile, and modular coupled hydrodynamics, gravity, cosmology, and galaxy-formation code Swift. The software package exploits hybrid task-based parallelism, asynchronous communications, and domain-decomposition algorithms based on balancing the workload, rather than the data, to efficiently exploit modern high-performance computing cluster architectures. Gravity is solved for using a fast-multipole-method, optionally coupled to a particle mesh solver in Fourier space to handle periodic volumes. For gas evolution, multiple modern flavours of Smoothed Particle Hydrodynamics are implemented. Swift also evolves neutrinos using a state-of-the-art particle-based method. Two complementary networks of sub-grid models for galaxy formation as well as extensions to simulate planetary physics are also released as part of the code. An extensive set of output options, including snapshots, light-cones, power spectra, and a coupling to structure finders are also included. We describe the overall code architecture, summarize the consistency and accuracy tests that were performed, and demonstrate the excellent weak-scaling performance of the code using a representative cosmological hydrodynamical problem with $\approx$$300$ billion particles. The code is released to the community alongside extensive documentation for both users and developers, a large selection of example test problems, and a suite of tools to aid in the analysis of large simulations run with Swift.Comment: 39 pages, 18 figures, submitted to MNRAS. Code, documentation, and examples available at www.swiftsim.co