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Ralf S. Klessen

Publications and source records attributed to Ralf S. Klessen.

At least 307 records · Page 17Linked to original sources

Formation sites of Population III star formation: The effects of different levels of rotation and turbulence on the fragmentation behavior of primordial gas

We use the moving-mesh code AREPO to investigate the effects of different levels of rotation and turbulence on the fragmentation of primordial gas and the formation of Population III stars. We consider 9 different combinations of turbulence and rotation and carry out 5 different realizations of each setup, yielding one of the largest sets of simulations of Population III star formation ever performed. We find that fragmentation in Population III star-forming systems is a highly chaotic process and show that the outcomes of individual realizations of the same initial conditions often vary significantly. However, some general trends are apparent. Increasing the turbulent energy promotes fragmentation, while increasing the rotational energy inhibits fragmentation. Within the 1000 yr period that we simulate, runs including turbulence yield flat protostellar mass functions while purely rotational runs show a more top-heavy distribution. The masses of the individual protostars are distributed over a wide range from a few $10^{-3} \, {\rm M_{\odot}}$ to several tens of ${\rm M_\odot}$. The total mass growth rate of the stellar systems remains high throughout the simulations and depends only weakly on the degree of rotation and turbulence. Mergers between protostars are common, but predictions of the merger fraction are highly sensitive to the criterion used to decide whether two protostars should merge. Previous studies of Population III star formation have often considered only one realization per set of initial conditions. However, our results demonstrate that robust trends can only be reliably identified by considering averages over a larger sample of runs.

astro-ph.GA↗

The Cloud Factory I: Generating resolved filamentary molecular clouds from galactic-scale forces

We introduce a new suite of simulations, "The Cloud Factory", which self-consistently forms molecular cloud complexes at high enough resolution to resolve internal substructure (up to 0.25 Msol in mass) all while including galactic-scale forces. We use a version of the Arepo code modified to include a detailed treatment of the physics of the cold molecular ISM, and an analytical galactic gravitational potential for computational efficiency. The simulations have nested levels of resolution, with the lowest layer tied to tracer particles injected into individual cloud complexes. These tracer refinement regions are embedded in the larger simulation so continue to experience forces from outside the cloud. This allows the simulations to act as a laboratory for testing the effect of galactic environment on star formation. Here we introduce our method and investigate the effect of galactic environment on filamentary clouds. We find that cloud complexes formed after a clustered burst of feedback, have shorter lengths and are less likely to fragment compared to quiescent clouds (e.g. the Musca filament) or those dominated by the galactic potential (e.g. Nessie). Spiral arms and differential rotation preferentially align filaments, but strong feedback randomises them. Long filaments formed within the cloud complexes are necessarily coherent with low internal velocity gradients, which has implications for the formation of filamentary star-clusters. Cloud complexes formed in regions dominated by supernova feedback have fewer star-forming cores, and these are more widely distributed. These differences show galactic-scale forces can have a significant impact on star formation within molecular clouds.

astro-ph.GA↗

Simulations of the star-forming molecular gas in an interacting M51-like galaxy

We present here the first of a series of papers aimed at better understanding the evolution and properties of giant molecular clouds (GMCs) in a galactic context. We perform high resolution, three-dimensional {\sc arepo} simulations of an interacting galaxy inspired by the well-observed M51 galaxy. Our fiducial simulations include a non-equilibrium, time-dependent, chemical network that follows the evolution of atomic and molecular hydrogen as well as carbon and oxygen self-consistently. Our calculations also treat gas self-gravity and subsequent star formation (described by sink particles), and coupled supernova feedback. In the densest parts of the simulated interstellar medium (ISM) we reach sub-parsec resolution, granting us the ability to resolve individual GMCs and their formation and destruction self-consistently throughout the galaxy. In this initial work we focus on the general properties of the ISM with a particular focus on the cold star-forming gas. We discuss the role of the interaction with the companion galaxy in generating cold molecular gas and controlling stellar birth. We find that while the interaction drives large-scale gas flows and induces spiral arms in the galaxy, it is of secondary importance in determining gas fractions in the different ISM phases and the overall star-formation rate. The behaviour of the gas on small GMC scales instead is mostly controlled by the self-regulating property of the ISM driven by coupled feedback.

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WARPFIELD-EMP: The Self-Consistent Prediction of Emission Lines from Evolving HII Regions in Dense Molecular Clouds

We present the {\sc warpfield} emission predictor, {\sc warpfield-emp}, which couples the 1D stellar feedback code {\sc warpfield} with the {\sc cloudy} \hii region/PDR code and the {\sc polaris} radiative transfer code, in order to make detailed predictions for the time-dependent line and continuum emission arising from the H{\sc ii} region and PDR surrounding an evolving star cluster. {\sc warpfield-emp} accounts for a wide range of physical processes (stellar winds, supernovae, radiation pressure, gravity, thermal conduction, radiative cooling, dust extinction etc.) and yet runs quickly enough to allow us to explore broad ranges of different cloud parameters. We compare the results of an extensive set of models with SITELLE observations of a large sample of \hii regions in NGC~628 and find very good agreement, particularly for the highest signal-to-noise observations. We show that our approach of modeling individual clouds from first principles (instead of in terms of dimensionless quantities such as the ionization parameter) allows us to avoid long-standing degeneracies in the interpretation of \hii region diagnostics and enables us to relate these diagnostics to important physical parameters such as cloud mass or cluster age. Finally, we explore the implications of our models regarding the reliability of simple metallicity diagnostics, the properties of long-lived embedded clusters, and the role played by winds and supernovae in regulating \hii region and PDR line emission.

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Relations Between Molecular Cloud Structure Sizes and Line Widths in the Large Magellanic Cloud

We present a comparative study of the size-line width relation for substructures within six molecular clouds in the Large Magellanic Cloud (LMC) mapped with the Atacama Large Millimeter/submillimeter Array (ALMA). Our sample extends our previous study, which compared a Planck detected cold cloud in the outskirts of the LMC with the 30 Doradus molecular cloud and found the typical line width for 1 pc radius structures to be 5 times larger in 30 Doradus. By observing clouds with intermediate levels of star formation activity, we find evidence that line width at a given size increases with increasing local and cloud-scale 8$μ$m intensity. At the same time, line width at a given size appears to independently correlate with measures of mass surface density. Our results suggest that both virial-like motions due to gravity and local energy injection by star formation feedback play important roles in determining intracloud dynamics.

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The CARMA-NRO Orion Survey: Core Emergence and Kinematics in the Orion A Cloud

We have investigated the formation and kinematics of sub-mm continuum cores in the Orion A molecular cloud. A comparison between sub-mm continuum and near infrared extinction shows a continuum core detection threshold of $A_V\sim$ 5-10 mag. The threshold is similar to the star formation extinction threshold of $A_V\sim$ 7 mag proposed by recent work, suggesting a universal star formation extinction threshold among clouds within 500 pc to the Sun. A comparison between the Orion A cloud and a massive infrared dark cloud G28.37+0.07 indicates that Orion A produces more dense gas within the extinction range 15 mag $\lesssim A_V \lesssim$ 60 mag. Using data from the CARMA-NRO Orion Survey, we find that dense cores in the integral-shaped filament (ISF) show sub-sonic core-to-envelope velocity dispersion that is significantly less than the local envelope line dispersion, similar to what has been found in nearby clouds. Dynamical analysis indicates that the cores are bound to the ISF. An oscillatory core-to-envelope motion is detected along the ISF. Its origin is to be further explored.

astro-ph.SR↗

On the extraction of power-law parts of the probability density functions in star-forming clouds

We present a new approach to extract the power-law part of a density/column-density probability density function (rho-pdf/N-pdf) in star-forming clouds. It is based on the mathematical method bPLFIT of Virkar & Clauset (2014) and assesses the power-law part of an arbitrary distribution, without any assumptions about the other part of this distribution. The slope and deviation point are derived as averaged values as the number of bins is varied. Neither parameter is sensitive to spikes and other local features of the tail. This adapted bPLFIT method is applied to two different sets of data from numerical simulations of star-forming clouds at scales 0.5 and 500 pc and displays rho-pdf and N-pdf evolution in agreement with a number of numerical and theoretical studies. Applied to Herschel data on the regions Aquila and Rosette, the method extracts pronounced power-law tails, consistent with those seen in simulations of evolved clouds.

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Radiative transfer with POLARIS. II.: Modeling of synthetic Galactic synchrotron observations

We present an updated version of POLARIS, a well established code designated for dust polarisation and line radiative transfer (RT) in arbitrary astrophysical environments. We extend the already available capabilities with a synchrotron feature for polarised emission. Here, we combine state-of-the-art solutions of the synchrotron RT coefficients with numerical methods for solving the complete system of equations of the RT problem, including Faraday rotation (FR) as well as Faraday conversion (FC). We validate the code against Galactic and extragalactic observations by performing a statistical analysis of synthetic all-sky synchrotron maps for positions within the galaxy and for extragalactic observations. For these test scenarios we apply a model of the Milky Way based on sophisticated magneto-hydrodynamic (MHD) simulations and population-synthesis post-processing techniques.We explore different parameters for modeling the distribution of free electrons and for a turbulent magnetic field component. We find that a strongly fluctuating field is necessary for simulating synthetic synchrotron observations on small scales, we argue that Faraday rotation alone can account for the depolarisation of the synchrotron signal, and we discuss the importance of the observer position within the Milky Way. Altogether, we conclude that POLARIS is a highly reliable tool for predicting synchrotron emission and polarisation, including Faraday rotation in a realistic galactic context. It can thus contribute to better understand the results from current and future observational missions.

astro-ph.GA↗

The relation between the turbulent Mach number and observed fractal dimensions of turbulent clouds

Supersonic turbulence is a key player in controlling the structure and star formation potential of molecular clouds (MCs). The three-dimensional (3D) turbulent Mach number, $\mathcal{M}$, allows us to predict the rate of star formation. However, determining Mach numbers in observations is challenging because it requires accurate measurements of the velocity dispersion. Moreover, observations are limited to two-dimensional (2D) projections of the MCs and velocity information can usually only be obtained for the line-of-sight component. Here we present a new method that allows us to estimate $\mathcal{M}$ from the 2D column density, $Σ$, by analysing the fractal dimension, $\mathcal{D}$. We do this by computing $\mathcal{D}$ for six simulations, ranging between $1$ and $100$ in $\mathcal{M}$. From this data we are able to construct an empirical relation, $\log\mathcal{M}(\mathcal{D}) = ξ_1(\text{erfc}^{-1} [(\mathcal{D}-\mathcal{D}_{\text{min}})/Ω] + ξ_2),$ where $\text{erfc}^{-1}$ is the inverse complimentary error function, $\mathcal{D}_{\text{min}} = 1.55 \pm 0.13$ is the minimum fractal dimension of $Σ$, $Ω= 0.22 \pm 0.07$, $ξ_1 = 0.9 \pm 0.1$ and $ξ_2 = 0.2 \pm 0.2$. We test the accuracy of this new relation on column density maps from $Herschel$ observations of two quiescent subregions in the Polaris Flare MC, `saxophone' and `quiet'. We measure $\mathcal{M} \sim 10$ and $\mathcal{M} \sim 2$ for the subregions, respectively, which is similar to previous estimates based on measuring the velocity dispersion from molecular line data. These results show that this new empirical relation can provide useful estimates of the cloud kinematics, solely based upon the geometry from the column density of the cloud.

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The geometry of the gas surrounding the Central Molecular Zone: on the origin of localised molecular clouds with extreme velocity dispersions

Observations of molecular gas near the Galactic centre ($| l | < 10^\circ$, $| b | < 1^\circ$) reveal the presence of a distinct population of enigmatic compact clouds which are characterised by extreme velocity dispersions ($Δv > 100\, \rm km/s$). These Extended Velocity Features (EVFs) are very prominent in the datacubes and dominate the kinematics of molecular gas just outside the Central Molecular Zone (CMZ). The prototypical example of such a cloud is Bania Clump 2. We show that similar features are naturally produced in simulations of gas flow in a realistic barred potential. We analyse the structure of the features obtained in the simulations and use this to interpret the observations. We find that the features arise from collisions between material that has been infalling rapidly along the dust lanes of the Milky Way bar and material that belongs to one of the following two categories: (i) material that has `overshot' after falling down the dust lanes on the opposite side; (ii) material which is part of the CMZ. Both types of collisions involve gas with large differences in the line-of-sight velocities, which is what produces the observed extreme velocity dispersions. Examples of both categories can be identified in the observations. If our interpretation is correct, we are directly witnessing (a) collisions of clouds with relative speeds of $\sim 200\, \rm km/s$ and (b) the process of accretion of fresh gas onto the CMZ.

astro-ph.GA↗

On the Indeterministic Nature of Star Formation on the Cloud Scale

Molecular clouds are turbulent structures whose star formation efficiency (SFE) is strongly affected by internal stellar feedback processes. In this paper we determine how sensitive the SFE of molecular clouds is to randomised inputs in the star formation feedback loop, and to what extent relationships between emergent cloud properties and the SFE can be recovered. We introduce the yule suite of 26 radiative magnetohydrodynamic (RMHD) simulations of a 10,000 solar mass cloud similar to those in the solar neighbourhood. We use the same initial global properties in every simulation but vary the initial mass function (IMF) sampling and initial cloud velocity structure. The final SFE lies between 6 and 23 percent when either of these parameters are changed. We use Bayesian mixed-effects models to uncover trends in the SFE. The number of photons emitted early in the cluster's life and the length of the cloud provide are the strongest predictors of the SFE. The HII regions evolve following an analytic model of expansion into a roughly isothermal density field. The more efficient feedback is at evaporating the cloud, the less the star cluster is dispersed. We argue that this is because if the gas is evaporated slowly, the stars are dragged outwards towards surviving gas clumps due to the gravitational attraction between the stars and gas. While star formation and feedback efficiencies are dependent on nonlinear processes, statistical models describing cloud-scale processes can be constructed.

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Optimal neighbourhood to nurture giants: a fundamental link between star forming galaxies and direct collapse black holes

Massive $10^{4-5}\rm\ M_{\odot}$ black hole seeds resulting from the \textit{direct} collapse of pristine gas require a metal-free atomic cooling halo with extremely low H$_2$ fraction, allowing the gas to cool isothermally in the presence of atomic hydrogen. In order to achieve this chemo-thermodynamical state, the gas needs to be irradiated by both: Lyman-Werner (LW) photons in the energy range $11.2-13.6$ eV capable of photodissociating H$_2$, and $0.76$ eV photons capable of photodetaching H$^-$. Employing cosmological simulations capable of creating the first galaxies in high resolution, we explore if there exists a subset that favours DCBH formation in their vicinity. We find a fundamental relation between the maximum distance at which a galaxy can cause DCBH formation and its star formation rate (SFR), which automatically folds in the chemo-thermodynamical effects of both H$_2$ photo-dissociation and H$^-$ photo-detachment. This is in contrast to the scatter in the LW flux parameter seen at the maximum distance. It shows up to a 3 order of magnitude scatter, which can be interpreted as a scatter in `J$_{crit}$'. Thus, computing the rates and/or the LW flux from a galaxy is no longer necessary to identify neighbouring sites of DCBH formation, as our relation allows one to distinguish regions where DCBH formation could be triggered in the vicinity of a galaxy of a given SFR.

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Titans of the Early Universe: The Prato Statement on the Origin of the First Supermassive Black Holes

In recent years, the discovery of massive quasars at z~7 has provided a striking challenge to our understanding of the origin and growth of supermassive black holes in the early Universe. Mounting observational and theoretical evidence indicates the viability of massive seeds, formed by the collapse of supermassive stars, as a progenitor model for such early, massive accreting black holes. Although considerable progress has been made in our theoretical understanding, many questions remain regarding how (and how often) such objects may form, how they live and die, and how next generation observatories may yield new insight into the origin of these primordial titans. This review focusses on our present understanding of this remarkable formation scenario, based on discussions held at the Monash Prato Centre from November 20--24, 2017, during the workshop "Titans of the Early Universe: The Origin of the First Supermassive Black Holes."

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The relation between the true and observed fractal dimensions of turbulent clouds

Observations of interstellar gas clouds are typically limited to two-dimensional (2D) projections of the intrinsically three-dimensional (3D) structure of the clouds. In this study, we present a novel method for relating the 2D projected fractal dimension ($\mathcal{D}_{\text{p}}$) to the 3D fractal dimension ($\mathcal{D}_{\text{3D}}$) of turbulent clouds. We do this by computing the fractal dimension of clouds over two orders of magnitude in turbulent Mach number $(\mathcal{M} = 1-100)$, corresponding to seven orders of magnitude in spatial scales within the clouds. This provides us with the data to create a new empirical relation between $\mathcal{D}_{\text{p}}$ and $\mathcal{D}_{\text{3D}}$. The proposed relation is $\mathcal{D}_{\text{3D}}(\mathcal{D}_{\text{p}}) = Ω_1 erfc ( ξ_1 erfc^{-1}[ (\mathcal{D}_{\text{p}} - \mathcal{D}_{\text{p,min}})/Ω_2 ] + ξ_2 ) + \mathcal{D}_{\text{3D,min}}$, where the minimum 3D fractal dimension, $\mathcal{D}_{\text{3D,min}} = 2.06 \pm 0.35$, the minimum projected fractal dimension, $\mathcal{D}_{\text{p,min}} = 1.55 \pm 0.13$, $Ω_1 = 0.47 \pm 0.18$, $Ω_2 = 0.22 \pm 0.07$, $ξ_1 = 0.80 \pm 0.18$ and $ξ_2 = 0.26 \pm 0.19$. The minimum 3D fractal dimension, $\mathcal{D}_{\text{3D,min}} = 2.06 \pm 0.35$, indicates that in the high $\mathcal{M}$ limit the 3D clouds are dominated by planar shocks. The relation between $\mathcal{D}_{\text{p}}$ and $\mathcal{D}_{\text{3D}}$ of molecular clouds may be a useful tool for those who are seeking to understand the 3D structures of molecular clouds, purely based upon 2D projected data and shows promise for relating the physics of the turbulent clouds to the fractal dimension.

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Observational constraints on the survival of pristine stars

There is a longstanding discussion about whether low mass stars can form from pristine gas in the early Universe. A particular point of interest is whether we can find surviving pristine stars from the first generation in our local neighbourhood. We present here a simple analytical estimate that puts tighter constraints on the existence of such stars. In the conventional picture, should these stars have formed in significant numbers and have preserved their pristine chemical composition until today, we should have found them already. With the presented method most current predictions for survivor counts larger than zero can be ruled out.

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Analyzing Inverse Problems with Invertible Neural Networks

In many tasks, in particular in natural science, the goal is to determine hidden system parameters from a set of measurements. Often, the forward process from parameter- to measurement-space is a well-defined function, whereas the inverse problem is ambiguous: one measurement may map to multiple different sets of parameters. In this setting, the posterior parameter distribution, conditioned on an input measurement, has to be determined. We argue that a particular class of neural networks is well suited for this task -- so-called Invertible Neural Networks (INNs). Although INNs are not new, they have, so far, received little attention in literature. While classical neural networks attempt to solve the ambiguous inverse problem directly, INNs are able to learn it jointly with the well-defined forward process, using additional latent output variables to capture the information otherwise lost. Given a specific measurement and sampled latent variables, the inverse pass of the INN provides a full distribution over parameter space. We verify experimentally, on artificial data and real-world problems from astrophysics and medicine, that INNs are a powerful analysis tool to find multi-modalities in parameter space, to uncover parameter correlations, and to identify unrecoverable parameters.

cs.LG↗

Collisional N-Body Dynamics Coupled to Self-Gravitating Magnetohydrodynamics Reveals Dynamical Binary Formation

We describe a star cluster formation model that includes individual star formation from self-gravitating, magnetized gas, coupled to collisional stellar dynamics. The model uses the Astrophysical Multi-purpose Software Environment (AMUSE) to integrate an adaptive-mesh magnetohydrodynamics code (FLASH) with a fourth order Hermite N-body code (ph4), a stellar evolution code (SeBa), and a method for resolving binary evolution (multiples). This combination yields unique star formation simulations that allow us to study binaries formed dynamically from interactions with both other stars and dense, magnetized gas subject to stellar feedback during the birth and early evolution of stellar clusters. We find that for massive stars, our simulations are consistent with the observed dynamical binary fractions and mass ratios. However, our binary fraction drops well below observed values for lower mass stars, presumably due to unincluded binary formation during initial star formation. Further, we observe a build up of binaries near the hard-soft boundary that may be an important mechanism driving early cluster contraction.

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Feeding vs. Falling: The growth and collapse of molecular clouds in a turbulent interstellar medium

In order to understand the origin of observed molecular cloud properties, it is critical to understand how clouds interact with their environments during their formation, growth, and collapse. It has been suggested that accretion-driven turbulence can maintain clouds in a highly turbulent state, preventing runaway collapse, and explaining the observed non-thermal velocity dispersions. We present 3D, AMR, MHD simulations of a kiloparsec-scale, stratified, supernova-driven, self-gravitating, interstellar medium, including diffuse heating and radiative cooling. These simulations model the formation and evolution of a molecular cloud population in the turbulent interstellar medium. We use zoom-in techniques to focus on the dynamics of the mass accretion and its history for individual molecular clouds. We find that mass accretion onto molecular clouds proceeds as a combination of turbulent and near free-fall accretion of a gravitationally bound envelope. Nearby supernova explosions have a dual role, compressing the envelope, boosting accreted mass, but also disrupting parts of the envelope and eroding mass from the cloud's surface. It appears that the inflow rate of kinetic energy onto clouds from supernova explosions is insufficient to explain the net rate of charge of the cloud kinetic energy. In the absence of self-consistent star formation, conversion of gravitational potential into kinetic energy during contraction seems to be the main driver of non-thermal motions within clouds. We conclude that although clouds interact strongly with their environments, bound clouds are always in a state of gravitational contraction, close to runaway, and their properties are a natural result of this collapse.

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