Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userAre turbulent spheres suitable initial conditions for star-forming clouds?
170
0
0.0
(
0
)
Added by
Ram\\'on Rey-Raposo
Publication date
2014
fields
Physics
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
To date, most numerical simulations of molecular clouds, and star formation within them, assume a uniform density sphere or box with an imposed turbulent velocity field. In this work, we select molecular clouds from galactic scale simulations as initial conditions, increase their resolution, and re-simulate them using the SPH code Gadget2. Our approach provides clouds with morphologies, internal structures, and kinematics that constitute more consistent and realistic initial conditions for simulations of star formation. We perform comparisons between molecular clouds derived from a galactic simulation, and spheres of turbulent gas of similar dimensions, mass and velocity dispersion. We focus on properties of the clouds such as their density, velocity structure and star formation rate. We find that the inherited velocity structure of the galactic clouds has a significant impact on the star formation rate and evolution of the cloud. Our results indicate that, although we can follow the time evolution of star formation in any simulated cloud, capturing the entire history is difficult as we ignore any star formation that might have occurred before initialisation. Overall, the turbulent spheres do not match the complexity of the galactic clouds.
rate research
Read More
Cold dark clouds are nearby members of the densest and coldest phase in the galactic interstellar medium, and represent the most accessible sites where stars like our Sun are currently being born. In this review we discuss recent progress in their study, including the newly discovered infrared dark clouds that are likely precursors to stellar clusters. At large scales, dark clouds present filamentary mass distributions with motions dominated by supersonic turbulence. At small, sub-parsec scales, a population of subsonic starless cores provides a unique glimpse of the conditions prior to stellar birth. Recent studies of starless cores reveal a combination of simple physical properties together with a complex chemical structure dominated by the freeze-out of molecules onto cold dust grains. Elucidating this combined structure is both an observational and theoretical challenge whose solution will bring us closer to understanding how molecular gas condenses to form stars.
Winds from massive stars have velocities of 1000 km/s or more, and produce hot, high pressure gas when they shock. We develop a theory for the evolution of bubbles driven by the collective winds from star clusters early in their lifetimes, which involves interaction with the turbulent, dense interstellar medium of the surrounding natal molecular cloud. A key feature is the fractal nature of the hot bubbles surface. The large area of this interface with surrounding denser gas strongly enhances energy losses from the hot interior, enabled by turbulent mixing and subsequent cooling at temperatures T = 10^4-10^5 K where radiation is maximally efficient. Due to the extreme cooling, the bubble radius scales differently (R ~ t^1/2) from the classical Weaver77 solution, and has expansion velocity and momentum lower by factors of 10-10^2 at given R, with pressure lower by factors of 10^2 - 10^3. Our theory explains the weak X-ray emission and low shell expansion velocities of observed sources. We discuss further implications of our theory for observations of the hot bubbles and cooled expanding shells created by stellar winds, and for predictions of feedback-regulated star formation in a range of environments. In a companion paper, we validate our theory with a suite of hydrodynamic simulations.
As both simulations and observations reach the resolution of the star-forming molecular clouds, it becomes important to clarify if these two techniques are discussing the same objects in galaxies. We compare clouds formed in a high resolution galaxy simulation identified as continuous structures within a contour, in the simulators position-position-position (PPP) co-ordinate space and the observers position-position-velocity space (PPV). Results indicate that the properties of the cloud populations are similar in both methods and up to 70% of clouds have a single counterpart in the opposite data structure. Comparing individual clouds in a one-to-one match reveals a scatter in properties mostly within a factor of two. However, the small variations in mass, radius and velocity dispersion produce significant differences in derived quantities such as the virial parameter. This makes it difficult to determine if a structure is truely gravitationally bound. The three cloud types originally found in the simulation in Fujimoto et al. (2014) are identified in both data sets, with around 80% of the clouds retaining their type between identification methods. We also compared our results when using a peak decomposition method to identify clouds in both PPP and PPV space. The number of clouds increased with this technique, but the overall cloud properties remained similar. However, the more crowded environment lowered the ability to match clouds between techniques to 40%. The three cloud types also became harder to separate, especially in the PPV data set. The method used for cloud identification therefore plays a critical role in determining cloud properties, but both PPP and PPV can potentially identify the same structures.
(Abridged). In this paper, we present results from a large set of numerical simulations that demonstrate that H2 formation occurs rapidly in turbulent gas. Starting with purely atomic hydrogen, large quantities of molecular hydrogen can be produced on timescales of 1 -- 2 Myr, given turbulent velocity dispersions and magnetic field strengths consistent with observations. Moreover, as our simulations underestimate the effectiveness of H2 self-shielding and dust absorption, we can be confident that the molecular fractions that we compute are strong lower limits on the true values. The formation of large quantities of H2 on the timescale required by rapid cloud formation models therefore appears to be entirely plausible. We also investigate the density and temperature distributions of gas in our model clouds. We show that the density probability distribution function is approximately log-normal, with a dispersion that agrees well with the prediction of Padoan, Nordlund & Jones (1997). The temperature distribution is similar to that of a polytrope, with an effective polytropic index gamma_eff simeq 0.8, although at low gas densities, the scatter of the actual gas temperature around this mean value is considerable, and the polytropic approximation does not capture the full range of behaviour of the gas.
Giant molecular clouds (GMCs) are the primary reservoirs of cold, star-forming molecular gas in the Milky Way and similar galaxies, and thus any understanding of star formation must encompass a model for GMC formation, evolution, and destruction. These models are necessarily constrained by measurements of interstellar molecular and atomic gas, and the emergent, newborn stars. Both observations and theory have undergone great advances in recent years, the latter driven largely by improved numerical simulations, and the former by the advent of large-scale surveys with new telescopes and instruments. This chapter offers a thorough review of the current state of the field.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
