ترغب بنشر مسار تعليمي؟ اضغط هنا

Interpreting the Star Formation Efficiency of Molecular Clouds with Ionising Feedback

109   0   0.0 ( 0 )
 نشر من قبل Sam Geen
 تاريخ النشر 2017
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

We investigate the origin of observed local star formation relations using radiative magnetohydrodynamic simulations with self-consistent star formation and ionising radiation. We compare these clouds to the density distributions of local star-forming clouds and find that the most diffuse simulated clouds match the observed clouds relatively well. We then compute both observationally-motivated and theoretically-motivated star formation efficiencies (SFEs) for these simulated clouds. By including ionising radiation, we can reproduce the observed SFEs in the clouds most similar to nearby Milky Way clouds. For denser clouds, the SFE can approach unity. These observed SFEs are typically 3 to 10 times larger than the total SFEs, i.e. the fraction of the initial cloud mass converted to stars. Converting observed to total SFEs is non-trivial. We suggest some techniques for doing so, though estimate up to a factor of ten error in the conversion.



قيم البحث

اقرأ أيضاً

Molecular clouds are supported by turbulence and magnetic fields, but quantifying their influence on cloud lifecycle and star formation efficiency (SFE) remains an open question. We perform radiation MHD simulations of star-forming giant molecular cl ouds (GMCs) with UV radiation feedback, in which the propagation of UV radiation via ray-tracing is coupled to hydrogen photochemistry. We consider 10 GMC models that vary in either initial virial parameter ($1lealpha_{v,0}le 5$) or dimensionless mass-to-magnetic flux ratio (0.5-8 and $infty$); the initial mass $10^5M_{odot}$ and radius 20pc are fixed. Each model is run with five different initial turbulence realizations. In most models, the duration of star formation and the timescale for molecular gas removal (primarily by photoevaporation) are 4-8Myr. Both the final SFE ($epsilon_*$) and time-averaged SFE per freefall time ($epsilon_{ff}$) are reduced by strong turbulence and magnetic fields. The median $epsilon_*$ ranges between 2.1% and 9.5%. The median $epsilon_{ff}$ ranges between 1.0% and 8.0% and anticorrelates with $alpha_{v,0}$, in qualitative agreement with previous analytic theory and simulations. However, the time-dependent $alpha_{v}(t)$ and $epsilon_{ff,obs}(t)$ based on instantaneous gas properties and cluster luminosity are positively correlated due to rapid evolution, making observational validation of star formation theory difficult. Our median $epsilon_{ff,obs}(t)approx$ 2% is similar to observed values. We show that the traditional virial parameter estimates the true gravitational boundedness within a factor of 2 on average, but neglect of magnetic support and velocity anisotropy can sometimes produce large departures. Magnetically subcritical GMCs are unlikely to represent sites of massive star formation given their unrealistic columnar outflows, prolonged lifetime, and low escape fraction of radiation.
The star formation in molecular clouds is inefficient. The ionizing EUV radiation ($h u geq 13.6$ eV) from young clusters has been considered as a primary feedback effect to limit the star formation efficiency (SFE). We here focus on effects of the stellar FUV radiation (6 eV $leq h u leq$ 13.6 eV) during the cloud disruption stage. The FUV radiation may further reduce the SFE via photoelectric heating, and it also affects the chemical states of the gas that is not converted to stars (cloud remnants) via photodissociation of molecules. We have developed a one-dimensional semi-analytic model which follows the evolution of both the thermal and chemical structure of a photodissociation region (PDR) during the dynamical expansion of an HII region. We investigate how the FUV feedback limits the SFE, supposing that the star formation is quenched in the PDR where the temperature is above a threshold value (e.g., 100K). Our model predicts that the FUV feedback contributes to reduce the SFEs for the massive ($M_{rm cl} gtrsim 10^5 M_{odot}$) clouds with the low surface densities ($Sigma_{rm cl} lesssim 100$ M$_{odot}$pc$^{-2}$). Moreover, we show that a large part of the H$_2$ molecular gas contained in the cloud remnants should be CO-dark under the FUV feedback for a wide range of cloud properties. Therefore, the dispersed molecular clouds are potential factories of the CO-dark gas, which returns into the cycle of the interstellar medium.
We test some ideas for star formation relations against data on local molecular clouds. On a cloud by cloud basis, the relation between the surface density of star formation rate and surface density of gas divided by a free-fall time, calculated from the mean cloud density, shows no significant correlation. If a crossing time is substituted for the free-fall time, there is even less correlation. Within a cloud, the star formation rate volume and surface densities increase rapidly with the corresponding gas densities, faster than predicted by models using the free-fall time defined from the local density. A model in which the star formation rate depends linearly on the mass of gas above a visual extinction of 8 mag describes the data on these clouds, with very low dispersion. The data on regions of very massive star formation, with improved star formation rates based on free-free emission from ionized gas, also agree with this linear relation.
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. The se 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.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا