On the Origin of the Global Schmidt Law of Star Formation

By Andrey V. Kravtsov. 2003

205 citations recorded by the source corpus.

One of the most puzzling properties of observed galaxies is the universality of the empirical correlation between the star formation rate and the average gas surface density on kiloparsec scales (the Schmidt law). In this study, I present results of self-consistent cosmological simulations of high-redshift galaxy formation that reproduce the Schmidt law naturally, without assuming it, and provide some clues to this puzzle. The simulations have a dynamic range high enough to identify individual star-forming regions. The results indicate that the global Schmidt law is a manifestation of the overall density distribution of the interstellar medium. In particular, the density probability distribution function (PDF) in the simulated disks has a well-defined generic shape that can be approximated by a lognormal distribution at high densities. The PDF in a given region of the disk depends on the local average surface density Σg. The dependence is such that the fraction of gas mass in the high-density tail of the distribution scales as Σ with n ≈ 1.4, which gives rise to the Schmidt-like correlation. The high-density tail of the PDF is remarkably insensitive to the inclusion of feedback and details of the cooling and heating processes. This indicates that the global star formation rate is determined by the supersonic turbulence driven by gravitational instabilities on large scales, rather than stellar feedback or thermal instabilities on small scales.

Subfields: Astronomy and Astrophysics

View Paper: https://www.semanticscholar.org/paper/54190ee02e78391a798e5a8a62ea589b14245865

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Citations in the corpus

Theory of Star Formation (2007, methodology): “Simulations by Kravtsov (2003), by Li, Mac Low, & Klessen (2005a,b, 2006), and by Tasker & Bryan (2006) show that the fraction of high-density gas scales as Σ1.”
Star formation and feedback in smoothed particle hydrodynamic simulations – I. Isolated galaxies (2006, methodology): “Kravtsov (2003) notices a steepening of the star formation rate with density in his simulations.”
Numerical simulations of the dark universe: State of the art and the next decade (2012, methodology): “The most commonly used AMR codes in the galaxy formation community are Hydro-Art [242, 330, 331], Enzo [332, 333], and Ramses [250] (with the Flash code [334] about to join the fray [335]).”
On the relation between the Schmidt and Kennicutt-Schmidt star formation laws and its implications for numerical simulations (2007, methodology): “This agrees well with the recipes used in numerical simulations, which typically set nH,c ∼ 10−1 cm−3, although some studies of individual galaxies have used much higher values (e.g., nH,c = 50 cm −3 for Kravtsov 2003 and 103 cm−3 for Li et al. 2005).”
Formation of Globular Clusters in Hierarchical Cosmology (2003, methodology): “While the detailed implementation of these processes is described elsewhere (Kravtsov 2003), below we summarize the details crucial to this study.”
Galaxy bimodality due to cold flows and shock heating (2004, background): “Similarly, Nagai & Kravtsov (2003) find in their simulation of a massive halo that the filamentary structure is associated with gas entropy (∝ T/ρ2/3) far below that of the surrounding halo gas.”
Understanding the shape and diversity of dwarf galaxy rotation curves in ΛCDM (2016, background): “…capture the momentum injection into the interstellar medium (ISM) generated by expanding bubbles of shock heated gas (e.g. Kimm et al. 2015); and (ii) star formation becomes self-regulated by stellar feedback (e.g. Kravtsov 2003; Saitoh et al. 2008; Hopkins et al. 2011, 2013; Agertz et al. 2013).”
Simulating the Formation of Molecular Clouds. I. Slow Formation by Gravitational Collapse from Static Initial Conditions (2006, background): “…model the transition from atomic to molecular gas, we have chosen to consider relatively small volumes of gas, which we visualize as being small sub-regions within larger, gravitationally collapsing regions, such as those found in the simulations of Kravtsov (2003) or Li, Mac Low & Klessen (2005).”
Bursting and quenching in massive galaxies without major mergers or AGNs (2007, background): “It shows as a function of halo mass the fraction of cold gas within the virial radius and outside the disc in dark matter haloes from cosmological simulations by A. Kravtsov (described in Kravtsov 2003; Kravtsov & Gnedin 2005, where they were used for other purposes).”
Simulating the Formation of Molecular Clouds. II. Rapid Formation from Turbulent Initial Conditions (2006, background): “…paper is to model the transition from atomic to molecular gas, we have chosen to consider relatively small volumes, which we visualize as being smaller subregions within larger, gravitationally collapsing clouds of gas, such as those found in the simulations of Kravtsov (2003) or Li et al. (2005).”
The formation of disc galaxies in a ΛCDM universe (2010, background): “The ISM has been shown to be represented by a lognormal density probability distribution function (PDF) (e.g. Kravtsov 2003; Wada & Norman 2007), or even a superposition of several lognormally distributed ISM phases (Robertson & Kravtsov 2008).”
ENZO: AN ADAPTIVE MESH REFINEMENT CODE FOR ASTROPHYSICS (2013, methodology): “Schmidt-Law method This method of star particle creation is designed to reproduce the global Schmidt law of star formation (Kravtsov 2003; Schmidt 1959).”
Jet-induced star formation in gas-rich galaxies (2011, methodology): “This method is widely used in hydrodynamic simulations (e.g. Kravtsov 2003; Springel & Hernquist 2003; Schaye & Dalla Vecchia 2008; Dubois & Teyssier 2008), supported by observations (Krumholz & Tan 2007) and is able to recover the Kennicutt–Schmidt law (Kennicutt 1998) in simulations.”
A General Theory of Turbulence-regulated Star Formation, from Spirals to Ultraluminous Infrared Galaxies (2005, methodology): “Kravtsov (2003) uses the probability distribution of densities in simulations to suggest that the fraction of high-density gas varies with the overall density to roughly the 1.4 power, explaining one form 250 of the Kennicutt-Schmidt law.”
ENVIRONMENTAL DEPENDENCE OF THE KENNICUTT–SCHMIDT RELATION IN GALAXIES (2010, background): “Likewise, large-scale instabilities seed the turbulence in the disk that can shape the global density PDF (Wada & Norman 2001; Elmegreen 2002; Kravtsov 2003; Krumholz & McKee 2005).”
A primer on hierarchical galaxy formation: the semi-analytical approach (2006, methodology): “To circumvent the spatial resolution problem faced by fixed-grid codes, much work has been done to develop adaptive-mesh refinement (AMR) codes (Bryan & Norman 1997; Teyssier 2002; Kravtsov 2003; Quilis 2004; Nagai & Kravtsov 2005).”
Comparing the statistics of interstellar turbulence in simulations and observations - Solenoidal versus compressive turbulence forcing (2009, background): “…to explain the stellar initial mass function (Padoan & Nordlund 2002; Hennebelle & Chabrier 2008), the star formation rate (Krumholz & McKee 2005), the star formation efficiency (Elmegreen 2008), and the Kennicutt-Schmidt relation on galactic scales (Elmegreen 2002; Kravtsov 2003; Tassis 2007).”
Dark matter cores all the way down (2015, background): “…us insensitive to the details of our ‘sub-grid’ numerical parameters (for a detailed discussion on this, see e.g. Kimm et al. 2015; for earlier work on the utility of resolving the interstellar medium (ISM) see e.g. Kravtsov 2003; Saitoh et al. 2008; Hopkins et al. 2011, 2013; Agertz et al. 2013).”
Theoretical Challenges in Galaxy Formation (2016, background): “…allow for metal enrichment and metal dependent radiation equilibrium cooling (for specific implementations see e.g. Ceverino & Klypin 2009; Kravtsov 2003; Oppenheimer & Davé 2006; Scannapieco et al. 2005; Tornatore et al. 2007; Vogelsberger et al. 2013; Wiersma, Schaye & Smith 2009) of…”
The confinement of star-forming galaxies into a main sequence through episodes of gas compaction, depletion and replenishment (2015, methodology): “The VELA simulations utilize the Adaptive Refinement Tree (ART) code (Kravtsov et al. 1997; Kravtsov 2003; Ceverino & Klypin 2009), which accurately follows the evolution of a gravitating N -body system and the Eulerian gas dynamics.”