Diagnosing the Role of MHD Turbulence in Massive Star Forma:on

Transcription

1 Diagnosing the Role of MHD Turbulence in Massive Star Forma:on Blakesley Burkhart Einstein Fellow Harvard- Smithsonian Center for Astrophysics With Min Young- Lee, Alex Lazarian, David Collins, Jonathan Tan, Snezana Stanimirovic, Mark Krumholz, Lars Hernquist, Annalisa Pillepich, Shy Genel

2 Can we do beper and get an answer!?

3 The Life Cycle of Gas in Galaxies Conference Ques:on: What are the ini:al condi:ons of massive star forma:on?

4 Star forma:on triggered by ISM turbulence cascade E(k) What is the ISM driving scale? What is the dissipa:on scale? K (inverse scale) Diagnos:cs should measure: 1) E(k), energy rate 2) MA (Alfven Mach number/b field) 3) MS (sonic Mach number) Turbulence, gravity, magne2c fields, feedback All important but dominate at which scales? Energy cascade sets seeds for massive stars? How to measure E(k) in order to test predic:ons/simula:ons?

5 How to Study MHD Turbulence Observa:onally? Tool box for studying MHD turbulence: Theory Astrophysical Turbulence = Numerics Diagnos:cs should measure: 1) E(k) 2) MA 3) MS Sta:s:cal Studies/ Scaling Laws

6 Burkhart et al. 2013b, c Burkhart & Lazarian 2012 Burkhart Lazarian Gaensler 2012 Gaensler et al Iacobelli et al Chepurnov, et al E(k) E(k) (Structure func:on) Burkhart et al. 2013b, c Burkhart Collins Lazarian 2014 Burkhart et al. 2013a Goodman et al Burkhart et al. 2010a Burkhart et al PCA Tofflemire et al Phase Coherence Burkhart & Lazarian in prep. Burkhart et al Brunt & Heyer 2002 Esquivel & Lazarian 2011

7 Outline of the Talk - Energy injec:on scale - Frac:on of turbulence energy - Spectral slope of density And velocity fluctua:ons E(k)

8 The Power Spectrum and Driving of Turbulence Where does turbulence come from? Kpc, large scales: supernova/ gravity Sub pc, small scales: winds, ouglows

9 Gas dispersion on Kpc scales driven by gravity/feedback as seen in simula:ons and observa:ons. Spirals and dwarfs (Illustris) Green et al. (2010) Krumholz & Burkhart 2015; Burkhart, Genel, Pillepich, Hernquist, 2016 in prep.

10 Iner:al Range Measurements Iner:al range provides: compressibility of the media, dynamic range of the cascade, and comparison with analy:cal predic:ons.

11 Supersonic power spectra: predic:ons confirmed by numerical simula:ons Velocity Power Spectrum Density Power Spectrum Kowal & Lazarian 2010 Burkhart et al Fleck 1996 model of compressible turbulence: velocity steepens and density shallows

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13 VCS of SMC (21cm) Chepurnov, Burkhart, Lazarian & Stanimirovic 2015

14 Velocity/density power spectrum reveal mul2phase ISM spectra in agreement with expecta2ons for supersonic turbulence For Supersonic Turbulence: density spectrum become shallower and velocity spectrum becomes steeper (rela:ve to Kolmogorov) Compare to - 5/3= Integrated intensity goes it - 3 In op:cally thick limit! Lazarian 04, Burkhart et al. 13 Density and velocity power spectrum from Lazarian & Pogosyan (2000, 2004) Velocity Coordinate Analysis (VCA) method.

15 The density PDF is important for theories of star forma:on 1) Ini:al mass func:on 2) Star forma:on efficiency 3) Star forma:on rate Collins et al. 2012

16 PDFs of Column Density- M s 2 nd moment: Variance (σ 2 linear and log PDF) vs. M s 3 rd moment: Skewness(linear PDF) vs. M s 4 th moment: Kurtosis(linear PDF) vs. M s e.g. Vazquez- Semandeni 94, Kowal et al. 07; Federrath et al. 08 Burkhart et al. 09,10; Burkhart & Lazarian 12; Kainulainen & Tan Skewness=A*M s +b Kurtosis=A*M s +b Linear Column Density PDF M s =0.5 =2.0 =8.0 s =4.5 Ms=0.5 Ms=2.0 Ms=4.5 Ms=8.0

17 Sonic Mach Number vs. Variance Rela:on: Where do the Molecular Clouds Fall? ENZO self- gravita:ng Cold HI Warm HI/DIG IRDCs (Kainulainen & Tan 2013) (Berkhuijsen & Fletcher 2008) log Burkhart, Collins, & Lazarian 2015 Burkhart & Lazarian 2012

18 Simula:ons: Power law tails; devia:ons from rela:on to M S Observa:ons: Bias from selec:on effects (closed contour), foregrounds etc. Can the atomic gas PDFs in GMCs give us a reliable clue to turbulence seed for the molecular gas? High B, M A =7 Low B, M A =20 Agrees well with observa:ons of Schneider et al. 2014

19 PDFs of turbulence: HI vs. Dust Diffuse HI and Hα: Lognormal distribu:on e.g. Berkhuijsen & Fletcher 2010 Dust/molecules: Lognormal debated (e.g. Alves et al. 2015) Power law distribu:on at high N e. g., Schneider et al What can the PDF of HI and dust in GMCs tell us about the distribu2on of gas?

20 Mul:phase View of Perseus: HI and H2 Total gas/dust (2MASS/IRAS) - =

21 Mul:phase View of the Atomic and Molecular Gas PDF of Perseus Sharp HI- H2 transi:on traced by PDFs near Krumholz, McKee & Tumlinson (2009) predicted value (~10 Msolar/pc 2 ). HI PDF traces lognormal (turbulence) H2 PDF traces power law tail (gravity) Total gas PDF shows the composi:on of both. Burkhart, Lee, Murray & Stanimiroivic 2015; Imara & Burkhart 2016

22 Summary 1) Turbulence driven on large scales sets the seeds for star forma:on. 2) Diagnos:cs needed for: sonic and Alfven Mach numbers and the velocity/density power spectrum. 3) Velocity power spectrum can be measured with VCS; Density power spectrum with integrated intensity maps. 4) Gravity alters the PDFs away from rela:on to sonic Mach number; evolved clouds show observa:onal signatures of collapse evolu:on. 5) HI in GMCs allows us to measure the lognormal por:on of the PDF (HI- H2 trans). Velocity Power Spectrum (VCS)- Lazarian & Pogosyan 2008; Chepurnov, Burkhart, Lazarian, Stanimirovic 2014 in prep. Dendrograms Goodman et al. 2009; Burkhart et al. 2013a PDFs- Burkhart et al. 2009, 2010; Burkhart Lazarian 2012; Burkhart, Collins, Lazarian 2014 in prep. Anisotropy- Burkhart et al. 2014, submiped. Bispectrum- Burkhart et al., 2010 Tsalis Sta2s2cs- Tofflemire, Burkhart, Lazarian, 12, ApJ, 736, 60 CO Diagnos2cs- Burkhart, Ossenkopf, Lazarian, Stutzki 2013a,b; Correia et al. 2014