What Sculpts the Interstellar Medium? Alyssa A. Goodman Harvard University.

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Presentation transcript:

What Sculpts the Interstellar Medium? Alyssa A. Goodman Harvard University

Galaxies & Museums

Galactic Rotation + Gravity –GMCs (10 5 =10 6 M D ) SNe, GRBs, OB  winds –Cloud complex (sub-GMC) MHD waves, MHD turbulence, shocks –More "internal structure," –sometimes resulting in "cores" Star-Formation, Evaporation –Eventual disappearance of gas Geology –Deposit of Marble Saws & Dynamite –Block with specific aspect ratio Series of chisels –Head, Arms, Legs, then Fingers, Toes, Eyes, Mouth –sometimes human form Wars, Wind –Eventual disappearance of art

Outflows MHD Waves Thermal Motions MHD Turbulence Infall SNe/GRB H II Regions  B, G, T or  's alone many different varieties

Tools for finding the tools Key Method: Key Method: Use the velocity field –third (really fourth) dimension –valuable information on energetics

Tools for finding the tools Introduction to measuring velocity structure -Introduction to measuring velocity structure-Blasting l UMaj Example: Specialized Velocity Analysis-Chiseling l Generic chiseling: Line width-Size relations l "In our own image": Coherent Dense Cores l Quality Control: The Spectral Correlation Function-"Weathering" l Sandblasting? Extinction Studies

Velocity as a "Fourth" Dimension No loss of information Loss of 1 dimension

W3 -49to-41km/sec Kannappan & Goodman 1999 & Dowell 1998 o4%polarizatin 13 CO Integrated Intensity Dust Thermal Emission

Blasting Pound & Goodman 1997 Ursa Major HLC Complex

very nearby“High-latitude”= very nearby (D UMAJ ~100 pc) ~No star formation~No star formation 1 Energy distribution very differentEnergy distribution very different than star- forming regions High Latitude Cloud High Latitude Cloud 2 Gravitational << Magnetic ≈ Kinetic Star-Forming Cloud Star-Forming Cloud 3 Gravitational ≈ Magnetic ≈ Kinetic (1) Magnani et al. 1996; (2) Myers, Goodman, Güsten & Heiles 1995; (3) Myers & Goodman 1988 High-latitude Clouds

The Velocity Field in Ursa Major Ursa MajorUrsa Major H I CO Pound & Goodman 1997

 v and v LSR Gradients Gradients vv v LSR Latitude [deg] Longitude [deg] Hat Creek H I Data

 v z,obs  v z, y z  Line width primarily tangential Line width primarily radial z  -y  v rad  v tan Line width primarily radial Line width primarily tangential  v tan   v rad  v tan   v rad In General......in Ursa Major implication:  

Confirmation: Position Velocity Diagrams for H I and CO CO H I Position Along Filament 1 Position Along Filament 2 CO Blueshifted w.r.t. H I in both filaments, in arc-like pattern

v z,obs Red Blue Observed in Ursa Major CO blueshifted w.r.t H I Shell y v z,rot v z,exp v z,rot v z,exp z

Implications of Ursa Major Study Many HLC’s may be related to “supershell” structures; some shells harder to identify than NCP Loop. (Commonly observed) velocity offsets between atomic and molecular gas may be due to impacts, followed by conservation of momentum. Use this as a clue in other cases.

Chiseling Generic Chiseling (  (B, G, T,  's )) Self-similar structure Line width-Size Relations (  v~R a ) "In our own image" Putting down the chisel: Coherent Dense Cores Quality Control The Spectral Correlation Function [which  (B, G, T,  's )?]

Self-similar Structure Self-similar Structure on scales from 100 pc to 0.1 pc...in Orion 65 pc Maddalena et al CO Map, 8.7 arcmin resolution Columbia-Harvard “Mini” Dutrey et al C 18 O Map, 1.7 arcmin resolution AT&T Bell-Labs 7-m 3.5 pc 0.6 pc Wiseman 1995 NH 3 Map, 8 arcsec resolution VLA 3.5 pc 0.6 pc

Types of Line width-Size Relations. Tracer 5 Tracer 1 Tracer 2 Tracer 3 Tracer 4 Ensemble of Clouds FWHM of Various Tracers Shown Observed Size Non-thermal Line Width Type 1: “Larson’s Law” Gives overall state of ISM~magnetic virial equilibrium. See Larson 1981; Myers & Goodman 1988 for examples.  v~R 0.5

“Larson’s Law” Scaling Relations (1981) “Larson’s Law” Scaling Relations (1981)Larson’s LawLarson’s Law (line width)~(size) 1/2 (density)~(size) -1 Curves assume M=K=G (Myers & Goodman 1988)

What chiseling can produce... (a.k.a. GMC or Cloud Complex)

Coherent Cores: “Islands of Calm in a Turbulent Sea” "Rolling Waves" by KanO Tsunenobu © The Idemitsu Museum of Arts.

Hint #1: Independent Core Rotation Goodman, Benson, Fuller & Myers 1993

Hint #2: Constant Line Width in Cores?

Example of the (Original) Evidence for Coherence  v NT [km s ] T A [K] "Radius" from Peak [parsecs] TMC-1C, NH 3 (1, 1)  v NT =(0.20±0.02)T A -0.11±  v NT [km s ] T A [K] "Radius" from Peak [parsecs]  v NT =(0.64±0.05)T A -0.7±0.2 TMC-1C, OH 1667 MHz  v NT  (1.0  0.2)R 0.27  0.08  v NT  (0.30  0.09)R 0.12  0.08 Type 4 Line width-“Size” Relations Goodman, Barranco, Heyer & Wilner 1998

Types of Line width-Size Relations.. “Type 4:” Single Cloud Observed in a Single Tracer Gives information on power spectrum of velocity fluctuations. See Barranco & Goodman 1998; Goodman, Barranco, Heyer & Wilner Observed Size Type 4 Non-thermal Line Width

Types of Line width-Size Relations.. Observed Size “Type 3:” Single Cloud Observed in Multiple Tracers Non-thermal Line Width Density

Types of Line width-Size Relations.. Observed Size “Type 3:” Single Cloud Observed in Multiple Tracers Non-thermal Line Width Gives pressure structure of an individual cloud. See Fuller & Myers

The (Newer) Evidence for Coherence Type 4 slope appears to decrease with density, as predicted. FCRAO C 17 O (1-0) FCRAO C 34 S (2-1)

The Newest Evidence for Coherence N 2 H + : Coherence in the Ionized Gas Goodman, Arce, Caselli, Heyer, Williams & Wilner 1999 TMC-1C

Coherent Dense Core ~0.1 pc (in Taurus) N~R 0.1 N~R 0.9

“Coherence” in Spatial Distribution of Stars Surface Density of Stellar Companions (Taurus) Parameterized Line Width-Size Relation Coherent Turbulent log  c (  ) [stars/sq. deg]  log  [deg ] Size [pc] R o  NT [km s -1 ] Larson 1995; see also Gomez et al. 1993; Simon 1997Goodman et al. 1998

The Cause of Coherence? No ambipolar diffusion yet... 3D MHD simulation of Ostriker, Gammie & Stone (1998) Most likely suspect: Loss of magnetic support due to reduced ionization fraction in core. (Scale gives clues.) Interesting question raised: What causes residual non-thermal line width?

Length Scales Relevant to Coherence

Timescales Crossing Time Generic line width-size relation Cores

Quality Control Learning More from “Too Much” Data Year N channels, S/N in 1 hour, N pixels (S/N)*N pixels *N channels N pixels S/N Product N channels

The Spectral Correlation Function Figure from Falgarone et al Simulation

Goals of “SCF” Project Develop a “sharp tool” for statistical analysis of ISM, using as much data of a data cube as possible Compare information from this tool with other tools (e.g CLUMPFIND, GAUSSCLUMPS, ACF, Wavelets), applied to same cubes Use best suite of tools to compare “real” & “simulated” ISM Adjust simulations to match, understanding physical inputs

How the SCF Works Measures similarity of neighboring spectra within a specified “beam” size –lag & scaling adjustable –signal-to-noise equalized See: Rosolowsky, Goodman, Wilner & Williams 1999.

A “Real” Molecular Cloud IRAM Key Project Data

Initial Comparisons using the SCF Falgarone et al L1512 (Real Cloud)“Matching?” Turbulence Simulation IRAM Key Project Data

Initial Comparisons using the SCF Gammie, Ostriker & Stone 1998 L1512 (Real Cloud) IRAM Key Project Data Better? MHD Simulation

Strong vs. Weak Field Stone, Gammie & Ostriker 1999 Driven Turbulence; M  K; no gravity Colors: log density Computational volume: Dark blue lines: B-field Red : isosurface of passive contaminant after saturation  =0.01  =1  T /10 K  n H 2 /100 cm -3  B /1.4  G  2

Goals of “SCF” Project Develop a “sharp tool” for statistical analysis of ISM, using as much data of a data cube as possible Compare information from this tool with other tools (e.g CLUMPFIND, GAUSSCLUMPS, ACF, Wavelets), applied to same cubes Use best suite of tools to compare “real” & “simulated” ISM Adjust simulations to match, understanding physical inputs

Results from SCF Project, 3/99 Some simulations do match quantitatively better than others (Goodman & Padoan 1999) –compared so far: Padoan et al.; Ostriker, Gammie & Stone; Vazquez, Porter, Pouquet et al; MacLow et al. Comparison with moment analysis shows SCF more discriminating (Rosolowsky et al. 1999) Noise analysis is critical for ALL methodsNoise –S/N cutoffs, corrections –Window size SCF used on Galactic H I can identify shells automatically (see Ballesteros, Vazquez & Goodman 1999)

The Effects of Noise The Effects of Noise

What Sculpts the ISM? Blasting Origin of High-Latitude Clouds Generic Chiseling Line width-Size Relations (  v~R a ) "In our own image" Coherent Dense Cores Quality Control The Spectral Correlation Function Which  (B, G, T,  's )?

To be discussed: The Role of Clay Agglomeration, Tidal Stripping, the IMF Weathering Museum Destroyed on 100,000 yr time scale Longest lifetime of Galactic ISM Structures? The Role of Chemistry How much structure is density, how much chemistry? Very Small-Scale Structure Interferometric Observations Extinction surveys & Pencil-beam Observations

Optical View of W3 Region

The Velocity Field in Ursa Major Ursa MajorUrsa Major Pound & Goodman 1997