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Dave Strickland (JHU). Collective Feedback from Massive Stars: The Status of Observational Data and Theoretical Models of Winds. Image credit: Westmoquette, Gallagher, Smith. Properties of one phase not necessarily representative of other phases or wind as a whole.
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Dave Strickland (JHU) Collective Feedback from Massive Stars: The Status of Observational Data and Theoretical Models of Winds Image credit: Westmoquette, Gallagher, Smith
Properties of one phase not necessarily representative of other phases or wind as a whole. The Multi-Phase Nature of Superwinds (Log T ~ 3.5 - 4) WIM/WNM, (Ha, Na I etc) (e.g. Heckman, Lehnert, Martin) Shocked molecular gas at walls (e.g. Sugai et al '03) Warm dust out to z~10 kpc (e.g. Radovich et al '03) (Log T = 6.2 ~ 6.7) Coronal (log T ~ 5.5) gas in winds (Heckman, Hoopes, Otte) Non-thermal radio emission: CR, B-fields (e.g. Sequist, Golla, Dahlem) Diffuse soft and hard X-ray emission
Superwinds Super-Simplified Starburst region Breakout from disk Wind flows into halo The IGM Hot/Very hot gas ? Entrained cooler gas dust B-fields ? Confined, return to disk
Superwinds Super-Simplified Starburst region Breakout from disk Wind flows into halo The IGM Hot/Very hot gas ? Entrained cooler gas dust B-fields ? Confined, return to disk Thermalization of SN + wind energy ε to create wind fluid (pressure-driven wind). ε = fn(?). Transport of wind fluid energy εTRANS Radiative losses (minimal) Observed radiation as tracers Transfer to entrained phases
Superwinds Super-Simplified Starburst region Breakout from disk Wind flows into halo The IGM Hot/Very hot gas ? Entrained cooler gas dust B-fields ? Confined, return to disk SN/winds return 0.25xSFR Hot metals: Zo ~ 10-15 Zo,solar, Zfe ~ 5 Zfe,solar. Additional mass added? Mass loadingβ≥ 1. Lx = fn(β3) Cold gas/metals accelerated (how?). VWNM, VWIM != VXRAY or Vwind Fluid Disk/halo ISM or local IGM properties control wind. Gravity is less important.
Thresholds for Creating Extra-Planar Structures IRAS warmth f60/f100 > 0.4. Presence of extraplanar emission and winds in starbursts (Lehnert & Heckman '95). Presence of radio halos around disk galaxies (Dahlem et al '95, '01). SN rate/area: e.g. LFIR/D252 or LFIR/rHa2 Prevalence of extraplanar H in halos of normal and starburst galaxies (eDIG), e.g. Rand, Dettmar, Collins, Hoopes, Rossa et al. Halo X-ray surface brightness proportional to SF/area (Strickland et al '04b) Dahlem et al '01 Rossa & Dettmar '03
Galaxies with Superwinds Are a Diverse Population • Winds transport energy, metals, gas+dust+B-fields from disks to the IGM with efficiencies that are unknown functions of galaxy mass, SFR, SFR/area, galaxy environment. • There will be similarities and differences across the population. Beware of simple analytical models/recipes! From Grimes et al, submitted. Represenative color (R=0.3-1,G=1-2,B=2-8 keV) From Grimes et al, submitted. Represenative color (R=0.3-1,G=1-2,B=2-8 keV)
Thermalization: Heating Efficiency • ε is the fraction of the original cc SNe and stellar wind mechanical energy available to drive flows. Per SN we get ~ ε x 1051 erg. • Hard to study observationally (faint hard thermal X-ray emission, mixed with non-thermal emission?). • ε will be a function of gaseous environment, SN/volume, SF history, etc. • Observational studies – caveat emptor: • Diffuse X-ray emission in Galactic/LMC stellar clusters (e.g. Stevens & Hartwell '03): 0.1 < ε < 0.6. • Diffuse hard X-ray emission in M82 (Griffiths et al '00, Strickland '04, Strickland et al, in prep) ε≥ 0.4. M82 central 2x2 kpc Chandra 2-8 keV
Numerical Studies of ε • 3-D hydro with multiple stars in cluster: Thermalization of stellar winds (Canto et al '00) -> Adiabatic (ε ~ 1). • 3-D hydro/analytic model with SNRs and photo-evaporation (Melioli et al '04) -> two-mode solution: • Efficient cloud evap -> radiative poissoning -> low efficiency. • If SNR interaction time < cloud evap -> high efficiency. • I.e. ε = fn(SN/volume, cloud/ISM properties), but still uncertain. HE =ε (from Melioli & de Gouveia Dal Pino '04)
Mass Loading of the Hot Wind Fluid Dwarf starburst NGC 1569 (Martin et al '02) Red: HGreen: Soft X-ray Blue: R-band Contours: HI X-rays emitter volume filling? Mass loaded WF, β~10 Ha, R-band 140” ~ 1.5 kpc Chandra X-ray NGC 3079, 40 x 40 kpc box. X-rays=blue Soft X-ray not volume-filling, must be from wind/ISM interaction. WF β < 3, as LX,WF proportional to β3.
Soft Thermal X-Ray Emission (Grimes et al, submitted) Starbursts: Dwarfs LIRGs SB ULIRGs AGN ULIRGs LX/unit mass SFR/unit galaxy mass
Soft Thermal X-Ray Emission (Grimes et al, submitted) Starbursts: Dwarfs LIRGs SB ULIRGs AGN ULIRGs X-ray size Roughly galaxy mass
Red: H Green: R-band Blue: Chandra 0.3-2.0 The Leo Triplet in the optical: NGC 3628, M65, M66 20 kpc Red: Ha+R Contours: X-ray emission 5 kpc
Current X-Ray Spectral Diagnostics Thermal (hot plasma) X-ray emission comprised of: • Line emission from highly ionized metals, fn(Ti, EI, abundances). • EI = volume emission integral = ne np dV = ff ne np V, where ff = filling factor. A single temperature plasma is effectively described as fn(absorption) * fn (kT, EI, Z-elements, ne t). Assume CIE. NIE not dynamically important. For soft spectra (kT < 2 keV), with alpha/Fe > 1, and low spec. res. a Z = 10 x Solar spectrum is effectively indistinguishable from a Z = Solar spectrum.
Near Future X-Ray Spectral Diagnostics High resolution X-ray spectroscopy of M82 & NGC 253 with Astro-E2 (for 2.5 yrs, then a ~10 yr wait for Constellation-X). Absolute metal abundances for soft thermal plasmas. Ionization and temperature distribution (no longer assuming CIE). Correct EI. Hot gas kinematics -> metal flow rates, Pram, etc. Simulated ASTRO-E2 spectrum of extra-planar M82 superwind emission (100ks) 0.5 E(keV) 1.0 2.0
Emission and Radiative Energy Losses If winds are to be confined the energy must be lost. X-ray losses: On average (1-3)/ε % in LIRGS (Strickland '04). FUV losses: NGC 1705: <5/ε % (Heckman et al '01) FFUV/Fx ~ 3 (NGC 4631, Otte '04), < 0.5 (M82, NGC 3079: Hoopes et al '04, '05) NB: Calzetti et al '04 find very significant losses in optical (different sample of galaxies). M82 NGC 1482 NGC 3628 NGC 4631 Red = Optical Ha emission (gas at T~104 K), Green = Optical R-band (stars), Blue = Chandra 0.3-2.0 keV X-ray emission (gas at T ~ 5x106 K), heavily smoothed. Each image is 20 kpc x 20 kpc (from Strickland et al '04b)
What Are the Important Parameters? Obviously: Total SFR, SFR/area, ε, β, but also: Lx~2e41 erg/s Mtot~6e8 Msol ETH~1.5e56 erg EKE~3.0e56 erg Lx~2e41 erg/s Mtot~2e8 Msol ETH~2.0e56 erg EKE~5.0e56 erg ISM distribution: Disk/Halo/Local IGM distribution. Models have same starburst strength, gravity, halo ISM. Differ only in disk ISM.
M82 Ha (McKeith et al '95) VHa ~ 600 km/s Velocities in Winds 2 Analytical wind theory (CC85): 1 Z (kpc) 0 • Free wind outside SB region VWF = 2800 (ε/β)0.5 km/s. • NOTE: Can't measure velocity of X-ray-emitting gas yet! • Terminal velocity of perfect cloud mass m cross section σ, injected at R0, in radial wind (opening angle Ω): vterm= fn(VWF)0.5 ~ 240 (ε x β)0.25 [(m/σ)x (R0/1kpc)x(Ω/1.6π)]-0.5 km/s. • Tesc = μmH vesc2/5k. • Vesc=600 km/s -> kTesc=0.45 keV, vesc=400 km/s -> kTesc=0.20 keV. -1 -2 0 -400 400 VLOS (km/s)
Comparison to Simulations: #1 Log n (cm-3) From Heckman et al '00. Cool dense gas is accelated to high v in hydro models. Cloud A: 180 km/s; Cloud B: 540 km/s; Cloud c: 350 km/s; Cloud D: 860 km/s
Comparison to Simulations: #2 The hot phase have higher velocities than the cooler phases. Cold gas (log T < 4.5) has little (<10%) of the energy in superwinds, but most (90%) of the total mass. Caveat: Relative differences between the phases depend on model parameters. From Strickland & Stevens '00.
Comparison to Observations: #1 Why trend with SFR? Radiation pressure cloud acceleration (Martin '05, Murray '05)? Low ε or high β in dwarfs? Simple entrainment models too simplistic? From Martin '05 (all starbursts). VNaI SFR (Msol/yr)
Cloud Survival and Entrainment Problems Clumps in winds have ages tdyn > several Myrs! Hydrodynamical cloud crushing tcc << 1 Myr. Simulations from Marcolini et al, in prep. Pure hydro: Clouds fragment in a few tcc.
Cloud Survival and Entrainment Problems Thermal conduction-induced dynamical effects stabilize cloud against fragmentation. Cost: Evaporation into hot phase. No-conduction: fOVI/fX = 1-40. Conduction: fOVI/fX = 0.7-3 Observed: ~ 1 (NGC 4631, Otte et al '04), < 0.1-1 (M82, NGC 3079, Hoopes et al '04, in prep)
Radio Halos and B-Fields in Superwinds Non-thermal radio emission from cosmic rays advected out in wind. Bgal = 2.6 x SFR0.13(Vallee '94). Radial magnetic fields in NGC 4631 and M82 imply that large-scale magnetic field dragged out by wind, i.e. PB < PTH or PRAM. (e.g Golla & Hummel '94). In which gas phase are the large-scale fields? From Golla & Hummel '94 B-field vectors
Known/Suspected/Mysterious • Star-forming galaxies above some threshold in SF/area appear to have multi-phase SN-driven outflows. • Flow is driven by thermal and ram pressure of hot/very hot gas. • Radiative losses in gas with T> 105 K are small (high εTRANS?) • Filling factor of soft X-ray gas low. Not volume filling. • SN heating efficiencies not well known, 1 > ε > 0.1 in Sbs? • Mass loading of hot gas: High in dwarfs, not in massive starbursts? • Disk/halo/IGM environment plays strongest role in shaping winds. • VHOT, VX-ray should be > VWNM, VWIM. Hot gas likeliest to escape. • Cool gas entrainment still not really understood. • Relationship between wind velocities and kTX? • Which galaxies dominate mass/metal/energy ejection to the IGM?
Examples of Where To Go From Here • Astro-E2 and Constellation-X can determine VHOT and ZHOT accurately. Hot gas mass flow rates, densities, energies (if ff known). • Better constraints on diffuse hard X-ray emission (ε,β). • Kinematics of warm gas in more winds and at larger z distances. Test entrainment/acceleration models. • More measures of extra-planar gas properties and luminosities as a fn(mass, SF, SF/area). • More theoretical work on cool gas acceleration + survival in winds. • 3-D (magneto)hydrodynamical models with multiple fluids, realistic SF-ing initial ISM distributions. • Testing of existing and future models against observational data.