the impulsive heating rate in shocked o star...
TRANSCRIPT
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The Impulsive Heating Rate in Shocked O Star Winds:
Determined Directly from High-Resolution X-ray Spectra
David CohenDepartment of Physics & Astronomy
Swarthmore College
Zack Li (Swarthmore ’16), Jon Sundqvist and Stan Owocki (Delaware), Véronique Petit (Florida Institute of Technology), Maurice Leutenegger (GSFC), Marc Gagné (West Chester), Asif ud-Doula (Penn St.)
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Soft-X-ray emission is ubiquitous in O stars
LX ~ 10-7 LBol (LX ~ 1031 to 1033 ergs s-1)
soft thermal spectrum: kT < 1 keV
minimal time variability
optical/IRCarina: ESO
Trumpler 14 in Carina: Chandra
HD 93129A (O2 If*)
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High- and low-mass stars have different X-ray production mechanisms
Massive stars show no correlation between rotation and X-ray emission
vsini vsini
low masshigh mass
X-r
ay lu
min
osity
No convective envelope; no dynamo; no corona
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Radiation-driven O star winds
ζ Pup (O4 supergiant): M ~ few 10-6 Msun/yr
UV spectrum: C IV 1548, 1551 Å
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Capella (G5 III)
ζ Pup (O4 If)
Chandra Medium Energy Grating (MEG)
Ne X Ne IX Fe XVII
~2000 km/s
(unresolved)
X-ray lines are Doppler-broadened => the X-ray emitting plasma is associated with the stellar wind
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Radiation-driven O star winds
kinetic power in the wind = 1/2 Mv∞2 (~10-3 Lbol)
typically 104 times larger than the observed Lx
Lx ~ 10-7 Lbol
for O stars
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X-rays = thermal emission = ~10-4 of wind KE
…How is this small fraction of the wind kinetic energy extracted ?
Trumpler 14 in Carina: Chandra
HD 93129A (O2 If*)
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Embedded Wind Shock (EWS) paradigm
numerous shocks distributed throughout the wind, generally above some onset radius
r =1.5R*
1-D radiation-hydro simulation
Line Deshadowing Instability (LDI) - intrinsic to line-driven flows
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Embedded Wind Shock (EWS) paradigm
r =1.5R*
Less than 1% of the mass of the wind is emitting X-rays>99% of the wind is cold and X-ray absorbing
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1-D rad-hydro simulation
with J. Sundqvist, S. Owocki, Z. Li
1.5 R* 5 R*
An animated gif of this simulation is available at http://astro.swarthmore.edu/~cohen/presentations/JOS_sim_lowkappamax.gif
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2-D radiation-hydro simulationsinitial work 12 years ago; line transport is expensive
Dessart & Owocki 2003
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Line-Deshadowing Instability (LDI)LDI (Milne 1926) is intrinsic to any radiation-driven outflow in which the momentum transfer is mediated by spectral lines
rapidly accelerating material moves out of the Doppler shadow of the material behind it
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courtesy Stan Owocki
line profile photospheric radiation
frequencyradiation force
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frequency
line profile photospheric radiation
radiation force
the Doppler shadow
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line profile photospheric radiation
frequencyradiation force
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frequency
line profile photospheric radiation
radiation force
positive velocity perturbation
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frequency
line profile photospheric radiation
radiation force
positive velocity perturbation
increases
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radiation force depends on changes in the local wind velocity (moving out of the Doppler shadow), but
acceleration depends on the force (Newton): strong feedback and resulting instability
Physics of the Line Deshadowing Instability (LDI)
stability analysis: Owocki, Castor, Rybicki (1988)
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put detailed spectral line transport in a radiation-hydro code
Feldmeier, Puls, & Pauldrach (1997)
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Simulations constrained by data? Can we reliably compute an X-ray spectrum from the simulations to compare to observations?
No. Not easily, anyway.
Resolving post-shock gas as it advects across the grid is very difficult.
Numerical instabilities related to radiative cooling are difficult to combat.
Several additional computational and physics issues: 1-D limitation; line-force cut-off; lower boundary conditions (to be discussed at the end).
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Open Questions
How efficient is the LDI at making shocks? How many shocks?
What is the distribution of shock strengths (temperatures)?
What is the spatial distribution of shocks?
How clumped is the wind?
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Big Question
what are the actual mass-loss rates of O star winds?
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Key issues addressed by new work
How efficient is the LDI at making shocks? How many shocks?
What is the distribution of shock strengths (temperatures)?
What is the spatial distribution of shocks?
How clumped is the wind?
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Key issues addressed by new work
What is the distribution of shock strengths (temperatures)?
closely related to: “what is the instantaneous distribution of plasma temperatures?” (the differential emission measure)
but this involves cooling as well as heating
And the cooling is difficult to model in detail in the numerical simulations
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Traditional emission measure approach
coronal (thermal, equilibrium, collisional, optically thin) X-ray emission scales as density squared
Wojdowski & Schulz (2005)
emission measure (EM) is a function of temperature
differential emission measure (DEM)
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Problems with the (D)EM
depends on the density (squared) of the hot plasma
overall level doesn’t tell you about the efficiency or rate of the heating…without a lot of modeling
temperature distribution depends on the cooling as well as the heating
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A new method for directly extracting information about shock heating from an X-ray spectrum
The method is surprisingly simple, because O star wind shocks are radiative. But the framework developed by Gayley (2014) can incorporate other cooling channels (adiabatic, conduction)
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Dense O star winds have radiative shocks
the X-ray emission level scales not as density squared but linearly with density
Lx from one shock-heated particle, integrated over its cooling ~ kTshock
there is a large, statistical sample of shocks representing all stages of shock evolution - a single X-ray observation is equivalent to completely tracking the evolution of a representative ensemble of shocks.
Total Lx from a shock ~ mass flux across the shock front (times the kTshock for each particle)
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Dense O star winds have radiative shocks
insight (e.g. Antokhin et al. 2004; Gayley 2014):
if radiation is the dominant cooling mechanism, the time-integrated spectrum of the post-shock plasma as it cools only depends on the initial shock temperature
not on the density; higher density cools faster but emits more strongly
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Dense O star winds have radiative shocks
insight (e.g. Antokhin et al. 2004; Gayley 2014):
each X-ray emission line is sensitive to shocks corresponding to a given temperature, Tline - and so it radiates in plasma shock-heated to temperatures Tline and greater
ζ Pup (O4 If)Ne X: Tline = 6 X 106 K
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Dense O star winds have radiative shocks
ζ Pup (O4 If)Ne X: Tline = 6 X 106 K
The X-ray spectrum thus contains information - almost directly - about the cumulative probability distribution of shock strengths, p(T) = the probability that a shock heats gas to at least T.
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X-ray luminosity from shock properties
Lx from from a single shock, heated to temperature Tshock:
N, average number of times a particle crosses a shock front as it advects
out through the wind
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X-ray luminosity from shock properties
Lline X-ray luminosity radiated into a single line as a shock cools:
N, average number of times a particle crosses a shock front as it advects
out through the wind
fraction of shock energy radiated in the line
(ignoring momentarily that not every shock is hot enough to generate emission in a given line)
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emissivities from APEC
Smith et al. (2001); Foster et al. (2012)
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fraction of shock energy radiated in the line
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Not every shock is strong (hot) enough to produce radiation in a given line
Lline X-ray luminosity radiated into a single line as a shock cools:
p(Tline), cumulative distribution of shock
temperatures
p(Tline): probability that a shock heats the wind to temperature, Tline, or higher (in which case the post-shock plasma will cool through Tline)
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the temperature “equivalent width” - tabulated from atomic physics, ionization equilibrium (APEC)
measured flux in an X-ray linecorrection for ISM attenuation
correction for wind attenuation
expectation value of the number of shocks a typical particle passes
through that heat it to Tline or greater
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correction for wind attenuation
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Embedded Wind Shock (EWS) paradigm
r =1.5R*
Less than 1% of the mass of the wind is emitting X-rays>99% of the wind is cold and X-ray absorbing
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correction for wind attenuation
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Chandra grating spectra confirmed the EWS scenario
zeta Pup (O4 If): 63 ks Chandra MEG
Chandra easily resolves the wind-broadened X-ray emission lines
VDoppler ~ Vwind
Ne X Ne IX Fe XVII
~2000 km/s
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lines are asymmetric:
ζ Pup (O4If)
Capella (G5 III)
this is a signature of wind absorption, and enables us to measure the wind mass-loss rate
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v = v∞(1-r/R★)β beta velocity law assumed
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Ro
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2 representative points in the wind that emit X-rays
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2 representative points in the wind that emit X-rays
absorption along the ray
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2 representative points in the wind that emit X-rays
absorption along the ray
extra absorption for redshifted photons from
the rear hemisphere
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mass-loss rates ~10-6: expect wind to be modestly optically thick
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Line profile shapes
Ro=1.5!
Ro=3!
Ro=10!
τ�=1,2,8 key parameters: Ro & τ★
v = v∞(1-r/R★)β
j ~ ρ2 for r/R* > Ro,!
= 0 otherwise
Owocki & Cohen 2001
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τ★ = 2.0Ro = 1.5 R★
ζ Pup: ChandraFit the model to dataFe XVII
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Apply a wind attenuation correction to each line in the Chandra spectrum
The attenuation corrections can be significant
and vary a lot from line to line
and they are not given by the simple exp(-tau) relationship.
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the temperature “equivalent width” - tabulated from atomic physics, ionization equilibrium (APEC)
measured flux in an X-ray linecorrection for ISM attenuation
correction for wind attenuation
expectation value of the number of shocks a typical particle passes
through that heat it to Tline or greater
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Five effectively single O stars with grating spectra in the Chandra archive
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No ~ 0.1 to 1 n ~ 2 to 3
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Turn-over or cut-off at high temperatures?
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Observation constraints on theory/simulations Track parcels as they flow through
the wind; discontinuities are shocks
Tshock = 106 (vshock/270 km/s)2 K
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Observation constraints on theory/simulations from 1-D numerical simulations
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Observation constraints on theory/simulations from 1-D numerical simulations
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Theory/simulation issues
Line force cut-off for most optically thick lines (numerical issues)
Lower boundary conditions: self-excited vs. perturbed; also limb darkening - role of clump-clump collisions
Multi-dimensional effects
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Feldmeier, Puls, & Pauldrach (1997)
clump-clump collisions - what about 2-D? 3-D?
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Lower boundary conditionsself-excited photospheric perturbations +
limb darkening
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Conclusions
impulsive heating with radiative cooling enables a simple correction for the cooling and the extraction of the impulsive heating rate and temperature distribution
EWS in O stars generate a relatively universal heating distribution: wind material undergoes roughly one shock, and strong shocks are much less commonly produced than weak ones
The rate seems to decline very sharply above 107 K