Transcript Slide - Agenda INFN

Imaging spectro-polarimetry of plasmas
John Howard
A Diallo, M Creese, (ANU) S Allen, R Ellis, M Fenstermacher,
W Meyer, G Porter (LLNL, GA)
J Chung, (NFRI) O Ford, J Svennson, R Konig, R Wolf (IPP) 1
Outline
• “Coherence imaging” interferometric systems
– Principles
– Spatial heterodyne Doppler coherence imaging systems
– Doppler tomography in the DIII-D divertor
• Motional Stark Effect imaging on KSTAR
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Measurement principles
Optical system and calibration
KSTAR measurements
Modeling results (using full QM treatment)
“Coherence imaging”:
An alternative approach to spectroscopy
A simple polarization interferometer gives contrast and phase at a single optical delay
Waveplate (delay f=2pLB/l)
Incident
Input
Slow
Interferogram
S = I(1+z cosf)
Fast
Polarizer
Spectral
To recover
the fringe properties, measurements are required at
Lines
multiple interferometric delays
Fourier transform
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Spatial heterodyne interferometer
Savart plate introduces lateral
displacement that gives an angular phase
shear  generates straight parallel fringes
imprinted on image.
Demodulate for brightness, fringe contrast,
fringe phase  plasma properties
DIII-D Divertor raw image
Why do “coherence imaging”?
• When spectral information content is small (e.g. shift, width), it suffices
to image the optical coherence (interferogram fringe contrast and phase)
of the light emission at a small number of optical delays.
• The spatial heterodyne coherence imaging system is a “snapshot”
imaging polarization interferometer that allows local estimates of
interferometric phase and contrast at one or more optical delays (with
multiple independent carriers).
• Why measure optical coherence?
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Interferometers have throughput advantage (for R>100)
Robust alignment, birefringent optics, simple instrument function
Can be deployed for synchronous fluctuation studies (Doppler, MSE)
2D imaging with simple interpretation
Interferometric quantities are invertible
Assume inhomogeneous, drifting Maxwellian distribution
For a single spectral line, the interferometer signal is
f0 is the dc phase delay offset.
It also includes a superimposed spatial
carrier.
DC level gives line-integrated emissivity:
fD is the Doppler shift phase
I(r) is the local emissivity
Fringe contrast gives emissivity-weighted “temperature”:
Ti(r) is the local ion temperature
TC is a constant “temperature”
characterizing the instrument resolution
(like a slit width)
Phase gives emissivity-weighted flow component in direction of view:
vD(r) is the local flow velocity
Scrape-off-layer and divertor Doppler spectroscopy on
the DIII-D tokamak - CIII 465nm and CII 514nm
SOL brightness projection
DIII-D Poloidal cross section
LCFS
Divertor raw image
SOL flow projection
With A Diallo, M. Creese, S Allen, R Ellis, W. Meyer, G Porter, M Fenstermacher
Demodulated DIII-D divertor brightness and
phase images during detachment
Foruier demodulated brightness (top) and phase (bottom) projections at
representative times during the divertor evolution
for DIII-D discharge #141170: (a) 500 ms, (b) 2000 ms and (c) 4000 ms.
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Typical DIII-D raw image data
Camera frame rate typically 10-20 frames per second, 688x520 pixels, 12 bits
Exposure time typically 10-100 ms
LabVIEW control software + demodulation
Tomographic reconstruction algorithm details
 Iterative linear reconstruction technique (ASIRT) on 1cm x 1cm grid
(no apriori constraints on the reconstruction domain)
 Assume toroidal symmetry
 Use reconstructed emissivity and computed B.dl/|B| as integral weights in
parallel flow speed tomography
Right: Line of sight trajectories in R-Z plane
for one projection-image column (above)
(Colour coding indicates integral weight)
Tomographically inverted DIII-D divertor
brightness and flow images
Fourier demodulated brightness
(top) and phase (bottom) projections
at representative times during the
divertor detachment for DIII-D
discharge #141170: (a) 500 ms, (b)
2000 ms and (c) 4000 ms.
Corresponding tomographic
inversions of brightness (top) and
phase (bottom)
The flow is seen only in regions
where the brightness is significant
With Diallo, Allen, Ellis, Porter, Meyer, Fenstermacher, Brooks, Boivin
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Comparison with UEDGE modeling
Some similarities between
UEDGE modeling and
tomographically inverted
brightness and parallel flow
speed.
But observed are ~2x as
high as modeling predicts.
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Outline
• “Coherence imaging” interferometric systems
– Principles
– Spatial heterodyne Doppler coherence imaging systems
– Doppler tomography in the DIII-D divertor
• Motional Stark Effect imaging on KSTAR
–
–
–
–
Measurement principles
Optical system and calibration
KSTAR measurements
Modeling results (using full QM treatment)
Motional Stark effect polarimetry senses the
internal magnetic field
Top view KSTAR MSE viewing geometry
Beam
A typical Doppler shifted Stark effect spectrum
Edge
Centre
View range
Edge
Modelled interferometric image of beam
Centre
Courtesy, Oliver Ford, IPP
Motional Stark effect (MSE) polarimetry measures the polarization orientation of Stark-split Da
656 nm emission from an injected neutral heating beam.
The splitting and polarization is produced by the induced E-field (E = v x B ) in the reference
frame of the injected neutral atom. MSE can deliver information about the internal magnetic
field inside a current-carrying plasma
Angle-varying Doppler shift  every observation position requires its own colour filter.
Interferometric approach – periodic filter allows 2-D spatial imaging  Bz(r,z)
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Oliver Ford, IPP
Imaging spectro-polarimetry for MSE
Recall simple polarization interferometer:
Quarter waveplate
Input
Waveplate (delay f)
Output signal
S = I(1+z cosf)
Polarizers
If input is polarized already (angle y), remove the first polarizer
Resulting interferogram fringe contrast depends on polarization orientation:
S = I(1+z cos2y cosf)
Add a quarter wave plate. Fringe phase depends on polarization orientation:
S = I[1+z cos(f + 2y)]
The p and s components interfere constructively (no need to isolate or separate)
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How do we image the multiplet?
For one of the multiplet components (e.g. p), the interferometer output is:
Sp = Ip [1+zp cos(fp+2y)]
For the orthogonal component (y  y+p/2) the sign is reversed
Ss = Is [1-zs cos(fs+2y)]
For MSE triplet, after adding the interferograms, the effective signal contrast
depends on the component contrast difference zp – zs. Choose interferometer optical
delay t to maximize the contrast difference zp – zs
Model of KSTAR isolated full energy Stark
multiplet and associated nett contrast
Edge
s
p
Centre
Good contrast (~80%) across full field of view (i.e. Stark splitting doesn’t
change significantly). But significant phase variation due to large Doppler shift
Optical delay 1000 waves  a-BBO plate thickness ~5 mm
2nm bandpass filter tilted to track Doppler shift across FOV
KSTAR parameters: Bt = 2.0T on axis, Ip = 600 kA
D beam, 85keV/amu, 1.0 degrees divergence
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Imaging MSE instrument
Insert shearing (Savart) plates to provide carrier fringes:
S = I0 [1 + z cos(kxx + f+2y) + z cos(kyy - f+2y) ]
Instrument produces orthogonal phase modulated spatial carriers
Demodulate fringe pattern to obtain Doppler shift f and polarization y
Optical system layout
Mirror
Telescope
Camera
Cell
Filter
From plasma
Power spectrum of interference pattern
Calibration image using Neon lamp at 660nm
-f+2y
f+2y
2e
All information is encoded on distinct spatial heterodyne carriers:
Polarimetric angles: (y, e) (orientation and ellipticity)
Interferometer contrast and phase: (z, f) (splitting and Doppler shift)
Typical calibration data
(a) Central horizontal slices across a sequence of demodulated polarization angle images y. The
Doppler phase image f is insensitive to the calibration polarizer angle. (Turning mirror removed).
(b) Deviation from linearity of the measured polarization angle at the centre of the calibration image
versus polarizer angle. Cell size for averaging is ~1.5-2 carrier wavelengths (10-14 pixels). There is
a small systematic variation. Random noise ~0.1 degrees (calibration image).
Typical MSE double heterodyne image
Plasma
Boundary/
port
opening
Radiation noise
Orthogonal spatial carriers
Pixelfly
1300x1000
100ms exp
Frame rate
10Hz
Internal reflection
and sparks
(not an issue for
imaging MSE)
This is our calibration image!
Day 2
Day
1 3
Day
Beam direction
Conclusion: Need new camera
Solution: CID camera + remote + shield
Measured and modelled Doppler phase images are in
good agreement
Measurement
Centre
Model
Edge
Line-of sight integration effects may account for the small
discrepancies.
Viewing from above mid-plane accounts for tilt of phase contours
System tolerant of large beam energy changes (70-90 keV)
QM modeling of system polarization response
• Apply QM model developed by Yuh, Scott,
Hutchinson, Isler etal to estimate importance of
Zeeman effect on MSE nett polarization (all
components E, v and B)
• No line of sight integration effects
• Statistical populations
• Uniform brightness beam (no CRM modeling)
• KSTAR viewing geometry
• Simple circular flux surfaces with Shafranov shift
• Spectro-polarimeter – sum over 36 cpts
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E,v and B components
Intensity
Centre
Orientation
Ellipticity
Edge
E (p)
V (s)
B
5% of
intensity
Comparison with ideal Stark effect model
Stark-Zeeman
Difference orientation angle
Geometric model (no Zeeman)
Difference orientation angle
variation across MSE image less
than ~0.1o
 Standard geometric models
for interpretation are OK
Measured and model “nett polarization” images
Low brightness
regions
Simple circular plasma model 2.0T, 600kA
Reflection artifact
A typical measured nett polarization image
- 2.0T, 600kA
Note: A fixed constant shift of 16 degrees
has been subtracted – thermal drift?
Nett polarization angle = plasma MSE angle - Gas MSE reference angle
Typical KSTAR midplane radial profile evolution
during RMP ELM suppression xpts
System should be self calibrating – edge polarization
angle is determined by toroidal current and PF coils –
other angles are referred to the edge.
(alleviates issues with thermal drifts, window Faraday
rotation, in situ calibration problems etc.)
Ramp up
Edge
Axis
Axis
Edge
Common mode noise structures from
beam-into-gas calibration have been removed
The imaging spectro-polarimeter encodes both
ellipticity and orientation
Image of 660nm lamp
transmission through a
polarizer followed by a wave
plate
Image of 660nm lamp
transmission through a
polarizer
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Plasma images show strong ellipticity
Orthogonal carriers
Ellipticity
Beam direction
Typical raw image of beam emission
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Ellipticity images
Beam emission images show larger than expected ellipticity
Beam into gas
Beam into plasma
85 keV
80 keV
Beam into gas
Ellipticity unlike QM
model. Window
linear birefringence?
Dependence on
beam energy
indicates other than
some B-dependent
optical effect.
Attributes of MSE imaging approach
 Analyse full multiplet so no need for narrowband filters
 Simple inexpensive instrument - No filter tuning issues or incidence angle
sensitivities
 Tolerant of beam energy changes (10-20%)
 Higher light efficiency ?
 Multiple heterodyne options, single channel or imaging
 2D toroidal current imaging (in principle) - Possibility of synchronous imaging of
sawteeth, MHD, ELMs, Er etc.
 Insensitive to “broadband” polarized background contamination
 Insensitive to non-statistical populations
 Full Stokes polarimetry  Possibility of self calibration based on unpolarized
plasma radiation (Voslamber 1995) mirror/window degradation
 Fringe phase shift gives 4y where y is the polarization tilt angle.
 Can be applied to spectrally complex elliptically polarized multiplets (Zeeman
effect)
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Conclusion
 Doppler Coherence Imaging systems can be used to
extract 2d images of plasma flows and temperature
 Imaging spectro-polarimeters utilizing spatial heterodyne
encoding can encode both Doppler and polarimetric
information
 Modeling indicates that imaging MSE should be a
reliable tool for obtaining 2d maps of the internal
magnetic field in tokamaks.
 IMSE significantly increases the information available to
infer the current profile.
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