spire imaging fourier transform spectrometer (fts) pipeline data processing
DESCRIPTION
SPIRE Imaging Fourier Transform Spectrometer (FTS) Pipeline Data Processing. Nanyao Lu (NHSC/IPAC). List of Topics. Overview of SPIRE (FTS) Spectrometer Overview of the FTS Pipeline. SPIRE Spectrometer. - PowerPoint PPT PresentationTRANSCRIPT
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
PACS page 1
SPIRE Imaging Fourier Transform Spectrometer (FTS) Pipeline Data
Processing
Nanyao Lu (NHSC/IPAC)
PACS page 2 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
List of Topics
• Overview of SPIRE (FTS) Spectrometer
• Overview of the FTS Pipeline
PACS page 3 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
SPIRE SpectrometerFourier Transform Spectrometer (FTS): The entire spectral coverage of 194-671 micron is observed in one go!
(SMEC)
(194-313 um)
(303-671 um)
PACS page 4 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Two Bolometer Detector Arrays
194 – 313 microns 303 – 671 microns
Beam = 17”- 21” Beam = 29”- 42”
PACS page 5 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Observing ModesTelescope Pointing
Single Pointing
Raster
Spatial Sampling
Sparse (2 beam spacing)
Intermediate(1 beam spacing)
Full(1/2 beam spacing; Nyquist)
Spectral Resolution High: 0.04 cm-1 (1.2 GHz), R=1290 – 370, e.g., line fluxes.
Intermediate: 0.24 cm-1 (7.2 GHz), R = 210– 60.
Low: 0.83 cm-1 (25 GHz), R = 62 – 18, e.g., dust continuum.
High + Low: Both High and Low scans.
Note: Data sampling at 25μm in OPD; Nyquist wave num. = 200 cm-1
Spectral resolution depends on the scan length
PACS page 6 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
From Interferogram to SpectrumInterferogram
Optical path difference (cm)
Sig
nal (
volts
) FourierTransform
Source Spectrum
PACS page 7 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
List of Topics
• Overview of SPIRE FTS Spectrometer
• Overview of the FTS Pipeline
PACS page 8 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Level 1 products:• unmodified interfergrams• average spectrum (apodized)• average spectrum (unapodized)
Interferograms (stored in Level 1)
Level 0.5 products:• detector time lines • scan mirror time line• house keeping time lines
Spectrometer Pipeline Data Flow
SPIRE Common Pipeline
1. Modify Detector Timelines
2. Create Interferogram
3. Modify Interferogram
4. Fourier Transform
5. Modify Spectra (V → Jy)
6. Spectral MappingLevel 2 product: Spectral Cubes (still under development)
PACS page 9 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
1st Level Deglitching
Remove Electrical Crosstalk
Clipping Correction
Time-domain Phase Correction
Bath Temperature Correction
Cross talk matrix
V(t)
V(t)
V(t)
V(t)
Step 1: Modify Timelines
V(t)
V(t)
Level 0.5 Timelines
Modified Level 0.5 Timelines
Non-linearity Correction
V(t)
Bolometer Nonlinearity Table
Bath temp. corr. product
Time constants
PACS page 10 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
1st Level Deglitching
Remove Electrical Crosstalk
Clipping Correction
Time-domain Phase Correction
Bath Temperature Correction
Cross talk matrix
V(t)
V(t)
V(t)
V(t)
Step 1: Modify Timelines
V(t)
V(t)
Modified Level 0.5 Timelines
Non-linearity Correction
V(t)
Bolometer Nonlinearity Table
Bath temp. corr. product
Time constants
Clipping Correction
PACS page 11 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
1st Level Deglitching
Remove Electrical Crosstalk
Clipping Correction
Time-domain Phase Correction
Bath Temperature Correction
Cross talk matrix
V(t)
V(t)
V(t)
V(t)
Step 1: Modify Timelines
V(t)
V(t)
Level 0.5 Timelines
Modified Level 0.5 Timelines
Non-linearity Correction
V(t)
Bolometer nonlinearity table
Bath temp. correction table
Time constants
PACS page 12 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Create Interferograms
Once time domain processing is complete, the detector signals and SMEC positions can be merged to create interferograms.
The created “unmodified” interferograms are also stored in Level 1 in case users want to do their own interferogram-to-spectrum process.
V(t)
Step 2: Create Interferograms
Level 0.5 Timelines
V(t)
Unmodified InterferogramsV(x)
(Stored in Level 1)
SMEC Positions
x(t')
PointingP(t'')
PACS page 13 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Create Interferograms
Once time domain processing is complete, the detector signals and SMEC positions can be merged to create interferograms.
The created “unmodified” interferograms are also stored in Level 1 in case users want to do their own interferogram-to-spectrum process.
V(t)
Step 2: Create Interferograms
Level 0.5 Timelines
V(t)
Unmodified InterferogramsV(x)
(Stored in Level 1)
SMEC Positions
x(t')
PointingP(t'')
PACS page 14 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Telescope/SCAL/Beamsplitter Correction
Baseline Removal
2nd Level Deglitching
Phase Correction
(Default apodization)
V(x)
V(x)
V(x)
V(x)
Step 3: Modify Interferograms
V(x)
V(x)
(Level 1) Interferograms
Modified Interferogram Products (both unapodized and apodized)
Reference background interferogram
Nonlinear phase calibration table
Norton Beer Order-1.5 function
PACS page 15 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Telescope/SCAL/Beamsplitter Correction
Baseline Correction
2nd Level Deglitching
Phase Correction
(Default) Apodization
V(x)
V(x)
V(x)
V(x)
Step 3: Modify Interferograms
V(x)
V(x)
(Level 1) Interferograms
Modified Interferogram Products
Reference background interferogram
Nonlinear phase
Norton Beer Order-1.5 function
PACS page 16 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Fourier Transform
Apply the Fourier Transform to each interferogram to create a set of spectra for each spectrometer detector.
Step 4: Transform Interferograms
SpectraV(σ)
Modified Interferograms
V(x)
PACS page 17 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Fourier Transform
Apply the Fourier Transform to each interferogram to create a set of spectra for each spectrometer detector.
Step 4: Transform Interferograms
SpectraV(σ)
Modified Interferograms
V(x)
PACS page 18 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Spectral Averaging
Flux Conversion: V->Jy
Remove Optical Crosstalk
V(σ)
V(σ)
Step 5: Modify Spectra
I(σ)
I(σ)
Spectra
Level 1 Spectrum Products
Extended-source case volt-to-Jy factors(both unapodized and apodized)
Detector optical crosstalk matrix
Spectra are all in extended-source calibration at Level 1.
PACS page 19 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Spectral Averaging
Flux Conversion: V->Jy
Remove Optical Crosstalk
V(σ)
V(σ)
Galaxy IC 342: SLW Channel Spectra
I(σ)
I(σ)
Spectra
Level 1 Spectrum Products
Point-source case volt-to-Jy factors
Detector optical crosstalk matrix
PACS page 20 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Spectral Averaging
Flux Conversion: V->Jy
Remove Optical Crosstalk
V(σ)
V(σ)
Galaxy IC 342: SSW Channel Spectra
I(σ)
I(σ)
Spectra
Level 1 Spectrum Products
Point-source case volt-to-Jy factors
Detector optical crosstalk matrix
PACS page 21 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
SpatialRegridding
V(t)
Step 6: Spatial Regridding (Level 1 to 2)
Level 1 Spectra
I(σ)
Level 2 Spectral CubeI(σ)
(Under development)
Level 1 Spectra
I(σ)
Level 1 Spectra
I(σ)
For all observing modes but the sparse spatial sampling mode, for which only a point-source spectrum is given at Level 2.
PACS page 22 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Caveats and Remarks• Noise doesn’t average down as 1/sqrt(n) after about n = 25 repeats
as a result of some systematic fringes.
• Flux calibration is accurate to 10-20% for SSW, ~30% for SLW.
• The background subtraction still uncertain below 25 cm-1 in SLW. So the continuum level could be off significantly there. However, line calibration Is not affected.
• Extended-source flux calibration provided for all detector channels in all observing modes. Additional point-source calibration is provided only for the central detectors (SSWD4 & SLWC3) in the sparse observing mode.
• Lines are usually unresolved, but have side lobes following a SINC function. A SINC function fit is required for total flux.
PACS page 23 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Residual Background in SLW
PACS page 24 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Reprocess your FTS Observations• You probably want to use data processed with the latest
calibration files.
• A modified HIPE 4 pipeline script is available at ~/scripts_readonly/SPIRE/spec/SPIRE_spec_SOF1_pipeline_hipe4_modified.py,
which you can use to reprocess your data with any of the following options:
• Use the latest calibration files (i.e., spire_cal_4_0).• Only process the central detectors (to speed up data
processing & to avoid overloading your computer memory).• Using a user-supplied interferogram for telescope/sky
background subtraction.
PACS page 25 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
Final Spectra are great!
SPIRE FTS SOF1 Pipeline and Calibration Files Trevor Fulton
25
PACS page 26 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
You can play with FTS spectrum of Mrk 231
SPIRE FTS SOF1 Pipeline and Calibration Files Trevor Fulton
26
(Van der Werf etal 2010)
PACS page 27 Nanyao Lu
NHSC SPIRE Data School – Pasadena28th - 30th June 2010
You can play with FTS spectrum of Mrk 231
SPIRE FTS SOF1 Pipeline and Calibration Files Trevor Fulton
27
There are 3 files in ~/scripts_readonly/spire/spec:
>>> Copy the following 2 files fro there to your home directory:SPIRE_spec_SOF1_pipeline_hipe4_modified.pySCalSpecInterRef_CR_nominal_20050222_50002972_average_fourier_ALL_DETS.fits
>>> Copy the following data to your ~/.hcss/lstore/ and then untar it there:50002975.tar