1. De-biasing interferometric visibilities in AMBER/VLTI data of weak sources
G. Li Causi1, S. Antoniucci2;1, E. Tatulli3
1 INAF-Osservatorio Astronomico di Roma, Via di Frascati 33, I Monteporzio Catone
2 Universit`a degli Studi di Roma ‘Tor Vergata’, via della Ricerca Scientifica 1, I Roma
3 INAF-Osservatorio Astrofisico di Arcetri, Largo E. Fermi 5, I Firenze
Our work begins with our mid resolution AMBER observations of the Young Stellar Object ZCMa, namely the primary IR component of this binary system “ZCMa A”, which took place in January 2006 wiht the UT1, UT2 and UT4.
Here you see an image showing a temporal sequence of what is registered in the interferometric channel for the Calibrator, on hte left, and the Target, on the right.
We can clearly see fringes on the Calibrator, bu it seems that we didn’t get fringes on the target.
FRINGES
FRINGES ?
Calib (HR2379_B02, 1.75mas, K=2.24)
Target (ZCMa A, K~4.2)
21th Jan 2006, UT1-UT2-UT4, AMBER 2.16µm, 50ms integration, seeing~0.6”; proposal: 76.C-0817 by Nisini B., Antoniucci S., Li Causi G. et al.
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

2. FRINGES ! Why? Are there FRINGES on the target? Hypotheses:
...FRINGES ARE NOT FORMED: the target has INTRINSIC NULL VISIBILITY (i.e. it is very large) FIBERS ARE NOT CENTERED on the target fringes do not form because of MALFUNCTIONS (vibrations, etc.)
...FRINGES ARE FORMED: but they are UNDER THE NOISE because the FLUX IS TOO LOW but the EYE CANNOT SEE THEM but they are HIDDEN BY ARTIFACTS
 FRINGES ARE THERE, as we can see by means of an enhanced elaboration (Fourier filtering on deviations from local median; we’ll see better in the following)
...but, if we do amdlib Extraction (amdlibComputeSpectralCalibration, amdlibComputeP2vm, amdlibExtractVis –b 1000), we obtain mean calibrated vis of:
1.14 +/  meaningless !
0.81 +/- 0.09
0.58 +/- 0.09
Why?
We could made some hypotheses to explain why we do not see fringes:
Fringes are not formed because of what is written
Fringes are formed but we do not see them because of what is written.
The real situation is that fringes are there, as we can see with a proper enhancement: we clearly see that there are at least two fringe patterns.
But, if we run the amdlib extraction with –b 1000 we get a meaningless visibility for baseline 1.
Why?
FRINGES !
Target (ZCMa A) enhanced
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

3. spurious peaks interference peaks
Let us have a look at the Fourier power spectrum of the interference channels:
spurious peaks
B1 
B3 
B2 
DC 
interference peaks
Looking at the average Power Spectrum of the interferemce frames for the Calibrator and the Target we recognize the 3 baselines peaks and the continuum peak at zero frequency, but we also notice some extra power in the indicated locations.
The strange thing is that we found exaclty the same extra peaks in the power spectrum of the interference channel of the Dark and in the power spectrum of the photometric channels of all of them! Even in the power spectrum of the DK channel shows the same spurious peaks!
Note that the brightest artifacts fall on the same spatial frequency of baseline 1: this is the reason why amdlib extracts a wrong visibility !
Target photometric channel
Calibrator average power spectrum
Target (ZCMa A) average power spectrum
Dark average power spectrum
There are spurious peaks, which means spurious fringes in the image frames, even in the Dark and even in the masked DK channel !
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

4. Hence  the fringes found in the Target are spurious !!
We can see that the enhancement of one photometric channel of a dark, where we don’t expect fringes at all, shows lots of fringes, with the same period and inclination as those in the Target:
We can see these spurious fringes if we enhance the sequence of one photometric channel of a Dark frames, i.e. the last place where we expect to find fringes.
We see lots of fringes! And with the same period and inclination of those we’ve found on the Target !
But this means that the fringes found in the Target are spurious !
Dark P2 channel - original
Dark P2 channel - enhanced
Hence  the fringes found in the Target are spurious !!
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

5. Removing the artifact:
Such spurious fringes are possibly caused by electromagnetic interferences on the detector itself.
Perhaps they could be removed by hardware, however current and past observations are corrupted.
So we have to remove them by software.
NOTE: the artifact is not removed by the normal Dark frame subtraction because the fringes have random phases.
Our approach:
compute averaged power spectrum from all the Dark frames;
identify artifact peaks in the frequency plane and make a binary mask for each channel;
Compute power spectrum of each target frame and replace realistic power estimation to the masked regions;
reconstruct corrected frames by inverse FT;
re-write the AMBER fits files
redo all the process for any fits of the observation, including WAVE_3T, P2VM, Calib, Target, Sky and Dark themselves, re-computing the mask from their respective Dark frames
After this pre-processing, launch the amdlib standard processing on the corrected files.
So, how can we remove this artifact ?
It is likely caused by some electromagnetic interference on the detector, so that it should be removed by hardware. Anyway, past and current observations are corrupted, so we have to remove it by software.
Our approach follows these steps: ---> click the red buttons
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

6. 1. Compute averaged power spectrum from all the Dark frames:
At first, we compute the average power spectrum from the Dark frames relative to the different types of data (i.e. Dark of sources, Dark of P2VM Calibration, Dark of Spectral Calibration etc.) in all their channels (interferometric, photometric and DK).
We see in these examples that the artifact pattern is always present.
Dark of Calib, Sky and Target interf and phot channels
Dark of Calib, Sky, Target DK channel
P2VM Dark interf and phot channels
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

7. 2. Make a binary mask for each channel:
We make a binary mask which identifies the artifac peaks (we use a sigma threshold and the simmetry of the power spectrum to do this).
We will use this mask to identify the frequency regions to correct.
MASK for Dark, Calib, Sky and Target interf and phot channels
MASK for Dark, Calib, Sky, Target DK channel
P2VM Dark interf and phot channels
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

8. Peaks are replaced by sigma-clipped average on each column
3. Replace realistic power estimation to the masked regions:
baseline 1 SIGNAL
Using the masks we replace the corrupted frequency regions with the sigma-clipped average along the frequency columns, which we assume as a good estimate of the un-corrupted power under the artifacts.
Now the only peaks in the inteference channels are the baselines signals and no peaks are finally present in the dark spectrum.
We see now in the Target power spectrum a clean baseline 1 peak !
Target (ZCMa A)
Peaks are replaced by sigma-clipped average on each column
Calib Target (ZCMa A) Dark
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

9. spurious fringes real fringes
4. Reconstruct corrected frames by inverse FT: Target
 Compare enhancements
spurious fringes
real fringes
If now we reconstruct the single frames by an inverse Fourier Transform and we enhance the image as done before, we clearly see that the spurious fringes are removed and the real baseline 1 fringes appear !
Target (ZCMa A) - original
Target (ZCMa A) - corrected
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

10. no residual spurious fringes
4. Check the residuals on Dark P2 channel
 Compare enhancements
spurious fringes
no residual spurious fringes
To be sure that this is not an artifact of our software, we checked that the same procedure applied to the proviously shown Photometric channel of the Dark doesn’t show up any residual fringe.
Dark P2 channel - original
Dark P2 channel - corrected
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

11. 0.81 +/- 0.11  now less than unity!
Now we launch the standard amdlib processing on the corrected files:
amdlib Extraction (amdlibComputeSpectralCalibration, amdlibComputeP2vm, amdlibExtractVis –b 1000), we obtain mean calibrated vis of:
0.81 +/  now less than unity!
0.87 +/- 0.09
0.63 +/- 0.09
At thi point, we can run the standard amdlib processing on the corrected frames. We noe get a baseline 1 visibility less than one.
More, if we run CheckDataQuality we see that we have increased the SNR of a factor of 5, as we see from the piston plot or the banana plot before and after the correction.
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

12. We also see that the dispersion of instrumental visibility among the files is reduced:
Calib - original
Calib - corrected V2 V2
We also see that the dispersion of intrumental (i.e. un-calibrated) visibilities among the files is reduced both for the calibrator and the target.
file #
file #
Target - original
Target - corrected
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

13. We applied the same pre-processing also to an observation of FU-ORI (magK=5.15, calib HD42807 magK=4.85) and we found a similar improvement in the SNR and visibility dispersion.
If we put all the observations together we see how the artifact damage increase with decreasing coherent flux, with different behaviours for the first baseline and the other two.
The same procedure has been applied to the FU-ORI observations of Eric and we’ve found the same improvement in SNR and in visibility dispersion.
If we made a plot of the instrumental squared visibility correction as function of the source magnitude, we notice that the artifact makes more damage as the sources become fainter, up to a 50% error for limiting magnitude targets.
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

14. http://www.mporzio.astro.it/~licausi/ADC/ Software availability:
The software that we have developed to perform the described pre-processing, which corrects the detector fringe artifact, is available at the following web address:
We’ve made a web page for you to download our software, which we will made available to the community, so that you can pre-process your data in order to better understand how visibilities are affected by the artifact. We are curious to know about your results.
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

15. SOME TECHNICAL NOTES:
Our filtering must be applied to frames already corrected for bad-pixels: in fact bad pixels translate into noticeable power offsets at all frequencies. Due to the fact that we replace the power but we cannot restore the phase, these offsets prevent to remove the artifact fringes because the offsets power themselves are assigned to the artifact phases. Thus our method only works when the median power is near the noise level, that is when bad pixels are removed. In practive, we perform a sigma-filtering on the frames before to apply the correction. Another way could be to apply our program on the amdlibRawCalibrate output, i.e. the frames already corrected by bad pixels, flat, dark and sky, then to run amdlibExtractVis on the corrected fits using a dummy unity flat with no dark and no sky.
Our analysis of the extracted visibilities, of both the original and corrected files, shows that the real visibility dispersion across the files is underestimated by ExtractVis with default parameters, while the –e THEORIC parameter provides a correct error estimate. We have checked this on the dark files, before and after correction of detector artifact: the default extraction provides errors not compatible with the expected null visibility, while the –e THEORIC setting provides a V compatible with zero.
Some technical notes:
We must apply the correction to already bad-pixel corrected frames, in order not to get a wrong result;
we notice that the visibility dispersion among the files are underestimated by the default settings of ExtractVis, while the –e THEORIC parameter gives more realistic errors. The default estimate of ExtractVis even doesn’t give a V compatible with zero if we extract a Dark frame, while we get this with –e THEORIC.
We don’t know why, point 2) is not true with FU-ORI data, for which –e THEORIC gives highly over-estimated errors....
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006

16. Do we get scientific results?
Our corrected and calibrated visibilities still do not seem to be scientifically meaningful (but we’ve not used frame selection yet):
baseline 1, the shortest, shows a V less than the other baselines, which is not easily modellable;
the value of V2 for baseline 1 is not compatible with observations of Keck Interferometer, published in the literature (Monnier et al. 2005, ApJ 624, 832).
Anyway, the story of low flux targets seems not yet come to an end.
In fact, our corrected and calibrated visibilities still shows values not easily modellable and not compatible with the Keck observations, published in the literature.
We do not know why this happens.
Keck b1 b2 b3
Gianluca Li Causi – INAF, Rome Astronomical Observatory - - Grenoble, 30th Nov 2006