Subject 
Brief discussion 
ALMA/Rau automatic editing 

uvdata automatic editing 

Automated RFI excision 
Impementation and extension of RFI excision algorithms. 
Example: A new approach which identifies and excises RFI in interferometric data using the fringestop pattern introduced by the correlator. This postcorrelation, offline scheme has been implemented for GMRT data. This concept is of general use and may be applied to excise RFI in data from any interferometer. RamanaAthreya 
Wideband, narrowfield imaging of isolated sources 
This corresponds to wideband imaging of area covering a relatively narrow field of view around the center of the antenna PB at the highest frequency. In this, errors due the frequency scaling of the PB and its rotation on the sky with Parallactic Angle (time) are minimized. 
The MSMFS algorithm (Rau, 2009), which can be configured to the simpler case of SaultWieringa MFS (Sault & Wieringa, 1994) algorithm where appropriate, is sufficient for this. In some (many?) cases, post deconvolution correction for wideband PB will be sufficient. SanjayBhatnagar 
Wideband, narrowfield imaging of confused sources 
This algorithm is an extension of Rau's MSMFS. The difference is that before running Rau's routine we make a narrowband image cube and clean it. Then outside of some radius R, specified by the user, we subtract all the clean components from the uv data in each narrowband. This way we remove all the strong sources far out in each narrowband FOV and can run Rau's algorithm on what is left inside of radius R. For example, R might be the FWHM at the highest frequency. Using this approach we should be able to image perhaps a quite large field but we need to test the limits of this algorithm. It seems very likely it will improve the "narrowfield" imaging and perhaps allow rather widefield to be imaged. SanjayBhatnagar 
Wideband, widerfield imaging 
For frequency spread of >10% imaging beyond approximately inner 10% of the PB, residual errors due the frequency and time dependence of the PB become significant. Errors due to frequency scaling of the PB and time dependent errors due to antenna pointing errors and rotation of the PB with Parallactic Angle (PA) are maximum at the halfpower point of the PB1. Therefore, for wideband continuum imaging of fields wider than the inner 10% of the sensitivity pattern, integration of the MSMFS algorithms with the AProjection algorithm is required. SanjayBhatnagar 
Full sensitivity, full beam wideband imaging 
Full sensitivity imaging, particularly at lower frequencies will require image deconvolution out to at least the first side lobe and correcting for time variable antenna pointing errors. SanjayBhatnagar 
Widefield, imageplane, instrumental polarization correction 
In order to correct the fullfield, instrumental polarization to fist order, this algorithm will 1) calculate the mean fullfield instrumental polarization from a model averaged over the observed Parallactic angles for Q and U, then 2) multiply this correction by the observed total intensity image and 3) subtract the resulting correction image from the observed, uncorrected Q and U images. SanjayBhatnagar 
Faraday Rotation Synthesis Imaging 
The algorithm of Brentjens & de Bruyn, (2005) is implemented using observed Q and U cubes and the resulting 3D imaged cleaned to produce an estimate of Faraday depth in each pixel. LeoniaKogan 
More sophisticated approaches to bandpass calibration 
Currently this is mostly done with estimating the antenna/datapath specific complex gain on a channelbychannel basis from observations of a very strong source. The actual function with frequency is much better behaved and some sort of functional representation may allow using weaker sources and/or give better results. Also, time variable. 
The instrumental (spurious) polarized response to unpolarized emission is a function of frequency and needs a better way of characterizing than broadband averages. Can/should this be incorporated into bandpass calibration? 
An efficient way of parameterizing (and modeling if possible) the antenna power pattern as a function of frequency. An efficient way of parameterizing (and modeling if possible) the antenna polarized response as a function of frequency. BillCotton 
Generalized pixel representation with (orthogonal) functional dependence on frequency 
What is the appropriate representation of a pixel in a broadband continuum image? Some representation of the spectrum (spectral index, curvature...) is necessary. Expansion of ln(flux) in powers of ln(nu) is traditional for overall spectra but this is not well adapted to imaging. An orthogonal basis set could be of great benefit in imaging. There needs to be a single parameter that can be used as a proxy for brightness in the traditional representation. 
The linearly polarized emission (Q + jU) in a pixel is even more complex than the spectrum of a pixel as the "polarization angle" is also a function of frequency. A single Faraday screen imparts a ramp in polarization angle proportional to lambda^2 but a complex emission/transmission case can have a more complicated behavior. Some paramaterized way of representating this behavior per pixel is needed. It would be best if this were related to the solution to the pixel Stokes I spectrum problem. BillCotton 
Full Stokes wideband narrowfield imaging 
FullStokes imaging close to the center of the PB, where direction dependence of the PB polarization is relatively weak. This will involve extending the MSMFS algorithm to the fullStokes case. SanjayBhatnagar 
Full Stokes wideband widefield imaging 
As in the case of StokesI imaging, this is the final goal and will involve integration of algorithms to correct for direction and time dependent polarization effects with MSMFS algorithm. This will probably also require incorporating Faraday Rotation Synthesis. SanjayBhatnagar 
Widefield spectral polarimetry imaging 

Pointing/primary beam corrections 

High dynamic range imaging, wideband 
In addition to the corrections for the direction dependent gains varying with time and frequency, high dynamic range imaging will also require algorithms for better modeling of complex emission as well as accounting for pixel quantization errors for compact emission. Conventional deconvolution algorithms (CLEAN and its variants and MEM and its variants) model the sky in the pixel bases. This fundamentally ignores coupling between image pixels in images with extended emission and the fact that even compact emissions may not be centered on an image pixel. Both these problems lead to residual deconvolution errors which limit the highest achievable imaging dynamic range. Several algorithms which model the sky in a scalesensitive basis have been recently developed. Most promising of them are the AspClean and the MSClean algorithms. Note that in principle some approaches to multiscale deconvolution can also correct for the pixelation errors (Voronkov & Wieringa, 2004). An alternate approach based on mutlifacet imaging to correct for pixelation errors also exists (Cotton & Uson, 2008). While the MSClean algorithm exists in CASA, AspClean algorithm has not yet been ported from AIPS++. 
This involves extending the multiscale deconvolution techniques for scalesensitive modeling of the emission along the frequency axis as well. Runtime efficiency of the available algorithms for large data volumes will be the crucial parameter to determine the optimal algorithm to use. SanjayBhatnagar 
High dynamic range imaging, directiondependent calibration 
Achieving high imaging dynamic range depends on calibration and correction for direction dependent errors. Since it is nearly impossible to measure these direction and time varying gains at the required accuracy and time resolution, algorithms to solve for these effects will be required. SanjayBhatnagar 
Maximum Entropy, other deconvolution algorithm improvements 

Mosaicking 

Corrections for ionospheric effects 

Rotation Measure Imaging 

3D Source Cataloging 

3D Visualization 

Specialized algorithms, e.g. recombination line stacking 

Weak feature detection in large spectral cubes 

Spectral dynamic range improvement for faint absorption detections 

Utility to analyze spectral line data cubes containing multiple chemical species with multiple transitions 

Improved techniques for estimating a time series in phase/group delay 
This is a critical component of phase (astrometric) calibration. The current technique is to estimate these independently in a series of "solution intervals" which may later be smoothed. Direct estimation of a time series functional form could force continuity and possibly other physical constraints which could improve the quality of the representation at high SNR and allow using lower SNR data for calibration. BillCotton 
Enhanced multifacet CLEAN 
It is possible to align the facets such that all the pixels are on a common grid, i.e, the pixels themselves are aligned. This allows multiple facets to be used in a common minor cycle CLEAN. The dirty beams of adjacent facets are close enough that the dirty beam of one will allow approximate subtraction of the response of a source in one facet from adjacent facets. Thus, all facets with significant emission can be CLEANed in a single major cycle; this allows a major reduction in the number of major cycles (I/O) and more opportunities for parallelization. 
The primary benefit of this should be a major performance increase. The potential payoff is large enough that it's worth a fair effort. I've started looking into it but haven't gotten far enough that I'm either really confident it will work (are the increased(?) W distortions managable?) or that I can predict the total amount of effort. BillCotton 