• Project 550: Applications of Matched Filtering for Improved Image Fidelity and Automated Line Identification

• Reviewer 5

Grade: 4

550 Applications of Matched Filtering for Improved Image Fidelity and Automated Line Identification

1. Alignment with NA ALMA Partnership strategic goals;

The proposed study had the potential to increase the return from future data as well as the ALMA science archive. I think that the matched filter for spectral line identification holds the most promise to be broadly useful to the community. The adaptive visibility weighting scheme also appears interesting and can boost the S/N in datasets. However, I am concerned that this adaptive weighting scheme will only be useful in very specific and controlled circumstances. Moreover it will only increase image fidelity when the source structure is known. The source structure cannot be known until the source is modeled, which requires uv-plane analysis and analysis in the uv-plane is always going to be superior to image-plane analysis.

2. Strength of the scientific case for the proposed ALMA upgrade concept; Comment on the relevance to the ‘ALMA 2030’ development documents.

If the ALMA bandwidth is broadened and the correlator capacity increased to handle the broader bandwidth at high spectral resolution, the matched filtering aspect of the proposal would be very important for exploiting these data produces.

3. Quality of the upgrade conceptual design;

The conceptual design for the spectral line matched filtering is excellent. The adaptive weighting is less well-defined and it would have been helpful to demonstrate its effectiveness on sources other than proto-planetary disks to show its general utility.

4. Readiness for production in the context of the ALMA Development Plan (the aim is to support a range of upgrades including both those which can be implemented rapidly and those requiring longer-term research and development);

Both aspects of the proposal have already gone through a proto-typing stage at the PI institute and look to be ready for attempted implementation into CASA. The main effort will be the integration of these techniques into CASA for general use.

5. Strength of the consortium organization (if applicable);

The consortium is excellent with broad expertise in astrochemistry, the author of the adaptive weighting and spectral line identification software, and CASA/interferometry experts at NRAO that can aid in the implementation of the software.

6. Qualifications of the key personnel of the Study;

Same as comment 5, these are among the most competent scientists in the field in terms of background and technical expertise.

7. Technical expertise, past experience (also in series production, if relevant) and technical facilities in the Institutes taking part in the Study;

CASA/interferometry experts at NRAO are included in the proposal and all relevent personnel are highly qualified to undertake this project.

8. Assessment of the level of risk inherent in the design;

The matched filter for spectral line identification has very little risk associated with it. The main degree of risk is how well the tool can be integrated into CASA and tested on the timeline of the project, but this is mitigated by the expertise of the team. There is already a standalone prototype, so the proposers are not starting from scratch.

The adaptive weighting scheme carries a moderate risk in my opinion, as I noted above, it is likely that this scheme is only applicable under very controled circumstances and it only pertains to increasing the S/N of deconvolved images. Since the main benefit is in the image plane, modeling efforts will not be helped with the additional S/N boost because modeling should be done in the uv-plane. Moreover, modeling must be done in order to construct the adaptive weights making the methodology a bit circular. The proposed method will make better images, but will not enhance the ability of investigators to constrain physical structures. Also, not many types of astrophysical objects have such well-defined structure that a scheme like this would be useful and there is a perhaps a danger in assuming that one knows their source structure apriori as this will add a bias to the resultant deconvolution process.

9. Strength of the Scientific Team supporting the Study;

See comments 5,6,7; the team is excellent, no weaknesses.

10. Level of support guaranteed by the Institutes;

Institute support is sufficient, main requirements are computing.

11. Budgeted cost of the Study;

The budgeted cost is quite reasonable, supporting the salary of the science lead and travel to NRAO sites to work with experts on implementation.

• Reviewer 7

Grade: 3

Title: Applications of Matched Filtering for Improved Image Fidelity and Automated Line Identification

1. Alignment with NA ALMA Partnership strategic goals; This proposal aligns with the strategic goals ● 1. Improve and extend technical capability by developing and implementing new software and computing technologies that improve and extend capabilities for scientific research (1.2) ● 5. Strengthen the North American Radio Astronomy community by training a PhD student (and later postdoc) who is expected to contribute to the field ( 5.2)

2. Strength of the scientific case for the proposed ALMA upgrade concept; Comment on the relevance to the “ALMA 2030” development documents. The adaptive weighting scheme has broad application to nearly all ALMA data and could become the default weighting scheme for imaging. Matched filtering has application to sources with many spectral lines. In Figure 2, they show a doubling of SNR using their adaptive visibility weighting scheme. While this is impressive, they do not address the apparent artifacts (black spots) in the adaptive weighting image. Where do these come from? What (negative?) brightness level are they at? Is this commonly seen in adaptively weighted images. They use the phrase “Line Identification” when what they really mean is Line Detection. Securely identifying a detected line can be much harder than finding the emission in the cube. The proposal has potential relevance to Roadmap goal 1. Improvements to the ALMA Archive: enabling gains in usability and impact for the observatory. If the delivered software were accepted as part of the ALMA pipeline or ADMIT, then the data products would be available in the archive.

3. Quality of the upgrade conceptual design; Concept is straightforward and well-explained, the authors have already done a lot of background work as part of Loomis’s PhD thesis, so they understand the problem well. The potential creation of science ready/value-added data products for the archive is good, and the identification of a potential connection with ADMIT signals the authors are aware of other related work coming out of this program. They don’t really discuss how they determine what the best match filter is to begin with. They assume a matched filter exists, and will develop the software and techniques to apply that filter to ALMA data cubes. Seems to me that discovering the optimal kernel is the hard part.

4. Readiness for production in the context of the ALMA Development Plan (the aim is to support a range of upgrades including both those which can be implemented rapidly and those requiring longer-term research and development); The investigators will produce CASA software that could be brought effectively into the mainline CASA development if assigned priority and resources.

5. Strength of the consortium organization (if applicable); NA

6. Qualifications of the key personnel of the Study; Investigators have experience with ALMA, JVLA and GBT data and science, as well as state of the art knowledge of visibility weighting schemes. Highly qualified.

7. Technical expertise, past experience (also in series production, if relevant) and technical facilities in the Institutes taking part in the Study; NRAO personnel involved have relevant expertise and experience.

8. Assessment of the level of risk inherent in the design; Risk is low. Investigators have already done a lot of work as part of Loomis PhD thesis.

9. Strength of the Scientific Team supporting the Study; See #6

10. Level of support guaranteed by the Institutes; NRAO staff are providing reasonable consulting support.

11. Budgeted cost of the Study; Comparatively low cost with delivery in only 7 months.

• Reviewer 9

Grade: 2.5

Title: 550 - Applications of Matched Filtering for Improved Image Fidelity and Automated Line Identification

1. Alignment with NA ALMA Partnership strategic goals;

Directly aligns with goals 1.2, 3.2, 4.2, 5.1, 5.2

2. Strength of the scientific case for the proposed ALMA upgrade concept; Comment on the relevance to the ‘ALMA 2030’ development documents.

The proposal directly addresses the recommended development path on “Improvements to the ALMA archive.” The proposed work will lead to better imaging performance, better line identification, and better continuum subtraction. Some of these can be directly implemented into the science-ready data products archived by ALMA, while others will enhance the quality of the “value-added” data products. There is some potential that this proposed work will even improve the observing efficiency of ALMA, as the new weighting scheme may routinely allow higher S/N to be achieved for a fixed observing time, or a decreased required observing time for a fixed S/N..

3. Quality of the upgrade conceptual design;

Overall very strong. A clear plan of work is presented. The time and cost estimates all seem reasonable. The scope of the work matches the scope of the science case. The plan to produce example CASA codes increase the long-term value and use of the proposed work. There are some risks that are not fully acknowledged, but they are overall minor (see below).

4. Readiness for production in the context of the ALMA Development Plan (the aim is to support a range of upgrades including both those which can be implemented rapidly and those requiring longer-term research and development);

This project is in an intermediate stage - it will build on existing work in order to identify and develop processing and analysis routines that can be incorporated into the CASA environment.

5. Strength of the consortium organization (if applicable);

N/A.

6. Qualifications of the key personnel of the Study;

Very strong. The team has the expertise and experience necessary to carry out this project. The scientific lead is a graduate student whose advisor is PI, and this student has already developed the software on which the proposed work is based.

7. Technical expertise, past experience (also in series production, if relevant) and technical facilities in the Institutes taking part in the Study;

See #6 above.

8. Assessment of the level of risk inherent in the design;

There is some inherent risk to this project. The project is centered around assessing the general applicability of a new imaging scheme, and a new line identification method. Both have already been shown to be highly successful, but in the limited case where the source is a protoplanetary disk with a position and velocity structure that is very well known. It is unclear how generally applicable these methods may be, and indeed there is some risk that one of the outcomes may be that they are not very generally applicable. However, this is likely a low probability outcome as these methods are likely applicable in at least some other cases. Furthermore, the advantages to these methods are clear, and thus identifying exactly what types of sources would benefit from them is worth pursuing.

9. Strength of the Scientific Team supporting the Study;

See #6 above.

10. Level of support guaranteed by the Institutes;

No comments of significance.

11. Budgeted cost of the Study;

The costs appear reasonable and appropriate.

• Reviewer 10

Grade: 5.0

Title: Applications of Matched Filtering for Improved Image Fidelity and Automated Line Identification (Oberg)

Summary: This proposal seeks to expand on two algorithmic innovations that will enhance the quality of science-ready data products from ALMA: i) a new adaptive gridding weighting scheme that uses prior information regarding the source model; and ii) automated spectral-line detection using matched filtering in the uv-plane. Proven versions of these algorithms will be migrated to CASA.

1. Alignment with NA ALMA Partnership strategic goals;

This proposal aligns most closely with the following NA ALMA strategic goal: • (1.2) Improve and extend technical capability by exploring, developing, and implementing new software and computing technologies that improve and extend capabilities for scientific research.

2. Strength of the scientific case for the proposed ALMA upgrade concept; Comment on the relevance to the ‘ALMA 2030’ development documents.

The scientific case for an innovation to Brigg’s adaptive gridding weighting is higher quality interferometric imaging for the case when an a priori source model is known. However the improvements in nominal dynamic range, as shown in Figure 1, are not large, nor is that unexpected.

The matched filter line detection approach using visibility-plane data addresses a key question in the general scientific exploitation of ALMA spectral-line data cubes, and will have broad scientific applicability.

The proposal is most closely aligned with the improvement in science exploitation of rich ALMA data products described under archive enhancements in the ‘ALMA 2030’ roadmap.

3. Quality of the upgrade conceptual design;

A proposal strength is that it will explore two innovations in data analysis that offer the promise of improving the quality of ALMA science-ready data products. The proposal could be strengthened by a clearer acknowledgement that both methods proposed add a priori information regarding the source model, so there is an implicit trade-off between the bias that introduces and the decreased variance in any resulting estimation (either in imaging or line parameters).

For adaptive gridding weighting, the discussion in the final paragraph of Section 4.1 suggests that an optimal a priori source model estimation method will be determined from uv-plane model fitting, or more conventional interferometric image formation in order to address this issue. This is somewhat circular, but also ignores a very long history regarding the performance of both methods of source model estimation that is already known.

The authors are completely correct that matched-filter estimation is optimal is the signal is known, but again this a priori information regarding the source model (or visibility counterpart) is not known with that degree of certainty. Estimation using matched-filtering with an incorrect source model may yield false detections.

4. Readiness for production in the context of the ALMA Development Plan (the aim is to support a range of upgrades including both those which can be implemented rapidly and those requiring longer-term research and development);

The authors have a python prototype implementation for immediate further research exploration. The transition to CASA will not be difficult for either algorithm, as narrowly defined, but the work at the end of Section 4.1 is less close to production.

5. Strength of the consortium organization (if applicable);

The consortium is well organized.

6. Qualifications of the key personnel of the Study;

The personnel are well-qualified for this study.

7. Technical expertise, past experience (also in series production, if relevant) and technical facilities in the Institutes taking part in the Study;

The institutional expertise and experience is completely adequate.

8. Assessment of the level of risk inherent in the design;

There is little risk in exploring the adaptive weighting innovation or the matched-filter line detection method. WBS 1.3 “Investigate multiple methods of source structure estimation for implementation” is way beyond the scope and not well-defined.

9. Strength of the Scientific Team supporting the Study;

The scientific team is excellent.

10. Level of support guaranteed by the Institutes;

There is no external contribution.

11. Budgeted cost of the Study;

The budget is appropriate for the python exploration of adaptive gridding weighting and matched-filter line detection, and incorporation of the gridding weighting in CASA with NRAO assistance. I believe the remaining scope of work is beyond the scale of the budget.

-- AlWootten - 2017-07-19