The Additional Representative
Images for Legacy (ARI-L)
Development Project- Exploiting Archives for Radio Astronomy in the SKA-era
15th december 2020 - M. Massardi

THE ALMA Science Archive in the ALMA 2030 roadmap...the ALMA Science Archive will become the primary source for
an increasing number of publications. The ability to efficiently
mine the archive contents is therefore vital for the communityand ALMA’s future...

Mining efficiency affects the science exploitation efficiency

The ALMA Science Archive from a miner perspective

THE ASA IS A GOLD MINE
- 3348 projects observed and archived
in 8 observing cycles- data are already calibrated- not all the possibilities have been exploited- archive will keep growing

BUT- dataset are big (>100MB in some cases)- images available are made for quality assurance= incomplete (<10 % in Cy 0-4,
better in later cycles, thanks to pipeline)= inhomogeneous across cycles= not easily comparable- to understand scripts users need interferometry
induction/skill (luckily there are the ARC nodes)- to run scripts CASA is needed (old versions …)

The ASA tools need images: ASA previews

The ASA tools need images: JVO

Image analysis tools(Burkutean et al. 2018)

Science needs images!

Statistical analysis requiring many datasets
are impossibly time comsuming(see the timeline of J0635-7516, calibrator
In hundreds of projects)
Images in the archive are incomplete andNot representative of the data content(see the comparison of published andarchived spectra for a pre-stellar object)
Science exploitation need complete,homogeneous, and easily accessible images

THE ARI-L DEVELOPMENT PROJECTThe “Additional Representative Images for Legacy (ARI-L) in the ASA”
project will produce and ingest into the ASA a set of additional image
products representative of the whole data content for more than 70% of
the observing projects in cycles 2-4 that can be processed through theALMA Imaging Pipeline, to complement the QA2-generated images.
In addition calibrated MS of the processed dataset will be released too.
The ARI-L philosophy:- THINK OF THE MINERS: we will produce imaging products highly relevant for
all science-cases and enhance the possibilities of exploitation of archival dataalso to non-expert data-miners,- HOMOGENEITY we shall provide a homogeneous view of archive data content
within ARI-L and wrt the following Cycles to compare datasets and to make amore conscious download selection,- COMPLETENESS we rate the 70% goal on the number of MOUs but we will try
to complete as many projects as possible to complement the ASA resources,- ADD VALUE TO THE ASA we aim at providing additional products that willcomplement and add value to the ASA, hence we have the responsibility ofthe quality of what we deliver to be ingested.

QUARANTINED

THE ARI-L
WORKFLOW
The PROJECTARI study:: action
items and open questions

Deliver images toESO
Store MS to
INAF-IA2QUARANTINED

THE ARI-L
WORKFLOW
The PROJECTARI study:: action
items and open questions

Deliver images toESO
Store MS to
INAF-IA2

THE ARI-L
PIPELINE& PRODUCTS
The PROJECTARI study:: action
items
and open questions
ALMA Pipeline became available for imaging in Cycle 4 (2017).
Later cycles are mostly imaged with the pipeline, but features became moreand more efficient with time: not all the datasets were pipelineable.
Earlier cycles were manually imaged.
When introduced, the pipeline was not commissioned to be back compatible,
so it can be used with earlier cycles but with care: our study demonstrated theranges and conditions of applicability and the rate of success for the pipeline
applied to earlier cycles (Massardi et al. 2018).
We, on first attempt, use the same parameters used in later cycles,
aiming for homogeneity of the archival products.
Hence, like for later cycles we produce in any analyzed MOUS:- 1 aggregated continuum image- 1 mfs image for each spw- 1 cube at the native resolution for each spw
for the phase, bandpass and check source calibrator and for eachscience target (notice that later cycles products include only continuum forcalibrators).

README

GENERAL ON ARI-L

BASIC PROJECT INFO

ARI-L QA NOTESEB INFO: TIME, ARRAY, SPW RANGE & RES., UVRANGETARGET INFO: RA, DEC, INTENT, ID,LAS, ANGULAR RES.

THE ARIQA
3-levels of Quality Assurance:- check that the ARI-L code run was performed correctly- perform a weblog review of the imaging pipeline products- compare ARI-L products with QA2 products on rms, peak flux, dynamicrange, having extracted the portion of the ARI-L products corresponding towhat is available as QA2 products, smooth them to the same resolutions.

CURRENT STATUS: rates

TOTAL MOUS:

672+1719+1085= 3476% of MOUS of each cycle

100

WE ARE NOW ATMONTH 18/36

50>1500 MOUS
ARIQA passed(342Cy4+ 1200Cy3)

June 2020 goal

>85% processing
success rate

20>80% ARIQA successrate

Dec 2019 goal

Successful tests

Cy 4Cy 3

Cy 2>75% overall current
success rate

CURRENT STATUS: delivery

M6: 2434 MOUS JUNE 2022
M5: 1824 MOUS DEC 2021
M4: 1217 MOUS JUNE 2021
M3:608 MOUS DEC 2020

M2:336 CY4M1:

100 MOUS DEC 2019

JUNE 2020

ARI-L PRODUCTS IN THE ASA
The ARI-L products do not modify the current deliverables,
but are included into ASA as “externally contributed products”.
More than 75000 ARI-L images are currently available

ARI-L WEBSITE
https://almascience.eso.org/alma-data/aril

Information for ARI-L products User:

https://sites.google.com/inaf.it/ari-l●

project rationale: why ARI-L●

project details: people, timelines,workflow, user guide●status of the products and project●contact details for support
help-desk@alma.inaf.it

DOCUMENTATION: User Guide

Collection of FAQ for quick recovery ofinformations.
Periodically updated
https://sites.google.com/inaf.it/ari-l/project/user-guide

DOCUMENTATION: first ARI-L paper

Information for general archival User:●

project rationale: why ARI-L●

project activities: what, how, QA●

description of the products and status●

examples of applications(with emphasis on cy4 and cy3 data)

Submitted on nov 1st 2020.
Users of ARI-L products are encouraged to acknowledge this paper.

JUST A FLAVOUR OF ARI-L SCIENCE

Massive star formation in O-type
young stellar object (G345.49+1.47)(PI: Cesaroni)+10 otherspw

The complete spectral coverage of theARI-L cubes shows the rich chemistryof this object, useful to investigate thepresence of Keplerian disks oroutflows and constrain themechanisms of massive starformation.

Massardi et al. subm.

JUST A FLAVOUR OF ARI-L SCIENCE

Massardi et al. subm.

Filamentary structure in star forming regions (PI: Kauffmann).
The QA2 images collects only one spectral line for each spectral windows (as requested to QA2analysts to establish the data quality).
The automasking used by the imaging pipeline exploited in ARI-L extracts structure to higher
significance with respect to the QA2 image.
The ARI-L complete spectrum can identify more spectral features that are present in the data.

JUST A FLAVOUR OF ARI-L SCIENCE
PKS 0635-752

PKS 0521-365

3C273

Massardi et al. subm.

JUST A FLAVOUR OF ARI-L SCIENCE

mom1 of CO(3-2) on SDP9 as published 3 yrs ago
compared with ARI-L momentum

Massardi et al. (2017 vs subm.)

SUMMARY-

The project is in full swing!

-Over 1500 MOUS have already successfully been delivered to theALMA Science Archive-All delivery milestones have been met (well ahead of time)-

Overall success-rate above the target of 70%-

A dedicated ALMA Science Portal page, a website, and a user guide
have been made publicly available-An ARI-L paper has just been submitted.

Please visit:https://almascience.eso.org/alma-data/aril