Astro Data Lab

We are happy to share with you the latest developments at Astro Data Lab in this April 2022 newsletter.

New datasets at Data Lab

Astro Data Lab has recently ingested several new and updated survey datasets: the DECam Local Volume Exploration Survey (DELVE DR2), CatWISE2020, and updates to the Rubin/LSST TRILEGAL simulations that include the Magellanic Clouds and binary stars (LSST-SIM DR2).

The Astro Data Lab team has already crossmatched the DELVE DR2 and CatWISE2020 catalogs with our reference datasets: Gaia EDR3 (for astrometry), AllWISE, NSC DR2, unWISE DR1 (for photometry), and SDSS DR16 (for spectroscopy). We have also added a few other useful columns such as nest4096, ring256, and htm9 for Healpix-based and Hierarchical Triangular Mesh (HTM)-based sky tessellation use cases. These pre-crossmatched tables are accessible in the schema browser, and through standard TAP/SQL/ADQL queries like all other catalogs at Data Lab.

The Astro Data Lab team evaluates periodically which external survey datasets we should source, ingest, and serve. We appreciate requests and suggestions from our users. Please contact us at datalab@noirlab.edu to send your request and, if possible, mention an example scientific use case.

DELVE DR2

DELVE DR2 combines new DECam observations with archival DECam data from the Dark Energy Survey, the DECam Legacy Survey, and other DECam community programs. DELVE DR2 consists of ~160,000 exposures that cover ~17,000 square degrees of the high Galactic latitude (|b| > 10 deg) sky in four broadband optical/near-infrared filters (g, r, i, z). DELVE DR2 provides point-source and automatic aperture photometry for over 2.5 billion astronomical sources with a 5σ point-source depth of g=24.3, r=23.9, i=23.5, and z=22.8 mag. DELVE DR2 covers more than four times the area of the previous DELVE data release and contains roughly five times as many astronomical objects. For more information about DELVE DR2, please see Drlica-Wagner et al. (2022).

CatWISE2020

CatWISE2020 is an all-sky catalog of W1 and W2 band infrared measurements from the WISE and NEOWISE surveys, collected between 2010 and 2018. The catalog comprises 1,890,715,640 entries, with a 90 percent completeness depth of W1=17.7 mag and W2=17.5 mag. This dataset includes six times as many exposures and spans over 16 times as large a time baseline as the dataset used for the AllWISE catalog, i.e. the CatWISE catalog includes fainter sources and provides far more accurate measurements of their motions than AllWISE (motions are accurate at the 20 mas/yr level for W1~15 mag sources, and at the ~100 mas/yr level for W1~17 mag sources). The original catalog is accessible from IRSA via Gator (select “CatWISE2020 Catalog” under “WISE/NEOWISE Enhanced and Contributed Products”). The version at Astro Data Lab is identical, but adds the following columns for convenience: htm9, nest4096, ring256, random_id, elon, elat, glon, glat. For a full description of CatWISE2020, please see Marocco et al. (2021).

LSST-SIM DR2

We have added nearly 1 billion new data points for the Magellanic Clouds to our existing LSST SIM DR2 table. The catalog was generated by Leo Girardi and collaborators using their TRILEGAL stellar population code and provides positions, proper motions, and LSST photometry (u, g, r, i, z, Y) for over 11.4 billion simulated stars in the Milky Way and Magellanic Clouds, down to the LSST stacked depth limit of 27.5 mag in the r band. For a description of the TRILEGAL model please see Girardi et al. (2012). Additionally, we have added a new table simdr2_binary to the LSST SIM DR2 schema containing information about binary systems. This table includes columns for both components plus the total system.

Renaming of our GitHub and PyPI to ‘astro-datalab’

Completing the merging of NOAO, Gemini, and Rubin Operations into the NOIRLab organization, at Astro Data Lab we have now also renamed GitHub and Pypi accounts. On both platforms we are now 'astro-datalab'.

On Pypi we host the 'datalab' command line package. The only change here is that now you would install it via:

pip install --ignore-installed --no-cache-dir astro-datalab

And uninstall the old package via:

pip uninstall noaodatalab

On GitHub any of your cloned or forked repositories from https://github.com/noaodatalab/ should continue to work for pulls. If you also want to make pull requests, please update the remote URL of your cloned repository to:

https://github.com/astro-datalab/REPOSITORY.git

or simply make a fresh clone:

git clone https://github.com/astro-datalab/REPOSITORY.git

Please feel free to contact us at datalab@noirlab.edu if you need help with updating any remote URL, or follow the instructions at:

https://docs.github.com/en/get-started/getting-started-with-git/managing-remote-repositories

New Science Example Notebooks

We have added new science example Jupyter notebooks to the Data Lab notebook suite:

1. Stacking SDSS Spectra of Galaxies Selected from the BPT Diagram

This notebook shows how to access and plot spectra of SDSS objects. It also demonstrates how to select emission-line galaxies based on their classification on a BPT diagram (Baldwin et. al., 1981) that identifies the primary source of ionization. We select 100 spectra for each of the four BPT classes and demonstrate fast retrieval and stacking using the Data Lab specClient, resulting in high signal-to-noise composite spectra in a matter of seconds.

2. Multi-wavelength Image Cutouts and SDSS Spectra of Active Galaxies with Extreme Emission-Line Ratios

In this notebook we investigate outliers that have extreme [NII]/H-alpha emission line ratios based on a SDSS DR12 value-added catalog of emission lines. We also show how to access and plot multiwavelength image cutouts and Sloan Digital Sky Survey (SDSS) spectra of emission-line galaxies. An interesting active galaxy with radio lobes and with broad lines in its spectrum is shown in Figure 1. The notebook allows the users to explore different BPT outlier galaxies and compare with results from a new emission-line fitting tool (GELATO; Hviding et al. 2022).

Figure 1. Example active galaxy identified from its extreme [NII]/H-alpha emission line ratio from the SDSS DR12 Portsmouth catalog. Top row: multi-wavelength image cutouts retrieved from the Legacy Survey (LS) Sky Viewer (from left to right: UV from GALEX, optical from SDSS and from LS, infrared from WISE, and radio from VLA). Bottom panel: rest-frame SDSS DR16 spectrum retrieved from the Data Lab specClient. Vertical lines mark the expected wavelengths of strong emission lines. We can see broad Balmer lines (H-beta and H-alpha) indicating a Type 1 Seyfert.

Opportunity to prepare for science with Rubin Observatory

On June 30, 2022 the Rubin Observatory will release Phase 2 of Data Preview 0 (DP0.2), reprocessed simulated LSST-like data, in the Rubin Science Platform (RSP). One of Rubin Observatory's goals for DP0 is to have experienced users of science platforms engage with the RSP and provide feedback. Thus, current users of NOIRLab’s Astro Data Lab are encouraged to learn more about DP0 (link below) and consider participating. Applications to participate are due April 30, 2022, and the only prerequisite for participation in DP0 is to have Rubin Observatory data rights. As described in the Data Policy astronomers working in the US and Chile have data rights (including students), as do named individuals on International Contributor teams.

Register now to participate in Phase 2 of Data Preview 0 (DP0.2)

Invitation to take short survey on behalf of US-ELTP

The US Extremely Large Telescope Program (US-ELTP) is a joint endeavor of NSF's NOIRLab and the organizations building the Giant Magellan Telescope (GMT) and the Thirty Meter Telescope (TMT). It will provide all US astronomers the opportunity to use this powerful, bi-hemispheric ELT system and to conduct research using archived data from GMT and TMT. US-ELTP is currently developing their plans for data services and science platforms. Current users of existing science platforms such as NOIRLab's Astro Data Lab and Rubin Science Platform already have significant experience, and are invited to take a short survey (5-10 minutes) to help US-ELTP in understanding the science platform needs of the community, including needed user support and training. If you would like to participate in the anonymous survey, please go to:

https://www.surveymonkey.com/r/WFC3P6X

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