The DECam Local Volume Exploration Survey (DELVE) combines archival DECam data with 126 nights of novel observations (PropID 2019A-0305) to study dwarf satellite galaxies over a wide range of luminosities and environments. DELVE is divided into three survey components (WIDE, MC, and DEEP), each of which have their own observational strategy and data reduction pipeline. By combining novel observations with existing data from DES, DECaLS, and other community programs, DELVE will provide complete contiguous DECam coverage of the entire high-Galactic-latitude southern sky. By the end of the survey, DELVE is expected to cover >17,000 deg2 to a depth of griz ~ 23.5 mag, ~2,200 deg2 around the Magellanic Clouds to a depth of gri ~ 24.5 mag, and ~135 deg2 around isolated Magellanic analogs in the Local Volume to a depth of gi ~ 25.5 mag.
For more complete information about DELVE, please visit: https://delve-survey.github.io.
|DELVE at a Glance|
|DELVE-WIDE||~17,000 deg2||griz||~23.5 mag|
|DELVE-MC||~2,200 deg2||gri||~24.5 mag|
|DELVE-DEEP||~135 deg2||gi||~25.5 mag|
DELVE seeks to understand the faintest and most dark-matter-dominated galaxies in a range of environments. The DELVE data enable the detection and characterization of dwarf galaxies over a broad range of luminosity, from the ultra-faint satellites of the Milky Way (L ~ 103L⊙), to the Magellanic Clouds (L ~ 109−10L⊙), and analogs of the Magellanic Clouds in the Local Volume. DELVE consists of:
- DELVE-WIDE: a high-Galactic-latitude wide-area survey focused on resolved stellar systems (e.g., ultra-faint satellite galaxies and stellar streams) in the Milky Way halo.
- DELVE-MC: a contiguous Magellanic Cloud periphery survey to study the structure, evolution, star formation history, and satellite population of the Magellanic Clouds.
- DELVE-DEEP: a deep targeted survey of four Magellanic Cloud analogs (Sextans B, NGC 55, NGC 300, IC 5152) in the Local Volume to study the satellite populations of isolated low-mass hosts.
These three survey components will provide complementary insights into the abundance and properties of satellite galaxies around hosts at different mass scales and in a variety of environments. Combined with a unified theoretical framework, DELVE will explore the dependence of satellite properties on effects of reionization, host halo properties, and environment, offering essential insights into the galaxy–halo connection. More information about DELVE can be found at: https://delve-survey.github.io.
Each subcomponent of DELVE uses slightly different data reduction pipelines. While DELVE DR1 and DR2 come solely from the WIDE survey, we provide brief descriptions of each pipeline below. More detailed descriptions of the DELVE data processing can be found in Drlica-Wagner et al. (2021).
- DELVE-WIDE: The DELVE-WIDE data are processed with the DES Data Management (DESDM) pipeline (Morganson et al. 2018). SourceExtractor is used to create catalogs from the reduced ("Final Cut") images, and Gaia DR2 (Gaia Collaboration 2018) is used for astrometric calibration. Photometric calibration is performed with the forward global calibration module (Burke et al. 2018) within the DES footprint and against ATLAS Refcat2 (Tonry et al. 2018) outside the DES footprint. The best references for the DELVE-WIDE processing are the DELVE DR1 paper (Drlica-Wagner et al. 2021) and the DESDM paper (Morganson et al. 2018).
The DELVE-MC images are reduced with the DECam Community Pipeline (Valdes et al. 2014), which is based on an early versions of the DESDM pipeline.
The DELVE-MC processing is performed using DELVERED, a modified version of the
DAOPhot-based PHOTRED (Nidever et al. 2017), an automated and robust PSF photometry pipeline based on the DAOPHOT suite of programs (Stetson 1987, 1994). Astrometric calibration is performed against Gaia DR2 and photometric calibration is performed against ATLAS Refcat2 (Tonry et al. 2018). The best current reference for the DELVE-MC processing is Nidever et al. (2017).
The DELVE Collaboration is currently exploring various options for processing the DELVE-DEEP data.
To date, the DELVE-DEEP data have been processed by both the DESDM pipeline for image coaddition and the
DELVEREDpipeline for crowded-field photometry.
The second DELVE data release (DELVE DR2; Drlica-Wagner et al. 2022) is hosted at the Astro Data Lab and consists of catalog-level coadds in griz from the DELVE-WIDE processing. DELVE DR2 covers >20,000 deg2 in each individual band and ~17,000 deg2 in all bands simultaneously. The DELVE DR2 catalog contains ~2.5 billion unique objects, and ~618 million unique objects that were observed in all four bands.
|DELVE DR2 Summary (delve_dr2.objects)|
|Area Covered (all bands)||16,972 deg2|
|Area Covered (griz)||24663, 22939, 21283, 22866 deg2|
|Depth (5σ PSF; griz)||24.3, 23.9, 23.5, 22.8 mag|
|Depth (5σ AUTO; griz)||23.9, 23.5, 23.0, 22.4 mag|
|Seeing (griz)||1.24, 1.10, 1.02, 1.00|
|Number of Objects||2,500,247,752|
|Photometric Uniformity||7.3 mmag|
|Astrometric Accuracy||22 mas|
The first DELVE data release (DELVE DR1; Drlica-Wagner et al. 2021) is hosted at the Astro Data Lab and consists of catalog-level coadds in griz from the DELVE-WIDE processing. DELVE DR1 covers >5,000 deg2 in each individual band and ~4,000 deg2 in all bands simultaneously. The DELVE DR1 catalog contains ~520 million unique objects.
|DELVE DR1 Summary (delve_dr1.objects)|
|Area Covered (all bands)||4,075 deg2|
|Area Covered (griz)||5599, 5106, 5065, 5153 deg2|
|Depth (5σ PSF; griz)||24.3, 23.9, 23.3, 22.8 mag|
|Depth (5σ AUTO; griz)||23.9, 23.4, 22.9, 22.4 mag|
|Seeing (griz)||1.28, 1.16, 1.07, 1.04|
|Number of Objects||519,737,142|
|Photometric Uniformity||9.1 mmag|
|Astrometric Accuracy||22 mas|
Browse the Data Access page (side menu) to find out about different ways to use the DELVE DR1 catalog or obtain DELVE image cutouts.
The Astro Data Lab also includes several value-added data products that have been derived from the DELVE data. More details on these products can be found below.
- Photometric redshifts for DELVE DR2 derived using a Mixture Density Network (link).