Douglas L. Tucker

Erratum: “A Pride of Satellites in the Constellation Leo? Discovery of the Leo VI Milky Way Satellite Ultra-faint Dwarf Galaxy with DELVE Early Data Release 3” (2025, ApJ, 979, 176), Tan, C. Y., Cerny, W., Drlica-Wagner, A., Pace, A. B., Geha, M., Ji, A. P., Li, T. S., Adamów, M., Anbajagane, D., Bom, C. R., Carballo-Bello, J. A., Carlin, J. L., Chang, C., Chaturvedi, A., Chiti, A., Choi, Y., Collins, M. L. M., Doliva-Dolinsky, A., Ferguson, P. S., Gruendl, R. A., James, D. J., Limberg, G., Navabi, M., Martínez-Delgado, D., Martínez-Vázquez, C. E., Medina, G. E., Mutlu-Pakdil, B., Nidever, D. L., Noël, N. E. D., Riley, A. H., Sakowska, J. D., Sand, D. J., Sharp, J., Stringfellow, G. S., Tolley, C., Tucker, D., Vivas, A. K., (DELVE Collaboration) Erratum: “A Pride of Satellites in the Constellation Leo? Discovery of the Leo VI Milky Way Satellite Ultra-faint Dwarf Galaxy with DELVE Early Data Release 3” (2025, ApJ, 979, 176), Tan, C. Y., Cerny, W., Drlica-Wagner, A., Pace, A. B., Geha, M., Ji, A. P., Li, T. S., Adamów, M., Anbajagane, D., Bom, C. R., Carballo-Bello, J. A., Carlin, J. L., Chang, C., Chaturvedi, A., Chiti, A., Choi, Y., Collins, M. L. M., Doliva-Dolinsky, A., Ferguson, P. S., Gruendl, R. A., James, D. J., Limberg, G., Navabi, M., Martínez-Delgado, D., Martínez-Vázquez, C. E., Medina, G. E., Mutlu-Pakdil, B., Nidever, D. L., Noël, N. E. D., Riley, A. H., Sakowska, J. D., Sand, D. J., Sharp, J., Stringfellow, G. S., Tolley, C., Tucker, D., Vivas, A. K., (DELVE Collaboration)

We present cosmological constraints from the Planck PSZ2 cosmological cluster sample, using weak-lensing shear profiles from Dark Energy Survey (DES) data and X-ray observations from the Chandra telescope for the mass calibration. We compute hydrostatic mass estimates for all clusters in the PSZ2 sample with a scaling relation between their integrated Sunyaev-Zeldovich signal and X-ray-derived hydrostatic mass, calibrated with the Chandra data. We introduce a method to correct these masses with a hydrostatic mass bias using shear profiles derived from wide-field galaxy surveys. We simultaneously fit the number counts of the PSZ2 sample and the mass calibration with the DES data, finding Ω _m = 0.312 ^+0.018 _−0.024 , σ ₈ = 0.777 ± 0.024, S ₈ ≡ σ ₈ √Ω _m /0.3 = 0.791 ^+0.023 _−0.021 , and (1− b ) = 0.844 ^+0.055 _−0.062 for our baseline analysis when combined with baryon acoustic oscillation data. When considering a hydrostatic mass bias evolving with mass, we find Ω _m = 0.353 ^+0.025 _−0.031 , σ ₈ = 0.751 ± 0.023, and S ₈ = 0.814 ^+0.019 _−0.020 . We verify the robustness of our results by exploring a variety of analysis settings, with a particular focus on the definition of the halo centre used for the extraction of shear profiles. We compare our results with a number of other cosmological analyses, in particular two recent analyses of cluster samples obtained from SPT and eROSITA data that share the same mass calibration data set. We find that our results are in overall agreement with most late-time probes, in very mild tension with CMB results (1.6 σ ), and in significant tension with results from eROSITA clusters (2.9 σ ). We confirm that our mass calibration is consistent with the eROSITA analysis by comparing masses for clusters present in both Planck and eROSITA samples, eliminating it as a potential cause of tension. We also compare our results with previous studies of the PSZ2 sample, finding a good agreement between the constraints derived in this work and previous constraints derived with the same sample, validating the use of wide-field lensing data for cluster mass calibration.

We present Rubin Data Preview 1 (DP1), the first data from the National Science Foundation–Department of Energy Vera C. Rubin Observatory, comprising raw and calibrated single-epoch images, coadds, difference images, detection catalogs, and ancillary data products. DP1 is based on 1792 optical–near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera (LSSTComCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile in late 2024. DP1 covers ∼15 deg ² distributed across seven roughly equal-sized noncontiguous fields, each independently observed in six broad photometric bands, ugrizy . The median FWHM of the point-spread function across all bands is approximately 1 . ″ 14, with the sharpest images reaching about 0 . ″ 58. The 5 σ point-source depths for coadded images in the deepest field, the Extended Chandra Deep Field South, are u = 24.55, g = 26.18, r = 25.96, i = 25.71, z = 25.07, and y = 23.1. Other fields are no more than 2.2 mag shallower in any band, where they have nonzero coverage. DP1 contains approximately 2.3 million distinct astrophysical objects, of which 1.6 million are extended in at least one band in coadds, and 431 solar system objects, of which 93 are new discoveries. DP1 is approximately 3.5 TB in size and is available to Vera C. Rubin Observatory data rights holders via the Rubin Science Platform, a cloud-based environment for the analysis of petascale astronomical data. While small compared to future LSST releases, its high quality and diversity of data support a broad range of early science investigations ahead of full operations in 2026.

We conduct a search for strong gravitational lenses in the Dark Energy Survey (DES) Year 6 imaging data. We implement a pre-trained Vision Transformer (ViT) for our machine learning (ML) architecture and adopt interactive machine learning to construct a training sample with multiple classes to address common types of false positives. Our ML model reduces ∼236 million DES cutout images to 22,564 targets of interest, including ∼85% of previously reported galaxy–galaxy lens candidates discovered in DES. These targets were visually inspected by citizen scientists, who ruled out ∼90% as false positives. Of the remaining 2618 candidates, 149 were expert-classified as “definite” lenses and 516 as “probable” lenses, for a total of 665 systems, with 147 of these candidates being newly identified. Additionally, we trained a second ViT to find double-source plane lens systems, finding at least one double-source system. Our main ViT excels at identifying galaxy–galaxy lenses, consistently assigning high scores to candidates with high expert assessments. The top 800 ViT-scored images include ∼100 of our “definite” lens candidates. This selection is an order of magnitude higher in purity than previous convolutional neural-network-based lens searches and demonstrates the feasibility of applying our methodology for discovering large samples of lenses in future surveys.

We report on the observation and measurement of astrometry, photometry, morphology, and activity of the interstellar object 3I/ATLAS, also designated C/2025 N1 (ATLAS) with the NSF-DOE Vera C. Rubin Observatory. Comet 3I/ATLAS, the third known interstellar object, was discovered on UT 2025 July 1. Rubin Observatory had coincidentally collected images of the object’s region of the sky during routine commissioning. Facilitated by Rubin’s high resolution and large aperture, we successfully recovered object detections from Rubin observations spanning UT 2025 June 21 (10 days before discovery, when 3I/ATLAS was 4.5 au from the Sun) through the date of discovery, and we acquired additional images through UT 2025 July 20 as part of commissioning. We measure on-sky locations of 3I/ATLAS in Rubin ugrizy bands, with a typical precision of ∼70 mas, and briefly describe the reason this is coarser than our measured static source astrometric precision of ∼3 mas in Rubin images. We measure grizy magnitudes of 3I/ATLAS photometry at ∼0.01 mag precision, detecting no short-term photometric variability above 0.01 mag. We derive an estimated near-nucleus dust-to-nucleus scattering cross-sectional ratio of η ≳ 13 on UT 2025 July 2 based on Rubin photometry and an upper limit nucleus size computed from Hubble Space Telescope observations. We find Rubin colors of g − r = (0.657 ± 0.013) mag, r − i = (0.235 ± 0.018) mag, i − z = (0.147 ± 0.042) mag, and z − y = (0.047 ± 0.052) mag. These data represent the earliest observations of this object by a large (≳8 m class) telescope and illustrate the type of measurements (and discoveries) Rubin’s Legacy Survey of Space and Time will provide after it begins in early 2026.

Aims . We investigate the utility of Rubin ’s Data Preview 1 (DP1) for estimating stellar number density profiles across the Milky Way halo. Methods . We used stellar broad-band near-UV to near-IR ugrizy photometry released in Rubin ’s DP1 to estimate distance and metallicity for blue main sequence stars brighter than r = 24 in three ~1.1 sq. deg. fields at southern Galactic latitudes. Results . Compared to TRILEGAL simulations of the Galaxy’s stellar content, we found a likely deficit of blue main sequence turn-off stars with 22 < r < 24. We interpreted this discrepancy as a signature of a steeper halo number density profile at galactocentric distances 10–50 kpc than the canonical ~1/ r ³ profile assumed in TRILEGAL simulations. Conclusions . This interpretation is consistent with earlier suggestions based on observations of more luminous, but much less numerous, evolved stellar populations, along with a few pencil beam surveys of blue main sequence stars in the northern sky. These results bode well for the future Galactic halo exploration with Rubin ’s Legacy Survey of Space and Time (LSST).

The properties of Milky Way satellite galaxies have important implications for galaxy formation, reionization, and the fundamental physics of dark matter. However, the population of Milky Way satellites includes the faintest known galaxies, and current observations are incomplete. To understand the impact of observational selection effects on the known satellite population, we perform rigorous, quantitative estimates of the Milky Way satellite galaxy detection efficiency in three wide-field survey datasets: the Dark Energy Survey Year 6, the DECam Local Volume Exploration Data Release 3, and the Pan-STARRS1 Data Release 1. Together, these surveys cover ∼13,600 deg ² to g ∼ 24.0 and ∼27,700 deg ² to g ∼ 22.5, spanning ∼91% of the high-Galactic-latitude sky (∣ b ∣ ≥ 15°). We apply multiple detection algorithms over the combined footprint and recover 49 known satellites above a strict census detection threshold. To characterize the sensitivity of our census, we run our detection algorithms on a large set of simulated galaxies injected into the survey data, which allows us to develop models that predict the detectability of satellites as a function of their properties. We then fit an empirical model to our data and infer the luminosity function, radial distribution, and size–luminosity relation of Milky Way satellite galaxies. Our empirical model predicts a total of 26 5 − 47 + 79 satellite galaxies with −20 ≤ M _V ≤ 0, half-light radii of 15 ≤ r _1/2 , (pc) ≤ 3000, and galactocentric distances of 10 ≤ D _GC (kpc) ≤ 300. We also identify a mild anisotropy in the angular distribution of the observed galaxies, at a significance of ∼2 σ , which can be attributed to the clustering of satellites associated with the LMC.

We describe the photometric dataset assembled from the full 6 yr of observations by the Dark Energy Survey (DES) in support of static-sky cosmology analyses. DES Y6 Gold is a curated dataset derived from DES Data Release 2 (DR2) that incorporates improved measurement, photometric calibration, object classification and value-added information. Y6 Gold comprises nearly 5000 deg ² of grizY imaging in the south Galactic cap and includes 669 million objects with a depth of i _AB ∼ 23.4 mag at a signal-to-noise ratio ∼ 10 for extended objects and a top-of-the-atmosphere photometric uniformity i _AB < 22.5. Additionally, it includes per-object quality information, and accompanying maps of the footprint coverage, masked regions, imaging depth, survey conditions, and astrophysical foregrounds that are used for cosmology analyses. After quality selections, benchmark samples contain 448 million galaxies and 120 million stars. This publication is complemented by data access and documentation.

We present analyses of the early data from Rubin Observatory’s Data Preview 1 (DP1) for the field of the globular cluster 47 Tuc. The DP1 data set for 47 Tuc includes four nights of observations from the Rubin Commissioning Camera (LSSTComCam), covering multiple bands (ugriy). We address challenges of crowding in the inner region of the cluster and toward the SMC in DP1, and demonstrate improved star–galaxy separation by fitting fifth-degree polynomials to the stellar loci in color–color diagrams and applying multidimensional sigma clipping. We compile a catalog of 3576 probable 47 Tuc member stars selected via a combination of isochrone, Gaia proper-motion, and color–color space matched filtering. We explore the sources of photometric scatter in the 47 Tuc color–color sequence, evaluating contributions from various potential sources, including differential extinction within the cluster. Finally, of the 72 well-characterized variables in the field, we recover three known variable stars, including two RR Lyrae and one eclipsing binary, in the coadd-based object catalog, and identify 62 in the difference image-based object catalog. Although the DP1 lightcurves have sparse temporal sampling, they appear to follow the patterns of densely sampled literature lightcurves well. Despite some data limitations for crowded-field stellar analysis, DP1 demonstrates the promising scientific potential for future LSST data releases.