Deep interferometric observations of a z≈1.12 barred spiral reveal bar-driven molecular inflows at a rate matching the galaxy's star formation rate of ~36 M⊙/yr.
Structural Parameters of Galaxies in CANDELS
2 Pith papers cite this work. Polarity classification is still indexing.
abstract
We present global structural parameter measurements of 109,533 unique, H_F160W-selected objects from the CANDELS multi-cycle treasury program. Sersic model fits for these objects are produced with GALFIT in all available near-infrared filters (H_F160W, J_F125W and, for a subset, Y_F105W). The parameters of the best-fitting Sersic models (total magnitude, half-light radius, Sersic index, axis ratio, and position angle) are made public, along with newly constructed point spread functions for each field and filter. Random uncertainties in the measured parameters are estimated for each individual object based on a comparison between multiple, independent measurements of the same set of objects. To quantify systematic uncertainties we create a mosaic with simulated galaxy images with a realistic distribution of input parameters and then process and analyze the mosaic in an identical manner as the real data. We find that accurate and precise measurements -- to 10% or better -- of all structural parameters can typically be obtained for galaxies with H_F160W < 23, with comparable fidelity for basic size and shape measurements for galaxies to H_F160W ~ 24.5.
fields
astro-ph.GA 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Optimizes ImageNet-pretrained AlexNet, UMAP, and a bagging multi-cluster voting scheme with K-means, Birch and Agg for unsupervised galaxy morphology classification, reporting improved stability and consistency with galaxy evolution expectations.
citing papers explorer
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NOEMA$^\rm{3D}$: A deep view of cold gas flows in a barred spiral galaxy at $z\sim1$
Deep interferometric observations of a z≈1.12 barred spiral reveal bar-driven molecular inflows at a rate matching the galaxy's star formation rate of ~36 M⊙/yr.
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Robustness Analysis of USmorph: II. Optimizing Feature Extraction, Dimensionality Reduction, and Clustering for Unsupervised Galaxy Morphology Classification
Optimizes ImageNet-pretrained AlexNet, UMAP, and a bagging multi-cluster voting scheme with K-means, Birch and Agg for unsupervised galaxy morphology classification, reporting improved stability and consistency with galaxy evolution expectations.