分类: 天文学 >> 天文学 提交时间: 2023-02-19
摘要: We use the Galaxy Morphology Posterior Estimation Network (GaMPEN) to estimate morphological parameters and associated uncertainties for $\sim 8$ million galaxies in the Hyper Suprime-Cam (HSC) Wide survey with $z \leq 0.75$ and $m \leq 23$. GaMPEN is a machine learning framework that estimates Bayesian posteriors for a galaxy's bulge-to-total light ratio ($L_B/L_T$), effective radius ($R_e$), and flux ($F$). By first training on simulations of galaxies and then applying transfer learning using real data, we trained GaMPEN with $<1\%$ of our dataset. This two-step process will be critical for applying machine learning algorithms to future large imaging surveys, such as the Rubin-Legacy Survey of Space and Time (LSST), the Nancy Grace Roman Space Telescope (NGRST), and Euclid. By comparing our results to those obtained using light-profile fitting, we demonstrate that GaMPEN's predicted posterior distributions are well-calibrated ($\lesssim 5\%$ deviation) and accurate. This represents a significant improvement over light profile fitting algorithms which underestimate uncertainties by as much as $\sim60\%$. For an overlapping sub-sample, we also compare the derived morphological parameters with values in two external catalogs and find that the results agree within the limits of uncertainties predicted by GaMPEN. This step also permits us to define an empirical relationship between the S\'ersic index and $L_B/L_T$ that can be used to convert between these two parameters. The catalog presented here represents a significant improvement in size ($\sim10 \times $), depth ($\sim4$ magnitudes), and uncertainty quantification over previous state-of-the-art bulge+disk decomposition catalogs. With this work, we also release GaMPEN's source code and trained models, which can be adapted to other datasets.
分类: 天文学 >> 天文学 提交时间: 2023-02-19
摘要: We present a machine-learning framework to accurately characterize
morphologies of Active Galactic Nucleus (AGN) host galaxies within $z<1$. We
first use PSFGAN to decouple host galaxy light from the central point source,
then we invoke the Galaxy Morphology Network (GaMorNet) to estimate whether the
host galaxy is disk-dominated, bulge-dominated, or indeterminate. Using optical
images from five bands of the HSC Wide Survey, we build models independently in
three redshift bins: low $(0
分类: 天文学 >> 天文学 提交时间: 2023-02-19
摘要: We conduct a systematic search for protocluster candidates at $z \geq 6$ in the COSMOS field using the recently released COSMOS2020 source catalog. We select galaxies using a number of selection criteria to obtain a sample of galaxies that have a high probability of being inside a given redshift bin. We then apply overdensity analysis to the bins using two density estimators, a Weighted Adaptive Kernel Estimator and a Weighted Voronoi Tessellation Estimator. We have found 15 significant ($>4\sigma$) candidate galaxy overdensities across the redshift range $6\le z\le7.7$. The majority of the galaxies appear to be on the galaxy main sequence at their respective epochs. We use multiple stellar-mass-to-halo-mass conversion methods to obtain a range of dark matter halo mass estimates for the overdensities in the range of $\sim10^{11-13}\,M_{\rm \odot}$, at the respective redshifts of the overdensities. The number and the masses of the halos associated with our protocluster candidates are consistent with what is expected from the area of a COSMOS-like survey in a standard $\Lambda$CDM cosmology. Through comparison with simulation, we expect that all the overdensities at $z\simeq6$ will evolve into a Virgo-/Coma-like clusters at present (i.e., with masses $\sim 10^{14}-10^{15}\,M_{\rm \odot}$). Compared to other overdensities identified at $z \geq 6$ via narrow-band selection techniques, the overdensities presented appear to have $\sim10\times$ higher stellar masses and star-formation rates. We compare the evolution in the total star-formation rate and stellar mass content of the protocluster candidates across the redshift range $6\le z\le7.7$ and find agreement with the total average star-formation rate from simulations.
分类: 天文学 >> 天文学 提交时间: 2023-02-19
摘要: We present the survey design, implementation, and outlook for COSMOS-Web, a 255 hour treasury program conducted by the James Webb Space Telescope in its first cycle of observations. COSMOS-Web is a contiguous 0.54 deg$^2$ NIRCam imaging survey in four filters (F115W, F150W, F277W, and F444W) that will reach 5$\sigma$ point source depths ranging $\sim$27.5-28.2 magnitudes. In parallel, we will obtain 0.19 deg$^2$ of MIRI imaging in one filter (F770W) reaching 5$\sigma$ point source depths of $\sim$25.3-26.0 magnitudes. COSMOS-Web will build on the rich heritage of multiwavelength observations and data products available in the COSMOS field. The design of COSMOS-Web is motivated by three primary science goals: (1) to discover thousands of galaxies in the Epoch of Reionization ($64$ and place constraints on the formation of the Universe's most massive galaxies ($M_\star>10^{10}$\,M$_\odot$), and (3) directly measure the evolution of the stellar mass to halo mass relation using weak gravitational lensing out to $z\sim2.5$ and measure its variance with galaxies' star formation histories and morphologies. In addition, we anticipate COSMOS-Web's legacy value to reach far beyond these scientific goals, touching many other areas of astrophysics, such as the identification of the first direct collapse black hole candidates, ultracool sub-dwarf stars in the Galactic halo, and possibly the identification of $z>10$ pair-instability supernovae. In this paper we provide an overview of the survey's key measurements, specifications, goals, and prospects for new discovery.