2,335 research outputs found

    Diverse Structural Evolution at z > 1 in Cosmologically Simulated Galaxies

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    From mock Hubble Space Telescope images, we quantify non-parametric statistics of galaxy morphology, thereby predicting the emergence of relationships among stellar mass, star formation, and observed rest-frame optical structure at 1 < z < 3. We measure automated diagnostics of galaxy morphology in cosmological simulations of the formation of 22 central galaxies with 9.3 < log10 M_*/M_sun < 10.7. These high-spatial-resolution zoom-in calculations enable accurate modeling of the rest-frame UV and optical morphology. Even with small numbers of galaxies, we find that structural evolution is neither universal nor monotonic: galaxy interactions can trigger either bulge or disc formation, and optically bulge-dominated galaxies at this mass may not remain so forever. Simulated galaxies with M_* > 10^10 M_sun contain relatively more disc-dominated light profiles than those with lower mass, reflecting significant disc brightening in some haloes at 1 < z < 2. By this epoch, simulated galaxies with specific star formation rates below 10^-9.7 yr^-1 are more likely than normal star-formers to have a broader mix of structural types, especially at M_* > 10^10 M_sun. We analyze a cosmological major merger at z ~ 1.5 and find that the newly proposed MID morphology diagnostics trace later merger stages while G-M20 trace earlier ones. MID is sensitive also to clumpy star-forming discs. The observability time of typical MID-enhanced events in our simulation sample is less than 100 Myr. A larger sample of cosmological assembly histories may be required to calibrate such diagnostics in the face of their sensitivity to viewing angle, segmentation algorithm, and various phenomena such as clumpy star formation and minor mergers.Comment: 23 pages, 16 figures, MNRAS accepted versio

    Morphological signatures of mergers in the TNG50 simulation and the Kilo-Degree Survey: the merger fraction from dwarfs to Milky Way-like galaxies

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    Using the TNG50 cosmological simulation and observations from the Kilo-Degree Survey (KiDS), we investigate the connection between galaxy mergers and optical morphology in the local Universe over a wide range of galaxy stellar masses (8.5log(M/M)118.5\leqslant\log(M_\ast/\text{M}_\odot)\leqslant11). To this end, we have generated over 16,000 synthetic images of TNG50 galaxies designed to match KiDS observations, including the effects of dust attenuation and scattering, and used the statmorph\mathrm{\mathtt{statmorph}} code to measure various image-based morphological diagnostics in the rr-band for both data sets. Such measurements include the Gini-M20M_{20} and concentration-asymmetry-smoothness statistics. Overall, we find good agreement between the optical morphologies of TNG50 and KiDS galaxies, although the former are slightly more concentrated and asymmetric than their observational counterparts. Afterwards, we trained a random forest classifier to identify merging galaxies in the simulation (including major and minor mergers) using the morphological diagnostics as the model features, along with merger statistics from the merger trees as the ground truth. We find that the asymmetry statistic exhibits the highest feature importance of all the morphological parameters considered. Thus, the performance of our algorithm is comparable to that of the more traditional method of selecting highly asymmetric galaxies. Finally, using our trained model, we estimate the galaxy merger fraction in both our synthetic and observational galaxy samples, finding in both cases that the galaxy merger fraction increases steadily as a function of stellar mass.Comment: 18 pages, 12 figures. Accepted for publication in MNRA

    Mock Galaxy Surveys for HST and JWST from the IllustrisTNG Simulations

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    We present and analyze a series of synthetic galaxy survey fields based on the IllustrisTNG Simulation suite. With the Illustris public data release and JupyterLab service, we generated a set of twelve lightcone catalogs covering areas from 5 to 365 square arcminutes, similar to several JWST Cycle 1 programs, including JADES, CEERS, PRIMER, and NGDEEP. From these catalogs, we queried the public API to generate simple mock images in a series of broadband filters used by JWST-NIRCam and the Hubble Space Telescope cameras. This procedure generates wide-area simulated mosaic images that can support investigating the predicted evolution of galaxies alongside real data. Using these mocks, we demonstrate a few simple science cases, including morphological evolution and close pair selection. We publicly release the catalogs and mock images through MAST, along with the code used to generate these projects, so that the astrophysics community can make use of these products in their scientific analyses of JWST deep field observations.Comment: Accepted to MNRA

    Synthetic Galaxy Images and Spectra from the Illustris Simulation

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    We present our methods for generating a catalog of 7,000 synthetic images and 40,000 integrated spectra of redshift z = 0 galaxies from the Illustris Simulation. The mock data products are produced by using stellar population synthesis models to assign spectral energy distributions (SED) to each star particle in the galaxies. The resulting synthetic images and integrated SEDs therefore properly reflect the spatial distribution, stellar metallicity distribution, and star formation history of the galaxies. From the synthetic data products it is possible to produce monochromatic or color-composite images, perform SED fitting, classify morphology, determine galaxy structural properties, and evaluate the impacts of galaxy viewing angle. The main contribution of this paper is to describe the production, format, and composition of the image catalog that makes up the Illustris Simulation Obsevatory. As a demonstration of this resource, we derive galactic stellar mass estimates by applying the SED fitting code FAST to the synthetic galaxy products, and compare the derived stellar masses against the true stellar masses from the simulation. We find from this idealized experiment that systematic biases exist in the photometrically derived stellar mass values that can be reduced by using a fixed metallicity in conjunction with a minimum galaxy age restriction.Comment: 21 pages, 17 figures, submitted to MNRAS. Comments welcom

    Modeling Mid-infrared Diagnostics of Obscured Quasars and Starbursts

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    We analyze the link between active galactic nuclei (AGNs) and mid-infrared flux using dust radiative transfer calculations of starbursts realized in hydrodynamical simulations. Focusing on the effects of galaxy dust, we evaluate diagnostics commonly used to disentangle AGN and star formation in ultraluminous infrared galaxies (ULIRGs). We examine these quantities as a function of time, viewing angle, dust model, AGN spectrum, and AGN strength in merger simulations representing two possible extremes of the ULIRG population: one is a typical gas-rich merger at z ~ 0, and the other is characteristic of extremely obscured starbursts at z ~ 2-4. This highly obscured burst begins star-formation-dominated with significant polycyclic aromatic hydrocarbon (PAH) emission, and ends with a ~10^9 yr period of red near-IR colors. At coalescence, when the AGN is most luminous, dust obscures the near-infrared AGN signature, reduces the relative emission from PAHs, and enhances the 9.7 μm absorption by silicate grains. Although generally consistent with previous interpretations, our results imply none of these indicators can unambiguously estimate the AGN luminosity fraction in all cases. Motivated by the simulations, we show that a combination of the extinction feature at 9.7 μm, the PAH strength, and a near-infrared slope can simultaneously constrain the AGN fraction and dust grain distribution for a wide range of obscuration. We find that this indicator, accessible to the James Webb Space Telescope, may estimate the AGN power as tightly as the hard X-ray flux alone, thereby providing a valuable future cross-check and constraint for large samples of distant ULIRGs
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