How Well Can We Measure Galaxy Dust Attenuation Curves? The Impact of the Assumed Star-dust Geometry Model in Spectral Energy Distribution Fitting

One of the most common methods for inferring galaxy attenuation curves is via spectral energy distribution (SED) modeling, where the dust attenuation properties are modeled simultaneously with other galaxy physical properties. In this paper, we assess the ability of SED modeling to infer these dust attenuation curves from broadband photometry, and suggest a new flexible model that greatly improves the accuracy of attenuation curve derivations. To do this, we fit mock SEDs generated from the Simba cosmological simulation with the Prospector SED fitting code. We consider the impact of the commonly-assumed uniform screen model and introduce a new non-uniform screen model parameterized by the fraction of unobscured stellar light. This non-uniform screen model allows for a non-zero fraction of stellar light to remain unattenuated, resulting in a more flexible attenuation curve shape by decoupling the shape of the UV attenuation curve from the optical attenuation curve. The ability to constrain the dust attenuation curve is significantly improved with the use of a non-uniform screen model, with the median offset in UV attenuation decreasing from $-0.30$ dex with a uniform screen model to $-0.17$ dex with the non-uniform screen model. With this increase in dust attenuation modeling accuracy, we also improve the star formation rates (SFRs) inferred with the non-uniform screen model, decreasing the SFR offset on average by $0.12$ dex. We discuss the efficacy of this new model, focusing on caveats with modeling star-dust geometries and the constraining power of available SED observations.Comment: Submitted to ApJ. 15 pages, 10 figure

How to Measure Galaxy Star Formation Histories. II. Nonparametric Models

Nonparametric star formation histories (SFHs) have long promised to be the `gold standard' for galaxy spectral energy distribution (SED) modeling as they are flexible enough to describe the full diversity of SFH shapes, whereas parametric models rule out a significant fraction of these shapes {\it a priori}. However, this flexibility is not fully constrained even with high-quality observations, making it critical to choose a well-motivated prior. Here, we use the SED-fitting code \texttt{Prospector} to explore the effect of different nonparametric priors by fitting SFHs to mock UV-IR photometry generated from a diverse set of input SFHs. First, we confirm that nonparametric SFHs recover input SFHs with less bias and return more accurate errors than do parametric SFHs. We further find that, while nonparametric SFHs robustly recover the overall shape of the input SFH, the primary determinant of the size and shape of the posterior star formation rate (SFR) as a function of time is the choice of prior, rather than the photometric noise. As a practical demonstration, we fit the UV-IR photometry of $\sim$6000 galaxies from the GAMA survey and measure inter-prior scatters in mass (0.1 dex), SFR$_{100\; \mathrm{Myr}}$ (0.8 dex), and mass-weighted ages (0.2 dex), with the bluest star-forming galaxies showing the most sensitivity. An important distinguishing characteristic for nonparametric models is the characteristic timescale for changes in SFR(t). This difference controls whether galaxies are assembled in bursts or in steady-state star formation, corresponding respectively to (feedback-dominated/accretion-dominated) models of galaxy formation and to (larger/smaller) confidence intervals derived from SED-fitting. High-quality spectroscopy has the potential to further distinguish between these proposed models of SFR(t).Comment: replacing with ApJ accepted versio

Australian ethnomedicinal plant extracts promote apoptosis-mediated cell death In human hepatocellular carcinoma in vitro

Introduction: Hepatocellular carcinoma (HCC) Is the leading cause of primary liver cancer with Its prevalence continuing to rise. Although the number of cases continues to rise In both developing and developed countries, prognosis remains poor due to a lack of successful treatments. Inspired by the prospect of developing complementary medicines for this condition, we explore several native Australian plants for anti-carcinogenic activity, especially against HCC. Methods: Cytotoxicity assays against HCC cell lines were conducted using various plant extracts. Biochemical profiling of the plant species was conducted for total phenolics and antioxidant capacity, while reverse transcription-polymerase chain reaction (RT-PCR) was used to determine the active apoptotic pathways. Results: Westringia fruticosa and Prostanthera ovalifolia (small-leaved variety) had high antioxidant (410 and 227 mg/g, respectively) and phenolic contents (72.7 and 42.7 mg/g, respectively). P ovalifolia (small-leaved variety) demonstrated the greatest cytotoxic activity against HepG2 cells (IC50 4.61 ± 0.98 pg/mL) followed by Solanum laciniatum leaves (11.79 ± 0.43 pg/mL) and fruit extracts (ripe, unripe) (14.85 ± 1.80 and 19 ± 1.32 pg/mL, respectively). RT-PCR results confirmed apoptotic events in HepG2 cells, exposed to ripe and unripe S. laciniatum fruit extracts, via caspase-3 pathway. The highest apoptotic induction occurred after 8 hr. Compared to unripe fruits, ripe fruits induced a greater level of apoptosis, as evidenced by a 73 % higher level of caspase-3 mRNA expression and 22 % lower IC50 value. Conclusion: With further investigation, these fruits may provide a valuable source of anticarcinogenic compounds for use as chemotherapeutic or complementary therapies

Rapid Quenching of Galaxies at Cosmic Noon

The existence of massive quiescent galaxies at high redshift seems to require rapid quenching, but it is unclear whether all quiescent galaxies have gone through this phase and what physical mechanisms are involved. To study rapid quenching, we use rest-frame colors to select 12 young quiescent galaxies at $z \sim 1.5$. From spectral energy distribution fitting, we find that they all experienced intense starbursts prior to rapid quenching. We confirm this with deep Magellan/FIRE spectroscopic observations for a subset of seven galaxies. Broad emission lines are detected for two galaxies and are most likely caused by AGN activity. The other five galaxies do not show any emission features, suggesting that gas has already been removed or depleted. Most of the rapidly quenched galaxies are more compact than normal quiescent galaxies, providing evidence for a central starburst in the recent past. We estimate an average transition time of $300\,\rm Myr$ for the rapid quenching phase. Approximately $4\%$ of quiescent galaxies at $z=1.5$ have gone through rapid quenching; this fraction increases to $23\%$ at $z=2.2$. We identify analogs in the TNG100 simulation and find that rapid quenching for these galaxies is driven by AGN, and for half of the cases, gas-rich major mergers seem to trigger the starburst. We conclude that these massive quiescent galaxies are not just rapidly quenched but also rapidly formed through a major starburst. We speculate that mergers drive gas inflow towards the central regions and grow supermassive black holes, leading to rapid quenching by AGN feedback.Comment: Submitted to ApJ. Comments are welcom

Inferring More from Less: Prospector as a Photometric Redshift Engine in the Era of JWST

The advent of the James Webb Space Telescope (JWST) signals a new era in exploring galaxies in the high-$z$ universe. Current and upcoming JWST imaging will potentially detect galaxies out to $z \sim 20$, creating a new urgency in the quest to infer accurate photometric redshifts (photo-$z$) for individual galaxies from their spectral energy distributions, as well as masses, ages and star formation rates. Here we illustrate the utility of informed priors encoding previous observations of galaxies across cosmic time in achieving these goals. We construct three joint priors encoding empirical constraints of redshifts, masses, and star formation histories in the galaxy population within the \prospector\ Bayesian inference framework. In contrast with uniform priors, our model breaks an age-mass-redshift degeneracy, and thus reduces the mean bias error in masses from 0.3 to 0.1 dex, and in ages from 0.6 to 0.2 dex in tests done on mock JWST observations. Notably, our model recovers redshifts at least as accurately as the state-of-the-art photo-$z$ code \eazy\ in deep JWST fields, but with two advantages: tailoring a model based on a particular survey renders mostly unnecessary given well-motivated priors; obtaining joint posteriors describing stellar, active galactic nuclei, gas, and dust contributions becomes possible. We can now confidently use the joint distribution to propagate full non-Gaussian redshift uncertainties into inferred properties of the galaxy population. This model, ``\prospector-$\beta$'', is intended for fitting galaxy photometry where the redshift is unknown, and will be instrumental in ensuring the maximum science return from forthcoming photometric surveys with JWST. The code is made publicly available online as a part of \prospector.Comment: Accepted for publication in ApJL. 13 pages, 6 figures, 2 tables. The code is made publicly available online as a part of Prospector; the version used in this work corresponds to the state of the Git repository at commit 820ad7

An Older, More Quiescent Universe from Panchromatic SED Fitting of the 3D-HST Survey

Galaxy observations are influenced by many physical parameters: stellar masses, star formation rates (SFRs), star formation histories (SFHs), metallicities, dust, black hole activity, and more. As a result, inferring accurate physical parameters requires high-dimensional models which capture or marginalize over this complexity. Here we re-assess inferences of galaxy stellar masses and SFRs using the 14-parameter physical model Prospector-$\alpha$ built in the Prospector Bayesian inference framework. We fit the photometry of 58,461 galaxies from the 3D-HST catalogs at $0.5 < z < 2.5$. The resulting stellar masses are $\sim0.1-0.3$ dex larger than the fiducial masses while remaining consistent with dynamical constraints. This change is primarily due to the systematically older SFHs inferred with Prospector. The SFRs are $\sim0.1-1+$ dex lower than UV+IR SFRs, with the largest offsets caused by emission from "old" ($t>100$ Myr) stars. These new inferences lower the observed cosmic star formation rate density by $\sim0.2$ dex and increase the observed stellar mass growth by $\sim 0.1$ dex, finally bringing these two quantities into agreement and implying an older, more quiescent Universe than found by previous studies at these redshifts. We corroborate these results by showing that the Prospector-$\alpha$ SFHs are both more physically realistic and are much better predictors of the evolution of the stellar mass function. Finally, we highlight examples of observational data which can break degeneracies in the current model; these observations can be incorporated into priors in future models to produce new & more accurate physical parameters.Comment: Replaced w/ accepted versio