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Abstract We present a complete census of candidate nuggets, i.e., dense galaxies likely formed by compaction with intense gas influx, within the volume-limited redshiftz∼ 0 REsolved Spectroscopy Of a Local VolumE (RESOLVE) survey. These nuggets span all evolutionary stages and 3 orders of magnitude in stellar mass (M_*∼ 10⁸to 10¹¹M_⊙) from the dwarf to the giant regime. We develop selection criteria for ourz∼ 0 nugget candidates based on structure and introduce the use of environmental criteria to eliminate nugget-like objects with suspected non-compaction origins. The resultingz∼ 0 nuggets follow expectations with respect to structure (i.e., density, size), population frequency, and likely origins. We show that the properties of our nugget census are consistent with permanent quenching above the gas-richness threshold scale (halo mass M_halo∼ 10^11.4M_⊙), cyclic temporary quenching below the threshold scale, and feedback from active galactic nuclei (AGN) assisting in permanent quenching. As predicted in simulations, most nuggets quench within a halo mass range ofM_halo∼ 10^11.45to 10^11.9M_⊙. We find ∼0.29 dex scatter around the star-forming main sequence for candidate blue nuggets below the threshold scale, which is consistent with temporary quenching as seen in simulations. A transitional population of green nuggets appears above the threshold scale. AGN also become more common in nuggets above this scale, and we see a likely AGN excess in nuggets versus comparably selected non-nuggets. Our results provide the first observational confirmation of the mass-dependent, AGN-mediated shift from cyclic quenching to halo quenching in nuggets. 

Abstract This paper represents an effort to provide robust constraints on the galaxy–halo connection and simultaneously test the Planck ΛCDM cosmology using a fully numerical model of small-scale galaxy clustering. We explore two extensions to the standard Halo Occupation Distribution model: assembly bias, whereby halo occupation depends on both halo mass and the larger environment, and velocity bias, whereby galaxy velocities do not perfectly trace the velocity of the dark matter within the halo. Moreover, we incorporate halo mass corrections to account for the impact of baryonic physics on the halo population. We identify an optimal set of clustering measurements to constrain this “decorated” HOD model for both low- and high-luminosity galaxies in SDSS DR7. We find that, for low-luminosity galaxies, a model with both assembly bias and velocity bias provides the best fit to the clustering measurements, with no tension remaining in the fit. In this model, we find evidence for both central and satellite galaxy assembly bias at the 99% and 95% confidence levels, respectively. In addition, we find evidence for satellite galaxy velocity bias at the 99.9% confidence level. For high-luminosity galaxies, we find no evidence for either assembly bias or velocity bias, but our model exhibits significant tension with SDSS measurements. We find that all of these conclusions still stand when we include the effects of baryonic physics on the halo mass function, suggesting that the tension we find for high-luminosity galaxies may be due to a problem with our assumed cosmological model. 

Abstract Applying halo models to analyze the small-scale clustering of galaxies is a proven method for characterizing the connection between galaxies and their host halos. Such works are often plagued by systematic errors or limited to clustering statistics that can be predicted analytically. In this work, we employ a numerical mock-based modeling procedure to examine the clustering of Sloan Digital Sky Survey DR7 galaxies. We apply a standard halo occupation distribution (HOD) model to dark matter only simulations with a ΛCDM cosmology. To constrain the theoreStical models, we utilize a combination of galaxy number density and selected scales of the projected correlation function, redshift-space correlation function, group multiplicity function, average group velocity dispersion, mark correlation function, and counts-in-cells statistics. We design an algorithm to choose an optimal combination of measurements that yields tight and accurate constraints on our model parameters. Compared to previous work using fewer clustering statistics, we find a significant improvement in the constraints on all parameters of our halo model for two different luminosity-threshold galaxy samples. Most interestingly, we obtain unprecedented high-precision constraints on the scatter in the relationship between galaxy luminosity and halo mass. However, our best-fit model results in significant tension (>4σ) for both samples, indicating the need to add second-order features to the standard HOD model. To guarantee the robustness of these results, we perform an extensive analysis of the systematic and statistical errors in our modeling procedure, including a first of its kind study of the sensitivity of our constraints to changes in the halo mass function due to baryonic physics. 

Software is a critical part of modern research, and yet there are insufficient mechanisms in the scholarly ecosystem to acknowledge, cite, and measure the impact of research software. The majority of academic fields rely on a one-dimensional credit model whereby academic articles (and their associated citations) are the dominant factor in the success of a researcher's career. In the petabyte era of astronomical science, citing software and measuring its impact enables academia to retain and reward researchers that make significant software contributions. These highly skilled researchers must be retained to maximize the scientific return from petabyte-scale datasets. Evolving beyond the one-dimensional credit model requires overcoming several key challenges, including the current scholarly ecosystem and scientific culture issues. This white paper will present these challenges and suggest practical solutions for elevating the role of software as a product of the research enterprise.