Sloan Digital Sky Survey Research Articles

AGN populations in the local Universe: Their alignment with the main sequence, stellar population characteristics, accretion efficiency, and the impact of AGN feedback

In this study, we used a sample of 338 galaxies – within the redshift range of 0.02 < z < 0.1 drawn from the Sloan Digital Sky Survey (SDSS) – for which there are available classifications based on their emission line ratios. We identified and selected Compton-thick (CT) AGN through the use of X-ray and infrared luminosities at 12 μm. We constructed the spectral energy distributions (SEDs) for all sources and fit them using the CIGALE code to derive properties related to both the AGN and host galaxies. Employing stringent criteria to ensure the reliability of SED measurements, our final sample comprises 14 CT AGN, 118 Seyfert 2 (Sy2), 82 composite, and 124 low-ionization nuclear emission-line regions (LINER) galaxies. Our analysis reveals that, irrespective of their classification, the majority of the sources lie below the star-forming main sequence (MS). Additionally, a lower level of AGN activity is associated with a closer positioning to the MS. Using the Dn4000 spectral index as a proxy for the age of stellar populations, we observe that, compared to other AGN classes, LINERs exhibit the oldest stellar populations. Conversely, CT sources are situated in galaxies with the youngest stellar populations. Furthermore, LINER and composite galaxies tend to show the lowest accretion efficiency, while CT AGN, on average, display the most efficient accretion among the four AGN populations. Our findings are consistent with a scenario in which the different AGN populations might not originate from the same AGN activity burst. Early triggers in gas-rich environments can create high-accretion-rate supermassive black holes (SMBHs), leading to a progression from CT to Sy2, while later triggers in gas-poor stages result in low-accretion-rate SMBHs like those found in LINERs.

Full shape cosmology analysis from BOSS in configuration space using neural network acceleration

Recently, a new wave of full modeling analyses have emerged within the Large-Scale Structure community, leading mostly to tighter constraints on the estimation of cosmological parameters, when compared with standard approaches used over the last decade by collaboration analyses of stage III experiments. However, the majority of these full-shape analyses have primarily been conducted in Fourier space, with limited emphasis on exploring the configuration space. Investigating n-point correlations in configuration space demands a higher computational cost compared to Fourier space because it typically requires an additional integration step. This can pose a limitation when using these approaches, especially when considering higher-order statistics. One avenue to mitigate the high computation time is to take advantage of neural network acceleration techniques. In this work, we present a full shape analysis of Sloan Digital Sky Survey III/BOSS in configuration space using a neural network accelerator. We show that the efficacy of the pipeline is enhanced by a time factor 103 without sacrificing precision, making it possible to reduce the error associated with the surrogate modeling to below 10-2 percent which is compatible with the precision required for current stage IV experiments such as DESI. We find Ω m = 0.286±0.009, H 0 = 68.8±1.2 kms-1Mpc-1 and A s × 109 = 2.09 +0.25 -0.29. Our results on public BOSS data are in good agreement with BOSS official results and compatible with other independent full modeling analyses. We explore relaxing the prior on ωb and varying ns , without significant changes in the mean values of the cosmological parameters posterior distributions, but enlarging their widths. Finally, we explore the information content of the multipoles when constraining cosmological parameters.

BreakBRD Galaxies: Evolutionary Clues through an Analysis of Gas Content

By combining newly obtained deep Green Bank Telescope 21 cm observations with optical spectroscopic data, we present an analysis of the gas content of break bulges in red disks (breakBRD) galaxies, a population denoted by their blue star-forming centers and red quenched disks that do not appear to follow the typical inside-out evolution of spiral galaxies. We confirm previous results that the neutral atomic hydrogen (H i) gas fractions of breakBRDs are, on average, lower than those of typical galaxies on the star-forming sequence (SFS), and find that their H i fractions are generally higher than green valley (GV) galaxies. H i depletion times for breakBRDs are roughly an order of magnitude lower than those of SFS galaxies, in stark contrast with GV galaxies that typically have much longer depletion times than SFS galaxies. The nuclear gas-phase metallicities of breakBRDs have a broader distribution than SFS galaxies and are skewed toward slightly above-average values. BreakBRDs are systematically offset from the baryonic Tully–Fisher relation toward lower baryonic mass at a given rotation velocity. They also have higher typical H i asymmetries than SFS galaxies, and of those galaxies with spatially resolved gas velocity fields from the Sloan Digital Sky Survey IV Mapping Nearby Galaxies at Apache Point Observatory survey, two-thirds are either highly distorted or completely misaligned relative to the stellar disk. Evidence supports a scenario where breakBRDs are in an early phase of quenching, and there is mixed evidence that their behavior is related to past merger activity.

Optimal constraints on Primordial non-Gaussianity with the eBOSS DR16 quasars in Fourier space

We present constraints on the amplitude of local Primordial Non-Gaussianities (PNG), f NL, using the quasar sample in the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16). We analyze the power spectrum monopole, testing for the presence of scale-dependent galaxy bias induced by local PNG. Our analysis makes use of optimal redshift weights that maximize the response of the quasar sample to the possible presence of non-zero PNG. We find -4 < f NL < 27 at 68% confidence level, which is among the strongest bounds with Large Scale Structure data. The optimal analysis reduces the error bar by ~10% compared to the standard one, but this improvement is lower than the one expected from previous forecasts. In addition, the larger volume of this dataset, when compared to previous releases of the eBOSS quasar catalog, does not always correspond to a reduction of the final uncertainty on local PNG. This could suggest the presence of still unknown systematic effects in the data.If the quasars have a lower response to local PNG, our optimal constraint becomes -23 < f NL < 21 at 68%, with an improvement of 30% over standardanalyses. We alsoshow how to use the optimal weights to put data-driven priors on the sample's response tolocal PNG.

Ionized gas in quiescent galaxies: Temperature measurement and constraint on the ionization source

In non-star-forming, passively evolving galaxies, regions with emission lines dominated by low-ionization species are classified as low-ionization emission regions (LIERs). The ionization mechanism behind such regions has long been a mystery. Active galactic nuclei (AGNs), which were once believed to be the source, have been found not to be the dominant mechanism, especially in regions distant from the galaxy nuclei. The remaining candidates, photoionization by post-asymptotic giant branch (pAGB) stars and interstellar shocks can only be distinguished with in-depth analysis. As the temperature predictions of these two models differ, temperature measurements can provide strong constraints on this puzzle. We selected a sample of 2795 quiescent red-sequence galaxies from the Sloan Digital Sky Survey IV (SDSS-IV) Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. We divided the sample spectra into three groups based on the flux ratio, and utilized stacking techniques to improve the signal-to-noise ratio of the observed spectra. We determined the temperature of and through their temperature-sensitive emission line ratios. Subsequently, we compared the measured temperatures with predictions from different models. The results demonstrate consistency with the interstellar shock model with pre-shock density n = 1 $ and solar metallicity, thus supporting shocks as the dominant ionization source of LIERs. Additionally, we also find that the interstellar dust extinction value measured through the Balmer decrement appears to be larger than that implied by the forbidden line ratios of low-ionization lines.

Classification of Blazars by Activity Types

We have carried out a spectral classification by the Activity Types for all sample of Blazars from the BZCAT v.5 Catalogue, namely the BZB, BZG, BZQ and BZU type objects. The classification is based on the Sloan Digital Sky Survey (SDSS) homogeneous medium-resolution optical spectroscopy and along with the standard BPT-type diagnostic diagrams, we have applied our newly introduced fine classification scheme with subtypes of AGN and considering many more features. Out of 3561 BZCAT objects, 1363 (38.3 %) having SDSS spectra were classified. After the new classification, 749 (54.9 %) of 1363 objects have changed their optical class.

Galaxy and Mass Assembly (GAMA): Stellar-to-dynamical Mass Relation. II. Peculiar Velocities

Empirical correlations connecting starlight to galaxy dynamics (e.g., the fundamental plane (FP) of elliptical/quiescent (Q) galaxies and the Tully–Fisher relation of spiral/star-forming (SF) galaxies) provide cosmology-independent distance estimation and are central to local Universe cosmology. In this work, we introduce the mass hyperplane (MH), which is the stellar-to-dynamical mass relation (M ⋆/M dyn) recast as a linear distance indicator. Building on recent FP studies, we show that both SF and Q galaxies follow the same empirical MH, then use this to measure the peculiar velocities (PVs) for a sample of 2496 galaxies at z < 0.12 from GAMA. The limiting precision of MH-derived distance/PV estimates is set by the intrinsic scatter in size, which we find to be ≈0.1 dex for both Q and SF galaxies (when modeled independently) and ≈0.11 dex when all galaxies are modeled together, showing that the MH is as good as the FP. To empirically validate our framework and distance/PV estimates, we compare the inferred distances to groups as derived using either Q or SF galaxies. A good agreement is obtained with no discernible bias or offset, having a scatter of ≈0.05 dex ≈12% in distance. Further, we compare our PV measurements for the Q galaxies to the previous PV measurements of the galaxies in common between GAMA and the Sloan Digital Sky Survey, which shows similarly good agreement. Finally, we provide comparisons of PV measurements made with the FP and the MH, then discuss possible improvements in the context of upcoming surveys such as the 4MOST Hemisphere Survey.

Constraining modified gravity scenarios with the 6dFGS and SDSS galaxy peculiar velocity data sets

ABSTRACT The detailed nature of dark energy remains a mystery, leaving the possibility that its effects might be explained by changes to the laws of gravity on large scales. The peculiar velocities of galaxies directly trace the strength of gravity on cosmic scales and provide a means to further constrain such models. We generate constraints on different scenarios of gravitational physics by measuring peculiar velocity (PV) and galaxy clustering two-point correlations, using redshifts and distances from the 6-degree Field Galaxy Survey and the Sloan Digital Sky Survey PV samples, and fitting them against models characteristic of different cosmologies. Our best-fitting results are all found to be in statistical agreement with general relativity, in which context we measure the low-redshift growth of structure to be $f\sigma _8 = 0.329^{+0.081}_{-0.083}$, consistent with the prediction of the standard Lambda cold dark matter model. We also fit the modified gravity scenarios of Dvali–Gabadadze–Porrati and a Hu–Sawicki model of $f(R)$ gravity, finding the $2\sigma$ limit of their characteristic parameters to be $r_{\rm c}H_0/c\gt 6.987$ and $-\log _{10}(|f_{R0}|)\gt 4.703$, respectively. These constraints are comparable to other literature values, though it should be noted that they are significantly affected by the prior adopted for their characteristic parameters. When applied to much larger upcoming PV surveys such as DESI, this method will place rapidly improving constraints on modified gravity models of cosmic expansion and growth.

A Survey of Galaxy Pairs in the SDSS Photometric Images based on Faster-RCNN

Galaxy pairs hold significant importance in understanding the evolution of galaxies, and the extensive search for a large sample of galaxy pairs is meaningful. In this article, we develop a deep learning-based approach for the search of galaxy pairs and conduct a comprehensive search on Sloan Digital Sky Survey (SDSS) images. In nine million photometric images, 17,965 physical galaxy pairs with spectral or photometric redshifts are detected. Four sets of results are provided, including physical pairs determined by two spectral redshifts, two photometric redshifts, one spectral redshift, and one photometric redshift, and visual irregular pairs that have no precise redshift information but can be inferred as physical galaxy pairs based on the morphological changes. Then their morphological and physical characteristics are explored, the redshifts of most targets are around 0.1, and as the redshift difference between two galaxies increases, the number of galaxy pairs gradually reduces. The distributions of star formation rate (SFR) are not the same for different morphologies of galaxy pairs, irregular pairs have higher SFR than the other three types, and statistics indicate that the SFR of galaxies depends on both nearby galaxies and internal properties. Color and stellar mass are also key properties of galaxies which can reflect the status of galaxy pairs. Compared to other surveys, a greater number of galaxy pair targets are detected, and this is also the first extensive detection of galaxy pairs in SDSS images using photometric redshifts. These galaxy pair samples can greatly aid in the study of galaxy evolution.

Automatic Search for Low-surface-brightness Galaxies from Sloan Digital Sky Survey Images Using Deep Learning

Low-surface-brightness (LSB) galaxies play a crucial role in our understanding of galaxy evolution and dark matter cosmology. However, efficiently detecting them in large-scale surveys is challenging, due to their dim appearance. In this study, we propose a two-step detection method based on deep learning to address this issue. First, an object detection model called GalCenterNet was designed to detect LSB galaxy candidates in astronomical images. The model was trained using a data set of 665 Sloan Digital Sky Survey (SDSS) images, which contained 667 LSB galaxies. On the test set, the model achieved an accuracy of 95.05% and a recall of 96.00%. Next, an anomaly detection technique known as Deep Support Vector Data Description was applied to identify abnormal sources, thus refining the LSB candidates. By applying the two-step detection method to SDSS images, we have obtained a sample of 37,536 LSB galaxy candidates. This wide-area sample contains diverse and abundant LSB galaxies, which are valuable for studying the properties of LSB galaxies and the role that the environment plays in their evolution. The proposed detection method enables end-to-end detection from the SDSS images to the final detection results. This approach will be further employed to efficiently identify objects in the upcoming Chinese Survey Space Telescope sky survey.

Automating galaxy morphology classification using k-nearest neighbours and non-parametric statistics

ABSTRACT Morphology is a fundamental property of any galaxy population. It is a major indicator of the physical processes that drive galaxy evolution and in turn the evolution of the entire Universe. Historically, galaxy images were visually classified by trained experts. However, in the era of big data, more efficient techniques are required. In this work, we present a k-nearest neighbours based approach that utilizes non-parametric morphological quantities to classify galaxy morphology in Sloan Digital Sky Survey images. Most previous studies used only a handful of morphological parameters to identify galaxy types. In contrast, we explore 1023 morphological spaces (defined by up to 10 non-parametric statistics) to find the best combination of morphological parameters. Additionally, while most previous studies broadly classified galaxies into early types and late types or ellipticals, spirals, and irregular galaxies, we classify galaxies into 11 morphological types with an average accuracy of ${\sim} 80\!-\!90 \, {{\rm per\, cent}}$ per T-type. Our method is simple, easy to implement, and is robust to varying sizes and compositions of the training and test samples. Preliminary results on the performance of our technique on deeper images from the Hyper Suprime-Cam Subaru Strategic Survey reveal that an extension of our method to modern surveys with better imaging capabilities might be possible.

Constraining holographic dark energy and analyzing cosmological tensions

We investigate cosmological constraints on the holographic dark energy (HDE) using the state-of-the-art cosmological datasets: Planck CMB angular power spectra and weak lensing power spectra, Atacama Cosmology Telescope (ACT) temperature power spectra, baryon acoustic oscillation (BAO) and redshift-space distortion (RSD) measurements from six-degree-field galaxy survey and Sloan Digital Sky Survey (DR12 & DR16) and the Cepheids-Supernovae measurement from SH0ES team (R22). We also examine the HDE model and ΛCDM with and without Neff (effective number of relativistic species) being treated as a free parameter. We find that the HDE model can relieve the tensions of H0 and S8 to certain degrees. With “Planck+ACT+BAO+RSD” datasets, the constraints are H0=69.70±1.39km s−1Mpc−1 and S8=0.823±0.011 in HDE model, which brings down the Hubble tension down to 1.92σ confidence level (C.L.) and the S8 tension to (1−2)σ C.L. By adding the R22 data, their values are improved as H0=71.86±0.93km s−1Mpc−1 and S8=0.813±0.010, which further brings the Hubble tension down to 0.85σ C.L. and relieves the S8 tension. We also quantify the goodness-of-fit of different models with Akaike information criterion (AIC) and Bayesian information criterion (BIC), and find that the HDE agrees with the observational data better than the ΛCDM and other extended models (treating Neff as free for fitting).

Central oxygen abundances in the spiral galaxies of the MaNGA survey: Galaxies with central starbursts

We examine whether there are deviations of the local central oxygen abundances in spiral galaxies from the general metallicity gradients. We compare the values of the central intersect oxygen abundances estimated from the metallicity gradient based on the integral field unit (IFU) spectroscopy from the Mapping Nearby Galaxies at the Apache Point Observatory (MaNGA) survey and the local central oxygen abundances obtained from the single-fibre observations from the Sloan Digital Sky Survey (SDSS). Special attention is placed on galaxies with recent and currently ongoing central starbursts (cSB galaxies). We selected a sample of 30 cSB galaxies from our total sample of 381 MaNGA galaxies, using the decrease in the D$_ n $4000 index (a stellar age indicator) in the circumnuclear region as the selection criterion. We found that the local central oxygen abundances follow the general metallicity gradients in the galaxies well and agree with the central intersect abundances within uncertainties of the central abundances determinations. Starbursts in the centres of cSB galaxies do not produce noticeable oxygen enrichments. The central starbursts imply that an appreciable amount of gas is present at the centres of cSB galaxies. The gas at the centre of galaxy can serve not only as a raw material for the star formation, but also as a fuel for the activity of the galactic nucleus (AGN). We found that the AGN is the main source of the ionising radiation at the centres of six cSB galaxies in our sample.

Ensemble Variability Properties of Active Galactic Nuclei in the SDSS DR17

We present the results from a study of ∼9600 broadline-selected active galactic nuclei (AGNs) with host galaxies detected from the Sloan Digital Sky Survey (SDSS) Data Release 17. We compute ensemble variability statistics based on a comparison of the original SDSS photometric data with spectrophotometric measurements obtained days to decades later in the Sloan g, r, and i bands. Galaxy and AGN templates have been fitted to the SDSS spectra to isolate the AGN component from the host galaxy. The sources have absolute magnitudes in the range −24 < M i < −18 and lie at redshifts less than z ∼ 0.9. A variability analysis reveals that the anticorrelation between luminosity and variability amplitude continues down to log(Lbol [erg s−1]) = 43.5, demonstrating that the relationship extends by 4 orders of magnitude in AGN luminosity. To further explore the connection between AGN luminosity and variability, we determine the black hole mass and the accretion rate through measurement of the Hβ line width and the monochromatic luminosity at rest frame 5100 Å. Our results suggest that the accretion rate is the dominant parameter impacting the amplitude of variability and that the anticorrelation between the accretion rate and amplitude extends to rates as low as 1% Eddington. Moreover, we also identify an anticorrelation between the variability amplitude and black hole mass, with the correlation appearing strongest among the AGNs with low accretion rates.

YOLOX-CS: An Automatic Search Algorithm for Low Surface Brightness Galaxies

The characteristics of Low Surface Brightness Galaxies (LSBGs) are very important for understanding the overall characteristics of galaxies. It is of great significance to search and expand the samples of Low Surface Brightness Galaxies by modern machine learning, especially deep learning algorithm. LSBGs are difficult to discern automatically and accurately with traditional methods because of their obscure features. However, deep learning does have the advantage of automatically identifying complex and effective features. To solve this problem, an algorithm named You Only Look Once version X-CS (YOLOX-CS) is proposed to search LSBG in large sample sky survey. Firstly, five classical target detection algorithms are compared through experiments and the optimal YOLOX algorithm is selected as the basic algorithm. Then, the YOLOX-CS framework is constructed by combining different attention mechanisms and different optimizers. The data set uses images from the Sloan Digital Sky Survey (SDSS), labelled from LSBG in the α.40-SDSS DR7 (the cross coverage area of 40% HI Arecibo Legacy Fast ALFA Survey and SDSS Data Release7) survey. Due to the small number of samples in this data set, Deep Convolutional Generative Adversarial Networks (DCGAN) model is used to expand the experimental test data. After comparing with a series of target detection algorithms, YOLOX-CS has a good test result in searching LSBG recall rate and Average Precision (AP) value in two data sets before and after expansion. The recall rate and AP value in the test set without expansion data set reach 97.75% and 97.83%, respectively. In the expanded data set of DCGAN model, under the same test set, the recall rate reaches 99.10% and the AP value reaches 98.94%, which proves that the algorithm has excellent performance in LSBG search. Finally, the algorithm is applied to SDSS photometric data, and 765 LSBG candidates are obtained.

Study of Double-mode RR Lyrae Stars in the Stripe 82 Region Using SDSS and ZTF

RRd stars are a subclass of RR Lyrae stars that pulsate simultaneously in the fundamental and the first-overtone radial modes. We report the analysis of 10 RRd stars discovered in the Sloan Digital Sky Survey (SDSS) Stripe 82 region of the Galactic halo using SDSS and Zwicky Transient Facility data. By combining the two data sets, we constructed ∼23 yr long lightcurves in gri bands, and conclude that out of 10, 9 were the classical RRd stars and 1 was the anomalous RRd star. We also observed the long-term variation, the Blazhko effect, in 3 classical RRd stars out of 10 stars, giving an incidence rate of 30%. The shortest Blazhko period observed was 226.4 ± 0.8 days and the longest was 2799 ± 75 days.

Mg/Fe] and variable initial mass function: Revision of [α/Fe] for massive galaxies

Observations of nearby massive galaxies have revealed that they are older and richer in metals and magnesium than their low-mass counterparts. In particular, the overabundance of magnesium compared to iron, [Mg/Fe], is interpreted to reflect the short star formation history that the current massive galaxies underwent early in the Universe. We present a systematic revision of the [Mg/Fe] – velocity dispersion (σ) relation based on stacked spectra of early-type galaxies with a high signal-to-noise ratio from the Sloan Digital Sky Survey. Using the penalized pixel-fitting (pPXF) method and the MILES single stellar population models, we fit a wide optical wavelength range to measure the net α-abundance. The combination of pPXF and α-enhanced MILES models incorrectly leads to an apparently decreasing trend of [α/Fe] with velocity dispersion. We interpret this result as a consequence of variations in the individual abundances of the different α-elements. This warrants caution for a naive use of full spectral fitting algorithms paired with stellar population models that do not take individual elemental abundance variations into account, especially when deriving averaged quantities such as the mean [α/Fe] of a stellar population. In addition, and based on line-strength measurements, we quantify the impact of a non-universal initial mass function on the recovered abundance pattern of galaxies. In particular, we find that a simultaneous fit of the slope of the initial mass function and the [Mg/Fe] results in a shallower [Mg/Fe]–σ relation. Therefore, our results suggest that star formation in massive galaxies lasted longer than what has been reported previously, although it still occurred significantly faster than in the solar neighbourhood.

Black Hole–Halo Mass Relation from UNIONS Weak Lensing

This Letter presents, for the first time, direct constraints on the black hole–halo mass relation using weak gravitational-lensing measurements. We construct type I and type II active galactic nucleus (AGN) samples from the Sloan Digital Sky Survey, with a mean redshift of 0.4 (0.1) for type I (type II) AGNs. This sample is cross correlated with weak-lensing shear from the Ultraviolet Near Infrared Optical Northern Survey. We compute the excess surface mass density of the halos associated with 36,181 AGNs from 94,308,561 lensed galaxies and fit the halo mass in bins of black hole mass. We find that more massive AGNs reside in more massive halos. The relation between halo mass and black hole mass is well described by a power law of slope 0.6 for both type I and type II samples, in agreement with models that link black hole growth to baryon feedback. We see no dependence on AGN type or redshift in the black hole–halo mass relation below a black hole mass of 108.5 M ⊙. Above that mass, we find more massive halos for the low-z type II sample compared to the high-z type I sample, but this difference may be interpreted as systematic error in the black hole mass measurements. Our results are consistent with previous measurements for non-AGN galaxies. At a fixed black hole mass, our weak-lensing halo masses are consistent with galaxy rotation curves but significantly lower than galaxy-clustering measurements. Finally, our results are broadly consistent with state-of-the-art hydrodynamical cosmological simulations, providing a new constraint for black hole masses in simulations.

Peculiar Velocity Reconstruction from Simulations and Observations Using Deep Learning Algorithms

In this paper, we introduce a U-Net model of deep learning algorithms for reconstructions of the 3D peculiar velocity field, which simplifies the reconstruction process with enhanced precision. We test the adaptability of the U-Net model with simulation data under more realistic conditions, including the redshift space distortion effect and halo mass threshold. Our results show that the U-Net model outperforms the analytical method that runs under ideal conditions, with a 16% improvement in precision, 13% in residuals, 18% in correlation coefficient, and 27% in average coherence. The deep learning algorithm exhibits exceptional capacities to capture velocity features in nonlinear regions and substantially improve reconstruction precision in boundary regions. We then apply the U-Net model trained under Sloan Digital Sky Survey (SDSS) observational conditions to the SDSS Data Release 7 data for observational 3D peculiar velocity reconstructions.

Properties of Nuclear Star Clusters in Low Surface Brightness Galaxies

Using the Systematically Measuring Ultra-Diffuse Galaxies and Sloan Digital Sky Survey catalogs and our own reprocessing of the Legacy Survey imaging, we investigate the properties of nuclear star clusters (NSCs) in galaxies having central surface brightnesses as low as 27 mag arcsec−2. We identify 273 (123 with known redshift) and 32 NSC-bearing galaxies in the two samples, respectively, where we require candidate NSCs to have a separation of less than 0.10r e from the galaxy center. We find that galaxies with low central surface brightness (μ 0,g > 24 mag arcsec−2) are more likely to contain an NSC if they (1) have a higher stellar mass, (2) have a higher stellar-to-total mass ratio, (3) have a brighter central surface brightness, (4) have a larger axis ratio, or (5) lie in a denser environment. Because of the correlations among these various quantities, it is likely that only one or two are true physical drivers. We also find scaling relations for the NSC mass with stellar mass (M NSC/ M⊙=106.02±0.03(M*,gal/108 M⊙)0.77±0.04 ) and halo mass (M NSC/ M⊙=106.11±0.05(Mh,gal/1010 M⊙)0.92±0.05 ), although it is the scaling with halo mass that is consistent with a direct proportionality. In galaxies with an NSC, M NSC ≈ 10−4 M h,gal. This proportionality echoes the finding of a direct proportionality between the mass (or number) of globular clusters (GCs) in galaxies and the galaxy’s total mass. These findings favor a related origin for GCs and NSCs.