NAUTILUS: boosting Bayesian importance nested sampling with deep learning

We introduce a novel approach to boost the efficiency of the importance nested sampling (INS) technique for Bayesian posterior and evidence estimation using deep learning. Unlike rejection-based sampling methods such as vanilla nested sampling (NS) or Markov chain Monte Carlo (MCMC) algorithms, importance sampling techniques can use all likelihood evaluations for posterior and evidence estimation. However, for efficient importance sampling, one needs proposal distributions that closely mimic the posterior distributions. We show how to combine INS with deep learning via neural network regression to accomplish this task. We also introduce NAUTILUS, a reference open-source Python implementation of this technique for Bayesian posterior and evidence estimation. We compare NAUTILUS against popular NS and MCMC packages, including EMCEE, DYNESTY, ULTRANEST and POCOMC, on a variety of challenging synthetic problems and real-world applications in exoplanet detection, galaxy SED fitting and cosmology. In all applications, the sampling efficiency of NAUTILUS is substantially higher than that of all other samplers, often by more than an order of magnitude. Simultaneously, NAUTILUS delivers highly accurate results and needs fewer likelihood evaluations than all other samplers tested. We also show that NAUTILUS has good scaling with the dimensionality of the likelihood and is easily parallelizable to many CPUs.Comment: 15 pages, 10 figures, submitted to MNRAS; code available at https://github.com/johannesulf/nautilu

Constraints on Assembly Bias from Galaxy Clustering

We constrain the newly-introduced decorated Halo Occupation Distribution (HOD) model using SDSS DR7 measurements of projected galaxy clustering or r-band luminosity threshold samples. The decorated HOD is a model for the galaxy-halo connection that augments the HOD by allowing for the possibility of galaxy assembly bias: galaxy luminosity may be correlated with dark matter halo properties besides mass, Mvir. We demonstrate that it is not possible to rule out galaxy assembly bias using DR7 measurements of galaxy clustering alone. Moreover, galaxy samples with Mr < -20 and Mr < -20.5 favor strong central galaxy assembly bias. These samples prefer scenarios in which high-concentration are more likely to host a central galaxy relative to low-concentration halos of the same mass. We exclude zero assembly bias with high significance for these samples. Satellite galaxy assembly bias is significant for the faintest sample, Mr < -19. We find no evidence for assembly bias in the Mr < -21 sample. Assembly bias should be accounted for in galaxy clustering analyses or attempts to exploit galaxy clustering to constrain cosmology. In addition to presenting the first constraints on HOD models that accommodate assembly bias, our analysis includes several improvements over previous analyses of these data. Therefore, our inferences supersede previously-published results even in the case of a standard HOD analysis.Comment: 15 pages, 8 figures. To be submitted to MNRAS. Comments Welcome. Python scripts to perform this analysis and MCMC chains will all be made publicly availabl

Maturing Satellite Kinematics into a Competitive Probe of the Galaxy-Halo Connection

The kinematics of satellite galaxies moving in a dark matter halo are a direct probe of the underlying gravitational potential. Thus, the phase-space distributions of satellites represent a powerful tool to determine the galaxy-halo connection from observations. By stacking the signal of a large number of satellite galaxies this potential can be unlocked even for haloes hosting a few satellites on average. In this work, we test the impact of various modelling assumptions on constraints derived from analysing satellite phase-space distributions in the non-linear, 1-halo regime. We discuss their potential to explain the discrepancy between average halo masses derived from satellite kinematics and gravitational lensing previously reported. Furthermore, we develop an updated, more robust analysis to extract constraints on the galaxy-halo relation from satellite properties in spectroscopic galaxy surveys such as the SDSS. We test the accuracy of this approach using a large number of realistic mock catalogues. Furthermore, we find that constraints derived from such an analysis are complementary and competitive with respect to the commonly used galaxy clustering and galaxy-galaxy lensing observables.Comment: 24 pages, 15 figures; resubmitted to MNRAS after first referee repor

Updated Results on the Galaxy-Halo Connection from Satellite Kinematics in SDSS

We present new results on the relationship between central galaxies and dark matter haloes inferred from observations of satellite kinematics in the Sloan Digital Sky Survey (SDSS) DR7. We employ an updated analysis framework that includes detailed mock catalogues to model observational effects in SDSS. Our results constrain the colour-dependent conditional luminosity function (CLF) of dark matter haloes, as well as the radial profile of satellite galaxies. Confirming previous results, we find that red central galaxies live in more massive haloes than blue galaxies at fixed luminosity. Additionally, our results suggest that satellite galaxies have a radial profile less centrally concentrated than dark matter but not as cored as resolved subhaloes in dark matter-only simulations. Compared to previous works using satellite kinematics by More et al., we find much more competitive constraints on the galaxy-halo connection, on par with those derived from a combination of galaxy clustering and galaxy-galaxy lensing. We compare our results on the galaxy-halo connection to other studies using galaxy clustering and group catalogues, showing very good agreement between these different techniques. We discuss future applications of satellite kinematics in the context of constraining cosmology and the relationship between galaxies and dark matter haloes.Comment: 18 pages, 10 figures, submitted to MNRAS, comments welcom

Anisotropic Satellite Galaxy Quenching: A Unique Signature of Energetic Feedback by Supermassive Black Holes?

The quenched fraction of satellite galaxies is aligned with the orientation of the halo's central galaxy, such that on average, satellites form stars at a lower rate along the major axis of the central. This effect, called anisotropic satellite galaxy quenching (ASGQ), has been found in observational data and cosmological simulations. Analyzing the IllustrisTNG simulation, Mart\'in-Navarro et al. (2021) recently argued that ASGQ is caused by anisotropic energetic feedback and constitutes "compelling observational evidence for the role of black holes in regulating galaxy evolution." In this letter, we study the causes of ASGQ in state-of-the-art galaxy formation simulations to evaluate this claim. We show that cosmological simulations predict that on average, satellite galaxies along the major axis of the dark matter halo tend to have been accreted at earlier cosmic times and are hosted by subhalos of larger peak halo masses. As a result, a modulation of the quenched fraction with respect to the major axis of the central galaxy is a natural prediction of hierarchical structure formation. We show that ASGQ is predicted by the UniverseMachine galaxy formation model, a model without anisotropic feedback. Furthermore, we demonstrate that even in the IllustrisTNG simulation, anisotropic satellite accretion properties are the main cause of ASGQ. Ultimately, we argue that ASGQ is not a reliable indicator of supermassive black hole feedback in galaxy formation simulations and, thus, should not be interpreted as such in observational data.Comment: 7 pages, 4 figures; Submitted to ApJL; Comments welcome

Brightest galaxies as halo centre tracers in SDSS DR7

Determining the positions of halo centres in large-scale structure surveys is crucial for many cosmological studies. A common assumption is that halo centres correspond to the location of their brightest member galaxies. In this paper, we study the dynamics of brightest galaxies with respect to other halo members in the Sloan Digital Sky Survey DR7. Specifically, we look at the line-of-sight velocity and spatial offsets between brightest galaxies and their neighbours. We compare those to detailed mock catalogues, constructed from high-resolution, dark-matter-only $N$-body simulations, in which it is assumed that satellite galaxies trace dark matter subhaloes. This allows us to place constraints on the fraction $f_{\rm BNC}$ of haloes in which the brightest galaxy is not the central. Compared to previous studies we explicitly take into account the unrelaxed state of the host haloes, velocity offsets of halo cores and correlations between $f_{\rm BNC}$ and the satellite occupation. We find that $f_{\rm BNC}$ strongly decreases with the luminosity of the brightest galaxy and increases with the mass of the host halo. Overall, in the halo mass range $10^{13} - 10^{14.5} h^{-1} M_\odot$ we find $f_{\rm BNC} \sim 30\%$, in good agreement with a previous study by Skibba et al. We discuss the implications of these findings for studies inferring the galaxy--halo connection from satellite kinematics, models of the conditional luminosity function and galaxy formation in general.Comment: 24 pages, 15 figures. Accepted for publication in MNRA

Evidence for non-stellar rest-frame near-IR emission associated with increased star formation in galaxies at z∼1z \sim 1

We explore the presence of non-stellar rest-frame near-IR ($2-5 \ \mu \mathrm{m}$) emission in galaxies at $z \sim 1$. Previous studies identified this excess in relatively small samples and suggested that such non-stellar emission, which could be linked to the $3.3 \ \mu \mathrm{m}$ polycyclic aromatic hydrocarbons feature or hot dust emission, is associated with an increased star formation rate (SFR). In this Letter, we confirm and quantify the presence of an IR excess in a significant fraction of galaxies in the 3D-HST GOODS catalogs. By constructing a matched sample of galaxies with and without strong non-stellar near-IR emission, we find that galaxies with such emission are predominantly star-forming galaxies. Moreover, star-forming galaxies with an excess show increased mid- and far-IR and H$\alpha$ emission compared to other star-forming galaxies without. While galaxies with a near-IR excess show a larger fraction of individually detected X-ray active galactic nuclei (AGNs), an X-ray stacking analysis, together with the IR-colors and H$\alpha$ profiles, shows that AGNs are unlikely to be the dominant source of the excess in the majority of galaxies. Our results suggest that non-stellar near-IR emission is linked to increased SFRs and is ubiquitous among star-forming galaxies. As such, the near-IR emission might be a powerful tool to measure SFRs in the era of the James Webb Space Telescope.Comment: 6 pages, 5 figures, accepted for publication in ApJ

The Galaxy Clustering Crisis in Abundance Matching

Galaxy clustering on small scales is significantly under-predicted by sub-halo abundance matching (SHAM) models that populate (sub-)haloes with galaxies based on peak halo mass, $M_{\rm peak}$. SHAM models based on the peak maximum circular velocity, $V_{\rm peak}$, have had much better success. The primary reason $M_{\rm peak}$ based models fail is the relatively low abundance of satellite galaxies produced in these models compared to those based on $V_{\rm peak}$. Despite success in predicting clustering, a simple $V_{\rm peak}$ based SHAM model results in predictions for galaxy growth that are at odds with observations. We evaluate three possible remedies that could "save" mass-based SHAM: (1) SHAM models require a significant population of "orphan" galaxies as a result of artificial disruption/merging of sub-haloes in modern high resolution dark matter simulations; (2) satellites must grow significantly after their accretion; and (3) stellar mass is significantly affected by halo assembly history. No solution is entirely satisfactory. However, regardless of the particulars, we show that popular SHAM models based on $M_{\rm peak}$ cannot be complete physical models as presented. Either $V_{\rm peak}$ truly is a better predictor of stellar mass at $z\sim 0$ and it remains to be seen how the correlation between stellar mass and $V_{\rm peak}$ comes about, or SHAM models are missing vital component(s) that significantly affect galaxy clustering.Comment: 25 pages, 22 figures, submitted to MNRAS, comments welcom

The Immitigable Nature of Assembly Bias: The Impact of Halo Definition on Assembly Bias

Dark matter halo clustering depends not only on halo mass, but also on other properties such as concentration and shape. This phenomenon is known broadly as assembly bias. We explore the dependence of assembly bias on halo definition, parametrized by spherical overdensity parameter, $\Delta$. We summarize the strength of concentration-, shape-, and spin-dependent halo clustering as a function of halo mass and halo definition. Concentration-dependent clustering depends strongly on mass at all $\Delta$. For conventional halo definitions ($\Delta \sim 200\mathrm{m}-600\mathrm{m}$), concentration-dependent clustering at low mass is driven by a population of haloes that is altered through interactions with neighbouring haloes. Concentration-dependent clustering can be greatly reduced through a mass-dependent halo definition with $\Delta \sim 20\mathrm{m}-40\mathrm{m}$ for haloes with $M_{200\mathrm{m}} \lesssim 10^{12}\, h^{-1}\mathrm{M}_{\odot}$. Smaller $\Delta$ implies larger radii and mitigates assembly bias at low mass by subsuming altered, so-called backsplash haloes into now larger host haloes. At higher masses ($M_{200\mathrm{m}} \gtrsim 10^{13}\, h^{-1}\mathrm{M}_{\odot}$) larger overdensities, $\Delta \gtrsim 600\mathrm{m}$, are necessary. Shape- and spin-dependent clustering are significant for all halo definitions that we explore and exhibit a relatively weaker mass dependence. Generally, both the strength and the sense of assembly bias depend on halo definition, varying significantly even among common definitions. We identify no halo definition that mitigates all manifestations of assembly bias. A halo definition that mitigates assembly bias based on one halo property (e.g., concentration) must be mass dependent. The halo definitions that best mitigate concentration-dependent halo clustering do not coincide with the expected average splashback radii at fixed halo mass.Comment: 19 pages, 13 figures. Updated to published version. Main result summarized in Figure 1