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  1. Abstract

    Supermassive black holes (SMBHs) reside at the center of every massive galaxy in the local universe with masses that closely correlate with observations of their host galaxy, implying a connected evolutionary history. The population of binary SMBHs, which form following galaxy mergers, is expected to produce a gravitational-wave background (GWB) detectable by pulsar timing arrays (PTAs). PTAs are starting to see hints of what may be a GWB, and the amplitude of the emerging signal is toward the higher end of model predictions. Simulated populations of binary SMBHs can be constructed from observations of galaxies and are used to make predictions about the nature of the GWB. The greatest source of uncertainty in these observation-based models comes from the inference of the SMBH mass function, which is derived from observed host galaxy properties. In this paper, I undertake a new approach for inferring the SMBH mass function, starting from a velocity dispersion function rather than a galaxy stellar mass function. I argue that this method allows for a more direct inference by relying on a larger suite of individual galaxy observations as well as relying on a more “fundamental” SMBH mass relation. I find that the resulting binary SMBH population contains more massive systems at higher redshifts than previous models. Additionally, I explore the implications for the detection of individually resolvable sources in PTA data.

     
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  2. ABSTRACT

    It is difficult to accurately identify galaxy mergers and it is an even larger challenge to classify them by their mass ratio or merger stage. In previous work we used a suite of simulated mergers to create a classification technique that uses linear discriminant analysis to identify major and minor mergers. Here, we apply this technique to 1.3 million galaxies from the SDSS DR16 photometric catalogue and present the probability that each galaxy is a major or minor merger, splitting the classifications by merger stages (early, late, post-coalescence). We present publicly available imaging predictor values and all of the above classifications for one of the largest-yet samples of galaxies. We measure the major and minor merger fraction (fmerg) and build a mass-complete sample of galaxies, which we bin as a function of stellar mass and redshift. For the major mergers, we find a positive slope of fmerg with stellar mass and negative slope of fmerg with redshift between stellar masses of 10.5 < M*(log M⊙) < 11.6 and redshifts of 0.03 < z < 0.19. We are able to reproduce an artificial positive slope of the major merger fraction with redshift when we do not bin for mass or craft a complete sample, demonstrating the importance of mass completeness and mass binning. We determine that the positive trend of the major merger fraction with stellar mass is consistent with a hierarchical assembly scenario. The negative trend with redshift requires that an additional assembly mechanism, such as baryonic feedback, dominates in the local Universe.

     
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  3. Abstract

    Despite the importance of active galactic nuclei (AGNs) in galaxy evolution, accurate AGN identification is often challenging, as common AGN diagnostics can be confused by contributions from star formation and other effects (e.g., Baldwin–Phillips–Terlevich diagrams). However, one promising avenue for identifying AGNs is “coronal emission lines” (“CLs”), which are highly ionized species of gas with ionization potentials ≥100 eV. These CLs may serve as excellent signatures for the strong ionizing continuum of AGNs. To determine if CLs are in fact strong AGN tracers, we assemble and analyze the largest catalog of optical CL galaxies using the Sloan Digital Sky Survey's Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) catalog. We detect CL emission in 71 MaNGA galaxies, out of the 10,010 unique galaxies from the final MaNGA catalog, with ≥5σconfidence. In our sample, we measure [Nev]λ3347,λ3427, [Fevii]λ3586,λ3760,λ6086, and [Fex]λ6374 emission and crossmatch the CL galaxies with a catalog of AGNs that were confirmed with broad-line, X-ray, IR, and radio observations. We find that [Nev] emission, compared to [Fevii] and [Fex] emission, is best at identifying high-luminosity AGNs. Moreover, we find that the CL galaxies with the least dust extinction yield the most iron CL detections. We posit that the bulk of the iron CLs are destroyed by dust grains in the galaxies with the highest [Oiii] luminosities in our sample, and that AGNs in the galaxies with low [Oiii] luminosities are possibly too weak to be detected using traditional techniques.

     
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  4. Abstract

    Pulsar timing arrays (PTAs) are galactic-scale gravitational wave (GW) detectors. Each individual arm, composed of a millisecond pulsar, a radio telescope, and a kiloparsecs-long path, differs in its properties but, in aggregate, can be used to extract low-frequency GW signals. We present a noise and sensitivity analysis to accompany the NANOGrav 15 yr data release and associated papers, along with an in-depth introduction to PTA noise models. As a first step in our analysis, we characterize each individual pulsar data set with three types of white-noise parameters and two red-noise parameters. These parameters, along with the timing model and, particularly, a piecewise-constant model for the time-variable dispersion measure, determine the sensitivity curve over the low-frequency GW band we are searching. We tabulate information for all of the pulsars in this data release and present some representative sensitivity curves. We then combine the individual pulsar sensitivities using a signal-to-noise ratio statistic to calculate the global sensitivity of the PTA to a stochastic background of GWs, obtaining a minimum noise characteristic strain of 7 × 10−15at 5 nHz. A power-law-integrated analysis shows rough agreement with the amplitudes recovered in NANOGrav’s 15 yr GW background analysis. While our phenomenological noise model does not model all known physical effects explicitly, it provides an accurate characterization of the noise in the data while preserving sensitivity to multiple classes of GW signals.

     
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  5. ABSTRACT

    The International Pulsar Timing Array 2nd data release is the combination of data sets from worldwide collaborations. In this study, we search for continuous waves: gravitational wave signals produced by individual supermassive black hole binaries in the local universe. We consider binaries on circular orbits and neglect the evolution of orbital frequency over the observational span. We find no evidence for such signals and set sky averaged 95 per cent upper limits on their amplitude h95. The most sensitive frequency is 10 nHz with h95 = 9.1 × 10−15. We achieved the best upper limit to date at low and high frequencies of the PTA band thanks to improved effective cadence of observations. In our analysis, we have taken into account the recently discovered common red noise process, which has an impact at low frequencies. We also find that the peculiar noise features present in some pulsars data must be taken into account to reduce the false alarm. We show that using custom noise models is essential in searching for continuous gravitational wave signals and setting the upper limit.

     
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  6. Abstract The 15 yr pulsar timing data set collected by the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) shows positive evidence for the presence of a low-frequency gravitational-wave (GW) background. In this paper, we investigate potential cosmological interpretations of this signal, specifically cosmic inflation, scalar-induced GWs, first-order phase transitions, cosmic strings, and domain walls. We find that, with the exception of stable cosmic strings of field theory origin, all these models can reproduce the observed signal. When compared to the standard interpretation in terms of inspiraling supermassive black hole binaries (SMBHBs), many cosmological models seem to provide a better fit resulting in Bayes factors in the range from 10 to 100. However, these results strongly depend on modeling assumptions about the cosmic SMBHB population and, at this stage, should not be regarded as evidence for new physics. Furthermore, we identify excluded parameter regions where the predicted GW signal from cosmological sources significantly exceeds the NANOGrav signal. These parameter constraints are independent of the origin of the NANOGrav signal and illustrate how pulsar timing data provide a new way to constrain the parameter space of these models. Finally, we search for deterministic signals produced by models of ultralight dark matter (ULDM) and dark matter substructures in the Milky Way. We find no evidence for either of these signals and thus report updated constraints on these models. In the case of ULDM, these constraints outperform torsion balance and atomic clock constraints for ULDM coupled to electrons, muons, or gluons. 
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    Free, publicly-accessible full text available June 29, 2024
  7. Abstract We report multiple lines of evidence for a stochastic signal that is correlated among 67 pulsars from the 15 yr pulsar timing data set collected by the North American Nanohertz Observatory for Gravitational Waves. The correlations follow the Hellings–Downs pattern expected for a stochastic gravitational-wave background. The presence of such a gravitational-wave background with a power-law spectrum is favored over a model with only independent pulsar noises with a Bayes factor in excess of 10 14 , and this same model is favored over an uncorrelated common power-law spectrum model with Bayes factors of 200–1000, depending on spectral modeling choices. We have built a statistical background distribution for the latter Bayes factors using a method that removes interpulsar correlations from our data set, finding p = 10 −3 (≈3 σ ) for the observed Bayes factors in the null no-correlation scenario. A frequentist test statistic built directly as a weighted sum of interpulsar correlations yields p = 5 × 10 −5 to 1.9 × 10 −4 (≈3.5 σ –4 σ ). Assuming a fiducial f −2/3 characteristic strain spectrum, as appropriate for an ensemble of binary supermassive black hole inspirals, the strain amplitude is 2.4 − 0.6 + 0.7 × 10 − 15 (median + 90% credible interval) at a reference frequency of 1 yr −1 . The inferred gravitational-wave background amplitude and spectrum are consistent with astrophysical expectations for a signal from a population of supermassive black hole binaries, although more exotic cosmological and astrophysical sources cannot be excluded. The observation of Hellings–Downs correlations points to the gravitational-wave origin of this signal. 
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    Free, publicly-accessible full text available June 29, 2024
  8. Abstract We present observations and timing analyses of 68 millisecond pulsars (MSPs) comprising the 15 yr data set of the North American Nanohertz Observatory for Gravitational Waves (NANOGrav). NANOGrav is a pulsar timing array (PTA) experiment that is sensitive to low-frequency gravitational waves (GWs). This is NANOGrav’s fifth public data release, including both “narrowband” and “wideband” time-of-arrival (TOA) measurements and corresponding pulsar timing models. We have added 21 MSPs and extended our timing baselines by 3 yr, now spanning nearly 16 yr for some of our sources. The data were collected using the Arecibo Observatory, the Green Bank Telescope, and the Very Large Array between frequencies of 327 MHz and 3 GHz, with most sources observed approximately monthly. A number of notable methodological and procedural changes were made compared to our previous data sets. These improve the overall quality of the TOA data set and are part of the transition to new pulsar timing and PTA analysis software packages. For the first time, our data products are accompanied by a full suite of software to reproduce data reduction, analysis, and results. Our timing models include a variety of newly detected astrometric and binary pulsar parameters, including several significant improvements to pulsar mass constraints. We find that the time series of 23 pulsars contain detectable levels of red noise, 10 of which are new measurements. In this data set, we find evidence for a stochastic GW background. 
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    Free, publicly-accessible full text available June 29, 2024