Search for: All records

Abstract Pulsar timing arrays have recently found evidence for nanohertz gravitational waves that are consistent with being produced by a cosmological population of binary supermassive black holes (SMBHs). However, the amplitude of this gravitational-wave background is larger than predicted from theoretical and empirical models of SMBH binary populations. We investigate preferential accretion onto the secondary, less massive SMBH of the binary as a potential solution to this discrepancy. We carry out the first observationally based analysis of the effect of preferential accretion on the SMBH binary population, and we find that preferential accretion onto the secondary SMBH increases the binary SMBH mass ratio, causing many minor galaxy mergers to lead to major SMBH mergers. The fraction of SMBH mergers that are major mergers increases by a factor of 2–3 when preferential accretion is included. Further, we find that only a small amount of preferential accretion (10% total SMBH mass growth) is needed to bring the predicted gravitational-wave background amplitude into agreement with observations. Preferential accretion has an even larger effect on gravitational-wave signals detected by LISA, which will probe SMBH binaries at higher redshifts where the environment is more gas-rich, and can also help explain the rapid buildup of overmassive black holes at high redshifts observed by the James Webb Space Telescope. It also shortens the time to the first detection of an individual SMBH binary emitting continuous waves. Preferential accretion strengthens the gravitational-wave signals produced by any binary embedded in a circumbinary disk, including LIGO sources. 

Abstract Supermassive black holes (SMBHs) with dynamically measured masses have shown empirical correlations with host galaxy properties. These correlations are often the only method available to estimate SMBH masses and gather statistics for large galaxy populations across a range of redshifts, even though the scaling relations themselves are derived from a small subset of nearby galaxies. Depending on the scaling relation used, estimated SMBH masses can vary significantly. The most widely used scaling relations are theM_BH–M_bulgeandM_BH–σrelations, whereM_bulgeis galaxy bulge mass andσis the bulge velocity dispersion. In this paper, we determine how severely the choice of scaling relation impacts SMBH mass estimates for different subsets of a large galaxy population. For this analysis, we use a sample of ∼400,000 galaxies, including 1240 Type 1 active galactic nuclei from the Sloan Digital Sky Survey. We calculate SMBH masses fromM_BH–M_bulgeandM_BH–σand compare to single-epoch virial SMBH masses from broad-line Hβ, which are derived independently of black hole–host galaxy scaling relations. We find that SMBH masses derived from the single-epoch virial relation for Hβare better reproduced byM_BH–σthanM_BH–M_bulge. Finally, in cases whereσandM_bulgecannot be measured directly, we show that it is possible to inferσfrom photometry with more accuracy than we can inferM_bulge. 

Abstract Spectroscopic observations of the quasar J0950+5128 spanning 22 yr reveal monotonic radial velocity variations in its broad Hβemission line. Moreover, the line profile becomes broader over time, necessitating careful measurements. We present robust Hβvelocity shift measurements obtained via cross correlation, applied to both the full spectra and to isolated broad Hβcomponents derived from spectral decomposition. We also examine the light curves for variability consistent with the spectroscopic trends. Using Lomb–Scargle periodogram analysis, we find no significant periodic signal. We consider several interpretations for the observed changes, including a binary supermassive black hole, dust-cloud obscuration, outflows, a recoiling black hole, and a single perturbed, disk-like broad-line region (BLR). We deem the binary and perturbed BLR scenarios to be physically plausible. The binary interpretation is the only one for which we can immediately compare a physical model to the available data. Thus, we incorporate radial velocity “jitter” to emulate typical quasar variability and fit the radial velocity curve with a Keplerian model to examine whether it can reproduce the observations. In this context, the available observations trace only a segment of the putative orbit. The fit yields a period of 33 yr (observed frame) and an eccentricity of 0.65, with lower limits on the semimajor axis and black hole mass of 10⁻² pc and 10⁷ M_⊙, respectively. Thus, J0950+5128 is a binary candidate deserving further study. The single, perturbed BLR interpretation remains viable but requires additional observations and modeling for further evaluation. Continued monitoring is, therefore, essential. 

Abstract Pulsar timing arrays (PTAs) are sensitive to low-frequency gravitational waves (GWs), which induce correlated changes in millisecond pulsars’ timing residuals. PTA collaborations around the world have recently announced evidence of a nanohertz gravitational wave background (GWB), which may be produced by a population of supermassive black hole binaries (SMBHBs). The GWB is often modeled as following a power-law power spectral density (PSD); however, a GWB produced by a cosmological population of SMBHBs is expected to have a more complex power spectrum due to the discrete nature of the sources. In this paper, we investigate using at-process PSD to model the GWB, which allows us to fit for both the underlying power-law amplitude and spectral index as well as deviations from that power law, which may be produced by individual nearby binaries. We create simulated data sets based on the properties of the NANOGrav 15 yr data set, and we demonstrate that thet-process PSD can accurately recover the PSD when deviations from a power law are present. With longer timed data sets and more pulsars, we expect the sensitivity of our PTAs to improve, which will allow us to precisely measure the PSD of the GWB and study the sources producing it. 

Abstract While supermassive black hole (SMBH) binaries are not the only viable source for the low-frequency gravitational wave background (GWB) signal evidenced by the most recent pulsar timing array (PTA) data sets, they are expected to be the most likely. Thus, connecting the measured PTA GWB spectrum and the underlying physics governing the demographics and dynamics of SMBH binaries is extremely important. Previously, Gaussian processes (GPs) and dense neural networks have been used to make such a connection by being built as conditional emulators; their input is some selected evolution or environmental SMBH binary parameters and their output is the emulated mean and standard deviation of the GWB strain ensemble distribution over many Universes. In this paper, we use a normalizing flow (NF) emulator that is trained on the entirety of the GWB strain ensemble distribution, rather than only mean and standard deviation. As a result, we can predict strain distributions that mirror underlying simulations very closely while also capturing frequency covariances in the strain distributions as well as statistical complexities such as tails, non-Gaussianities, and multimodalities that are otherwise not learnable by existing techniques. In particular, we feature various comparisons between the NF-based emulator and the GP approach used extensively in past efforts. Our analyses conclude that the NF-based emulator not only outperforms GPs in the ease and computational cost of training but also outperforms in the fidelity of the emulated GWB strain ensemble distributions. 

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. 

ABSTRACT We examine the effect of supermassive black hole (SMBH) mass scaling relation choice on the inferred SMBH mass population since redshift z ∼ 3. To make robust predictions for the gravitational wave background (GWB), we must have a solid understanding of the underlying SMBH demographics. Using the SDSS and 3D-HST + CANDELS surveys for 0 < z < 3, we evaluate the inferred SMBH masses from two SMBH–galaxy scaling relations: MBH–Mbulge and MBH–σ. Our SMBH mass functions come directly from stellar mass measurements for MBH–Mbulge, and indirectly from stellar mass and galaxy radius measurements along with the galaxy mass fundamental plane for MBH–σ. We find that there is a substantial difference in predictions especially for z > 1, and this difference increases out to z = 3. In particular, we find that using velocity dispersion predicts a greater number of SMBHs with masses greater than 109 M⊙. The GWB that pulsar timing arrays find evidence for is higher in amplitude than expected from GWB predictions which rely on high-redshift extrapolations of local SMBH mass–galaxy scaling relations. The difference in SMBH demographics resulting from different scaling relations may be the origin for the mismatch between the signal amplitude and predictions. Generally, our results suggest that a deeper understanding of the potential redshift evolution of these relations is needed if we are to draw significant insight from their predictions at z > 1. 

Abstract Evidence for a low-frequency gravitational-wave background using pulsar timing arrays has generated recent interest in its underlying contributing sources. However, multiple investigations have seen that the significance of the evidence does not change with the choice of pulsar modeling techniques, but the resulting parameters from the gravitational wave searches do. PSR J1455−3330 is one of the longest-observed pulsars in the array monitored by the North American Nanohertz Observatory for Gravitational Waves (NANOGrav), but showed no evidence for long-timescale red noise, either intrinsic or the common signal found among many pulsars in the array. In this work, we argue that NANOGrav’s piecewise-constant function used to model variations in radio-frequency-dependent dispersive delay should not be used for this pulsar, and a much simpler physical model of a fixed solar wind density plus a linear or quadratic trend in dispersion measure is preferred. When the original model is replaced, (i) the pulsar’s timing parallax signal changes from an upper limit to a significant detection, (ii) red noise becomes significant, and (iii) the red noise is consistent with the common signal found for the other pulsars. Neither of these signals is radio-frequency dependent. While the same physical motivation will not apply to many of the pulsars currently used in pulsar timing arrays, we argue for careful, physically motivated timing and noise modeling of pulsars used in precision timing experiments. 

Abstract Pulsar timing arrays (PTAs) have recently entered the detection era, quickly moving beyond the goal of simply improving sensitivity at the lowest frequencies for the sake of observing the stochastic gravitational wave background (GWB), and focusing on its accurate spectral characterization. While all PTA collaborations around the world use Fourier-domain Gaussian processes to model the GWB and intrinsic long time-correlated (red) noise, techniques to model the time-correlated radio-frequency-dependent (chromatic) processes have varied from collaboration to collaboration. Here we test a new class of models for PTA data, Gaussian processes based on time-domain kernels that model the statistics of the chromatic processes starting from the covariance matrix. As we will show, these models can be effectively equivalent to Fourier-domain models in mitigating chromatic noise. This work presents a method for Bayesian model selection across the various choices of kernel as well as deterministic chromatic models for nonstationary chromatic events and the solar wind. As PTAs turn toward high frequency (>1 yr⁻¹) sensitivity, the size of the basis used to model these processes will need to increase, and these time-domain models present some computational efficiencies compared to Fourier-domain models.