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Asteroseismic time series data have imprints of stellar oscillation modes, whose detection and characterization through time series analysis allows us to probe stellar interior physics. Such analyses usually occur in the Fourier domain by computing the Lomb–Scargle (LS) periodogram, an estimator of the power spectrum underlying unevenly sampled time series data. However, the LS periodogram suffers from the statistical problems of (1) inconsistency (or noise) and (2) bias due to high spectral leakage. Here, we develop a multitaper power spectrum estimator using the nonuniform fast Fourier transform ( mtNUFFT ) to tackle the inconsistency and bias problems of the LS periodogram. Using a simulated light curve, we show that the mtNUFFT power spectrum estimate of solar-like oscillations has lower variance and bias than the LS estimate. We also apply our method to the Kepler-91 red giant, and combine it with PBjam peakbagging to obtain mode parameters and a derived age estimate of 3.97 ± 0.52 Gyr. PBjam allows the improvement of age precision relative to the 4.27 ± 0.75 Gyr APOKASC-2 (uncorrected) estimate, whereas partnering mtNUFFT with PBjam speeds up peakbagging thrice as much as LS. This increase in efficiency has promising implications for Galactic archaeology, in addition to stellar structure and evolution studies. Our new method generally applies to time-domain astronomy and is implemented in the public Python package tapify , available at https://github.com/aaryapatil/tapify .

The scaling relation between the size of a galaxy’s globular cluster (GC) population ( N _GC ) and the galaxy’s stellar mass ( M _* ) is usually described with a continuous, linear model, but in reality it is a count relationship that should be modeled as such. For massive galaxies, a negative binomial (NB) model has been shown to describe the data well, but it is unclear how the scaling relation behaves at low galaxy masses where a substantial portion of galaxies have N _GC = 0. In this work, we test the utility of Poisson and NB models for describing the low-mass end of the N _GC − M _* scaling relation. We introduce the use of zero-inflated versions of these models, which allow for larger zero populations (e.g., galaxies without GCs) than would otherwise be predicted. We evaluate our models with a variety of predictive model comparison methods, including predictive intervals, the leave-one-out cross-validation criterion, and posterior predictive comparisons. We find that the NB model is consistent with our data, but the naive Poisson is not. Moreover, we find that zero inflation of the models is not necessary to describe the population of low-mass galaxies that lack GCs, suggesting that a single formation and evolutionary process acts over all galaxy masses. Under the NB model, there does not appear to be anything unique about the lack of GCs in many low-mass galaxies; they are simply the low-mass extension of the larger N _GC − M _* scaling relation.

Studying transient phenomena, such as individual pulses from pulsars, has garnered considerable attention in the era of astronomical big data. Of specific interest to this study are rotating radio transients (RRATs), nulling, and intermittent pulsars. This study introduces a new algorithm named LuNfit, tailored to correct the selection biases originating from the telescope and detection pipelines. Ultimately LuNfit estimates the intrinsic luminosity distribution and nulling fraction of the single pulses emitted by pulsars. LuNfit relies on Bayesian nested sampling so that the parameter space can be fully explored. Bayesian nested sampling also provides the additional benefit of simplifying model comparisons through the Bayes ratio. The robustness of LuNfit is shown through simulations and applying LuNfit onto pulsars with known nulling fractions. LuNfit is then applied to three RRATs, J0012+5431, J1538+1523, and J2355+1523, extracting their intrinsic luminosity distribution and burst rates. We find that their nulling fractions are 0.4(2), 0.749(5), and 0.995(2), respectively. We further find that a log-normal distribution likely describes the single pulse luminosity distribution of J0012+5431 and J1538+1523, while the Bayes ratio for J2355+1523 slightly favors an exponential distribution. We show the conventional method of correcting selection effects by “scaling up” the missed fraction of radio transients can be unreliable when the mean luminosity of the source is faint relative to the telescope sensitivity. Finally, we discuss the limitations of the current implementation of LuNfit while also delving into potential enhancements that would enable LuNfit to be applied to sources with complex pulse morphologies.

We present results from angular cross correlations between select samples of CHIME/FRB repeaters and galaxies in three photometric galaxy surveys, which have shown correlations with the first CHIME/FRB catalog containing repeating and nonrepeating sources: Wide-field Infrared Survey Explorer (WISE) × SCOS, DESI-BGS, and DESI-LRG. We find a statistically significant correlation ( p -value 395 pc cm ^−3 and WISE × SCOS galaxies with redshift z > 0.275. We demonstrate that the correlation arises surprisingly because of a statistical association between FRB 20200320A (extragalactic DM ≈ 550 pc cm ^−3 ) and a galaxy group in the same dark matter halo at redshift z ≈ 0.32. We estimate that the host halo, along with an intervening halo at redshift z ≈ 0.12, accounts for at least ∼30% of the extragalactic DM. Our results strongly motivate incorporating galaxy group and cluster catalogs into direct host association pipelines for FRBs with $\lesssim 1^{\prime} $ localization precision, effectively utilizing the two-point information to constrain FRB properties such as their redshift and DM distributions. In addition, we find marginal evidence for a negative correlation at 99.4% confidence limit between a sample of repeating FRBs with baseband data (median extragalactic DM = 354 pc cm ^−3 ) and DESI-LRG galaxies with redshift 0.3 ≤ z < 0.45, suggesting that the repeaters might be more prone than apparent nonrepeaters to propagation effects in FRB–galaxy correlations due to intervening free electrons over angular scales ∼0.°5.

FRB 20180916B is a repeating fast radio burst (FRB) with a 16.3 day periodicity in its activity. In this study, we present morphological properties of 60 FRB 20180916B bursts detected by CHIME/FRB between 2018 August and 2021 December. We recorded raw voltage data for 45 of these bursts, enabling microseconds time resolution in some cases. We studied variation of spectro-temporal properties with time and activity phase. We find that the variation in dispersion measure (DM) is ≲1 pc cm ^−3 and that there is burst-to-burst variation in scattering time estimates ranging from ∼0.16 to over 2 ms, with no discernible trend with activity phase for either property. Furthermore, we find no DM and scattering variability corresponding to the recent change in rotation measure from the source, which has implications for the immediate environment of the source. We find that FRB 20180916B has thus far shown no epochs of heightened activity as have been seen in other active repeaters by CHIME/FRB, with its burst count consistent with originating from a Poissonian process. We also observe no change in the value of the activity period over the duration of our observations and set a 1 σ upper limit of 1.5 × 10 ^−4 day day ^−1 on the absolute period derivative. Finally, we discuss constraints on progenitor models yielded by our results, noting that our upper limits on changes in scattering and DM as a function of phase do not support models invoking a massive binary companion star as the origin of the 16.3 day periodicity.

Galaxy stellar mass is known to be monotonically related to the size of the galaxy’s globular cluster (GC) population for Milky Way sized and larger galaxies. However, the relation becomes ambiguous for dwarf galaxies, where there is some evidence for a downturn in GC population size at low galaxy masses. Smaller dwarfs are increasingly likely to have no GCs, and these zeros cannot be easily incorporated into linear models. We introduce the Hierarchical Errors-in-variables ERrors-in-variables BAyesian Lognormal hurdle (HERBAL) model to represent the relationship between dwarf galaxies and their GC populations, and apply it to the sample of Local Group galaxies, where the luminosity range coverage is maximal. This bimodal model accurately represents the two populations of dwarf galaxies: those that have GCs and those that do not. Our model thoroughly accounts for all uncertainties, including measurement uncertainty, uncertainty in luminosity to stellar mass conversions, and intrinsic scatter. The hierarchical nature of our Bayesian model also allows us to estimate galaxy masses and individual mass-to-light ratios from luminosity data within the model. We find that 50% of galaxies are expected to host GC populations at a stellar mass of ${\mathrm{log}}_{10}({M}_{* })=6.996$ , and that the expected mass of GC populations remains linear down to the smallest galaxies. Our hierarchical model recovers an accurate estimate of the Milky Way stellar mass. Under our assumed error model, we find a nonzero intrinsic scatter of ${0.59}_{-0.21}^{+0.3}$ (95% credible interval) that should be accounted for in future models.

The CHIME/FRB project has detected hundreds of fast radio bursts (FRBs), providing an unparalleled population to statistically probe the foreground media that they illuminate. One such foreground medium is the ionized halo of the Milky Way (MW). We estimate the total Galactic electron column density from FRB dispersion measures (DMs) as a function of Galactic latitude using four different estimators, including ones that assume spherical symmetry of the ionized MW halo and ones that imply more latitudinal variation in density. Our observation-based constraints of the total Galactic DM contribution for ∣ b ∣ ≥ 30°, depending on the Galactic latitude and selected model, span 87.8–141 pc cm ^−3 . This constraint implies upper limits on the MW halo DM contribution that range over 52–111 pc cm ^−3 . We discuss the viability of various gas density profiles for the MW halo that have been used to estimate the halo’s contribution to DMs of extragalactic sources. Several models overestimate the DM contribution, especially when assuming higher halo gas masses (∼3.5 × 10 ^12 M _⊙ ). Some halo models predict a higher MW halo DM contribution than can be supported by our observations unless the effect of feedback is increased within them, highlighting the impact of feedback processes in galaxy formation.

We present a hierarchical Bayesian method for estimating the total mass and mass profile of the Milky Way Galaxy. The new hierarchical Bayesian approach further improves the framework presented by Eadie et al. and Eadie and Harris and builds upon the preliminary reports by Eadie et al. The method uses a distribution function to model the Galaxy and kinematic data from satellite objects, such as globular clusters (GCs), to trace the Galaxy’s gravitational potential. A major advantage of the method is that it not only includes complete and incomplete data simultaneously in the analysis, but also incorporates measurement uncertainties in a coherent and meaningful way. We first test the hierarchical Bayesian framework, which includes measurement uncertainties, using the same data and power-law model assumed in Eadie and Harris and find the results are similar but more strongly constrained. Next, we take advantage of the new statistical framework and incorporate all possible GC data, finding a cumulative mass profile with Bayesian credible regions. This profile implies a mass within 125 kpc of with a 95% Bayesian credible region of . Our results also provide estimates of the true specific energies of all the GCs. By comparing these estimated energies to the measured energies of GCs with complete velocity measurements, we observe that (the few) remote tracers with complete measurements may play a large role in determining a total mass estimate of the Galaxy. Thus, our study stresses the need for more remote tracers with complete velocity measurements. [ABSTRACT FROM AUTHOR]

We present new deep photometry of the rich globular cluster (GC) systems around the Brightest Cluster Galaxies UGC 9799 (Abell 2052) and UGC 10143 (Abell 2147), obtained with the Hubble Space Telescope (HST) ACS and WFC3 cameras. For comparison, we also present new reductions of similar HST/ACS data for the Coma supergiants NGC 4874 and 4889. All four of these galaxies have huge cluster populations (to the radial limits of our data, comprising from 12,000 to 23,000 clusters per galaxy). The metallicity distribution functions (MDFs) of the GCs can still be matched by a bimodal-Gaussian form where the metal-rich and metal-poor modes are separated by dex, but the internal dispersions of each mode are so large that the total MDF becomes very broad and nearly continuous from [Fe/H] ≃ −2.4 to solar. There are, however, significant differences between galaxies in the relative numbers of metal-rich clusters, suggesting that they underwent significantly different histories of mergers with massive gas-rich halos. Last, the proportion of metal-poor GCs rises especially rapidly outside projected radii , suggesting the importance of accreted dwarf satellites in the outer halo. Comprehensive models for the formation of GCs as part of the hierarchical formation of their parent galaxies will be needed to trace the systematic change in structure of the MDF with galaxy mass, from the distinctly bimodal form in smaller galaxies up to the broad continuum that we see in the very largest systems. [ABSTRACT FROM AUTHOR]

We present mass and mass profile estimates for the Milky Way (MW) Galaxy using the Bayesian analysis developed by Eadie et al. and using globular clusters (GCs) as tracers of the Galactic potential. The dark matter and GCs are assumed to follow different spatial distributions; we assume power-law model profiles and use the model distribution functions described in Evans et al. and Deason et al. We explore the relationships between assumptions about model parameters and how these assumptions affect mass profile estimates. We also explore how using subsamples of the GC population beyond certain radii affect mass estimates. After exploring the posterior distributions of different parameter assumption scenarios, we conclude that a conservative estimate of the Galaxy’s mass within 125 kpc is , with a 50% probability region of . Extrapolating out to the virial radius, we obtain a virial mass for the MW of with 50% credible region of (. If we consider only the GCs beyond 10 kpc, then the virial mass is ( kpc). We also arrive at an estimate of the velocity anisotropy parameter β of the GC population, which is with a 50% credible region (0.21, 0.35). Interestingly, the mass estimates are sensitive to both the dark matter halo potential and visible matter tracer parameters, but are not very sensitive to the anisotropy parameter. [ABSTRACT FROM AUTHOR]

A powerful method to measure the mass profile of a galaxy is through the velocities of tracer particles distributed through its halo. Transforming this kind of data accurately to a mass profile , however, is not a trivial problem. In particular, limited or incomplete data may substantially affect the analysis. In this paper we develop a Bayesian method to deal with incomplete data effectively; we have a hybrid-Gibbs sampler that treats the unknown velocity components of tracers as parameters in the model. We explore the effectiveness of our model using simulated data and then apply our method to the Milky Way (MW) using velocity and position data from globular clusters and dwarf galaxies. We find that, in general, missing velocity components have little effect on the total mass estimate. However, the results are quite sensitive to the outer cluster Pal 3. Using a basic Hernquist model with an isotropic velocity dispersion, we obtain credible regions for the cumulative mass profile of the MW and provide estimates for the model parameters with 95% Bayesian credible intervals. The mass contained within 260 kpc is , with a 95% credible interval of . The Hernquist parameters for the total mass and scale radius are and kpc, where the uncertainties span the 95% credible intervals. The code we developed for this work, Galactic Mass Estimator (GME), will be available as an open source package in the R Project for Statistical Computing. [ABSTRACT FROM AUTHOR]