arXiv subjects

Will M. Farr

Publications and source records attributed to Will M. Farr.

At least 73 records · Page 4Linked to original sources

arXiv2020

A trend in the effective spin distribution of LIGO binary black holes with mass

Binary black holes (BBHs) detected by gravitational wave (GW) observations could be broadly divided into two formation channels: those formed through field binary evolution and those assembled dynamically in dense stellar systems. Each of these formation channels, and their sub-channels, populate a distinct region in the effective spin-mass ($χ_{\rm eff}-M$) plane. Depending on the branching ratio of different channels, an ensemble of BBHs could show a trend in this plane. Here we fit a mass-dependent distribution for $χ_{\rm eff}$ to the GWTC-1 BBHs from the first and second observing runs of Advanced LIGO and Advanced Virgo. We find a negative correlation between mass and the mean effective spin ($\barχ_{\mathrm{eff}}$), and positive correlation with its dispersion ($σ_{χ_\mathrm{eff}}$) at 75\% and 80\% confidence. This trend is robust against the choice of mass variable, but most pronounced when the mass variable is taken to be the chirp mass of the binary. The result is consistent with significant contributions from both dynamically assembled and field binaries in the GWTC-1 catalog. The upcoming LIGO O3a data release will critically test this interpretation.

gr-qc↗

arXiv2019

emcee v3: A Python ensemble sampling toolkit for affine-invariant MCMC

emcee is a Python library implementing a class of affine-invariant ensemble samplers for Markov chain Monte Carlo (MCMC). This package has been widely applied to probabilistic modeling problems in astrophysics where it was originally published, with some applications in other fields. When it was first released in 2012, the interface implemented in emcee was fundamentally different from the MCMC libraries that were popular at the time, such as PyMC, because it was specifically designed to work with "black box" models instead of structured graphical models. This has been a popular interface for applications in astrophysics because it is often non-trivial to implement realistic physics within the modeling frameworks required by other libraries. Since emcee's release, other libraries have been developed with similar interfaces, such as dynesty (Speagle 2019). The version 3.0 release of emcee is the first major release of the library in about 6 years and it includes a full re-write of the computational backend, several commonly requested features, and a set of new "move" implementations.

astro-ph.IM↗

arXiv2019

The Most Massive Binary Black Hole Detections and the Identification of Population Outliers

Advanced LIGO and Virgo detected ten binary black holes (BBHs) in their first two observing runs (O1 and O2). Analysis of these events found strong evidence for a dearth of BBHs with component masses greater than $\sim45 \ M_\odot$, as would be expected from a pair-instability mass gap. Meanwhile, a standalone analysis of the merger GW170729 found its primary mass $m_1 = {51.2^{+16.2}_{-11.0} \ M_\odot}$, with the majority of its posterior support at $m_1 > 45 \ M_\odot$. Although this appears to be in contradiction with the existence of a limit at $\sim45\ M_\odot$, we argue that individual events cannot be evaluated without reference to the entire population. When GW170729 is analyzed jointly with the rest of the detections, as part of a full hierarchical population analysis, its inferred primary mass tightens considerably, to $m_1 = {38.9^{+7.3}_{-4.5} \ M_\odot}$. For a large sample of events in the presence of noise, apparent outliers in the detected distribution are inevitable, even if the underlying population forbids outliers. We discuss methods of distinguishing between statistical fluctuations and population outliers using posterior predictive tests. Applying these tests to the primary mass distribution in O1 and O2, we find that the ten detections are consistent with even the simplest power-law plus maximum-mass model considered by the LVC. This supports the claim that GW170729 is not a population outlier. We also provide non-parametric constraints on the rate of high-mass mergers and conservatively bound the rate of mergers with $m_1 > 45 \ M_\odot$ at $2.8^{+5.4}_{-2.0}\%$ of the total merger rate. After 100 detections like those of O1 and O2 from a population with a maximum primary mass of $45 \, M_\odot$, it would be common for the most massive system to have an observed maximum-likelihood mass $m_1 \gtrsim 70 \, M_\odot$.

astro-ph.HE↗

arXiv2019

Noise spectral estimation methods and their impact on gravitational wave measurement of compact binary mergers

Estimating the parameters of gravitational wave signals detected by ground-based detectors requires an understanding of the properties of the detectors' noise. In particular, the most commonly used likelihood function for gravitational wave data analysis assumes that the noise is Gaussian, stationary, and of known frequency-dependent variance. The variance of the colored Gaussian noise is used as a whitening filter on the data before computation of the likelihood function. In practice the noise variance is not known and it evolves over timescales of dozens of seconds to minutes. We study two methods for estimating this whitening filter for ground-based gravitational wave detectors with the goal of performing parameter estimation studies. The first method uses large amounts of data separated from the specific segment we wish to analyze and computes the power spectral density of the noise through the mean-median Welch method. The second method uses the same data segment as the parameter estimation analysis, which potentially includes a gravitational wave signal, and obtains the whitening filter through a fit of the power spectrum of the data in terms of a sum of splines and Lorentzians. We compare these two methods and argue that the latter is more reliable for gravitational wave parameter estimation.

gr-qc↗

arXiv2019

Hierarchical test of general relativity with gravitational waves

We propose a hierarchical approach to testing general relativity with multiple gravitational wave detections. Unlike existing strategies, our method does not assume that parameters quantifying deviations from general relativity are either common or completely unrelated across all sources. We instead assume that these parameters follow some underlying distribution, which we parametrize and constrain. This can be then compared to the distribution expected from general relativity, i.e. no deviation in any of the events. We demonstrate that our method is robust to measurement uncertainties and can be applied to theories of gravity where the parameters beyond general relativity are related to each other, as generally expected. Our method contains the two extremes of common and unrelated parameters as limiting cases. We apply the hierarchical model to the population of 10 binary black hole systems so far detected by LIGO and Virgo. We do this for a parametrized test of gravitational wave generation, by modeling the population distribution of beyond-general-relativity parameters with a Gaussian distribution. We compute the mean and the variance of the population and show that both are consistent with general relativity for all parameters we consider. In the best case, we find that the population properties of the existing binary signals are consistent with general relativity at the ~1% level. This hierarchical approach subsumes and extends existing methodologies, and is more robust at revealing potential subtle deviations from general relativity with increasing number of detections.

gr-qc↗

arXiv2019

A Future Percent-Level Measurement of the Hubble Expansion at Redshift 0.8 With Advanced LIGO

Simultaneous measurements of distance and redshift can be used to constrain the expansion history of the universe and associated cosmological parameters. Merging binary black hole (BBH) systems are standard sirens---their gravitational waveform provides direct information about the luminosity distance to the source. Because gravity is scale-free, there is a perfect degeneracy between the source masses and redshift; some non-gravitational information is necessary to break the degeneracy and determine the redshift of the source. Here we suggest that the pair instability supernova (PISN) process, thought to be the source of the observed upper-limit on the black hole (BH) mass in merging BBH systems at $\sim 45 \, M_\odot$, imprints a mass scale in the population of BBH mergers and permits a measurement of the redshift-luminosity-distance relation with these sources. We simulate five years of BBH detections in the Advanced LIGO and Virgo detectors with realistic assumptions about the BBH merger rate, a mass distribution incorporating a smooth PISN cutoff, and measurement uncertainty. We show that after one year of operation at design sensitivity (circa 2021) the BBH population can constrain $H(z)$ to $6.1\%$ at a pivot redshift $z \simeq 0.8$. After five years (circa 2025) the constraint improves to $2.9\%$. This measurement relies only on general relativity and the presence of a cutoff mass scale that is approximately fixed or calibrated across cosmic time; it is independent of any distance ladder or cosmological model. Observations by future ``third-generation'' gravitational wave detectors, which can see BBH mergers throughout the universe, would permit sub-percent cosmographical measurements to $z \gtrsim 4$ within one month of observation.

astro-ph.CO↗

arXiv2019

The Impact of metallicity evolution of the universe on the maximum mass of LIGO binary black holes

We can be biased against observing massive black holes to merge in the local universe as the bounds on the maximum black hole mass ($M_{BH}^{\rm max}$) depends on the assumptions regarding the metallicity evolution of the star forming gas across the cosmic time. We investigate the bounds on the metallicity evolution, mass distribution and delay times of the binary black hole sources based on the ten observed events by LIGO. We parametrize $M_{BH}^{\rm max}$ to be a function of metallicity which itself is modeled to evolve with redshift in either a modest or rapid fashion. Rapid metallicity evolution models predict a stringent bound of $M_{BH}^{\rm max}=44^{+9}_{-5}M_{\odot}$, while the bound on $M_{BH}^{\rm max}$ in the models with modest metallicity evolution is $M_{BH}^{\rm max}=52^{+16}_{-9} M_{\odot}$. Therefore, inferring $M_{BH}^{\rm max}$ from GW data depends on the assumed metal enrichment history of the universe that is not severely constrained at the moment.

astro-ph.HE↗

arXiv2019

The K2 Bright Star Survey I: Methodology and Data Release

While the Kepler Mission was designed to look at tens of thousands of faint stars (V > 12), brighter stars that saturated the detector are important because they can be and have been observed very accurately by other instruments. By analyzing the unsaturated scattered-light `halo' around these stars, we have retrieved precise light curves of most of the brightest stars in K2 fields from Campaign~4 onwards. The halo method does not depend on the detailed cause and form of systematics, and we show that it is effective at extracting light curves from both normal and saturated stars. The key methodology is to optimize the weights of a linear combination of pixel time series with respect to an objective function. We test a range of such objective functions, finding that lagged Total Variation, a generalization of Total Variation, performs well on both saturated and unsaturated K2 targets. Applying this to the bright stars across the K2 Campaigns reveals stellar variability ubiquitously, including effects of stellar pulsation, rotation, and binarity. We describe our pipeline and present a catalogue of the 161 bright stars, with classifications of their variability, asteroseismic parameters for red giants with well-measured solar-like oscillations, and remarks on interesting objects. These light curves are publicly available as a High Level Science Product from the Mikulski Archive for Space Telescopes (MAST).

astro-ph.SR↗

arXiv2019

Testing the no-hair theorem with GW150914

We analyze gravitational-wave data from the first LIGO detection of a binary black-hole merger (GW150914) in search of the ringdown of the remnant black hole. Using observations beginning at the peak of the signal, we find evidence of the fundamental quasinormal mode and at least one overtone, both associated with the dominant angular mode ($\ell=m=2$), with $3.6σ$ confidence. A ringdown model including overtones allows us to measure the final mass and spin magnitude of the remnant exclusively from postinspiral data, obtaining an estimate in agreement with the values inferred from the full signal. The mass and spin values we measure from the ringdown agree with those obtained using solely the fundamental mode at a later time, but have smaller uncertainties. Agreement between the postinspiral measurements of mass and spin and those using the full waveform supports the hypothesis that the GW150914 merger produced a Kerr black hole, as predicted by general relativity, and provides a test of the no-hair theorem at the ${\sim}10\%$ level. An independent measurement of the frequency of the first overtone yields agreement with the no-hair hypothesis at the ${\sim 20}\%$ level. As the detector sensitivity improves and the detected population of black hole mergers grows, we can expect that using overtones will provide even stronger tests.

gr-qc↗

arXiv2019

Bayesian hierarchical inference of asteroseismic inclination angles

The stellar inclination angle-the angle between the rotation axis of a star and our line of sight-provides valuable information in many different areas, from the characterisation of the geometry of exoplanetary and eclipsing binary systems, to the formation and evolution of those systems. We propose a method based on asteroseismology and a Bayesian hierarchical scheme for extracting the inclination angle of a single star. This hierarchical method therefore provides a means to both accurately and robustly extract inclination angles from red giant stars. We successfully apply this technique to an artificial dataset with an underlying isotropic inclination angle distribution to verify the method. We also apply this technique to 123 red giant stars observed with $\textit{Kepler}$. We also show the need for a selection function to account for possible population-level biases, that are not present in individual star-by-star cases, in order to extend the hierarchical method towards inferring underlying population inclination angle distributions.

astro-ph.SR↗

arXiv2019

Constraining the Black Hole Initial Mass Function with LIGO/VIRGO Observations

Prior to the detection of black holes (BHs) via the gravitational waves (GWs) they generate at merger, the presence of BHs was inferred in X-ray binaries, mostly via dynamical measurements, with masses in the range between $\sim 5-20~M_\odot$. The LIGO discovery of the first BHs via GWs was surprising in that the two BHs that merged had masses of $35.6^{+4.8}_{-3.0}$ and $30.6^{+3.0}_{-4.4}\,M_\odot$, which are both above the range inferred from X-ray binaries. With 20 BH detections from the O1/O2 runs, the distribution of masses remains generally higher than the X-ray inferred one, while the effective spins are generally lower, suggesting that, at least in part, the GW-detected population might be of dynamical origin rather than produced by the common evolution of field binaries. Here we perform high-resolution N-body simulations of a cluster of isolated BHs with a range of initial mass spectra and upper mass cut-offs, and study the resulting binary mass spectrum resulting from the dynamical interactions. Our clusters have properties similar to those of the massive remnants in an OB association $\sim 10 \, \mathrm{Myr}$ after formation. We perform a likelihood analysis for each of our dynamically-formed binary population against the data from the O1 and O2 LIGO/Virgo runs. We find that an initial mass spectrum $M_{\rm BH}\propto M^{-2.35}$ with an upper mass cutoff $M_{\rm max}\sim 50M_\odot$ is favored by the data, together with a slight preference for a merger rate that increases with redshift.

astro-ph.HE↗

arXiv2019

Accuracy Requirements for Empirically-Measured Selection Functions

I give formulas for the accuracy to which a selection function must be measured via Monte-Carlo injections in order to have un-biased population inference. The number of found injections scales linearly with the number of objects in the population; the coefficient in front of the linear term depends on both the distribution of injections and the inferred population distribution.

astro-ph.IM↗

arXiv2019

Extracting distribution parameters from multiple uncertain observations with selection biases

We derive a Bayesian framework for incorporating selection effects into population analyses. We allow for both measurement uncertainty in individual measurements and, crucially, for selection biases on the population of measurements, and show how to extract the parameters of the underlying distribution based on a set of observations sampled from this distribution. We illustrate the performance of this framework with an example from gravitational-wave astrophysics, demonstrating that the mass ratio distribution of merging compact-object binaries can be extracted from Malmquist-biased observations with substantial measurement uncertainty.

physics.data-an↗

arXiv2018

Digging the population of compact binary mergers out of the noise

Coalescing compact binaries emitting gravitational wave (GW) signals, as recently detected by the Advanced LIGO-Virgo network, constitute a population over the multi-dimensional space of component masses and spins, redshift, and other parameters. Characterizing this population is a major goal of GW observations and may be approached via parametric models. We demonstrate hierarchical inference for such models with a method that accounts for uncertainties in each binary merger's individual parameters, for mass-dependent selection effects, and also for the presence of a second population of candidate events caused by detector noise. Thus, the method is robust to potential biases from a contaminated sample and allows us to extract information from events that have a relatively small probability of astrophysical origin.

astro-ph.IM↗

arXiv2018

Does the Black Hole Merger Rate Evolve with Redshift?

We explore the ability of gravitational-wave detectors to extract the redshift distribution of binary black hole (BBH) mergers. The evolution of the merger rate across redshifts $0 < z \lesssim 1$ is directly tied to the formation and evolutionary processes, providing insight regarding the progenitor formation rate together with the distribution of time delays between formation and merger. Because the limiting distance to which BBHs are detected depends on the masses of the binary, the redshift distribution of detected binaries depends on their underlying mass distribution. We therefore consider the mass and redshift distributions simultaneously, and fit the merger rate density, ${dN}/{dm_1\,dm_2\,dz}$. Our constraints on the mass distribution agree with previously published results, including evidence for an upper mass cutoff at $\sim 40 \ M_\odot$. Additionally, we show that the current set of six BBH detections are consistent with a merger rate density that is uniform in comoving volume. Although our constraints on the redshift distribution are not yet tight enough to distinguish between BBH formation channels, we show that it will be possible to distinguish between different astrophysically motivated models of the merger rate evolution with $\sim 100$--$300$ LIGO-Virgo detections (to be expected within 2--5 years). Specifically, we will be able to infer whether the formation rate peaks at higher or lower redshifts than the star formation rate, or the typical time delay between formation and merger. Meanwhile, with $\sim 100$ detections, the inferred redshift distribution will place constraints on more exotic scenarios such as modified gravity.

astro-ph.HE↗

arXiv2018

Accuracy of inference on the physics of binary evolution from gravitational-wave observations

The properties of the population of merging binary black holes encode some of the uncertain physics of the evolution of massive stars in binaries. The binary black hole merger rate and chirp mass distribution are being measured by ground-based gravitational-wave detectors. We consider isolated binary evolution and explore how accurately the physical model can be constrained with such observations by applying the Fisher information matrix to the merging black hole population simulated with the rapid binary population synthesis code COMPAS. We investigate variations in four COMPAS parameters: common envelope efficiency, kick velocity dispersion, and mass loss rates during the luminous blue variable and Wolf--Rayet stellar evolutionary phases. We find that 1000 observations would constrain these model parameters to a fractional accuracy of a few percent. Given the empirically determined binary black hole merger rate, we can expect gravitational-wave observations alone to place strong constraints on the physics of stellar and binary evolution within a few years.

astro-ph.HE↗

arXiv2018

Aldebaran b's temperate past uncovered in planet search data

The nearby red giant Aldebaran is known to host a gas giant planetary companion from decades of ground-based spectroscopic radial velocity measurements. Using Gaussian Process-based Continuous Auto-Regressive Moving Average (CARMA) models, we show that these historic data also contain evidence of acoustic oscillations in the star itself, and verify this result with further dedicated ground-based spectroscopy and space-based photometry with the Kepler Space Telescope. From the frequency of these oscillations we determine the mass of Aldebaran to be $1.16 \pm 0.07 \, M_\odot$, and note that this implies its planet will have been subject to insolation comparable to the Earth for some of the star's main sequence lifetime. Our approach to sparse, irregularly sampled time series astronomical observations has the potential to unlock asteroseismic measurements for thousands of stars in archival data, and push to lower-mass planets around red giant stars.

astro-ph.SR↗

arXiv2018

exocartographer: A Bayesian Framework for Mapping Exoplanets in Reflected Light

Future space telescopes will directly image extrasolar planets at visible wavelengths. Time-resolved reflected light from an exoplanet encodes information about atmospheric and surface inhomogeneities. Previous research has shown that the light curve of an exoplanet can be inverted to obtain a low-resolution map of the planet, as well as constraints on its spin orientation. Estimating the uncertainty on 2D albedo maps has so far remained elusive. Here we present exocartographer, a flexible open-source Bayesian framework for solving the exo-cartography inverse problem. The map is parameterized with equal-area HEALPix pixels. For a fiducial map resolution of 192 pixels, a four-parameter Gaussian process describing the spatial scale of albedo variations, and two unknown planetary spin parameters, exocartographer explores a 198-dimensional parameter space. To test the code, we produce a light curve for a cloudless Earth in a face-on orbit with a 90$^\circ$ obliquity. We produce synthetic white light observations of the planet: 5 epochs of observations throughout the planet's orbit, each consisting of 24 hourly observations with a photometric uncertainty of $1\%$ (120 data). We retrieve an albedo map and$-$for the first time$-$its uncertainties, along with spin constraints. The albedo map is recognizably of Earth, with typical uncertainty of $30\%$. The retrieved characteristic length scale is 88$\pm 7 ^\circ$, or 9800 km. The obliquity is recovered with a $1-σ$ uncertainty of $0.8^\circ$. Despite the uncertainty in the retrieved albedo map, we robustly identify a high albedo region (the Sahara desert) and a large low-albedo region (the Pacific Ocean).

astro-ph.EP↗