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Reed Essick

Publications and source records attributed to Reed Essick.

At least 55 records · Page 3Linked to original sources

Direct Astrophysical Tests of Chiral Effective Field Theory at Supranuclear Densities

Recent observations of neutron stars with gravitational waves and X-ray timing provide unprecedented access to the equation of state (EoS) of cold dense matter at densities difficult to realize in terrestrial experiments. At the same time, predictions for the EoS with reliable uncertainty estimates from chiral effective field theory ($χ$EFT) bound our theoretical ignorance. In this work, we analyze astrophysical data using a nonparametric representation of the neutron-star EoS conditioned on $χ$EFT to directly constrain the underlying physical properties of the compact objects. We discuss how the data alone constrain the EoS at high densities when we condition on $χ$EFT at low densities. We also demonstrate how to exploit astrophysical data to directly test the predictions of $χ$EFT for the EoS up to twice nuclear saturation density, and estimate the density at which these predictions might break down. We find that the existence of massive pulsars, gravitational waves from GW170817, and NICER observations of PSR J0030+0451 favor $χ$EFT predictions for the EoS up to nuclear saturation density over a more agnostic analysis by as much as a factor of 7 for the quantum Monte Carlo (QMC) calculations used in this work. While $χ$EFT predictions using QMC are fully consistent with gravitational-wave data up to twice nuclear saturation density, NICER observations suggest that the EoS stiffens relative to these predictions at nuclear saturation density. Additionally, we marginalize over the uncertainty in the density at which $χ$EFT begins to break down, constraining the radius of a $1.4\,M_\odot$ neutron star to $R_{1.4}=11.40^{+1.38}_{-1.04}$ ($12.54^{+0.71}_{-0.63}$) km and the pressure at twice nuclear saturation density to $p(2n_\mathrm{sat})=14.2^{+18.1}_{-8.4}$ ($28.7^{+15.3}_{-15.0}$) MeV/fm$^3$ with massive pulsar and gravitational-wave (and NICER) data.

astro-ph.HE↗

Discriminating between Neutron Stars and Black Holes with Imperfect Knowledge of the Maximum Neutron Star Mass

Although gravitational-wave signals from exceptional low-mass compact binary coalescences, like GW170817, may carry matter signatures that differentiate the source from a binary black hole system, only one out of every eight events detected by the current Advanced LIGO and Virgo observatories are likely to have signal-to-noise ratios large enough to measure matter effects, even if they are present. Nonetheless, the systems' component masses will generally be constrained precisely. Constructing an explicit mixture model for the total rate density of merging compact objects, we develop a hierarchical Bayesian analysis to classify gravitational-wave sources according to the posterior odds that their component masses are drawn from different subpopulations. Accounting for current uncertainty in the maximum neutron star mass, and adopting different reasonable models for the total rate density, we examine two recent events from the LIGO-Virgo Collaboration's third observing run, GW190425 and GW190814. For population models with no overlap between the neutron star and black hole mass distributions, we typically find that there is a $\gtrsim 70\%$ chance that GW190425 was a binary neutron star merger rather than a neutron-star--black-hole merger. On the other hand, we find that there is a $\lesssim 6\%$ chance that GW190814 involved a slowly spinning neutron star, regardless of our assumed population model.

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Incorporation of Statistical Data Quality Information into the GstLAL Search Analysis

We present updates to GstLAL, a matched filter gravitational-wave search pipeline, in Advanced LIGO and Virgo's third observing run. We discuss the incorporation of statistical data quality information into GstLAL's multi-dimensional likelihood ratio ranking statistic and additional improvements to search for gravitational wave candidates found in only one detector. Statistical data quality information is provided by iDQ, a data quality pipeline that infers the presence of short-duration transient noise in gravitational-wave data using the interferometer's auxiliary state, which has operated in near real-time since before LIGO's first observing run in 2015. We look at the performance and impact on noise rejection by the inclusion of iDQ information in GstLAL's ranking statistic, and discuss GstLAL results in the GWTC-2 catalog, focusing on two case studies; GW190424A, a single-detector gravitational-wave event found by GstLAL and a period of time in Livingston impacted by a thunderstorm.

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Does Matter Matter? Using the mass distribution to distinguish neutron stars and black holes

Gravitational-wave detectors have opened a new window through which we can observe black holes (BHs) and neutron stars (NSs). Analyzing the 11 detections from LIGO/Virgo's first gravitational-wave catalog, GWTC-1, we investigate whether the power-law fit to the BH mass spectrum can also accommodate the binary neutron star (BNS) event GW170817, or whether we require an additional feature, such as a mass gap, in between the NS and BH populations. We find that with respect to the power-law fit to binary black hole (BBH) masses, GW170817 is an outlier at the 0.13\% level, suggesting a distinction between NS and BH masses. A single power-law fit across the entire mass range is in mild tension with: (a) the detection of one source in the BNS mass range ($\sim 1$--$2.5 \,M_\odot$), (b) the absence of detections in the "mass-gap" range ($\sim 2.5$--$5 \,M_\odot$), and (c) the detection of 10 sources in the BBH mass range ($\gtrsim 5 \,M_\odot$). Instead, the data favor models with a feature between NS and BH masses, including a mass gap (Bayes factor of 4.6) and a break in the power law, with a steeper slope at NS masses compared to BH masses (91\% credibility). We estimate the merger rates of compact binaries based on our fit to the global mass distribution, finding $\mathcal{R}_\mathrm{BNS} = 871^{+3015}_{-805} \ \mathrm{Gpc}^{-3} \ \mathrm{yr}^{-1}$ and $\mathcal{R}_\mathrm{BBH} = 47.5^{+57.9}_{-28.8} \ \mathrm{Gpc}^{-3} \ \mathrm{yr}^{-1}$. We conclude that, even in the absence of any prior knowledge of the difference between NSs and BHs, the gravitational-wave data alone already suggest two distinct populations of compact objects.

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Nonparametric constraints on neutron star matter with existing and upcoming gravitational wave and pulsar observations

Observations of neutron stars, whether in binaries or in isolation, provide information about the internal structure of the most extreme material objects in the Universe. In this work, we combine information from recent observations to place joint constraints on the properties of neutron star matter. We use (i) lower limits on the maximum mass of neutron stars obtained through radio observations of heavy pulsars, (ii) constraints on tidal properties inferred through the gravitational waves neutron star binaries emit as they coalesce, and (iii) information about neutron stars' masses and radii obtained through X-ray emission from surface hot spots. In order to combine information from such distinct messengers while avoiding the kind of modeling systematics intrinsic to parametric inference schemes, we employ a nonparametric representation of the neutron-star equation of state based on Gaussian processes conditioned on nuclear theory models. We find that existing astronomical observations imply $R_{1.4}=12.32^{+1.09}_{-1.47}\,\mathrm{km}$ for the radius of a $1.4\,M_{\odot}$ neutron star and $p(2ρ_\mathrm{nuc})=3.8^{+2.7}_{-2.9}\times10^{34}\,\mathrm{dyn}/\mathrm{cm}^2$ for the pressure at twice nuclear saturation density at the 90% credible level. The upper bounds are driven by the gravitational wave observations, while X-ray and heavy pulsar observations drive the lower bounds. Additionally, we compute expected constraints from potential future astronomical observations and find that they can jointly determine $R_{1.4}$ to ${\cal{O}}(1)\,\mathrm{km}$ and $p(2ρ_\mathrm{nuc})$ to 80% relative uncertainty in the next five years.

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iDQ: Statistical Inference of Non-Gaussian Noise with Auxiliary Degrees of Freedom in Gravitational-Wave Detectors

Gravitational-wave detectors are exquisitely sensitive instruments and routinely enable ground-breaking observations of novel astronomical phenomena. However, they also witness non-stationary, non-Gaussian noise that can be mistaken for astrophysical sources, lower detection confidence, or simply complicate the extraction of signal parameters from noisy data. To address this, we present iDQ, a supervised learning framework to autonomously detect noise artifacts in gravitational-wave detectors based only on auxiliary degrees of freedom insensitive to gravitational waves. iDQ has operated in low latency throughout the advanced detector era at each of the two LIGO interferometers, providing invaluable data quality information about each detection to date in real-time. We document the algorithm, describing the statistical framework and possible applications within gravitational-wave searches. In particular, we construct a likelihood-ratio test that simultaneously accounts for the presence of non-Gaussian noise artifacts and utilizes information from both the observed gravitational-wave strain signal and thousands of auxiliary degrees of freedom. We also present several examples of iDQ's performance with modern interferometers, showing iDQ's ability to autonomously reproduce known data quality monitors and identify noise artifacts not flagged by other analyses.

astro-ph.IM↗

Enhancing Gravitational-Wave Science with Machine Learning

Machine learning has emerged as a popular and powerful approach for solving problems in astrophysics. We review applications of machine learning techniques for the analysis of ground-based gravitational-wave detector data. Examples include techniques for improving the sensitivity of Advanced LIGO and Advanced Virgo gravitational-wave searches, methods for fast measurements of the astrophysical parameters of gravitational-wave sources, and algorithms for reduction and characterization of non-astrophysical detector noise. These applications demonstrate how machine learning techniques may be harnessed to enhance the science that is possible with current and future gravitational-wave detectors.

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Counting on Short Gamma-Ray Bursts: Gravitational-Wave Constraints of Jet Geometry

The detection of GW170817 in gravitational waves and gamma rays revealed that short gamma-ray bursts are associated with the merger of neutron-stars. Gamma rays are thought to result from the formation of collimated jets, but the details of this process continue to elude us. One fundamental observable is the emission profile of the jet as a function of viewing angle. We present two methods to measure the effective angular width, $θ_B$, of short gamma-ray burst (sGRB) jets using gravitational wave and gamma-ray data, assuming all sGRBs have the same angular dependence for their luminosities. The first is a counting experiment, where we combine the known detection thresholds of the LIGO/Virgo and Fermi Gamma Ray Burst Monitor detectors to infer parameters of systems that are detected in gravitational waves. This method requires minimal knowledge about each event, beyond whether or not they were detected in gamma-rays. The second method uses additional information from the gravitational-wave and electromagnetic data to estimate parameters of the source, and thereby improve constraints on jet properties. Applying our methods to GW170817, we find only weak constraints on the sGRB luminosity profile, with statistical uncertainty dominating differences between models. We also analyze simulated events from future observing runs, and find that with 5 and 100 BNS detections, the counting method constrains the relative uncertainty in $θ_B$ to within 51% and 12%, respectively. Incorporating gravitational-wave parameter estimation would further tighten these constraints to 43% and 9.6%. In the limit of many detections, incorporating parameter estimation achieves only marginal improvements; we conclude that the majority of the information about jet structure comes from the relative sensitivities of gravitational-wave and gamma-ray detectors as encoded in simple counting experiments.

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Nonparametric Inference of Neutron Star Composition, Equation of State, and Maximum Mass with GW170817

The detection of GW170817 in gravitational waves provides unprecedented constraints on the equation of state (EOS) of the ultra-dense matter within the cores of neutron stars (NSs). We extend the nonparametric analysis first introduced in Landry & Essick (2019), and confirm that GW170817 favors soft EOSs. We infer macroscopic observables for a canonical 1.4 $M_{\odot}$ NS, including the tidal deformability $Λ_{1.4} = 211^{+312}_{-137}$ ($491^{+216}_{-181}$) and radius $R_{1.4}= 10.86^{+2.04}_{-1.42}$ ($12.51^{+1.00}_{-0.88}$) km, as well as the maximum mass for nonrotating NSs, $M_{max} = 2.064^{+0.260}_{-1.34}$ ($2.017^{0.238}_{-0.087}$) $M_\odot$, with nonparametric priors loosely (tightly) constrained to resemble candidate EOSs from the literature. Furthermore, we find weak evidence that GW170817 involved at least one NS based on gravitational-wave data alone ($B^{NS}_{BBH}= 3.3 \pm 1.4$), consistent with the observation of electromagnetic counterparts. We also investigate GW170817's implications for the maximum spin frequency of millisecond pulsars, and find that the fastest known pulsar is spinning at more than 50% of its breakup frequency at 90% confidence. We additionally find modest evidence in favor of quark matter within NSs, and GW170817 favors the presence of at least one disconnected hybrid star branch in the mass--radius relation over a single stable branch by a factor of 2. Assuming there are multiple stable branches, we find a suggestive posterior preference for a sharp softening around nuclear density followed by stiffening around twice nuclear density, consistent with a strong first-order phase transition. While the statistical evidence in favor of new physics within NS cores remains tenuous with GW170817 alone, these tantalizing hints reemphasize the promise of gravitational waves for constraining the supranuclear EOS.

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Calibrating gravitational-wave detectors with GW170817

The waveform of a compact binary coalescence is predicted by general relativity. It is therefore possible to directly constrain the response of a gravitational-wave (GW) detector by analyzing a signal's observed amplitude and phase evolution as a function of frequency. GW signals alone constrain the relative amplitude and phase between different frequencies within the same detector and between different detectors. We analyze GW170817's ability to calibrate the LIGO/Virgo detectors, finding a relative amplitude calibration precision of approximately $\pm20\%$ and relative phase precision of $\pm15^\circ$ (1-$σ$ uncertainty) between the LIGO Hanford and Livingston detectors. Incorporating additional information about the distance and inclination of the source from electromagnetic observations, the relative amplitude of the LIGO detectors can be tightened to $\sim\pm15\%$. We investigate the ability of future events to improve astronomical calibration. By simulating the cumulative uncertainties from an ensemble of detections, we find that with several hundred events with electromagnetic counterparts, or several thousand events without counterparts, we reach percent-level astronomical calibration. This corresponds to $\sim$5-10 years of operation at advanced LIGO and Virgo design sensitivity. It is to be emphasized that direct {\em in-situ}\/ measurements of detector calibration provide significantly higher precision than astronomical sources, and already constrain the calibration to a few percent in amplitude and a few degrees in phase. In this sense, our astronomical calibrators only corroborate existing calibration measurements. Nonetheless, astrophysical calibration may become an important corroboration of existing calibration methods, providing a completely independent constraint of potential systematics.

astro-ph.IM↗

Non-parametric inference of the neutron star equation of state from gravitational wave observations

We develop a non-parametric method for inferring the universal neutron star (NS) equation of state (EOS) from gravitational wave (GW) observations. Many different possible realizations of the EOS are generated with a Gaussian process conditioned on a set of nuclear-theoretic models. These synthetic EOSs are causal and thermodynamically stable by construction, span a broad region of the pressure-density plane, and can be selected to satisfy astrophysical constraints on the NS mass. Associating every synthetic EOS with a pair of component masses $M_{1,2}$ and calculating the corresponding tidal deformabilities $Λ_{1,2}$, we perform Monte Carlo integration over the GW likelihood for $M_{1,2}$ and $Λ_{1,2}$ to directly infer a posterior process for the NS EOS. We first demonstrate that the method can accurately recover an injected GW signal, and subsequently use it to analyze data from GW170817, finding a canonical deformability of $Λ_{1.4} = 160^{+448}_{-113}$ and $p(2ρ_{\mathrm{nuc}})=1.35^{+1.8}_{-1.2}\times 10^{34}~\mathrm{dyn}/\mathrm{cm}^2$ for the pressure at twice the nuclear saturation density at 90$\%$ confidence, in agreement with previous studies, when assuming a loose EOS prior. With a prior more tightly constrained to resemble the theoretical EOS models, we recover $Λ_{1.4} = 556^{+163}_{-172}$ and $p(2ρ_{\mathrm{nuc}})=4.73^{+1.4}_{-2.5}\times 10^{34}~\mathrm{dyn}/\mathrm{cm}^2$. We further infer the maximum NS mass supported by the EOS to be $M_\mathrm{max}=2.09^{+0.37}_{-0.16}$ ($2.04^{+0.22}_{-0.002}$) $M_\odot$ with the loose (tight) prior. The Bayes factor between the two priors is $B^{\mathcal{A}}_{\mathcal{I}} \simeq 1.12$, implying that neither is strongly preferred by the data and suggesting that constraints on the EOS from GW170817 alone may be relatively prior-dominated.

gr-qc↗

A Comparison of p-g Tidal Coupling Analyses

Two recent studies have attempted to constrain the proposed $p$-$g$ tidal instability with gravitational-wave data from GW170817. The studies use Bayesian methods to compare a model that includes $p$-$g$ tidal effects with one that does not. Using the same data, they arrive at very different conclusions. Reyes & Brown find that the observations of GW170817 strongly disfavor the existence of $p$-$g$ mode coupling. However, the LIGO and Virgo Collaborations find that neither model is strongly favored. We investigate the origin of this discrepancy by analyzing Reyes & Brown's publicly available posterior samples. Contrary to their claims, we find that their samples do not disfavor $p$-$g$ mode coupling.

astro-ph.HE↗

Tidal Dissipation in WASP-12

WASP-12 is a hot Jupiter system with an orbital period of $P= 1.1\textrm{ day}$, making it one of the shortest-period giant planets known. Recent transit timing observations by Maciejewski et al. (2016) and Patra et al. (2017) find a decreasing period with $P/|\dot{P}| = 3.2\textrm{ Myr}$. This has been interpreted as evidence of either orbital decay due to tidal dissipation or a long term oscillation of the apparent period due to apsidal precession. Here we consider the possibility that it is orbital decay. We show that the parameters of the host star are consistent with either a $M_\ast \simeq 1.3 M_\odot$ main sequence star or a $M_\ast \simeq 1.2 M_\odot$ subgiant. We find that if the star is on the main sequence, the tidal dissipation is too inefficient to explain the observed $\dot{P}$. However, if it is a subgiant, the tidal dissipation is significantly enhanced due to nonlinear wave breaking of the dynamical tide near the star's center. The subgiant models have a tidal quality factor $Q_\ast'\simeq 2\times10^5$ and an orbital decay rate that agrees well with the observed $\dot{P}$. It would also explain why the planet survived for $\simeq 3\textrm{ Gyr}$ while the star was on the main sequence and yet is now inspiraling on a 3 Myr timescale. Although this suggests that we are witnessing the last $\sim 0.1\%$ of the planet's life, the probability of such a detection is a few percent given the observed sample of $\simeq 30$ hot Jupiters in $P<3\textrm{ day}$ orbits around $M_\ast>1.2 M_\odot$ hosts.

astro-ph.EP↗

Frequency-Dependent Responses in 3rd Generation Gravitational-Wave Detectors

Interferometric gravitational wave detectors are dynamic instruments. Changing gravitational-wave strains influence the trajectories of null geodesics and therefore modify the interferometric response. These effects will be important when the associated frequencies are comparable to the round-trip light travel time down the detector arms. The arms of advanced detectors currently in operation are short enough that the strain can be approximated as static, but planned 3$^\mathrm{rd}$ generation detectors, with arms an order of magnitude longer, will need to account for these effects. We investigate the impact of neglecting the frequency-dependent detector response for compact binary coalescences and show that it can introduce large systematic biases in localization, larger than the statistical uncertainty for 1.4-1.4$M_\odot$ neutron star coalescences at $z\lesssim1.7$. Analysis of $3^\mathrm{rd}$ generation detectors therefore must account for these effects.

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Parameter estimation for gravitational-wave bursts with the BayesWave pipeline

We provide a comprehensive multi-aspect study on the performance of a pipeline used by the LIGO-Virgo Collaboration for estimating parameters of gravitational-wave bursts. We add simulated signals with four different morphologies (sine-Gaussians, Gaussians, white-noise bursts, and binary black hole signals) to simulated noise samples representing noise of the two Advanced LIGO detectors during their first observing run. We recover them with the BayesWave (BW) pipeline to study its accuracy in sky localization, waveform reconstruction, and estimation of model-independent waveform parameters. BW localizes sources with a level of accuracy comparable for all four morphologies, with the median separation of actual and estimated sky locations ranging from 25.1$^{\circ}$ to 30.3$^{\circ}$. This is a reasonable accuracy in the two-detector case, and is comparable to accuracies of other localization methods studied previously. As BW reconstructs generic transient signals with sine-Gaussian wavelets, it is unsurprising that BW performs the best in reconstructing sine-Gaussian and Gaussian waveforms. BW's accuracy in waveform reconstruction increases steeply with network signal-to-noise ratio (SNR$_{\rm net}$), reaching a $85\%$ and $95\%$ match between the reconstructed and actual waveform below SNR$_{\rm net} \approx 20$ and SNR$_{\rm net} \approx 50$, respectively, for all morphologies. BW's accuracy in estimating central moments of waveforms is only limited by statistical errors in the frequency domain, and is affected by systematic errors too in the time domain as BW cannot reconstruct low-amplitude parts of signals overwhelmed by noise. The figures of merit we introduce can be used in future characterizations of parameter estimation pipelines.

astro-ph.HE↗

An information-theoretic approach to the gravitational-wave burst detection problem

The observational era of gravitational-wave astronomy began in the Fall of 2015 with the detection of GW150914. One potential type of detectable gravitational wave is short-duration gravitational-wave bursts, whose waveforms can be difficult to predict. We present the framework for a new detection algorithm for such burst events -- \textit{oLIB} -- that can be used in low-latency to identify gravitational-wave transients independently of other search algorithms. This algorithm consists of 1) an excess-power event generator based on the Q-transform -- \textit{Omicron} --, 2) coincidence of these events across a detector network, and 3) an analysis of the coincident events using a Markov chain Monte Carlo Bayesian evidence calculator -- \textit{LALInferenceBurst}. These steps compress the full data streams into a set of Bayes factors for each event; through this process, we use elements from information theory to minimize the amount of information regarding the signal-versus-noise hypothesis that is lost. We optimally extract this information using a likelihood-ratio test to estimate a detection significance for each event. Using representative archival LIGO data, we show that the algorithm can detect gravitational-wave burst events of astrophysical strength in realistic instrumental noise across different burst waveform morphologies. We also demonstrate that the combination of Bayes factors by means of a likelihood-ratio test can improve the detection efficiency of a gravitational-wave burst search. Finally, we show that oLIB's performance is robust against the choice of gravitational-wave populations used to model the likelihood-ratio test likelihoods.

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Impact of the tidal p-g instability on the gravitational wave signal from coalescing binary neutron stars

Recent studies suggest that coalescing neutron stars are subject to a fluid instability involving the nonlinear coupling of the tide to $p$-modes and $g$-modes. Its influence on the inspiral dynamics and thus the gravitational wave signal is, however, uncertain because we do not know precisely how the instability saturates. Here we construct a simple, physically motivated model of the saturation that allows us to explore the instability's impact as a function of the model parameters. We find that for plausible assumptions about the saturation, current gravitational wave detectors might miss $> 70\%$ of events if only point particle waveforms are used. Parameters such as the chirp mass, component masses, and luminosity distance might also be significantly biased. On the other hand, we find that relatively simple modifications to the point particle waveform can alleviate these problems and enhance the science that emerges from the detection of binary neutron stars.

astro-ph.HE↗

On similarity of binary black hole gravitational-wave skymaps: to observe or to wait?

Localization estimates for GW150914, the first binary black hole detected by the LIGO instruments, were shared with partner facilities for electromagnetic follow-up. While the source was a compact binary coalescence (CBC), it was first identified by algorithms that search for unmodeled signals, which produced the skymaps that directed electromagnetic observations. Later on, CBC specific algorithms produced refined versions, which showed significant differences. In this paper we show that those differences were not accidental and that CBC and unmodeled skymaps for binary black holes will frequently be different; we thus provide a way to determine whether to observe electromagnetically as promptly as possible (following a gravitational-wave detection), or to wait until CBC skymaps become available, should they not be available in low latency. We also show that, unsurprisingly, CBC algorithms can yield much smaller searched areas.

gr-qc↗