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Register a new userRapid and accurate parameter inference for coalescing, precessing compact binaries
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Added by
Richard O'Shaughnessy
Publication date
2018
fields
Physics
and research's language is
English
Authors
Jacob Lange
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Extending prior work by Pankow et al, we introduce RIFT, an algorithm to perform Rapid parameter Inference on gravitational wave sources via Iterative Fitting. We demonstrate this approach can correctly recover the parameters of coalescing compact binary systems, using detailed comparisons of RIFT to the well-tested LALInference software library. We provide several examples where the unique speed and flexibility of RIFT enables otherwise intractable or awkward parameter inference analyses, including (a) adopting either costly and novel models for outgoing gravitational waves; and (b) mixed approximations, each suitable to different parts of the compact binary parameter space. We demonstrate how RIFT{} can be applied to binary neutron stars, both for parameter inference and direct constraints on the nuclear equation of state.
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Inferring astrophysical information from gravitational waves emitted by compact binaries is one of the key science goals of gravitational-wave astronomy. In order to reach the full scientific potential of gravitational-wave experiments we require techniques to mitigate the cost of Bayesian inference, especially as gravitational-wave signal models and analyses become increasingly sophisticated and detailed. Reduced order models (ROMs) of gravitational waveforms can significantly reduce the computational cost of inference by removing redundant computations. In this paper we construct the first reduced order models of gravitational-wave signals that include the effects of spin-precession, inspiral, merger, and ringdown in compact object binaries, and which are valid for component masses describing binary neutron star, binary black hole and mixed binary systems. This work utilizes the waveform model known as IMRPhenomPv2. Our ROM enables the use of a fast reduced order quadrature (ROQ) integration rule which allows us to approximate Bayesian probability density functions at a greatly reduced computational cost. We find that the ROQ rule can be used to speed up inference by factors as high as 300 without introducing systematic bias. This corresponds to a reduction in computational time from around half a year to a half a day, for the longest duration/lowest mass signals. The ROM and ROQ rule are available with the main inference library of the LIGO Scientific Collaboration, LALInference.
The detection rate for compact binary mergers has grown as the sensitivity of the global network of ground based gravitational wave detectors has improved, now reaching the stage where robust automation of the analyses is essential. Automated low-latency algorithms have been developed that send out alerts when candidate signals are detected. The alerts include sky maps to facilitate electromagnetic follow up observations, along with probabilities that the system might contain a neutron star, and hence be more likely to generate an electromagnetic counterpart. Data quality issues, such as loud noise transients (glitches), can adversely affect the low-latency algorithms, causing false alarms and throwing off parameter estimation. Here a new analysis method is presented that is robust against glitches, and capable of producing fully Bayesian parameter inference, including sky maps and mass estimates, in a matter of minutes. Key elements of the method are wavelet-based de-noising, penalized maximization of the likelihood during the initial search, rapid sky localization using pre-computed inner products, and heterodyned likelihoods for full Bayesian inference.
Ground-based gravitational wave detectors are sensitive to a narrow range of frequencies, effectively taking a snapshot of merging compact-object binary dynamics just before merger. We demonstrate that by adopting analysis parameters that naturally characterize this picture, the physical parameters of the system can be extracted more efficiently from the gravitational wave data, and interpreted more easily. We assess the performance of MCMC parameter estimation in this physically intuitive coordinate system, defined by (a) a frame anchored on the binarys spins and orbital angular momentum and (b) a time at which the detectors are most sensitive to the binarys gravitational wave emission. Using anticipated noise curves for the advanced-generation LIGO and Virgo gravitational wave detectors, we find that this careful choice of reference frame and reference time significantly improves parameter estimation efficiency for BNS, NS-BH, and BBH signals.
Inferring the source properties of a gravitational wave signal has traditionally been very computationally intensive and time consuming. In recent years, several techniques have been developed that can significantly reduce the computational cost while delivering rapid and accurate parameter inference. One of the most powerful of these techniques is the heterodyned likelihood, which uses a reference waveform to base-band the likelihood calculation. Here an efficient implementation of the heterodyned likelihood is presented that can be used for a wide range of signal types and for both ground based and space based interferometers. The computational savings relative to direct calculation of the likelihood vary between two and four orders of magnitude depending on the system. The savings are greatest for low mass systems such as neutron star binaries. The heterodyning procedure can incorporate marginalization over calibration uncertainties and the noise power spectrum.
Gravitational waves detected from well-localized inspiraling binaries would allow to determine, directly and independently, both binary luminosity and redshift. In this case, such systems could behave as standard candles providing an excellent probe of cosmic distances up to z < 0.1 and thus complementing other indicators of cosmological distance ladder.
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