It has become increasingly useful to answer questions in gravitational-wave astronomy using transdimensional models where the number of free parameters can be varied depending on the complexity required to fit the data. Given the growing interest in transdimensional inference, we introduce a new package for the Bayesian inference Library (Bilby) called tBilby. The tBilby package allows users to set up transdimensional inference calculations using the existing Bilby architecture with off-the-shelf nested samplers and/or Markov Chain Monte Carlo algorithms. Transdimensional models are particularly helpful when we seek to test theoretically uncertain predictions described by phenomenological models. For example, bursts of gravitational waves can be modelled using a superposition of N wavelets where N is itself a free parameter. Short pulses are modelled with small values of N whereas longer, more complicated signals are represented with a large number of wavelets stitched together. Other transdimensional models have found use describing instrumental noise and the population properties of gravitational-wave sources. We provide a few demonstrations of tBilby, including fitting the gravitational-wave signal GW150914 with a superposition of N sine-Gaussian wavelets. We outline our plans to further develop the tbilby code suite for a broader range of transdimensional problems.
more »
« less
Transdimensional Inference for Gravitational-wave Astronomy with Bilby
Abstract It has become increasingly useful to answer questions in gravitational-wave astronomy usingtransdimensionalmodels, where the number of free parameters can be varied depending on the complexity required to fit the data. Given the growing interest in transdimensional inference, we introduce a new package for the Bayesian inference Library (Bilby), calledtBilby. ThetBilbypackage allows users to set up transdimensional inference calculations using the existingBilbyarchitecture with off-the-shelf nested samplers and/or Markov Chain Monte Carlo algorithms. Transdimensional models are particularly helpful when seeking to test theoretically uncertain predictions described by phenomenological models. For example, bursts of gravitational waves can be modeled using a superposition ofNwavelets, whereNis itself a free parameter. Short pulses are modeled with small values ofN, whereas longer, more complicated signals are represented with a large number of wavelets stitched together. Other transdimensional models have been used to describe instrumental noise and the population properties of gravitational-wave sources. We provide a few demonstrations oftBilby, including fitting the gravitational-wave signal GW150914 with a superposition ofNsine-Gaussian wavelets. We outline our plans to further develop thetBilbycode suite for a broader range of transdimensional problems.
more »
« less
- Award ID(s):
- 2207758
- PAR ID:
- 10567214
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astrophysical Journal Supplement Series
- Volume:
- 276
- Issue:
- 2
- ISSN:
- 0067-0049
- Format(s):
- Medium: X Size: Article No. 50
- Size(s):
- Article No. 50
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract We describe the public release of the Cluster Monte Carlo (CMC) code, a parallel, star-by-starN-body code for modeling dense star clusters.CMCtreats collisional stellar dynamics using Hénon’s method, where the cumulative effect of many two-body encounters is statistically reproduced as a single effective encounter between nearest-neighbor particles on a relaxation timescale. The star-by-star approach allows for the inclusion of additional physics, including strong gravitational three- and four-body encounters, two-body tidal and gravitational-wave captures, mass loss in arbitrary galactic tidal fields, and stellar evolution for both single and binary stars. The public release ofCMCis pinned directly to theCOSMICpopulation synthesis code, allowing dynamical star cluster simulations and population synthesis studies to be performed using identical assumptions about the stellar physics and initial conditions. As a demonstration, we present two examples of star cluster modeling: first, we perform the largest (N= 108) star-by-starN-body simulation of a Plummer sphere evolving to core collapse, reproducing the expected self-similar density profile over more than 15 orders of magnitude; second, we generate realistic models for typical globular clusters, and we show that their dynamical evolution can produce significant numbers of black hole mergers with masses greater than those produced from isolated binary evolution (such as GW190521, a recently reported merger with component masses in the pulsational pair-instability mass gap).more » « less
-
Abstract Observed evolution of the total mass distribution with redshift is crucial to testing galaxy evolution theories. To measure the total mass distribution, strong gravitational lenses complement the resolved dynamical observations that are currently limited toz≲ 0.5. Here we present the lens models for a pilot sample of seven galaxy-scale lenses from theASTRO3DGalaxy Evolution with Lenses (AGEL) survey. TheAGELlenses, modeled using HST/WFC3-F140W images with Gravitational Lens Efficient Explorer (GLEE) software, have deflector redshifts in the range 0.3 <zdefl< 0.9. Assuming a power-law density profile with slopeγ, we measure the total density profile for the deflector galaxies via lens modeling. We also measure the stellar velocity dispersions (σobs) for four lenses and obtainσobsfromSDSS-BOSSfor the remaining lenses to test our lens models by comparing observed and model-predicted velocity dispersions. For the sevenAGELlenses, we measure an average density profile slope of −1.95 ± 0.09 and aγ–zrelation that does not evolve with redshift atz< 1. Although our result is consistent with some observations and simulations, it differs from other studies atz< 1 that suggest theγ–zrelation evolves with redshift. The apparent conflicts among observations and simulations may be due to a combination of (1) systematics in the lensing and dynamical modeling; (2) challenges in comparing observations with simulations; and (3) assuming a simple power law for the total mass distribution. By providing more lenses atzdefl> 0.5, theAGELsurvey will provide stronger constraints on whether the mass profiles evolve with redshift as predicted by current theoretical models.more » « less
-
Abstract Several features in the mass spectrum of merging binary black holes (BBHs) have been identified using data from the Third Gravitational Wave Transient Catalog (GWTC-3). These features are of particular interest as they may encode the uncertain mechanism of BBH formation. We assess if the features are statistically significant or the result of Poisson noise due to the finite number of observed events. We simulate catalogs of BBHs whose underlying distribution does not have the features of interest, apply the analysis previously performed on GWTC-3, and determine how often such features are spuriously found. We find that one of the features found in GWTC-3, the peak at ∼35M☉, cannot be explained by Poisson noise alone: peaks as significant occur in 1.7% of catalogs generated from a featureless population. This peak is therefore likely to be of astrophysical origin. The data is suggestive of an additional significant peak at ∼10M☉, though the exact location of this feature is not resolvable with current observations. Additional structure beyond a power law, such as the purported dip at ∼14M☉, can be explained by Poisson noise. We also provide a publicly available package,GWMockCat, that creates simulated catalogs of BBH events with correlated measurement uncertainty and selection effects according to user-specified underlying distributions and detector sensitivities.more » « less
-
Abstract We report a gravitational-wave parameter estimation algorithm,AMPLFI, based on likelihood-free inference using normalizing flows. The focus ofAMPLFIis to perform real-time parameter estimation for candidates detected by machine-learning based compact binary coalescence search,Aframe. We present details of our algorithm and optimizations done related to data-loading and pre-processing on accelerated hardware. We train our model using binary black-hole (BBH) simulations on real LIGO-Virgo detector noise. Our model has million trainable parameters with training times h. Based on online deployment on a mock data stream of LIGO-Virgo data,Aframe+AMPLFIis able to pick up BBH candidates and infer parameters for real-time alerts from data acquisition with a net latency of s.more » « less
An official website of the United States government
