The space-based gravitational wave detector LISA will observe mergers of massive black hole binary systems (MBHBs) to cosmological distances, as well as inspiralling stellar-origin (or stellar-mass) binaries (SBHBs) years before they enter the LIGO/Virgo band. Much remains to be explored for the parameter recovery of both classes of systems. Previous MBHB analyses relied on inspiral-only signals and/or a simplified Fisher matrix analysis, while SBHBs have not yet been extensively analyzed with Bayesian methods. We accelerate likelihood computations by (i) using a Fourier-domain response of the LISA instrument, (ii) using a reduced-order model for non-spinning waveforms that include a merger-ringdown and higher harmonics, (iii) setting the noise realization to zero and computing overlaps in the amplitude/phase representation. We present the first simulations of Bayesian inference for the parameters of massive black hole systems including consistently the merger and ringdown of the signal, as well as higher harmonics. We clarify the roles of LISA response time and frequency dependencies in breaking degeneracies and illustrate how degeneracy breaking unfolds over time. We also find that restricting the merger-dominated signal to its dominant harmonic can make the extrinsic likelihood very degenerate. Including higher harmonics proves to be crucial to break degeneracies and considerably improves the localization of the source, with a surviving bimodality in the sky position. We also present simulations of Bayesian inference for the extrinsic parameters of SBHBs, and show that although unimodal, their posterior distributions can have non-Gaussian features.
The Advanced Laser Interferometer Antenna (ALIA) and the Big Bang Observer (BBO) have been proposed as follow on missions to the Laser Interferometer Space Antenna (LISA). Here we study the capabilities of these observatories, and how they relate to the science goals of the missions. We find that the Advanced Laser Interferometer Antenna in Stereo (ALIAS), our proposed extension to the ALIA mission, will go considerably further toward meeting ALIA's main scientific goal of studying intermediate mass black holes. We also compare the capabilities of LISA to a related extension of the LISA missio…
We demonstrate the use of automatic Bayesian inference for the analysis of LISA data sets. In particular we describe a new automatic Reversible Jump Markov Chain Monte Carlo method to evaluate the posterior probability density functions of the a priori unknown number of parameters that describe the gravitational wave signals present in the data. We apply the algorithm to a simulated LISA data set containing overlapping signals from white dwarf binary systems (DWD) and to a separate data set containing a signal from an extreme mass ratio inspiral (EMRI). We demonstrate that the approach works w…
Detectability of Gravitational-Wave Memory with LISA: A Bayesian Approach
CEA（法国原子能和替代能源委员会）；Université Paris-Saclay（巴黎萨克雷大学）；Centre national d’études spatiales (CNES)（法国国家空间研究中心）；CERN（欧洲核子研究组织）；Institut de Física d’Altes Energies (IFAE)（高能物理研究所）；The Barcelona Institute of Science and Technology（巴塞罗那科学技术研究院）；Niels Bohr Institute（尼尔斯·玻尔研究所）；KU Leuven（荷语鲁汶大学）；Leuven Gravity Institute（鲁汶引力研究所）；SISSA（国际高等研究院）；INFN Sezione di Trieste（意大利国家核物理研究所的里雅斯特分部）；IFPU - Institute for Fundamental Physics of the Universe（宇宙基础物理研究所）
We present a Bayesian parameter-estimation pipeline to measure the properties of inspiralling stellar-mass black hole binaries with LISA. Our strategy (i) is based on the coherent analysis of the three noise-orthogonal LISA data streams, (ii) employs accurate and computationally efficient post-Newtonian waveforms accounting for both spin-precession and orbital eccentricity, and (iii) relies on a nested sampling algorithm for the computation of model evidences and posterior probability density functions of the full 17 parameters describing a binary. We demonstrate the performance of this approa…
A main scientific output of the LISA Pathfinder mission is to provide a noise model that can be extended to the future gravitational wave observatory, LISA. The success of the mission depends thus upon a deep understanding of the instrument, especially the ability to correctly determine the parameters of the underlying noise model. In this work we estimate the parameters of a simplified model of the LISA Technology Package (LTP) instrument. We describe the LTP by means of a closed-loop model that is used to generate the data, both injected signals and noise. Then, parameters are estimated usin…
The Laser Interferometer Space Antenna (LISA), which is currently under construction, is designed to measure gravitational wave signals in the milli-Hertz frequency band. It is expected that tens of millions of Galactic binaries will be the dominant sources of observed gravitational waves. The Galactic binaries producing signals at mHz frequency range emit quasi monochromatic gravitational waves, which will be constantly measured by LISA. To resolve as many Galactic binaries as possible is a central challenge of the upcoming LISA data set analysis. Although it is estimated that tens of thousan…
One of the greatest data analysis challenges for the Laser Interferometer Space Antenna (LISA) is the need to account for a large number of gravitational wave signals from compact binary systems expected to be present in the data. We introduce the basis of a Bayesian method that we believe can address this challenge, and demonstrate its effectiveness on a simplified problem involving one hundred synthetic sinusoidal signals in noise. We use a reversible jump Markov chain Monte Carlo technique to infer simultaneously the number of signals present, the parameters of each identified signal, and t…
We consider the problem of characterisation of burst sources detected with the Laser Interferometer Space Antenna (LISA) using the multi-modal nested sampling algorithm, MultiNest. We use MultiNest as a tool to search for modelled bursts from cosmic string cusps, and compute the Bayesian evidence associated with the cosmic string model. As an alternative burst model, we consider sine-Gaussian burst signals, and show how the evidence ratio can be used to choose between these two alternatives. We present results from an application of MultiNest to the last round of the Mock LISA Data Challenge, …
The Laser Interferometer Space Antenna (LISA) will detect and characterize $\sim10^4$ Galactic Binaries consisting predominantly of two White Dwarfs (WD). An interesting prospect within this population is a third object--another WD star, a Circumbinary Exoplanet (CBP), or a Brown Dwarf (BD)--in orbit about the inner WD pair. We present the first fully Bayesian detection and posterior analysis of sub-stellar objects with LISA, focusing on the characterization of CBPs. We used an optimistic astrophysically motivated catalogue of these CBP third-body sources, including their orbital eccentricity …
Bayesian P-spline recovery of stochastic gravitational-wave backgrounds in LISA
The University of Auckland（奥克兰大学）；Auckland University of Technology（奥克兰理工大学）；Université Côte d’Azur（蔚蓝海岸大学）；Observatoire de la Côte d’Azur（蔚蓝海岸天文台）；CNRS（法国国家科学研究中心）
We report on the performance of an end-to-end Bayesian analysis pipeline for detecting and characterizing galactic binary signals in simulated LISA data. Our principal analysis tool is the Blocked-Annealed Metropolis Hasting (BAM) algorithm, which has been optimized to search for tens of thousands of overlapping signals across the LISA band. The BAM algorithm employs Bayesian model selection to determine the number of resolvable sources, and provides posterior distribution functions for all the model parameters. The BAM algorithm performed almost flawlessly on all the Round 1 Mock LISA Data Ch…
We present a parameter estimation procedure based on a Bayesian framework by applying a Markov Chain Monte Carlo algorithm to the calibration of the dynamical parameters of a space based gravitational wave detector. The method is based on the Metropolis-Hastings algorithm and a two-stage annealing treatment in order to ensure an effective exploration of the parameter space at the beginning of the chain. We compare two versions of the algorithm with an application to a LISA Pathfinder data analysis problem. The two algorithms share the same heating strategy but with one moving in coordinate dir…
Bayesian power spectral density estimation for LISA noise based on penalized splines with a parametric boost
The University of Auckland（奥克兰大学）；Auckland University of Technology（奥克兰理工大学）；Université Côte d’Azur, Observatoire de la Côte d’Azur, Artemis, CNRS（蔚蓝海岸大学，蔚蓝海岸天文台，Artemis，法国国家科学研究中心）
Gravitational-wave parameter estimation with gaps in LISA: a Bayesian data augmentation method
NASA Goddard Space Flight Center（美国宇航局戈达德太空飞行中心）；Artémis UMR 7250, Observatoire de la Côte d’Azur（蔚蓝海岸天文台阿尔特弥斯联合研究实验室）；Laboratoire Astroparticules et Cosmologie, Université Paris Diderot（巴黎第七大学亚原子物理与宇宙学实验室）
The main goal of the LISA Pathfinder (LPF) mission is to fully characterize the acceleration noise models and to test key technologies for future space-based gravitational-wave observatories similar to the eLISA concept. The data analysis team has developed complex three-dimensional models of the LISA Technology Package (LTP) experiment on-board LPF. These models are used for simulations, but more importantly, they will be used for parameter estimation purposes during flight operations. One of the tasks of the data analysis team is to identify the physical effects that contribute significantly…
PTA-Compatible Domain Walls at LISA and Taiji: Bayesian Reconstruction and Multiband Inference
Nanjing Normal University（南京师范大学）；Scuola Superiore Meridionale, Università degli studi di Napoli “Federico II”（那不勒斯费德里科二世大学南方高等学院）；INFN - Sezione di Napoli（意大利国家核物理研究所那不勒斯分部）
The Laser Interferometer Space Antenna (LISA) defines new demands on data analysis efforts in its all-sky gravitational wave survey, recording simultaneously thousands of galactic compact object binary foreground sources and tens to hundreds of background sources like binary black hole mergers and extreme mass ratio inspirals. We approach this problem with an adaptive and fully automatic Reversible Jump Markov Chain Monte Carlo sampler, able to sample from the joint posterior density function (as established by Bayes theorem) for a given mixture of signals "out of the box'', handling the total…
Probing fundamental physics with Extreme Mass Ratio Inspirals: a full Bayesian inference for scalar charge
Max Planck Institute for Gravitational Physics (Albert Einstein Institute)（马克斯·普朗克引力物理研究所（阿尔伯特·爱因斯坦研究所））；School of Mathematical Sciences & School of Physics and Astronomy, University of Nottingham（诺丁汉大学数学科学学院与物理与天文学学院）；Nottingham Centre of Gravity, University of Nottingham（诺丁汉大学重力研究中心）；Gran Sasso Science Institute (GSSI)（格兰萨索科学研究所）；INFN, Laboratori Nazionali del Gran Sasso（意大利国家核物理研究所，格兰萨索国家实验室）；School of Mathematics and Statistics, University College Dublin（都柏林大学学院数学与统计学院）；Niels Bohr International Academy, Niels Bohr Institute（尼尔斯·玻尔国际学院，尼尔斯·玻尔研究所）；Department of Physics, National University of Singapore（新加坡国立大学物理系）；Department of Mathematics, National University of Singapore（新加坡国立大学数学系）；Laboratoire des 2 Infinis – Toulouse (L2IT-IN2P3), Universitè de Toulouse, CNRS（图卢兹双无穷实验室（L2IT-IN2P3），图卢兹大学，法国国家科学研究中心）
Extreme mass ratio inspirals (EMRIs) are thought to be one of the most exciting gravitational wave sources to be detected with LISA. Due to their complicated nature and weak amplitudes the detection and parameter estimation of such sources is a challenging task. In this paper we present a statistical methodology based on Bayesian inference in which the estimation of parameters is carried out by advanced Markov chain Monte Carlo (MCMC) algorithms such as parallel tempering MCMC. We analysed high and medium mass EMRI systems that fall well inside the low frequency range of LISA. In the context o…
In this paper we describe a Bayesian inference framework for analysis of data obtained by LISA. We set up a model for binary inspiral signals as defined for the Mock LISA Data Challenge 1.2 (MLDC), and implemented a Markov chain Monte Carlo (MCMC) algorithm to facilitate exploration and integration of the posterior distribution over the 9-dimensional parameter space. Here we present intermediate results showing how, using this method, information about the 9 parameters can be extracted from the data.
Stellar-mass black hole binaries (SBHBs), like those currently being detected with the ground-based gravitational-wave (GW) observatories LIGO and Virgo, are also an anticipated GW source for LISA. LISA will observe them during the early inspiral stage of evolution; some of them will chirp through the LISA band and reappear some time later in the band of $3^{rd}$ generation ground-based detectors. SBHBs could serve as laboratories for testing the theory of General Relativity and inferring the astrophysical properties of the underlying population. In this study, we assess LISA's ability to infe…
In this work, we discuss the improvement that the joint network of LISA and Taiji could provide on exploring two kinds of black hole formation mechanisms. For astrophysical origin, we consider light seed and heavy seed scenarios, and generate populations accordingly. We find that the joint network has the potential to observe growing light seeds in the range 15 < z < 20, while single detector can hardly see, which would shed light on the light seeding mechanism. For the heavy seeds, the joint network only improves the signal-to-noise ratio. For primordial origin, we calculate the event rate at…
Electromagnetic observations have provided strong evidence for the existence of massive black holes in the center of galaxies, but their origin is still poorly known. Different scenarios for the formation and evolution of massive black holes lead to different predictions for their properties and merger rates. LISA observations of coalescing massive black hole binaries could be used to reverse engineer the problem and shed light on these mechanisms. In this paper, we introduce a pipeline based on hierarchical Bayesian inference to infer the mixing fraction between different theoretical models b…
We consider the observation of stellar-mass black holes binaries with the Laser Interferometer Space Antenna (LISA). Preliminary results based on Fisher information matrix analyses have suggested that gravitational waves from those sources could be very sensitive to possible deviations from the theory of general relativity and from the strong equivalence principle during the low-frequency binary inspiral. We perform a full Markov Chain Monte Carlo Bayesian analysis to quantify the sensitivity of these signals to two phenomenological modifications of general relativity, namely a putative gravit…
Discriminating scalar ultralight dark matter from quasi-monochromatic gravitational waves in LISA
Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology（高等能源物理研究所，巴塞罗那科学与技术研究院）；Observatoire de Paris, Université PSL, Sorbonne Université, Université de Lille（巴黎天文台，巴黎文理研究大学，索邦大学，里尔大学）
We are developing a Bayesian approach based on Markov chain Monte Carlo techniques to search for and extract information about white dwarf binary systems with the Laser Interferometer Space Antenna (LISA). Here we present results obtained by applying an initial implementation of this method to some of the data sets released in Round 1B of the Mock LISA Data Challenges. For Challenges 1B.1.1a and 1b the signals were recovered with parameters lying within the 95.5% posterior probability interval and the correlation between the true and recovered waveform is in excess of 99%. Results were not sub…
The Laser Interferometer Space Antenna (LISA) is expected to detect gravitational radiation from a large number of compact binary systems. We present a method by which these signals can be identified and have their parameters estimated. Our approach uses Bayesian inference, specifically the application of a Markov chain Monte Carlo method. The simulation study that we present here considers a large number of sinusoidal signals in noise, and our method estimates the number of periodic signals present in the data, the parameters for these signals and the noise level. The method is significantly …
In the next decade, the Laser Interferometer Space Antenna (LISA) will detect the coalescence of massive black hole binaries (MBHBs) in the range $[10^4, 10^8] \, \rm M_{\odot}$, up to $z\sim10$. Their gravitational wave (GW) signal is expected to be accompanied by an electromagnetic counterpart (EMcp), generated by the gas accreting on the binary or on the remnant BH. In this work, we present the number and characteristics (such as redshift and mass distribution, apparent magnitudes or fluxes) of EMcps detectable jointly by LISA and some representative EM telescopes. We combine state-of-the-a…
White dwarf stars are a well-established tool for studying Galactic stellar populations. Two white dwarfs in a tight binary system offer us an additional messenger - gravitational waves - for exploring the Milky Way and its immediate surroundings. Gravitational waves produced by double white dwarf (DWD) binaries can be detected by the future Laser Interferometer Space Antenna (LISA). Numerous and widespread DWDs have the potential to probe shapes, masses and formation histories of the stellar populations in the Galactic neighbourhood. In this work we outline a method for estimating the total s…
The upcoming Laser Interferometer Space Antenna (LISA) will detect a large gravitational-wave foreground of Galactic white dwarf binaries. These sources are exceptional for their probable detection at electromagnetic wavelengths, some long before LISA flies. Studies in both gravitational and electromagnetic waves will yield strong constraints on system parameters not achievable through measurements of one messenger alone. In this work, we present a Bayesian inference pipeline and simulation suite in which we study potential constraints on binaries in a variety of configurations. We show how us…
Galactic ultra compact binaries are expected to be the dominant source of gravitational waves in the milli-Hertz frequency band. Of the tens of millions of galactic binaries with periods shorter than an hour, it is estimated that a few tens of thousand will be resolved by the future Laser Interferometer Space Antenna (LISA). The unresolved remainder will be the main source of ``noise'' between 1-3 milli-Hertz. Typical galactic binaries are millions of years from merger, and consequently their signals will persist for the the duration of the LISA mission. Extracting tens of thousands of overlap…
