Laser Interferometer Space Antenna Data Research Articles

Detecting Gravitational-wave Bursts from Black Hole Binaries in the Galactic Center with LISA

Stellar-mass black hole binaries (BHBs) in galactic nuclei are gravitationally perturbed by the central supermassive black hole (SMBH) of the host galaxy, potentially inducing strong eccentricity oscillations through the eccentric Kozai–Lidov mechanism. These highly eccentric binaries emit a train of gravitational-wave (GW) bursts detectable by the Laser Interferometer Space Antenna (LISA)—a planned space-based GW detector—with signal-to-noise ratios up to ∼100 per burst. In this work, we study the GW signature of BHBs orbiting our galaxy’s SMBH, Sgr A*, which are consequently driven to very high eccentricities. We demonstrate that an unmodeled approach using a wavelet decomposition of the data effectively yields the time-frequency properties of each burst, provided that the GW frequency peaks between 10−3 and 10−1 Hz. The wavelet parameters may be used to infer the eccentricity of the binary, measuring log10(1−e) within an error of 20%. Our proposed search method can thus constrain the parameter space to be sampled by complementary Bayesian inference methods, which use waveform templates or orthogonal wavelets to reconstruct and subtract the signal from LISA data.

Neutron star – white dwarf binaries: probing formation pathways and natal kicks with LISA

ABSTRACT Neutron star–white dwarf (NS + WD) binaries offer a unique opportunity for studying NS-specific phenomena with gravitational waves. In this paper, we employ the binary population synthesis technique to study the Galactic population of NS + WD binaries with the future Laser Interferometer Space Antenna (LISA). We anticipate approximately $\mathcal {O}(10^2)$ detectable NS + WD binaries by LISA, encompassing both circular and eccentric ones formed via different pathways. Despite the challenge of distinguishing these binaries from more prevalent double white dwarfs (especially at frequencies below 2 mHz), we show that their eccentricity and chirp mass distributions may provide avenues to explore the NS natal kicks and common envelope evolution. Additionally, we investigate the spatial distribution of detectable NS + WD binaries relative to the Galactic plane and discuss prospects for identifying electromagnetic counterparts at radio wavelengths. Our results emphasise LISA’s capability to detect and characterize NS + WD binaries and to offer insights into the properties of the underlying population. Our conclusions carry significant implications for shaping LISA data analysis strategies and future data interpretation.

Bilby in space: Bayesian inference for transient gravitational-wave signals observed with LISA

ABSTRACT The Laser Interferometer Space Antenna (LISA) is scheduled to launch in the mid-2030s, and is expected to observe gravitational-wave candidates from massive black hole binary mergers, extreme mass ratio inspirals, and more. Accurately inferring the source properties from the observed gravitational-wave signals is crucial to maximize the scientific return of the LISA mission. bilby, the user-friendly Bayesian inference library, is regularly used for performing gravitational-wave inference on data from existing ground-based gravitational-wave detectors. Given that Bayesian inference with LISA includes additional subtitles and complexities beyond its ground-based counterpart, in this work we introduce bilby_lisa , a python package that extends bilby to perform parameter estimation with LISA. We show that full nested sampling can be performed to accurately infer the properties of LISA sources from transient gravitational-wave signals in (a) zero noise and (b) idealized instrumental noise. By focusing on massive black hole binary mergers, we demonstrate that higher order multipole waveform models can be used to analyse a year’s worth of simulated LISA data, and discuss the computational cost and performance of full nested sampling compared with techniques for optimizing likelihood calculations, such as the heterodyned likelihood.

Adapting the PyCBC pipeline to find and infer the properties of gravitational waves from massive black hole binaries in LISA

The laser interferometer space antenna (LISA), due for launch in the mid 2030s, is expected to observe gravitational waves (GWs) from merging massive black hole binaries (MBHBs). These signals can last from days to months, depending on the masses of the black holes, and are expected to be observed with high signal to noise ratios (SNRs) out to high redshifts. We have adapted the PyCBC software package to enable a template bank search and inference of GWs from MBHBs. The pipeline is tested on the LISA data challenge’s Challenge 2a (‘Sangria’), which contains MBHBs and thousands of galactic binaries (GBs) in simulated instrumental LISA noise. Our search identifies all six MBHB signals with more than 92% of the optimal SNR. The subsequent parameter inference step recovers the masses and spins within their 90% confidence interval. Sky position parameters have eight high likelihood modes which are recovered but often our posteriors favour the incorrect sky mode. We observe that the addition of GBs biases the parameter recovery of masses and spins away from the injected values, reinforcing the need for a global fit pipeline which will simultaneously fit the parameters of the GB signals before estimating the parameters of MBHBs.

The LISA Data Challenge Radler analysis and time-dependent ultra-compact binary catalogues

Context. Galactic binaries account for the loudest combined continuous gravitational wave signal in the Laser Interferometer Space Antenna (LISA) band, which spans a frequency range of 0.1 mHz–1 Hz. Aims. A superposition of low frequency Galactic and extragalactic signals and instrument noise comprise the LISA data stream. Resolving as many Galactic binary signals as possible and characterising the unresolved Galactic foreground noise after their subtraction from the data are a necessary step towards a global fit solution to the LISA data. Methods. We analysed a simulated gravitational wave time series of tens of millions of ultra-compact Galactic binaries hundreds of thousands of years from merger. This dataset is called the Radler galaxy and is part of the LISA Data Challenges. We used a Markov chain Monte Carlo search pipeline specifically designed to perform a global fit to the Galactic binaries and detector noise. Our analysis was performed for increasingly larger observation times of 1.5, 3, 6 and 12 months. Results. We show that after one year of observing, as many as ten thousand ultra-compact binary signals are individually resolvable. Ultra-compact binary catalogues corresponding to each observation time are presented. The Radler galaxy is a training dataset, with binary parameters for every signal in the data stream included. We compare our derived catalogues to the LISA Data Challenge Radler catalogue to quantify the detection efficiency of the search pipeline. Included in the appendix is a more detailed analysis of two corner cases that provide insight into future improvements to our search pipeline.

Prototype global analysis of LISA data with multiple source types

The novel data analysis challenges posed by the Laser Interferometer Space Antenna (LISA) arise from the overwhelmingly large number of astrophysical sources in the measurement band and the density with which they are found in the data. Robust detection and characterization of the numerous gravitational wave sources in LISA data can not be done sequentially, but rather through a simultaneous global fit of a data model containing the full suite of astrophysical and instrumental features present in the data. While previous analyses have focused on individual source types in isolation, here we present the first demonstration of a LISA global fit analysis containing combined astrophysical populations. The prototype pipeline uses a blocked Metropolis Hastings algorithm to alternatingly fit to a population of ultracompact galactic binaries, known “verification binaries” already identified by electromagnetic observations, a population of massive black hole mergers, and an instrument noise model. The global LISA analysis software suite (GLASS) is assembled from independently developed samplers for the different model components. The modular design enables flexibility to future development by defining standard interfaces for adding new, or updating additional, components to the global fit without being overly prescriptive for how those modules must be internally designed. The GLASS pipeline is demonstrated on data simulated for the LISA Data Challenge 2b. Results of the analysis and a road-map for continued development are described in detail.14 MoreReceived 11 January 2023Accepted 27 January 2023DOI:https://doi.org/10.1103/PhysRevD.107.063004© 2023 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasGravitational wavesGravitation, Cosmology & Astrophysics

Nonlocal parameter degeneracy in the intrinsic space of gravitational-wave signals from extreme-mass-ratio inspirals

Extreme-mass-ratio inspirals will be prized sources for the upcoming space-based gravitational-wave observatory Laser Interferometer Space Antenna (LISA). The hunt for these is beset by many open theoretical and computational problems in both source modeling and data analysis. We draw attention here to one of the most poorly understood: the phenomenon of nonlocal correlations in the space of extreme-mass-ratio-inspiral signals. Such correlations are ubiquitous in the continuum of possible signals (degeneracy) and severely hinder the search for actual signals in LISA data. However, they are unlikely to manifest in a realistic set of putative signals (confusion). We develop an inventory of new analysis tools in order to conduct an extensive qualitative study of degeneracy---its nature, causes, and implications. Previously proposed search strategies for extreme-mass-ratio inspirals are reviewed in the light of our results, and additional guidelines are suggested for the scientific analysis of such sources.

Gravitational waves from double white dwarfs as probes of the milky way

ABSTRACT Future gravitational wave detectors, such as the Laser Interferometer Space Antenna (LISA), will be able to resolve a significant number of the ultra compact stellar-mass binaries in our own Galaxy and its neighbourhood. These will be mostly double white dwarf (DWD) binaries, and their underlying population characteristics can be directly correlated to the different properties of the Galaxy. In particular with LISA, we will be able to resolve ${\sim}\mathcal {O}(10^4)$ binaries, while the rest will generate a confusion foreground signal. Analogously to how the total electromagnetic radiation emitted by a galaxy can be related to the underlying total stellar mass, in this work, we propose a framework to infer the same quantity by investigating the spectral shape and amplitude of the confusion foreground signal. For a fixed DWD evolution model and thus a fixed binary fraction, we retrieve percentage-level relative errors on the total stellar mass, which improves for increasing values of the mass. At the same time, we find that variations in the Milky Way shape at a fixed mass and at scale heights smaller than 500 pc are not distinguishable based on the shape of stochastic signal alone. We perform this analysis on simulations of the LISA data, estimating the resolvable sources based on signal-to-noise criteria. Finally, we utilize the catalogue of resolvable sources to probe the characteristics of the underlying population of DWD binaries. We show that the DWD frequency, coalescence time and chirp mass (up to <0.7 M⊙) distributions can be reconstructed from LISA data with no bias.

Resolving Galactic binaries using a network of space-borne gravitational wave detectors

Extracting gravitational wave (GW) signals from individual Galactic binaries (GBs) against their self-generated confusion noise is a key data analysis challenge for space-borne detectors operating in the $\ensuremath{\approx}0.1$ to $\ensuremath{\approx}10\text{ }\text{ }\mathrm{mHz}$ range. Given the likely prospect that there will be multiple such detectors, namely Laser Interferometer Space Antenna (LISA), Taiji, and Tianqin, with overlapping operational periods in the next decade, it is important to examine the extent to which the joint analysis of their data can benefit GB resolution and parameter estimation. To investigate this, we use realistic simulated LISA and Taiji data containing the set of $30\ifmmode\times\else\texttimes\fi{}{10}^{6}$ GBs used in the first LISA data challenge (Radler) and an iterative source extraction method called GBSIEVER introduced in an earlier work. We find that a coherent network analysis of LISA-Taiji data boosts the number of confirmed sources by $\ensuremath{\approx}75%$ over that from a single detector. The residual after subtracting out the reported sources from the data of any one of the detectors is much closer to the confusion noise expected from an ideal, but infeasible, multisource resolution method that perfectly removes all sources above a given signal-to-noise ratio threshold. While parameter estimation for sources common to both the single detector and network improves broadly in line with the enhanced signal-to-noise ratio of GW sources in the latter, deviation from the scaling of error variance predicted by Fisher information analysis is observed for a subset of the parameters.

Bayesian parameter estimation of Galactic binaries in LISA data with Gaussian process regression

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 thousands of these overlapping gravitational wave signals are resolvable, and the rest blurs into a galactic foreground noise; extracting tens of thousands of signals using Bayesian approaches is still computationally expensive. We developed a new end-to-end pipeline using Gaussian Process Regression to model the log-likelihood function in order to rapidly compute Bayesian posterior distributions. Using the pipeline we are able to solve the Lisa Data Challenge (LDC) 1-3 consisting of noisy data as well as additional challenges with overlapping signals and particularly faint signals.

Characterization of time delay interferometry combinations for the LISA instrument noise

Time delay interferometry (TDI) is a post-processing technique used in the Laser Interferometer Space Antenna (LISA) to reduce laser frequency noise by building an equal-arm interferometer via combining time-shifted raw phase measurements. The set of so-called 2nd generation TDI variables which sufficiently suppress laser frequency noise considering realistic LISA orbital dynamics has recently been expanded by a large number of additional solutions. In this paper, we characterize these new TDI channels by relating them to the well-known 1st generation variables $\alpha$, $\beta$, $\gamma$, and $\zeta$. We compute explicitly how each 2nd generation variable can be approximated as a linear combination of these four 1st generation variables, and show numerically that these approximations are accurate enough to model the noises not suppressed by TDI. We use these results to discuss how the newly found channels might be advantageous to use for the LISA data analysis. In addition, we demonstrate that newly found variants of the variable $\zeta$ significantly out-perform the ones previously known from the literature.

Experimental verification of intersatellite clock synchronization at LISA performance levels

The Laser Interferometer Space Antenna (LISA) aims to observe gravitational waves in the mHz regime over its 10-year mission time. LISA will operate laser interferometers between three spacecrafts. Each spacecraft will utilize independent clocks which determine the sampling times of onboard phasemeters to extract the interferometric phases and, ultimately, gravitational wave signals. To suppress limiting laser frequency noise, signals sampled by each phasemeter need to be combined in postprocessing to synthesize virtual equal-arm interferometers. The synthesis in turn requires a synchronization of the independent clocks. This article reports on the experimental verification of a clock synchronization scheme down to LISA performance levels using a hexagonal optical bench. The development of the scheme includes data processing that is expected to be applicable to the real LISA data with minor modifications. Additionally, some noise coupling mechanisms are discussed.

Detection and characterization of instrumental transients in LISA Pathfinder and their projection to LISA

The LISA Pathfinder (LPF) mission succeeded outstandingly in demonstrating key technological aspects of future space-borne gravitational-wave detectors, such as the Laser Interferometer Space Antenna (LISA). Specifically, LPF demonstrated with unprecedented sensitivity the measurement of the relative acceleration of two free-falling cubic test masses. Although most disruptive non-gravitational forces have been identified and their effects mitigated through a series of calibration processes, some faint transient signals of yet unexplained origin remain in the measurements. If they appear in the LISA data, these perturbations (also called glitches) could skew the characterization of gravitational-wave sources or even be confused with gravitational-wave bursts. For the first time, we provide a comprehensive census of LPF transient events. Our analysis is based on a phenomenological shapelet model allowing us to derive simple statistics about the physical features of the glitch population. We then implement a generator of synthetic glitches designed to be used for subsequent LISA studies, and perform a preliminary evaluation of the effect of the glitches on future LISA data analyses.

Prospects for Detecting Exoplanets around Double White Dwarfs with LISA and Taiji

Abstract Recently, Tamanini & Danielski discussed the possibility of detecting circumbinary exoplanets (CBPs) orbiting double white dwarfs (DWDs) with the Laser Interferometer Space Antenna (LISA). Extending their methods and criteria, we discuss the prospects for detecting exoplanets around DWDs not only by LISA, but also by Taiji, a Chinese space-borne gravitational-wave (GW) mission that has slightly better sensitivity at low frequencies. We first explore how different binary masses and mass ratios affect the abilities of LISA and Taiji to detect CBPs. Second, for certain known detached DWDs with high signal-to-noise ratios, we quantify the possibility of CBP detections around them. Third, based on the DWD population obtained from the Mock LISA Data Challenge, we present basic assessments of the CBP detections in our Galaxy during a 4 yr mission time for LISA and Taiji. We discuss the constraints on the detectable zone of each system, as well as the distributions of the inner/outer edge of the detectable zone. With the DWD population, we further inject two different planet distributions with an occurrence rate of 50% and constrain the total detection rates. We briefly discuss the prospects for detecting habitable CBPs around DWDs with a simplified model. These results can provide helpful inputs for upcoming exoplanetary projects and help analyze planetary systems after the common envelope phase.

Bayesian time delay interferometry

Laser frequency noise (LFN) is the dominant source of noise expected in the Laser Interferometer Space Antenna (LISA) mission, at $\sim$7 orders of magnitude greater than the typical signal expected from gravitational waves (GWs). Time-delay interferometry (TDI) suppresses LFN to an acceptable level by linearly combining measurements from individual spacecraft delayed by durations that correspond to their relative separations. Knowledge of the delay durations is crucial for TDI effectiveness. The work reported here extends upon previous studies using data-driven methods for inferring the delays during the post-processing of raw phasemeter data, also known as TDI ranging (TDIR). Our TDIR analysis uses Bayesian methods designed to ultimately be included in the LISA data model as part of a "Global Fit" analysis pipeline. Including TDIR as part of the Global Fit produces GW inferences which are marginalized over uncertainty in the spacecraft separations and allows for independent estimation of the spacecraft orbits. We demonstrate Markov Chain Monte Carlo (MCMC) inferences of the six time-independent delays required in the rigidly rotating approximation of the spacecraft configuration (TDI 1.5) using simulated data. The MCMC uses fractional delay interpolation (FDI) to digitally delay the raw phase meter data, and we study the sensitivity of the analysis to the filter length. Varying levels of complexity in the noise covariance matrix are also examined. Delay estimations are found to result in LFN suppression well below the level of secondary noises and constraints on the armlengths to $\mathcal{O}(30)\ {\rm cm}$ over the ${\sim}2.5\ {\rm Gm}$ baseline.

Characterization of the stochastic signal originating from compact binary populations as measured by LISA

The Laser Interferometer Space Antenna (LISA) mission, scheduled for launch in the early 2030s, is a gravitational wave observatory in space designed to detect sources emitting in the milli-Hertz band. In contrast to the present ground based detectors, the LISA data are expected to be a signaldominated, with strong and weak gravitational wave signals overlapping in time and in frequency. Astrophysical population models predict a sufficient number of signals in the LISA band to blend together and form an irresolvable foreground noise. In this work, we present a generic method for characterizing the foreground signals originating from a given astrophysical population of coalescing compact binaries. Assuming idealized detector conditions and perfect data analysis technique capable of identifying and removing the bright sources, we apply an iterative procedure which allows us to predict the different levels of foreground noise.

Effect of data gaps on the detectability and parameter estimation of massive black hole binaries with LISA

Massive black hole binaries are expected to provide the strongest gravitational wave signals for the Laser Interferometer Space Antenna (LISA), a space mission targeting $\ensuremath{\sim}\mathrm{mHz}$ frequencies. As a result of the technological challenges inherent in the mission's design, implementation, and long duration (4 yr nominal), the LISA data stream is expected to be affected by relatively long gaps where no data is collected (either because of hardware failures, or because of scheduled maintenance operations, such as repointing of the antennas toward the Earth). Depending on their mass, massive black hole binary signals may range from quasitransient to very long lived, and it is unclear how data gaps will impact detection and parameter estimation of these sources. Here, we will explore this question by using state-of-the-art astrophysical models for the population of massive black hole binaries. We will investigate the potential detectability of massive black hole binary signals by observing the effect of gaps on their signal-to-noise ratios. We will also assess the effect of the gaps on parameter estimation for these sources, using the Fisher information matrix formalism as well as full Bayesian analyses. Overall, we find that the effect of data gaps due to regular maintenance of the spacecraft is negligible, except for systems that coalesce within such a gap. The effect of unscheduled gaps, however, will probably be more significant than that of scheduled ones.

Adapting time-delay interferometry for LISA data in frequency

Time-delay interferometry (TDI) is a post-processing technique used to reduce laser noise in heterodyne interferometric measurements with unequal armlengths, a situation characteristic of space gravitational detectors such as Laser Interferometer Space Antenna (LISA). This technique consists in properly time-shifting and linearly combining the interferometric measurements in order to reduce the laser noise by several orders of magnitude and to detect gravitational waves. In this communication, we show that the Doppler shift due to the time evolution of the armlengths leads to an unacceptably large residual noise when using interferometric measurements expressed in units of frequency and standard expressions of the TDI variables. We also present a technique to mitigate this effect by including a scaling of the interferometric measurements in addition to the usual time-shifting operation when constructing the TDI variables. We demonstrate analytically and using numerical simulations that this technique allows one to recover standard laser noise suppression which is necessary to measure gravitational waves.

Archival searches for stellar-mass binary black holes in LISA data

Stellar-mass binary black holes will sweep through the frequency band of the Laser Interferometer Space Antenna (LISA) for months to years before appearing in the audio-band of ground-based gravitational-wave detectors. One can expect several tens of these events up to a distance of $500 \,\mathrm{Mpc}$ each year. The LISA signal-to-noise ratio for such sources even at these close distances will be too small for a blind search to confidently detect them. However, next generation ground-based gravitational-wave detectors, expected to be operational at the time of LISA, will observe them with signal-to-noise ratios of several thousands and measure their parameters very accurately. We show that such high fidelity observations of these sources by ground-based detectors help in archival searches to dig tens of signals out of LISA data each year.

Global analysis of the gravitational wave signal from Galactic binaries

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 overlapping galactic signals and characterizing the unresolved component is a central challenge in LISA data analysis, and a key contribution to arriving at a global solution that simultaneously fits for all signals in the band. Here we present an end-to-end analysis pipeline for galactic binaries that uses trans-dimensional Bayesian inference to develop a time-evolving catalog of sources as data arrive from the LISA constellation.