Extraction of gravitational wave signals from LISA data in the presence of artifacts
Eleonora Castelli, Quentin Baghi, John G. Baker, Jacob Slutsky, Jérôme Bobin, Nikolaos Karnesis, Antoine Petiteau, Orion Sauter, Peter Wass, William J. Weber
The Laser Interferometer Space Antenna (LISA) mission is being developed by ESA with NASA participation. As it has recently passed the Mission Adoption milestone, models of the instruments and noise performance are becoming more detailed, and likewise prototype data analyses must as well. Assumptions such as Gaussianity, stationarity, and data continuity are unrealistic, and must be replaced with physically motivated data simulations, and data analysis methods adapted to accommodate such likely imperfections. To this end, the LISA Data Challenges have produced datasets featuring time-varying and unequal constellation armlength, and measurement artifacts including data interruptions and instrumental transients. In this work, we assess the impact of these data artifacts on the inference of Galactic Binary and Massive Black Hole properties. Our analysis shows that the treatment of noise transients and gaps is necessary for effective parameter estimation, as they substantially corrupt the analysis if unmitigated. We find that straightforward mitigation techniques can significantly if imperfectly suppress artifacts. For the Galactic Binaries, mitigation of glitches was essentially total, while mitigations of the data gaps increased parameter uncertainty by approximately 10%. For the Massive Black Hole binaries the particularly pernicious glitches resulted in a 30% uncertainty increase after mitigations, while the data gaps can increase parameter uncertainty by up to several times. Critically, this underlines the importance of early detection of transient gravitational waves to ensure they are protected from planned data interruptions.
Based on the rate of resolved stellar origin black hole and neutron star mergers measured by LIGO and Virgo, it is expected that these detectors will also observe an unresolved Stochastic Gravitational Wave Background (SGWB) by the time they reach design sensitivity. Since the same binaries observed by LIGO and Virgo pass through the LISA mHz frequency band at an earlier stage of their orbital evolution,it is foreseen that their SGWB will also be observable by LISA with Signal to Noise Ratio (SNR) $\sim 53$. Unlike the stochastic signal from Galactic white dwarf binaries, for which a subtracti…
The LISA Data Challenges Working Group within the LISA Consortium has started publishing datasets to benchmark, compare, and build LISA data analysis infrastructure as the Consortium prepares for the launch of the mission. We present our solution to the dataset from LISA Data Challenge (LDC) 1A containing a single massive black hole binary signal. This solution is built from a fully-automated and GPU-accelerated pipeline consisting of three segments: a brute-force initial search; a refining search that uses the efficient Likelihood computation technique of Heterodyning (also called Relative Bi…
We present here results from the first-ever search for dark photon dark matter that could have coupled to baryons in LISA Pathfinder, the technology demonstrator for a space-based gravitational-wave antenna. After analyzing approximately three months of data taken by LISA Pathfinder in the frequency range $[2\times 10^{-5},5]$ Hz, corresponding to dark photon masses of $[8\times 10^{-20},2\times 10^{-14}]$ eV/$c^2$, we find no evidence of a dark-matter signal, and set upper limits on the strength of the dark photon/baryon coupling. To perform this search, we leveraged methods that search for q…
The Laser Interferometer Space Antenna (LISA) will open a rich discovery space in the milli-Hertz gravitational wave band. In addition to the anticipated signals from many millions of binary systems, this band may contain new and previously un-imagined sources for which we currently have no models. To detect unmodeled and unexpected signals we need to be able to separate them from instrumental noise artifacts, or glitches. Glitches are a regular feature in the data from ground based laser interferometers, and they were also seen in data from the LISA Pathfinder mission. In contrast to the situ…
Accurate and efficient simulation-based inference for massive black-hole binaries with LISA
Universitá degli Studi di Milano-Bicocca（米兰比可卡大学）；INFN, Sezione di Milano-Bicocca（意大利国家核物理研究所米兰比可卡分部）；Max Planck Institute for Gravitational Physics (Albert Einstein Institute)（马克斯·普朗克引力物理学研究所（爱因斯坦研究所））；Nottingham Centre of Gravity & School of Mathematical Sciences, University of Nottingham（诺丁汉大学引力研究中心与数学科学学院）；Institute for Gravitational Wave Astronomy & School of Physics and Astronomy, University of Birmingham（伯明翰大学引力波天文学研究所与物理天文学院）
Time-delay interferometry (TDI) is a data processing technique for LISA designed to suppress the otherwise overwhelming laser noise by several orders of magnitude. It is widely believed that TDI can only be applied once all phase or frequency measurements from each spacecraft have been synchronized to a common time frame. We demonstrate analytically, using as an example the commonly-used Michelson combination X, that TDI can be computed using the raw, unsynchronized data, thereby avoiding the need for an initial synchronization processing step and significantly simplifying the initial noise re…
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 $\approx 0.1$ mHz to $\approx 10$ mHz range. Given the likely prospect that there will be multiple such detectors, namely 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 Ta…
The detection of galactic binaries as sources of gravitational waves promises an unprecedented wealth of information about these systems, but also raises several challenges in signal processing. In particular the large number of expected sources and the risk of misidentification call for the development of robust methods. We describe here an original non-parametric reconstruction of the imprint of galactic binaries in measurements affected by instrumental noise typical of the space-based gravitational wave observatory LISA. We assess the impact of various approaches based on sparse signal mode…
Importance of including small body spin effects in the modelling of intermediate mass-ratio inspirals. II Accurate parameter extraction of strong sources using higher-order spin effects
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…
Standard methodologies for the extraction of the stochastic gravitational wave background (SGWB) from auto- or cross-correlation of interferometric signals often involve the use of a filter function. The standard optimal filter maximizes the signal-to-noise ratio (SNR) between the total SGWB and the noise. We derive expressions for the optimal filter and SNR in the presence of a target SGWB plus other unwanted components. We also generalize the methodology to the case of template-free reconstruction. The formalism allows to easily perform analyses and forecasts that marginalize over foreground…
Using Simulation, Comparison and Grid Search To Find all Possible Binary Black Hole Source Parameters For Extreme Mass-Ratio Inspiral Gravitational Wave Signals
