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Register a new userA Data-Driven Approach for Extraction of Event-Waveform: Application to Gravitational Waves
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We develop a general data-driven and template-free method for the extraction of event waveforms in the presence of background noise. Recent gravitational-wave observations provide one of the significant scientific areas requiring data analysis and waveform extraction capability. We use our method to find the waveforms for the reported events from the first, second, and third LIGO observation runs (O1, O2, and O3). Using the instantaneous frequencies derived by the Hilbert transform of the extracted waveforms, we provide the physical time delays between the arrivals of gravitational waves to the detectors.
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Searches for gravitational waves crucially depend on exact signal processing of noisy strain data from gravitational wave detectors, which are known to exhibit significant non-Gaussian behavior. In this paper, we study two distinct non-Gaussian effects in the LIGO/Virgo data which reduce the sensitivity of searches: first, variations in the noise power spectral density (PSD) on timescales of more than a few seconds; and second, loud and abrupt transient `glitches of terrestrial or instrumental origin. We derive a simple procedure to correct, at first order, the effect of the variation in the PSD on the search background. Given the knowledge of the existence of localized glitches in particular segments of data, we also develop a method to insulate statistical inference from these glitches, so as to cleanly excise them without affecting the search background in neighboring seconds. We show the importance of applying these methods on the publicly available LIGO data, and measure an increase in the detection volume of at least $15%$ from the PSD-drift correction alone, due to the improved background distribution.
As an essential part of Chinau00e2u0080u0099s Gravitational Waves Program, the Ali CMB Polarization Telescope (AliCPT) is a ground-based experiment aiming at the Primordial Gravitational Waves (PGWs) by measuring B-mode polarization of Cosmic Microwave Background (CMB). First proposed in 2014 and currently in fast construction phase, AliCPT is Chinau00e2u0080u0099s first CMB project that plans for commissioning in 2019. Led by the Institute of High Energy Physics (IHEP) under the Chinese Academy of Sciences (CAS), the project is a worldwide collaboration of more than fifteen universities and research institutes. Ali CMB Project is briefly introduced.
Gravitational waves (GWs) produced by sound waves in the primordial plasma during a strong first-order phase transition in the early Universe are going to be a main target of the upcoming Laser Interferometer Space Antenna (LISA) experiment. In this short note, I draw a global picture of LISAs expected sensitivity to this type of GW signal, based on the concept of peak-integrated sensitivity curves (PISCs) recently introduced in [1909.11356, 2002.04615]. In particular, I use LISAs PISC to perform a systematic comparison of several thousands of benchmark points in ten different particle physics models in a compact fashion. The presented analysis (i) retains the complete information on the optimal signal-to-noise ratio, (ii) allows for different power-law indices describing the spectral shape of the signal, (iii) accounts for galactic confusion noise from compact binaries, and (iv) exhibits the dependence of the expected sensitivity on the collected amount of data. An important outcome of this analysis is that, for the considered set of models, galactic confusion noise typically reduces the number of observable scenarios by roughly a factor two, more or less independent of the observing time. The numerical results presented in this paper are also available on Zenodo [http://doi.org/10.5281/zenodo.3837877].
The recent completion of Advanced LIGO suggests that gravitational waves (GWs) may soon be directly observed. Past searches for gravitational-wave transients have been impacted by transient noise artifacts, known as glitches, introduced into LIGO data due to instrumental and environmental effects. In this work, we explore how waveform complexity, instead of signal-to-noise ratio, can be used to rank event candidates and distinguish short duration astrophysical signals from glitches. We test this framework using a new hierarchical pipeline that directly compares the Bayesian evidence of explicit signal and glitch models. The hierarchical pipeline is shown to have strong performance, and in particular, allows high-confidence detections of a range of waveforms at realistic signal-to-noise ratio with a two detector network.
Gravitational-wave memory manifests as a permanent distortion of an idealized gravitational-wave detector and arises generically from energetic astrophysical events. For example, binary black hole mergers are expected to emit memory bursts a little more than an order of magnitude smaller in strain than the oscillatory parent waves. We introduce the concept of orphan memory: gravitational-wave memory for which there is no detectable parent signal. In particular, high-frequency gravitational-wave bursts ($gtrsim$ kHz) produce orphan memory in the LIGO/Virgo band. We show that Advanced LIGO measurements can place stringent limits on the existence of high-frequency gravitational waves, effectively increasing the LIGO bandwidth by orders of magnitude. We investigate the prospects for and implications of future searches for orphan memory.
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