Search

The spin orientations of spinning binary black hole (BBH) mergers detected by ground-based gravitational wave detectors such as LIGO and Virgo can provide important clues about the formation of such binaries. However, these spin tilts, i.e., the angles between the spin vector of each black hole and the binary's orbital angular momentum vector, can change due to precessional effects as the black holes evolve from a large separation to their merger. The tilts inferred at a frequency in the sensitive band of the detectors by comparing the signal with theoretical waveforms can thus be significantly different from the tilts when the binary originally formed. These tilts at the binary's formation are well approximated in many scenarios by evolving the BBH backwards in time to a formally infinite separation. Using the tilts at infinite separation also places all binaries on an equal footing in analyzing their population properties. In this paper, we perform parameter estimation for simulated BBHs and investigate the differences between the tilts one infers directly close to merger and those obtained by evolving back to infinite separation. We select simulated observations such that their configurations show particularly large differences in their orientations close to merger and at infinity. While these differences may be buried in the statistical noise for current detections, we show that in future plus-era (A$+$ and Virgo$+$) detectors, they can be easily distinguished in some cases. We also consider the tilts at infinity for BBHs in various spin morphologies and at the endpoint of the up-down instability. In particular, we find that we are able to easily identify the up-down instability cases as such from the tilts at infinity., Comment: 18 pages, 10 figures

We present, for the first time, recoil velocity estimates for binary neutron star mergers using data from numerical relativity simulations. We find that binary neutron star merger remnants can have recoil velocity of the order of a few tens of km/s and as high as $150$ km/s in our dataset. These recoils are attained due to equivalent contributions from the anisotropic gravitational wave emission as well as the asymmetric ejection of dynamical matter during the merger. We provide fits for net recoil velocity as well as its ejecta component as a function of the amount of ejected matter, which may be useful when constraints on the ejected matter are obtained through electromagnetic observations. We also estimate the mass and spin of the remnants and find them to be in the range $[2.34, 3.38] M_{\odot}$ and $[0.63, 0.82]$ respectively, for our dataset., Comment: 14 pages, 9 figures

The LIGO-Virgo gravitational wave detectors have confidently observed 4 events involving neutron stars: two binary neutron star (BNS) mergers (GW170817 and GW190425), and two neutron star-black hole mergers (GW200105 and GW200115). However, our theoretical understanding of the remnant properties of such systems is incomplete due to the complexities related to the modeling of matter effects and the very high computational cost of corresponding numerical relativity simulations. An important such property is the recoil velocity, which is imparted onto the remnant due to the anisotropic emission of gravitational radiation and the dynamical ejection of matter in the kilonova. In this work, we combine gravitational radiation as well as dynamical ejecta distributions, computed by the Computational Relativity numerical simulations, to get accurate estimates for BNS remnant recoil velocities. We find that recoils due to ejection of matter dominate those caused by gravitational wave emission. Knowledge of BNS remnant recoil velocities is important in determining if the remnant is retained by its environment for future hierarchical mergers which, in turn, can form binaries with black holes in the so-called lower mass gap of 3 to 5 solar masses., Comment: The results, analysis and conclusions of this IAU Proceedings article are incomplete and have been superseded by arXiv:2308.03955

We present the design and performance of the GROWTH-India telescope, a 0.7 m robotic telescope dedicated to time-domain astronomy. The telescope is equipped with a 4k back-illuminated camera giving a 0.82-degree field of view and sensitivity of m_g ~20.5 in 5-min exposures. Custom software handles observatory operations: attaining high on-sky observing efficiencies (>~ 80%) and allowing rapid response to targets of opportunity. The data processing pipelines are capable of performing PSF photometry as well as image subtraction for transient searches. We also present an overview of the GROWTH-India telescope's contributions to the studies of Gamma-ray Bursts, the electromagnetic counterparts to gravitational wave sources, supernovae, novae and solar system objects., Comment: 17 pages, 8 figures, Accepted for publication in The Astronomical Journal

A number of synoptic sky surveys are underway or being planned. Typically they are done with small telescopes and relatively short exposure times. A search for transient or variable sources involves comparison with deeper baseline images, ideally obtained through the same telescope and camera. With that in mind we have stacked images from the 0.68~m Schmidt telescope on Mt. Bigelow taken over ten years as part of the Catalina Sky Survey. In order to generate deep reference images for the Catalina Real-time Transient Survey, close to 0.8 million images over 8000 fields and covering over 27000~sq.~deg. have gone into the deep stack that goes up to 3 magnitudes deeper than individual images. CRTS system does not use a filter in imaging, hence there is no standard passband in which the optical magnitude is measured. We estimate depth by comparing these wide-band unfiltered co-added images with images in the $g$-band and find that the image depth ranges from 22.0--24.2 across the sky, with a 200-image stack attaining an equivalent AB magnitude sensitivity of 22.8. We compared various state-of-the-art software packages for co-adding astronomical images and have used SWarp for the stacking. We describe here the details of the process adopted. This methodology may be useful in other panoramic imaging applications, and to other surveys as well. The stacked images are available through a server at Inter-University Centre for Astronomy and Astrophysics (IUCAA)., Comment: 16 pages, 15 figures

Two important parameters inferred from the gravitational wave signals of binaries of precessing black holes are the spin tilt angles, i.e., the angles at which the black holes' spin axes are inclined with respect to the binary's orbital angular momentum. The LIGO-Virgo parameter estimation analyses currently provide spin tilts at a fiducial reference frequency, often the lowest frequency used in the data analysis. However, the most astrophysically interesting quantities are the spin tilts when the binary was formed, which can be significantly different from those at the reference frequency for strongly precessing binaries. The spin tilts at formally infinite separation are a good approximation to the tilts at formation in many formation channels and can be computed efficiently for binary black holes using precession-averaged evolution. Here, we present a new code for computing the tilts at infinity that combines the precession-averaged evolution with orbit-averaged evolution at high frequencies and illustrate its application to GW190521 and other binary black hole detections from O3a. We have empirically determined the transition frequency between the orbit-averaged and precession-averaged evolution to produce tilts at infinity with a given accuracy. We also have regularized the precession-averaged equations in order to obtain good accuracy for the very close-to-equal-mass binary parameters encountered in practice. This additionally allows us to investigate the singular equal-mass limit of the precession-averaged expressions, where we find an approximate scaling of $1/(1 - q)$ with the mass ratio $q$., Comment: 25 pages, 16 figures

Instrumental and environmental transient noise bursts in gravitational-wave detectors, or glitches, may impair astrophysical observations by adversely affecting the sky localization and the parameter estimation of gravitational-wave signals. Denoising of detector data is especially relevant during low-latency operations because electromagnetic follow-up of candidate detections requires accurate, rapid sky localization and inference of astrophysical sources. NNETFIX is a machine learning-based algorithm designed to remove glitches detected in coincidence with transient gravitational-wave signals. NNETFIX uses artificial neural networks to estimate the portion of the data lost due to the presence of the glitch, which allows the recalculation of the sky localization of the astrophysical signal. The sky localization of the denoised data may be significantly more accurate than the sky localization obtained from the original data or by removing the portion of the data impacted by the glitch. We test NNETFIX in simulated scenarios of binary black hole coalescence signals and discuss the potential for its use in future low-latency LIGO-Virgo-KAGRA searches. In the majority of cases for signals with a high signal-to-noise ratio, we find that the overlap of the sky maps obtained with the denoised data and the original data is better than the overlap of the sky maps obtained with the original data and the data with the glitch removed., Comment: 26 pages, 10 figures, 10 tables

Random projection (RP) is a powerful dimension reduction technique widely used in the analysis of high dimensional data. We demonstrate how this technique can be used to improve the computational efficiency of gravitational wave searches from compact binaries of neutron stars or black holes. Improvements in low-frequency response and bandwidth due to detector hardware upgrades pose a data analysis challenge in the advanced LIGO era as they result in increased redundancy in template databases and longer templates due to the higher number of signal cycles in-band. The RP-based methods presented here address both these issues within the same broad framework. We first use RP for an efficient, singular value decomposition inspired template matrix factorization and develop a geometric intuition for why this approach works. We then use RP to calculate approximate time-domain match correlations in a lower dimensional vector space. For searches over parameters corresponding to non-spinning binaries with a neutron star and a black hole, a combination of the two methods can reduce the total on-line computational cost by an order of magnitude over a nominal baseline. This can, in turn, help free-up computational resources needed to go beyond current spin-aligned searches to more complex ones involving generically spinning waveforms., Comment: Matches the published version in Physical Review D (Rapid Communication) Phys. Rev. D 99, 101503(R) (2019)