arXiv subjects

Leo C. Y. Ng

Publications and source records attributed to Leo C. Y. Ng.

2 recordsLinked to original sources

arXiv2026

ler: LVK (LIGO-Virgo-KAGRA collaboration) event (compact-binary mergers) rate calculator and simulator

ler is a Python package for simulating compact-binary gravitational-wave populations and estimating detectable event rates for current and future LIGO-Virgo-KAGRA detector networks. The package provides a unified framework for unlensed and strongly lensed binary black hole, binary neutron star, and neutron star-black hole mergers. It samples source and lens populations, evaluates detector selection effects, solves lens equations for strongly lensed systems, and computes image properties such as magnifications and time delays. The framework supports multiple source-population and lens models, including SIS, SIE, and EPL plus external shear, and allows users to replace default distributions and detection criteria through modular interfaces. Computational efficiency is obtained through vectorized sampling, inverse-transform and importance-sampling strategies, multiprocessing, and just-in-time compiled routines. ler is designed for large-scale Monte Carlo studies in which rates and selected populations must be evaluated repeatedly, including forecasts for observing runs, studies of lensing candidate validation, and selection-function calculations for population inference. The package is distributed with documentation (https://ler.hemantaph.com/), validation examples, and reproducible workflows.

astro-ph.IM↗

arXiv2025

Uncovering faint lensed gravitational-wave signals and reprioritizing their follow-up analysis using galaxy lensing forecasts with detected counterparts

Like light, gravitational waves can be gravitationally lensed by massive astrophysical objects. Strong gravitational lensing by galaxies and galaxy clusters is anticipated to become observable in the coming years. This phenomenon will manifest as multiple copies of the original wave, each exhibiting identical frequency evolution but distinct arrival times, amplitudes, and overall phases. Some of these images can be below the detection threshold and require targeted search methods, based on tailor-made template banks. These searches can be made more sensitive by using our knowledge of the typical distribution and morphology of lenses to predict the time delay, magnification, and image-type ordering of the lensed images. Here, we show that when a subset of the galaxy lensed images is super-threshold, they can be used to construct a more constrained prediction of the arrival time of the remaining signals, enhancing our ability to identify lensing candidate signals. Our suggested method effectively reduces the list of triggers requiring follow-up and generally re-ranks the genuine counterpart higher in the lensing candidate list. So, using information provided by the two or three super-threshold images, one can identify additional lensed images, also strengthening the evidence for the lensed signal hypothesis.

gr-qc↗