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Simon M. C. Yeung

Publications and source records attributed to Simon M. C. Yeung.

2 recordsLinked to original sources

wolensing: A Python package for computing the amplification factor for gravitational waves with wave-optics effects

The wolensing Python package offers a solution for gravitational wave lensing computations within the full wave-optics regime. This tool is primarily designed to calculate the gravitational lensing amplification factor including diffractive effects, an essential component for generating accurate lensed gravitational wave waveforms. These waveforms are integral to astrophysical and cosmological studies related to gravitational-wave lensing. Integrating with lensingGW (Pagano, Hannuksela, and Li 2020), wolensing provides solutions for image positions in the high-frequency regime where wave and geometrical optics converge. This functionality allows the amplification factor to be applicable across a wider frequency range. Another key feature of wolensing is its ability to plot time delay contours on the lens plane, offering researchers a visual tool to better understand the relationship between the lens system and the amplification factor. wolensing is compatible with various lens models in lenstronomy (Birrer et al. 2021). There are also built-in lens models including point mass, singular isothermal sphere (SIS),and nonsingular isothermal ellipsoid (NIE) with jax (Bradbury et al. 2018) supporting GPU computation. Users can accommodate different lens models in the code with jax. wolensing is available as an open-source package on PyPI and can be installed via pip.

astro-ph.IM↗

Detectability of microlensed gravitational waves

Gravitational lensing describes the bending of the trajectories of light and gravitational waves due to the gravitational potential of a massive object. Strong lensing by galaxies can create multiple images with different overall amplifications, arrival times, and image types. If, furthermore, the gravitational wave encounters a star along its trajectory, microlensing will take place. Previously, it has been shown that the effects of microlenses on strongly-lensed type-I images could be negligible in practice, at least in the low magnification regime. In this work, we study the same effect on type-II strongly-lensed images by computing the microlensing amplification factor. As opposed to being magnified, type-II images are typically demagnified. Moreover, microlensing on top of type-II images induces larger mismatches with un-microlensed waveforms than type-I images. These results are broadly consistent with recent literature and serve to confirm the findings. In addition, we investigate the possibility of detecting and analysing microlensed signals through Bayesian parameter estimation with an isolated point mass lens template, which has been adopted in recent parameter estimation literature. In particular, we simulate gravitational waves microlensed by a microlens embedded in a galaxy potential near moderately magnified type-I and II macroimages, with variable lens masses, source parameters and macromagnifcations. Generally, an isolated point mass model could be used as an effective template to detect a type-II microlensed image but not for type-I images, demonstrating the necessity for more realistic microlensing search templates.

gr-qc↗