Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash 87 tok/s
Gemini 2.5 Pro 51 tok/s Pro
GPT-5 Medium 16 tok/s
GPT-5 High 18 tok/s Pro
GPT-4o 104 tok/s
GPT OSS 120B 459 tok/s Pro
Kimi K2 216 tok/s Pro
2000 character limit reached

Lensing bias on cosmological parameters from bright standard sirens (2310.12764v2)

Published 19 Oct 2023 in astro-ph.CO

Abstract: Next generation gravitational waves (GWs) observatories are expected to measure GW signals with unprecedented sensitivity, opening new, independent avenues to learn about our Universe. The distance-redshift relation is a fulcrum for cosmology and can be tested with GWs emitted by merging binaries of compact objects, called standard sirens, thanks to the fact that they provide the absolute distance from the source. On the other hand, fluctuations of the intervening matter density field induce modifications on the measurement of luminosity distance compared to that of a homogeneous universe. Assuming that the redshift information is obtained through the detection of an electromagnetic counterpart, we investigate the impact that lensing of GWs might have in the inference of cosmological parameters. We treat lensing as a systematic error and check for residual bias on the values of the cosmological parameters. We do so by means of mock catalogues of bright sirens events in different scenarios relevant to Einstein Telescope. For our fiducial scenario, the lensing bias can be comparable to or greater than the expected statistical uncertainty of the cosmological parameters, although non-negligible fluctuations in the bias values are observed for different realisations of the mock catalogue. We also discuss some mitigation strategies that can be adopted in the data analysis. Overall, our work highlights the need to model lensing effects when using standard sirens as probes of the distance-redshift relation.

Citations (2)
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run prompts on this paper using GPT-5.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.