Reconstructing the Hubble Parameter with Future Gravitational-wave Missions Using Machine Learning

Reconstructing the Hubble Parameter with Future Gravitational-wave Missions Using Machine Learning

We study the prospects of Gaussian processes (GPs), a machine-learning (ML) algorithm, as a tool to reconstruct the Hubble parameter H ( z ) with two upcoming gravitational-wave (GW) missions, namely, the evolved Laser Interferometer Space Antenna (eLISA) and the Einstein Telescope (ET). Assuming va...

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Bibliographic Details
Main Authors: Purba Mukherjee, Rahul Shah, Arko Bhaumik, Supratik Pal
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:The Astrophysical Journal
Subjects:
Hubble diagram
Hubble constant
Gravitational waves
Gravitational wave detectors
Interferometers
Gaussian Processes regression
Online Access:https://doi.org/10.3847/1538-4357/ad055f

Internet

https://doi.org/10.3847/1538-4357/ad055f

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