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About:

Welcome to PEREGRINE! A public, open-source pipeline designed for targeted inference of gravitational wave signals from multiple source types.

Access:

Currently, PEREGRINE has two public branches:

  • cbc: Inferring source parameters of standard LVKC CBC sources.
  • overlapping: Inferring source parameters of overlapping or coincident gravitational wave detections in a 2G network.

Papers using PEREGRINE:

  • DOI Sequential simulation-based inference for gravitational wave signals (Bhardwaj, Alvey, Miller, Nissanke, Weniger)
  • DOI What to do when things get crowded? Scalable joint analysis of overlapping gravitational wave signals (Alvey, Bhardwaj, Nissanke, Weniger)

The algorithm:

PEREGRINE leverages the power of (Truncated Marginal) Neural Ratio Estimation (TMNRE) via the open-source package swyft.

Contact:

For any queries related to PEREGRINE, please feel free to contact:

Usage:

If you use PEREGRINE in your analysis, or find it useful, we would ask that you please use the following citations:

@article{Bhardwaj:2023xph,
    author = "Bhardwaj, Uddipta and Alvey, James and Miller, Benjamin Kurt and Nissanke, Samaya and Weniger, Christoph",
    title = "{Peregrine: Sequential simulation-based inference for gravitational wave signals}",
    eprint = "2304.02035",
    archivePrefix = "arXiv",
    primaryClass = "gr-qc",
    month = "4",
    year = "2023"
}
@article{Miller:2022shs,
    author = "Miller, Benjamin Kurt and Cole, Alex and Weniger, Christoph and Nattino, Francesco and Ku, Ou and Grootes, Meiert W.",
    title = "{swyft: Truncated Marginal Neural Ratio Estimation in
Python}",
    doi = "10.21105/joss.04205",
    journal = "J. Open Source Softw.",
    volume = "7",
    number = "75",
    pages = "4205",
    year = "2022"
}

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