ESIGMAPy: a Python package to generate ESIGMAHM waveforms

ESIGMAHM is an eccentric, aligned-spin, inspiral-merger-ringdown (IMR) waveform model with higher-order modes. It is composed of two pieces:

• Inspiral piece (called InspiralESIGMAHM): The inspiral piece comes from a combination of post-Newtonian theory, self-force, and black hole perturbation theory. It is currently implemented in a private fork of LALSuite (interested users are welcome to write to the developers for access at [email protected]).

• Plunge-merger-ringdown piece: Assuming moderate starting eccentricities that will decay by the late inspiral, we use the quasi-circular NR surrogate NRSur7dq4 for the plunge-merger-ringdown piece for ESIGMAHM. This requires the NRSur7dq4's data file to be downloaded.

  (Note: We also allow other LALSuite waveform models to be used as the plunge-merger-ringdown piece; see the optional argument merger_ringdown_approximant in the generation functions get_imr_esigma_waveform and get_imr_esigma_modes here. However, the default and the most tested choice is NRSur7dq4)

The full IMR waveform ESIGMAHM is then produced by smoothly attaching the inspiral piece InspiralESIGMAHM to the plunge-merger-ringdown piece NRSur7dq4. This attachment is done via ESIGMAPy.

Installing InspiralESIGMAHM

• Getting the source code: The LALSuite fork containing the implementation of InspiralESIGMAHM is currently private, but interested users are welcome to write to the developers for access at [email protected].

  Clone this LALSuite fork and checkout the relevant commit identified by the tag ESIGMAHMv1 which contains the current stable implementation of the inspiral piece of ESIGMAHM.

  git clone https://git.ligo.org/kaushik.paul/lalsuite.git
  cd lalsuite
  git checkout ESIGMAHMv1
  

• Installing the code:

  • Activate your conda environment. Make sure that the swig version in this environment is below 4.2.1 (you can check this by running conda list swig). If not, install its version 4.2.0 by running conda install -c conda-forge swig=4.2.0.

  • Now choose/create a directory where you want to install ESIGMA. Let the absolute path of this directory be /path/to/esigmahm.

  • Go back inside the above cloned LALSuite fork, and sequentially run the following commands:

    ./00boot
    ./configure --prefix="/path/to/esigmahm" --enable-swig-python --disable-laldetchar --disable-lalpulsar --disable-lalapps --enable-mpi=yes --enable-hdf5 CFLAGS="-Wno-error" CXXFLAGS="-Wno-error" CPPFLAGS="-Wno-error" 
    make
    make install
    

• Configuring conda to source this LALSuite fork automatically on activating the conda environment

  • With your conda environment activated, run the following commands:

    cd $CONDA_PREFIX/etc/conda/activate.d
    ln -s /path/to/esigmahm/etc/lalsuite-user-env.sh
    

Installing NRSur7dq4

• Download the NRSur7dq4 data file in some directory. Let's say the absolute path to this directory is /path/to/NRSur7dq4.
• Append the path of this directory to the shell environment variable LAL_DATA_PATH by running: export LAL_DATA_PATH="$LAL_DATA_PATH:/path/to/NRSur7dq4"
• To avoid performing the above step in every new terminal session, either add the above command to your .bashrc file, or follow the instructions here, replacing PYTHONPATH with LAL_DATA_PATH, to set this environment variable automatically on activating your conda environment.

Installing ESIGMAPy

• Activate your conda environment and install ESIGMAPy by running: pip install esigmapy.

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Trying out ESIGMAHM

If everything goes fine, you should be able to generate ESIGMAHM waveforms. The instructions to do so and the various functionalities that ESIGMAHM offers are detailed in this tutorial notebook.

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Citation

If you use ESIGMAHM in your work, please consider citing it:

Paul et. al., "ESIGMAHM: An Eccentric, Spinning inspiral-merger-ringdown waveform model with Higher Modes for the detection and characterization of binary black holes", arXiv:2409.13866 (2024)

@article{Paul:2024ujx,
    author = "Paul, Kaushik and Maurya, Akash and Henry, Quentin and Sharma, Kartikey and Satheesh, Pranav and Divyajyoti and Kumar, Prayush and Mishra, Chandra Kant",
    title = "{ESIGMAHM: An Eccentric, Spinning inspiral-merger-ringdown waveform model with Higher Modes for the detection and characterization of binary black holes}",
    eprint = "2409.13866",
    archivePrefix = "arXiv",
    primaryClass = "gr-qc",
    month = "9",
    year = "2024"
}

ESIGMAHM is built on the ENIGMA framework, which was developed in arXiv:1609.05933, arXiv:1711.06276, arXiv:2008.03313. Thus, in addition to citing ESIGMAHM, please consider citing these works related to ENIGMA as well.

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📬 Contact Us

If you have any questions, issues, or suggestions regarding the model, feel free to reach out to us at [email protected]!