GWDALI Software (version 0.1.4)

Software developed to perform parameter estimations of gravitational waves from compact objects coalescence (CBC) via Gaussian and Beyond-Gaussian approximation of GW likelihood. The Gaussian approximation is related to Fisher Matrix, from which it is direct to compute the covariance matrix by inverting the Fisher Matrix [1]. GWDALI also deals with the not-so-infrequent cases of Fisher Matrix with zero-determinant. The Beyond-Gaussian approach uses the Derivative Approximation for LIkelihoods (DALI) algorithm proposed in [2] and applied to gravitational waves in [3], whose model parameter uncertainties are estimated via Monte Carlo sampling but less costly than using the GW likelihood with no approximation. Check our paper in arXiv.

• Published Paper (Astronomy and Computing)

• pypi page

• github page

Installation

To install the software run the command below:

$ pip install gwdali

Contents:

• Usage
• API
• Derivative Approximation for LIkelihood (DALI)
• Priors
• GW Sources Characterization
• Detectors (Position/Orientation/Shape)
• License
• About the Author

References

[1] L. S. Finn and D. F. Chernoff, “Observing binary inspiral in gravitational radiation: One interferometer,” Phys. Rev. D, vol. 47, pp. 2198–2219, 1993.

[2] E. Sellentin, M. Quartin, and L. Amendola, “Breaking the spell of gaussianity: forecasting with higher order fisher matrices,” Monthly Notices of the Royal Astronomical Society, vol. 441, no. 2, pp. 1831–1840, 2014.

[3] Z. Wang, C. Liu, J. Zhao, and L. Shao, “Extending the fisher information matrix in gravitational-wave data analysis,” arXiv preprint arXiv:2203.02670, 2022.