This is the wiki page for the review of GWMAT: Gravitational Wave Microlensing Analysis Tools. GWMAT is a python package containing various useful tools for the study of microlensing (ML) of Gravitational Waves (GWs). There are 5 key elements to it which I list below:
1. A utils module named [py_lgw.py](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/py_lgw.py) - Contains various classes which are used for various purposes by other elements of GWMAT. Some classes of this module heavily rely on _LAL_ and _PyCBC_. There are 7 classes as of now which I describe below:
-[point_lens](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/py_lgw.py#L37): contains functions related to the study of point lens including efficient computation of the amplification factor. In such cases, two images are formed, one minima (type I) and one saddle (type II).
-[cosmology](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/py_lgw.py#L168): contains basic functions to compute cosmological distances as functions of redshift, and vice-versa.
-[cbc_analysis](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/py_lgw.py#L235): contains basic functions relevant to CBC mergers.
-[cbc_parameter_conversions](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/py_lgw.py#L479): contains functions related to parameter conversions relevant for binaries.
-[fitting_factor_domain](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/py_lgw.py#L532): contains functions relevant to fitting factor computation.
-[misc_funcs](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/py_lgw.py#L629): some miscellaneous functions.
-[lensed_wf_gen](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/py_lgw.py#L720): A Child Class inherited from all of the above classes. Contains functions related to microlensed WF generation (with or w/o noise), SNR computation, snr_to_distance (or vice versa) estimates, etc.
This is the wiki page for the review of GWMAT: Gravitational Wave Microlensing Analysis Tools. GWMAT is a python package containing various useful tools for the study of microlensing (ML) of Gravitational Waves (GWs).
2.[FF_compute_module.py](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/FF_compute_module.py) - A module to compute the fitting factor (maximum match). It can handle both unlensed (UL) and microlensed (ML) recoveries. For UL, it maximises the match in 4D parameter space of (m_chirp, q, spin1z, spin2z). For ML, it can either maximise in 5D space of (m_chirp, q, spin1z=spin2z, Mlz, y), or in the 6D space of (m_chirp, q, spin1z, spin2z, Mlz, y), where Mlz and y are microlensing parameters representing redshifted point lens mass and the impact parameter, respectively.
### Developers
3.[point_lens_BBH_fdwf.py](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/point_lens_BBH_fdwf.py): contains frequency domain waveform source model for running PE assuming point lens hypothesis using Bilby, i.e., a 17D waveform model incorporating two extra parameters (Mlz, y) in addition to 15 BBH parameters. The source model [point_lens_BBH_fdwf](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/point_lens_BBH_fdwf.py#L272) uses a lookup table for fast and efficient computation of microlensing effects due to a point-lens. The details on how to generate the lookup table can be found at [point_lens_lookup_table_gen.ipynb](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/notebooks/point_lens_lookup_table_gen.ipynb). Apart from this, a source model that only employs analytic and geometric approximation is also available as [point_lens_BBH_fdwf_analytic](https://git.ligo.org/anuj.mishra/GWMAT/-/blob/main/src/point_lens_BBH_fdwf.py#L300).
4. Amplification factor, F(f), computation for micro + macro cases in case of type-I (minima) images. The code can handle tens of thousands of microlenses.
5. Same as above, but for the case of type-II (saddle-point) images.
