Skip to main content

VBMicrolensing is a tool for efficient computation in gravitational microlensing events using the advanced contour integration method, supporting single, binary and multiple lenses.

Project description

VBMicrolensing

VBMicrolensing is a tool for efficient computation in gravitational microlensing events using the advanced contour integration method, supporting single, binary and multiple lenses.

In particular, VBMicrolensing is designed for the following calculations:

  • Magnification by single, binary and multiple lenses
  • Centroid of the images generated by single and binary lenses
  • Critical curves and caustics of binary and multiple lenses
  • Complete light curves including several higher order effects: limb darkening of the source, binary source, parallax, xallarap, circular and elliptic orbital motion.

VBMicrolensing is written as a C++ library and wrapped as a Python package, the user can call the code from either C++ or Python. This new code encompasses the well-known VBBinaryLensing code, which is at the basis of several platforms for microlensing modeling. VBBinaryLensing will still be available as a legacy software, but will no longer be maintained.

VBMicrolensing has been developed by Valerio Bozza, University of Salerno, with a substantial contribution by Vito Saggese, University of Naples. We also acknowledge a long list of collaborators who contributed to testing and development of particular aspects over the years: Etienne Bachelet, Fran Bartolic, Sebastiano Calchi Novati, Giovanni Covone, Giuseppe D'Ago, Tyler Heintz, Ava Hoag, Markus Hundertmark, Elahe Khalouei, Radek Poleski, Paolo Rota, Sedighe Sajadian, Rachel Street, Jiyuan Zhang, Keto Zhang, Weicheng Zhang, Wei Zhu.

Attribution

Any use of this code for scientific publications should be acknowledged by a citation to the works relevant to your study:

If specifically relevant to your work, please also cite J. Skowron and A. Gould, arXiv:1203.1034.

Installation

Python

The easiest way to install VBMicrolensing is through pip install VBMicrolensing

In alternative, in order to use the latest build, clone this GitHub repository on your computer, enter your local copy of the repository and run

pip install .

Currently, VBMicrolensing works on Linux, Windows, MacOS and python >= 2.7. The package requires a C++ compiler supporting C++17.

C++

If you just want to use the C++ library, clone this repository, all cpp files and the VBMicrolensing.h are located in in VBMicrolensing/lib and should be added to your project.

The package also contains the following files:

  • VBMicrolensing/data/ESPL.tbl - Pre-calculated table for Extended-source-point-lens
  • VBMicrolensing/data/OB151212coords.txt - Sample file with event coordinates
  • VBMicrolensing/data/satellite1.txt - Sample table for satellite position (Spitzer)
  • VBMicrolensing/data/satellite2.txt - Sample table for satellite position (Kepler)

Documentation

Full documentation for the use of VBmicrolensing in python and documentation for the use of VBmicrolensing in C++ are available.

Furthermore, the vast majority of functions are documented with Python docstrings which can be accessed as, for example, ?VBBL.BinaryMag2() in a Jupyter notebook.

We also provide some examples showing the capabilities of the package. In particular, we reproduce some known triple-lense microlensing events.

License

VBMicrolensing is freely available to the community under the GNU Lesser General Public License Version 3 included in this repository.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

vbmicrolensing-4.1.0.tar.gz (520.4 kB view details)

Uploaded Source

Built Distribution

VBMicrolensing-4.1.0-cp311-cp311-win_amd64.whl (719.4 kB view details)

Uploaded CPython 3.11 Windows x86-64

File details

Details for the file vbmicrolensing-4.1.0.tar.gz.

File metadata

  • Download URL: vbmicrolensing-4.1.0.tar.gz
  • Upload date:
  • Size: 520.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.9

File hashes

Hashes for vbmicrolensing-4.1.0.tar.gz
Algorithm Hash digest
SHA256 be654b8980ab3f135ea297beb6e3aebe3dc48a787fb26e3724c7ebc450f82dff
MD5 4861ef030c74b50420a6244bbaee592b
BLAKE2b-256 0cc59a7d9e8f7d1aeb2e8bec27e8cacba7219ee00dc16a08922126dadf4ab802

See more details on using hashes here.

File details

Details for the file VBMicrolensing-4.1.0-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for VBMicrolensing-4.1.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 3a3ab2224df636fcc79c0233ca1abb978f853f4f69b49b66bd7abdb10e7e6b1c
MD5 769c061c31712948f16854c8785a44a8
BLAKE2b-256 fa021d88fb59a97b67c913d41510b3f99e819777254ef41788c76baf16fac1db

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page