SensaLisa is a lightweight, user-friendly Python toolkit for generating and visualizing sensitivity curves for the Laser Interferometer Space Antenna (LISA).
Designed for both gravitational-wave researchers and students, SensaLisa provides an intuitive interface for computing detector sensitivity without requiring extensive setup or familiarity with the underlying implementation.
Features
- Generate LISA sensitivity curves with minimal code.
- Fast and lightweight implementation.
- Simple, intuitive API designed for research workflows.
- Publication-quality plots with customizable visualization.
- Modular design for easy integration into existing analysis pipelines.
- Suitable for education, rapid prototyping, and scientific research.
Why SensaLisa?
Many sensitivity curve implementations are embedded inside larger software packages or require unnecessary setup for simple analyses.
SensaLisa focuses on one objective:
Making LISA sensitivity calculations simple, transparent, and accessible.
Whether you are exploring detector performance, testing waveform models, or preparing figures for a publication, SensaLisa allows you to generate sensitivity curves in just a few lines of code.
Installation
git clone https://github.com/BHUVANAKASHI/SensaLisa.git
cd SensaLisa
pip install -r requirements.txt
or install directly from source
pip install .
Quick Start
from sensalisa import ...
# Example code here
Generate a LISA sensitivity curve with only a few commands.
Applications
SensaLisa can be used for
- LISA sensitivity studies
- Signal-to-noise ratio calculations
- Gravitational-wave data analysis
- Detector performance visualization
- Research and teaching
Citation
If SensaLisa contributes to your research, please cite the repository and any accompanying publication.
@software{SensaLisa,
author = {Bhuvaneshwari Kashi},
title = {SensaLisa: A User-Friendly Toolkit for LISA Sensitivity Curves},
year = {2025},
url = {https://github.com/BHUVANAKASHI/SensaLisa}
}
Contributing
Contributions, feature requests, and bug reports are welcome.
Please open an Issue or submit a Pull Request.
Acknowledgements
SensaLisa is inspired by and partially adapts components from the LISA_Sensitivity toolkit developed by the eXtreme Gravity Institute. We gratefully acknowledge the original authors for their implementation of the LISA sensitivity model and their contribution to the gravitational-wave community.
SensaLisa extends this foundation by providing a streamlined, user-friendly interface, simplified workflows, and enhanced visualisation tools for generating and exploring LISA sensitivity curves.
License
This project is released under the MIT License.
References
This project builds upon the following work:
- Robson, T., Cornish, N. J., & Liu, C. (2019). The construction and use of LISA sensitivity curves. Classical and Quantum Gravity, 36(10), 105011.
- LISA_Sensitivity Toolkit: https://github.com/eXtremeGravityInstitute/LISA_Sensitivity
Metadata
Release files for SensaLisa 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sensalisa-0.1.0.tar.gz | 9.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sensalisa-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.0 kB
Release files / sensalisa-0.1.0.tar.gz
| Download URL | sensalisa-0.1.0.tar.gz |
|---|---|
| Size | 9.9 kB |
| Tags | Source |
|
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twine/7.0.0 CPython/3.12.3
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Release files / sensalisa-0.1.0-py3-none-any.whl
| Download URL | sensalisa-0.1.0-py3-none-any.whl |
|---|---|
| Size | 8.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.3
|