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Software . 2025
Data sources: ZENODO
ZENODO
Software . 2025
Data sources: Datacite
ZENODO
Software . 2025
Data sources: Datacite
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High frequency gravitational wave plotter: Noise-equivalent strain

Authors: Muia, Francesco; Ringwald, Andreas; Tamarit, Carlos;

High frequency gravitational wave plotter: Noise-equivalent strain

Abstract

HFGWplotter_Sh: Plotter of noise equivalent strain for gravitational wave detectors Created by Francesco Muia, Andreas Ringwald and Carlos Tamarit. Code maintained by Carlos Tamarit Credit for the data of the plots go the authors of arXiv:2501.11723, whose results and figures are the basis of this plotter HFGWplotter_Sh is an interactive web application designed for visualizing and analyzing sensitivitiy curves for gravitational wave experiments. It offers a user-friendly interface for plotting detector sensitivity curves, allowing researchers and enthusiasts to explore and interpret gravitational wave data effectively. The code uploaded here corresponds to June 2025. For update versions please visit the GitHub page: https://github.com/ctamaritd/HFGWPlotter_Sh Online version As of June 2025, the app is running online at https://incandenza-01.zdv.uni-mainz.de/Shplot/ Dependencies Requires python3 with the following additional dependencies: numpy scipy bokeh flask matplotlib For example, assuming python3 is installed you can create a python virtual environment $python3 -m venv python-virtual-env Inside the environment, you can install the dependencies using pip $pip install numpy scipy bokeh flask matplotlib To load the environment: $source python-virtual-env/bin/activate How to run If you are using a virtual environment, make sure it is activated (see "source" command above) Execute the following command in the main folder python3 app_local.py The plot can be accessed in a browser by entering the following local address: http://127.0.0.1:5003/Shplot Project Structure The application is organized as follows: HFGWplotter_Sh/ # Project directory │ ├── Curves # Repository containing all the curves to be plotted │ └── DetectorCurves # Repository containing all detector curves │ │ ├── aux # Repository containing auxiliary files │ ├── aux_functions.py # File containing auxiliary functions │ ├── data_files.py # File containing information about the curves to be plotted │ └── imports.py # File containing all the imports │ ├── Shplot │ ├──static/ # Static files │ │ ├── css/ # CSS files │ │ │ └── styles.css # Main stylesheet │ │ └── js/ # JavaScript files │ │ └── scripts.js # JavaScript logic │ │ │ └── templates/ # HTML templates │ └── index.html # Main HTML template │ ├── app_local.py # Main Flask application └── README.md # README file Features Current Features Interactive plotting of gravitational wave sensitivitiy curves Toggle visibility of different gravitational wave detector sensitivity curves. Annotations on the plot that provide additional information. Customizable plot ranges and dimensions through interactive sliders. Users can upload their own curves from a csv file Contributing Contributions to HFGWplotter are welcome, whether they be in the form of feature requests, bug reports, or pull requests. For major changes, please open an issue first to discuss what you would like to change. License MIT License.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average