About

Author

Mükremin Nergiz
Geophysical Engineer & Software Developer
Independent Researcher, Sivas, Türkiye

ORCID: orcid.org/0009-0001-6789-2774
Contact: e-mail

Why this tool

Before a survey, the practical question is rarely "what does the anomaly look like?" but "will we see the target at all, and how dense must the stations be?". Detectability answers that in seconds, shows the physics behind the answer and gives a script that anyone can rerun, so the reasoning can be checked, cited and improved.

How to cite

Nergiz, M. (2026). Detectability: Pre-survey detectability, modelled and reproducible (Version 0.1.1) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.23931815

@software{nergiz_detectability,
  author    = {Nergiz, Mükremin},
  title     = {Detectability: Pre-survey detectability, modelled and reproducible},
  version   = {0.1.1},
  year      = {2026},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.23931815},
  url       = {https://doi.org/10.5281/zenodo.23931815}
}

The DOI always points to the latest version; each release also has its own DOI on Zenodo.

Licence and code

The Python library is open source under the BSD-3-Clause licence. Source code: github.com/mukremin-nergiz/detectability.

Install

pip install "git+https://github.com/mukremin-nergiz/detectability"

Python 3.10 or newer; the only dependency is NumPy. Programmatic use over HTTP: POST /api/evaluate (see the API reference). In ChatGPT and Claude: see this page.

Privacy

The tool stores nothing about you. Inputs, including the survey location, are sent to the server only to compute the result and are not kept; the location is used to compute the Earth's magnetic field at the site. "Use my location" asks your browser for permission first. The link you copy keeps your inputs in the address itself.