Acknowledgments
===============

DeepSeek
--------

This project was developed with significant assistance from **DeepSeek** (深度求索), an AI language model that contributed to:

- Theoretical derivations of centroid timescales and envelope growth rate Λ
- Implementation of core estimators (τ_s, τ_u, τ_g, τ_2, τ_3, τ_pole)
- Development of QSmooth and QSynthetic classes
- Debugging and packaging for PyPI
- Documentation and Read the Docs setup
- Manuscript preparation and revision

The authors also acknowledge the use of **Qwen** during the manuscript preparation phases.

Contributors
------------

- Ahmad Muhammad (Lead developer)
- Salim Jibrin Danbatta
- Muhammad Abubakar Isah
- Ibrahim Yahaya Muhammad
- Sulaiman Sulaiman Ahmad
- Abdelrahman Ghozlan
- Ahmet Sait AlAli

Citation
--------

If you use QSignature in your research, please cite:

.. code-block:: bibtex

   @inproceedings{qsignature2026_isdfs,
       author = {A. Muhammad, S. J. Danbatta, M. A. Isah, I. Y. Muhammad, S. S. Ahmad, and A. Ghozlan},
       title = {QSignature 1.0: A dynamical regime classification framework for causal time series data},
       booktitle = {2026 14th International Symposium on Digital Forensics and Security (ISDFS)},
       publisher = {IEEE},
       year = {2026},
       doi = {10.1109/ISDFS69419.2026.11459049}
   }

   @article{qsignature2026_theorems,
       author = {Ahmad Muhammad and Salim Jibrin Danbatta and Muhammad Abubakar Isah and Ibrahim Yahaya Muhammad},
       title = {Theorems for Inferring Canonical Environmental Signature from Causal Response},
       journal = {Research Square},
       doi = {10.21203/rs.3.rs-8916580/v1},
       year = {2026}
   }