"Finding the stable points where a Matrix respects a Vector's Identity."
As a Quantum Learner and Qiskit Advocate, I built this tool to move beyond abstract numbers and visualize the stability of states. In Quantum Computing, an Eigenvector isn't just a math result; it is a "Stationary State" that maintains its direction even when a Quantum Gate acts upon it.
This interactive Streamlit application allows researchers and learners to "hunt" for the stable directions (Eigenvectors) of 2x2 matrices, including common Quantum Gates like Pauli-X and Pauli-Z.
-
Geometric Intuition: Watch in real-time as the Blue Input Vector (
$v$ ) is transformed into the Red Output Vector ($Av$ ). -
Arithmetic Verification: A live (
$Row \times Column$ ) breakdown to demystify the transformation. -
The Ratio Check (
$\lambda$ ): Automatically calculates the Eigenvalue, proving if the$X$ and$Y$ components scaled by the same factor. - Research Log: Save your discoveries to a local database and export them as a CSV for global collaborations.
- Python 3.x
- Streamlit (UI Framework)
- NumPy (Linear Algebra)
- Matplotlib (Vector Visualization)
- Pandas (Data Logging)
- Clone this repository:
git clone [https://github.com/learningdungeon/EigenFunction](https://github.com/learningdungeon/EigenFunction) cd EigenFunction - Install dependencies:
pip install streamlit numpy matplotlib pandas
- Run the App:
streamlit run app.py
Noor Ul Ain Faisal Education & Technology | Qiskit Advocate | Friend of OQI.CERN | Quantum Software Engineering and Cyber Security
Making complex quantum ideas accessible to businesses and learners through research and global collaboration.
“In a world of rotations, find your axis.”
Credit: Gemini