This repository contains an in-depth study and implementation of the Quantum Fourier Transform (QFT), developed in Python as part of research conducted during the Quantum Information Processing course.
KEY FEATURES
✅ Quantum Fourier Transform (QFT) Implementation – A fundamental algorithm in quantum computing, crucial for applications like Shor’s algorithm and quantum signal processing.
✅ Mathematical & Computational Analysis – Provides a detailed breakdown of the QFT, including its mathematical foundations, quantum circuit representation, and efficiency compared to classical Fourier Transform methods.
✅ High-Performance Python Code – Optimized implementation leveraging quantum computing libraries.
✅ Research-Driven Approach – Developed as part of an academic research project, ensuring theoretical depth and practical insights into quantum computation.
PROJECT OVERVIEW
The Quantum Fourier Transform is a quantum analog of the classical Discrete Fourier Transform (DFT), enabling exponential speedups in specific quantum algorithms.
This project explores:
- Theoretical principles of QFT and its role in quantum computing.
- Implementation of QFT using Python, integrating quantum computing frameworks such as Qiskit.
- Comparative analysis with classical Fourier methods, highlighting computational advantages and quantum speedup.
- By bridging theory and practical implementation, this repository serves as a valuable resource for those interested in quantum algorithms, computational complexity, and quantum information science.
📌 Ideal for researchers, students, and enthusiasts exploring the intersection of quantum mechanics and computational mathematics.