Quantum State Classification Using QNN

This project implements parameterised quantum circuits (PQCs) and quantum neural networks for entanglement and separability classification of multi-qubit quantum states. Developed in collaboration with Thirumalai and Diksha Sharma.

📌 Key Highlights

• Variational Architectures: Designs and tests ansatz structures optimized for state classification tasks.
• Entanglement Detection: High-accuracy boundary identification distinguishing entangled from separable state geometries.
• Noise Resilience: Evaluated under depolarizing and amplitude damping noise channels on simulated backends.