Ranawalid256/Quantum-Archaeology-Egypt

Quantum ML model to predict archaeology scores in Egypt # Quantum-Archaeology-Egypt Quantum ML model to predict archaeology scores in Egypt Quantum Archaeology: Predicting the Past with Future Tech TEAM 8 In this project, we explore a bold intersection between ancient Egyptian archaeology and quantum machine learning. Using a real-world dataset of 500 archaeological sites across Egypt — enriched with features like location, looting risk, material composition, and climate impact — we designed a quantum regression model to predict an AI Prediction Score for each site. Our goal? To help prioritize excavation efforts, protect cultural heritage, and bring quantum intelligence into historical preservation. --- What I Did? Preprocessed archaeological data with scikit-learn Built a Quantum Neural Network using Qiskit and EstimatorQNN Designed a variational quantum circuit Trained with SPSA optimizer and compared it to Random Forest Evaluated both models using RMSE, MAE, and R² Visualized results and residuals to understand performance ⚙ Tech Stack Qiskit, Qiskit Machine Learning, scikit-learn, pandas, matplotlib, seaborn 💡 Why This Matters This project is a proof-of-concept that quantum machine learning can be applied to real, culturally relevant problems — even with limited qubits and hybrid models. It’s not just a model. It’s a step toward using the technology of tomorrow to protect the treasures of the past. our presentation link docs.google.com It’s not just a model. It’s a step toward using the technology of tomorrow to protect the treasures of the past.