Amphan Quantum
AI-powered decision support system leveraging Quantum Approximate Optimization Algorithms (QAOA) to solve complex cyclone evacuation routing.
Why it exists
Born in a high-stress, 40-hour quantum hackathon hosted by SRM University AP. Cyclone evacuations are high-stakes graph problems where classical routers clog up; we turned to quantum math to see if we could map safety routes through the noise.
How it works
- Formulates evacuation routing as a Quadratic Unconstrained Binary Optimization (QUBO) problem.
- Executes variational circuits using QAOA (via Qiskit) to find low-congestion path assignments.
- Connects the quantum backend to a FastAPI middleware that parses route data.
- Visualizes real-world safety paths dynamically using a React + Leaflet map interface.
What happened
We had 40 hours, a shared whiteboard, and a lot of caffeine. It was my second big quantum project, and we spent the first half just wrestling with Qiskit state vectors and the second half building a UI to make the quantum math look alive. We ran out of time, but the code compiled, the qubits converged on a route, and the maps actually loaded.
What I'd change
Currently, the QUBO matrix scales quadratically with graph nodes. I'd implement graph decomposition beforehand so we can run the algorithm on actual coastal cities without melting local classical simulators.