<ul><li>The Quantum Excess Evaluation Algorithm involves calculating excess payouts in insurance scenarios.</li><li>The algorithm models reinsurance payments based on loss and retention limit parameters.</li><li>It uses lognormal distribution assumptions for losses and insurer payments with a set retention limit.</li><li>The implementation in Python involves utilizing quantum computing concepts and circuits.</li><li>Quantum Monte Carlo simulations are used to compute expected values and simulate excess payouts.</li><li>Comparing Quantum Monte Carlo to Classical Monte Carlo shows faster convergence due to reduced error growth.</li><li>The Python implementation includes setting up qubit states, quantum circuit operations, and measurement simulations.</li><li>The use of Quantum Subtractor and controlled rotations is vital in computing expected reinsurance payments.</li><li>Qiskit libraries are employed for quantum operations, with a focus on efficient circuit design.</li><li>The ultimate goal is to showcase the benefits of Quantum Monte Carlo over Classical Monte Carlo for insurance risk assessment.</li></ul>

Implementing the Quantum Excess Evaluation Algorithm in Python

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