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This invention describes a way to solve complex optimization problems, like finding the best solution among many possibilities, by using a quantum computer. A regular computer first prepares the problem data, then sends it to a quantum computer. The quantum computer uses a method inspired by natural evolution, called a genetic algorithm, to find a solution by manipulating quantum bits. Finally, the quantum solution is translated back for a regular computer to understand. The claims specifically narrow this to genetic algorithms that perform selection and crossover operations by rearranging groups of quantum bits.
Why it matters: Since 2017, quantum computing hardware has advanced from early experimental stages to more accessible, albeit still noisy, devices. This progress makes the practical development and testing of quantum genetic algorithms, as described, more feasible to explore and refine, though significant challenges in error correction and scalability remain.
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