Quantum Computing and the Infinite Salesmen Problem

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Quantum computing has the potential to significantly reduce solving times for complex problems like the traveling salesman problem, but it is not a straightforward solution that instantly provides answers. The superposition of qubits allows for the representation of multiple states simultaneously, but when measured, only one outcome is observed, which necessitates careful manipulation of qubits during calculations. Misconceptions about quantum computers solving NP-complete problems in polynomial time are common; they require more than just superposition, often needing entanglement and specific algorithms like Grover's for efficiency. Current research in quantum computing focuses on simulating quantum systems, with applications in areas like RSA encryption and visual recognition, but limitations remain, necessitating the development of new algorithms. Understanding quantum computing requires a grasp of how superpositions and amplitudes interact, which is crucial for leveraging their computational advantages.
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You can define "0", "1" and its interpretation in any way you like, you just have to do it consistently in the preparation of the states and the interpretation of the results.

In a similar way, you can compute 2+4 on every conventional computer, and get 6 independent of the details of the implementation in hardware (or maybe 5.9999 with some bugged CPUs ;)).
 

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