Quantum Machine Learning
Heisenberg's Uncertainty Principle states that it is impossible to simultaneously know both the position and momentum of a quantum particle with absolute precision. This principle emphasizes the fundamental limitations of measurement in quantum mechanics, indicating that the more accurately we know one of these properties, the less accurately we can know the other. This idea is crucial for understanding the behavior of particles at the quantum level and has significant implications for quantum computing, where information is processed in ways that are inherently probabilistic.
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