Concept
Markov chain
Related lectures (259)
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Explores invariant measures in Markov chains, discussing irreducibility, periodicity, and unique solutions.
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Explains positive and null-recurrence in Markov chains and the classification of states in equivalence classes.
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Explores the properties of invariant distributions in Markov chains and provides examples of their application.
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Covers the detailed balance principle in the Metropolis algorithm and the choice of trial step and starting configuration.
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Covers the concept of geometric ergodicity in the context of convergence diagnostics for Markov chains.
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Explores quantum density matrix, mixed states, von Neumann entropy, and quantum measurements.
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Explores NISQ devices and IBM Q, covering noisy quantum circuits, qubit technologies, and quantum algorithm development.