Markov Chains: Recurrence and Transience

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Explores Markov chains' properties, expectations, and recurrence in Poisson processes.

Covers the definitions and state probabilities of discrete-time Markov chains.

Explores Markov chains and stationary distributions, emphasizing the importance of identifying them for improving convergence.

Explores Markov chain games, hitting probabilities, and expected hitting times in a target set.

Explores NISQ devices and IBM Q, covering noisy quantum circuits, qubit technologies, and quantum algorithm development.

Explores Markov chains with absorbing classes through exercises on transition matrices and expected values.

Covers examples of absorbing Markov chains in discrete time.

Explores discrete-time Markov chains, emphasizing first passage time probabilities and minimal solutions.

Covers the introduction and properties of Markov chains, including transition matrices and stochastic processes.

Explores birth and death chains, hitting probabilities, and expected game durations in Markov chains.