Entanglement Entropy in Quantum Simulations
How entanglement entropy is computed in simulations with tensor networks and Monte Carlo methods, and what it reveals about many-body systems.
How entanglement entropy is computed in simulations with tensor networks and Monte Carlo methods, and what it reveals about many-body systems.
Transfer entropy measures directed information flow between systems. How a quantum version is defined and its uses in communication and networks.
The quantum Jensen-Shannon divergence is a symmetric, bounded measure of how different two quantum states are. Definition, properties and uses.
Quantum Rényi entropies and entropy power inequalities: definitions, relations to von Neumann entropy and uses in communication.
Min-entropy measures the maximum probability of guessing a value. How its quantum version sets how much randomness can be extracted.
Quantum Rényi divergences form families, such as Petz and sandwiched, that generalize relative entropy. Properties and uses in security proofs.
Distinguishability measures for quantum states compared: trace distance, fidelity, relative entropy and others, with their uses.
The capacity region of a quantum network describes which combinations of rates are achievable at once. Channels, constraints and protocols.
How quantum information moves through a circuit: encoding, gates, entanglement, measurement and the limits information theory places on it.
Entropy production in quantum systems quantifies irreversibility and connects to the second law. Theory, fluctuation relations and experiments.
Non-Markovian quantum dynamics has memory: information can flow back from the environment. How it is measured and why it matters.
Smooth min-entropy and related measures are used to prove the security of QKD and randomness extraction. What these entropies measure.