Simulation
A method that models stochastic factors in a quantum network, such as random memory waiting times and entanglement generation probabilities, through stochastic process modeling in order to obtain fidelity distributions. It has a high computational cost.
Timeline (last 90 days)
Analytical methods struggle with complex factors such as stochastic memory effects, and when these effects significantly affect the fidelity distribution, simulation becomes necessary.
Simulation can characterize stochastic processes such as random memory waiting times and entanglement generation probabilities, providing a more accurate fidelity distribution, but its computational cost is high and may fail to meet the real-time requirements of online control.
All Facts (2)
Analytical methods struggle with complex factors such as stochastic memory effects, and when these effects significantly affect the fidelity distribution, simulation becomes necessary.
50%UnverifiedSimulation can characterize stochastic processes such as random memory waiting times and entanglement generation probabilities, providing a more accurate fidelity distribution, but its computational cost is high and may fail to meet the real-time requirements of online control.
50%