Unverified50% confidenceDecision RuleExact time
Analytical methods struggle with complex factors such as stochastic memory effects, and when these effects significantly affect the fidelity distribution, simulation becomes necessary.
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10/19/2026
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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.78% similarUnverifiedWhen one component of a system already has randomness, stacking a probabilistic component on top of it exponentially amplifies debugging difficulty.75% similarVerifiedExcessive domain randomization can cause policies to become overly conservative, and certain real-world phenomena (such as deformation of flexible objects) are difficult to cover through simple parameter randomization.73% similarUnverifiedPoint-wise sample selection strategies suffer from sensitivity and redundancy problems, which easily lead to overfitting of the acquisition function.73% similarUnverifiedThe effectiveness of this method depends on the choice of the base distribution and the specific form of the Stein operator, and it may face challenges in scenarios with large distribution shifts.73% similar
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