Scaling of Ergodicity in Binary Systems
classification
❄️ cond-mat.stat-mech
keywords
averageergodicbinaryergodicityestimatelengthsub-sequencestime
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Given pseudo-random binary sequence of length $L$, assuming it consists of $k$ sub-sequences of length $N$. We estimate how $k$ scales with growing $N$ to obtain a {\it limiting} ergodic behaviour, to fulfill the basic definition of ergodicity (due to Boltzmann). The average of the consecutive sub-sequences plays the role of time (temporal) average. This average then compared to ensemble average to estimate quantitative value of a simple metric called Mean Ergodic Time (MET), when system is ergodic.
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