2017
DOI: 10.1103/physrevb.95.045306
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Nonrenewal statistics in transport through quantum dots

Abstract: The distribution of waiting times between successive tunneling events is an already established method to characterize current fluctuations in mesoscopic systems. Here, I investigate mechanisms generating correlations between subsequent waiting times in two model systems, a pair of capacitively coupled quantum dots and a single-level dot attached to spin-polarized leads. Waiting time correlations are shown to give an insight into the internal dynamics of the system, for example they allow distinction between d… Show more

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Cited by 27 publications
(59 citation statements)
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“…28 Renewal theory assumes that successive waiting times between transport events are statistically independent equally distributed random variables. In this case the joint probability density of two successive waiting times w 2 (τ 2 , τ 1 ) can be factorised into a product of two single-time distributions w 1 (τ 2 )w 1 (τ 1 ), that means that the distribution is totally "renewed" after waiting time τ 1 .…”
Section: 2627mentioning
confidence: 99%
“…28 Renewal theory assumes that successive waiting times between transport events are statistically independent equally distributed random variables. In this case the joint probability density of two successive waiting times w 2 (τ 2 , τ 1 ) can be factorised into a product of two single-time distributions w 1 (τ 2 )w 1 (τ 1 ), that means that the distribution is totally "renewed" after waiting time τ 1 .…”
Section: 2627mentioning
confidence: 99%
“…Transitions pÒq Ø pÒÓq, associated with the tunneling of spin Ó electrons, cause the slow switching between these transport channels. Such a phenomenon, referred to as the telegraphic switching, is already known to generate both the super-Poissonian noise and the correlations between subsequent waiting times [4]. Additionally, the system may be trapped in the configuration pÓÓq which leads to the current blockade.…”
Section: Resultsmentioning
confidence: 99%
“…2a). Additionally, the randomness parameter is not equal to the Fano factor which indicates that the subsequent waiting times are correlated [4] (when the waiting times are uncorrelated, both parameters are always equal [9]). This is confirmed by the direct calculation of the cross-correlation of subsequent waiting times (Fig.…”
Section: Resultsmentioning
confidence: 99%
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