| Literature DB >> 22530093 |
N Ubbelohde, K Roszak, F Hohls, N Maire, R J Haug, T Novotný.
Abstract
Studies of non-equilibrium current fluctuations enable assessing correlations involved in quantum transport through nanoscale conductors. They provide additional information to the mean current on charge statistics and the presence of coherence, dissipation, disorder, or entanglement. Shot noise, being a temporal integral of the current autocorrelation function, reveals dynamical information. In particular, it detects presence of non-Markovian dynamics, i.e., memory, within open systems, which has been subject of many current theoretical studies. We report on low-temperature shot noise measurements of electronic transport through InAs quantum dots in the Fermi-edge singularity regime and show that it exhibits strong memory effects caused by quantum correlations between the dot and fermionic reservoirs. Our work, apart from addressing noise in archetypical strongly correlated system of prime interest, discloses generic quantum dynamical mechanism occurring at interacting resonant Fermi edges.Entities:
Year: 2012 PMID: 22530093 PMCID: PMC3332523 DOI: 10.1038/srep00374
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Shot noise power measurement around the Fermi edge singularity.
(a) Simplified schematic of the studied device consisting of an InAs QD (pyramid) between emitter (E, blue) and collector (C, red) and the equivalent detection circuit. (b) Energy levels of the dot and leads. Left: zero applied bias with unoccupied dot level high above the lead chemical potential. Right: threshold bias when the dot level aligns with the emitter chemical potential and the current strongly enhanced by the Fermi edge singularity starts flowing. (c) Mean current I (solid line) and shot noise power S (symbols) as functions of applied voltage at T = 70 mK and B = 0 T. (d) Energy dependence of γ and γ in the off-resonant regime as determined from the measured current and shot noise (symbols outside the shaded region) and around the resonance with γ fixed and γ calculated from the mean current (lines within the shaded region). (e) Fano factor around the resonant edge (corresponding to the shaded range of (c) and (d)). Experimental values supplemented with their estimated errors (details in the Methods section) are contrasted with the Markovian approximation based on tunnel rate values from (d) (black line) and the full non-Markovian theory (blue line).
Figure 2Mean current fits for FES in magnetic field.
Top (bottom) panel: I–V curves for different temperatures (colour-coded as shown by the middle panel and horizontally shifted with respect to each other for clarity) at B = 9.75T (B = 0). Experimental data are plotted in colour and the black dashed curves are the theoretical fits for a unique set of 6 (4) parameters at all temperatures. Middle panel: Differential conductance dI/dV as a function of the bias voltage and magnetic field at the lowest temperature T = 70 mK. The Zeeman splitting of the edge is clearly visible. The top and bottom panels depict the cuts along the corresponding borders of the middle panel; the shaded stripes in the panels indicate matching ranges for the lowest temperature curves.
Figure 3Memory effects on the FES noise.
Top (bottom) panel: mean current (Fano factor) for two values of the magnetic field specified in the top panel and various temperatures shown in the bottom panel. Measured Fano factor with the estimated error-bars (explained in the Methods section) is compared to theoretical predictions based on parameters obtained from the fits of Fig. 2. Insets: Comparison of non-Markovian theory (solid lines) with the Markovian approximation (dashed lines) for corresponding magnetic fields (individual insets) and temperatures (curves within insets; horizontally displaced for clarity). Differences between the two curves are highlighted by colours according to their sign. Left detail: zoom onto the low-temperature Fano factor curve in the region around the upper Fermi edge shown by the dashed rectangle. Measured data with their error-bars are supplemented with both the non-Markovian as well as Markovian predictions in the spirit of the insets.