scholarly journals Conductance fluctuations, weak localization, and shot noise for a ballistic constriction in a disordered wire

1994 ◽  
Vol 50 (4) ◽  
pp. 2450-2457 ◽  
Author(s):  
C. W. J. Beenakker ◽  
J. A. Melsen
Author(s):  
Yan Fyodorov ◽  
Dmitry Savin

This article discusses some applications of concepts from random matrix theory (RMT) to condensed matter physics, with emphasis on phenomena, predicted or explained by RMT, that have actually been observed in experiments on quantum wires and quantum dots. These observations range from universal conductance fluctuations (UCF) to weak localization, non-Gaussian thermopower distributions, and sub-Poissonian shot noise. The article first considers the UCF phenomenon, nonlogarithmic eigenvalue repulsion, and sub-Poissonian shot noise in quantum wires before analysing level and wave function statistics, scattering matrix ensembles, conductance distribution, and thermopower distribution in quantum dots. It also examines the effects (not yet observed) of superconductors on the statistics of the Hamiltonian and scattering matrix.


2014 ◽  
Vol 568 (5) ◽  
pp. 052028 ◽  
Author(s):  
Alejandro Ferrón ◽  
Daniel Domínguez ◽  
María José Sánchez

1993 ◽  
Vol 48 (20) ◽  
pp. 15218-15236 ◽  
Author(s):  
Daniel Loss ◽  
Herbert Schoeller ◽  
Paul M. Goldbart

2005 ◽  
Vol 17 (4) ◽  
pp. 923-947 ◽  
Author(s):  
Magnus J. E. Richardson ◽  
Wulfram Gerstner

The subthreshold membrane voltage of a neuron in active cortical tissue is a fluctuating quantity with a distribution that reflects the firing statistics of the presynaptic population. It was recently found that conductance-based synaptic drive can lead to distributions with a significant skew. Here it is demonstrated that the underlying shot noise caused by Poissonian spike arrival also skews the membrane distribution, but in the opposite sense. Using a perturbative method, we analyze the effects of shot noise on the distribution of synaptic conductances and calculate the consequent voltage distribution. To first order in the perturbation theory, the voltage distribution is a gaussian modulated by a prefactor that captures the skew. The gaussian component is identical to distributions derived using current-based models with an effective membrane time constant. The well-known effective-time-constant approximation can therefore be identified as the leading-order solution to the full conductance-based model. The higher-order modulatory prefactor containing the skew comprises terms due to both shot noise and conductance fluctuations. The diffusion approximation misses these shot-noise effects implying that analytical approaches such as the Fokker-Planck equation or simulation with filtered white noise cannot be used to improve on the gaussian approximation. It is further demonstrated that quantities used for fitting theory to experiment, such as the voltage mean and variance, are robust against these non-Gaussian effects. The effective-time-constant approximation is therefore relevant to experiment and provides a simple analytic base on which other pertinent biological details may be added.


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