Decreased Fast Time Scale Spectral Diffusion of a Nonpolar InGaN Quantum Dot

ACS Photonics ◽  
2021 ◽  
Author(s):  
Claudius Kocher ◽  
John C. Jarman ◽  
Tongtong Zhu ◽  
Gunnar Kusch ◽  
Rachel A. Oliver ◽  
...  
Keyword(s):  
Quantum Dot ◽  
Time Scale ◽  
Spectral Diffusion ◽  
Fast Time ◽  
Fast Time Scale

The effect of fast-time-scale turbulence on magnetohydrodynamical behaviour

1984 ◽  
Vol 31 (1) ◽  
pp. 81-92 ◽  
Author(s):  
R. O. Dendy ◽  
D. Ter Haar
Keyword(s):  
Time Scale ◽  
Normal Modes ◽  
Dispersion Relations ◽  
Magnetized Plasma ◽  
Fast Time ◽  
Fast Time Scale ◽  
Scale Turbulence ◽  
The Ideal

We show what corrections have to be made to the equations of ideal magneto-hydrodynamics when there is fast-time-scale turbulence present in a magnetized plasma. We show how the dispersion relations for the ideal Alfvén and magnetoacoustic MHD normal modes are modified when such turbulence is present. Finally, we discuss the relation of our work to that of other authors.

scholarly journals NogoA restricts synaptic plasticity in the adult hippocampus on a fast time scale

2011 ◽  
Vol 108 (6) ◽  
pp. 2569-2574 ◽  
Author(s):  
A. Delekate ◽  
M. Zagrebelsky ◽  
S. Kramer ◽  
M. E. Schwab ◽  
M. Korte
Keyword(s):  
Synaptic Plasticity ◽  
Time Scale ◽  
Fast Time ◽  
Fast Time Scale ◽  
Adult Hippocampus

Transient lens spectroscopy in a fast time scale

1994 ◽  
Vol 230 (1-2) ◽  
pp. 87-92 ◽  
Author(s):  
Masahide Terazima
Keyword(s):  
Time Scale ◽  
Fast Time ◽  
Fast Time Scale

Averaging of Attractors and Inertial Manifolds for Parabolic PDE With Random Coefficients

2005 ◽  
Vol 5 (4) ◽  
Author(s):  
Igor D. Chueshov ◽  
Björn Schmalfuß
Keyword(s):  
Evolution Equation ◽  
Time Scale ◽  
Inertial Manifolds ◽  
Inertial Manifold ◽  
Fast Time ◽  
Time Behavior ◽  
Long Time Behavior ◽  
Scaling Parameter ◽  
Fast Time Scale ◽  
Long Time

AbstractThe averaging method has been used to study random or non-autonomous systems on a fast time scale. We apply this method to a random abstract evolution equation on a fast time scale whose long time behavior can be characterized by a random attractor or a random inertial manifold. The main purpose is to show that the long-time behavior of such a system can be described by a deterministic evolution equation with averaged coefficients. Our first result provides an averaging result on finite time intervals which we use to show that under a dissipativity assumption the attractors of the fast time scale systems are upper semicontinuous when the scaling parameter goes to zero. Our main result deals with a global averaging procedure. Under some spectral gap condition we show that inertial manifolds of the fast time scale system tend to an inertial manifold of the averaged system when the scaling parameter goes to zero. These general results can be applied to semilinear parabolic differential equations containing a scaled ergodic noise on a fast time scale which includes scaled almost periodic motions.

scholarly journals Fast Temporal Dynamics of Visual Cue Integration

Perception ◽  
10.1068/p3314 ◽  
2002 ◽  
Vol 31 (4) ◽  
pp. 421-434 ◽  
Author(s):  
Jochen Triesch ◽  
Dana H Ballard ◽  
Robert A Jacobs
Keyword(s):  
Visual Tracking ◽  
Probabilistic Model ◽  
Time Scale ◽  
Temporal Dynamics ◽  
Target Object ◽  
Cue Integration ◽  
Fast Time ◽  
Single Trial ◽  
Visual Cue ◽  
Fast Time Scale

The integration of information from different sensors, cues, or modalities lies at the very heart of perception. We are studying adaptive phenomena in visual cue integration. To this end, we have designed a visual tracking task, where subjects track a target object among distractors and try to identify the target after an occlusion. Objects are defined by three different attributes (color, shape, size) which change randomly within a single trial. When the attributes differ in their reliability (two change frequently, one is stable), our results show that subjects dynamically adapt their processing. The results are consistent with the hypothesis that subjects rapidly re-weight the information provided by the different cues by emphasizing the information from the stable cue. This effect seems to be automatic, ie not requiring subjects' awareness of the differential reliabilities of the cues. The hypothesized re-weighting seems to take place in about 1 s. Our results suggest that cue integration can exhibit adaptive phenomena on a very fast time scale. We propose a probabilistic model with temporal dynamics that accounts for the observed effect.

Dissolved Oxygen Tracking and Control of Blowers at Fast Time Scale

2004 ◽  
Vol 37 (11) ◽  
pp. 281-287 ◽  
Author(s):  
R Piotrowski ◽  
K Duzinkiewicz ◽  
M.A Brdys
Keyword(s):  
Dissolved Oxygen ◽  
Time Scale ◽  
Fast Time ◽  
Fast Time Scale ◽  
And Control
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