We model the effects of atomic thermal motion on the propagation of a light pulse in an electromagnetically induced transparency medium by introducing a set of effectively temperature-dependent parameters, including the Rabi frequency of the coupling
field, optical density and relaxation rate of the ground state coherence, into the governing equations. The validity of this effective theory is verified by the close agreement between the theoretical results and the experimental data.
We present a numerical scheme to study the dynamics of slow light and light storage in an electromagneticallyinduced- transparency (EIT) medium at finite temperatures. Allowing for the motional coupling, we derive a set of coupled Schr{o}dinger equat
ions describing a boosted closed three-level EIT system according to the principle of Galilean relativity. The dynamics of a uniformly moving EIT medium can thus be determined by numerically integrating the coupled Schrodinger equations for atoms plus one ancillary Maxwell-Schrodinger equation for the probe pulse. The central idea of this work rests on the assumption that the loss of ground-state coherence at finite temperatures can be ascribed to the incoherent superposition of density matrices representing the EIT systems with various velocities. Close agreements are demonstrated in comparing the numerical results with the experimental data for both slow light and light storage. In particular, the distinct characters featuring the decay of ground-state coherence can be well verified for slow light and light storage. This warrants that the current scheme can be applied to determine the decaying profile of the ground-state coherence as well as the temperature of the EIT medium.
Modeling of headway/spacing between two consecutive vehicles has many applications in traffic flow theory and transport practice. Most known approaches only study the vehicles running on freeways. In this paper, we propose a model to explain the spac
ing distribution of queuing vehicles in front of a signalized junction based on random-matrix theory. We show that the recently measured spacing distribution data well fit the spacing distribution of a Gaussian symplectic ensemble (GSE). These results are also compared with the spacing distribution observed for car parking problem. Why vehicle-stationary-queuing and vehicle-parking have different spacing distributions (GSE vs GUE) seems to lie in the difference of driving patterns.
