Weak-light gap solitons in a resonant three-level system

In this chapter we study with the tools developed in Chapter 3 the basic models that are the foundations of light–matter interaction. We start with Rabi dynamics, then consider the optical Bloch equations that add phenomenologically the lifetime of the populations. As decay and pumping are often important, we cover the Lindblad form, a correct, simple and powerful way to describe various dissipation mechanisms. Then we go to a full quantum picture, quantizing also the optical field. We first investigate the simpler coupling of bosons and then culminate with the Jaynes–Cummings model and its solution to the quantum interaction of a two-level system with a cavity mode. Finally, we investigate a broader family of models where the material excitation operators differ from the ideal limits of a Bose and a Fermi field.

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Gap solitons and transmissivity of one-dimensional asymmetric systems

Physical Review B ◽

10.1103/physrevb.47.5748 ◽

1993 ◽

Vol 47 (10) ◽

pp. 5748-5755 ◽

Cited By ~ 7

Author(s):

J. M. Bilbault ◽

C. Tatuam Kamga ◽

M. Remoissenet

Keyword(s):

One Dimensional ◽

Gap Solitons

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Two-dimensional optical gap solitons and vortices in a coherent atomic ensemble loaded on optical lattices

Communications in Nonlinear Science and Numerical Simulation ◽

10.1016/j.cnsns.2021.105911 ◽

2021 ◽

pp. 105911

Author(s):

Zhiming Chen ◽

Jianhua Zeng

Keyword(s):

Optical Lattices ◽

Atomic Ensemble ◽

Two Dimensional ◽

Optical Gap ◽

Gap Solitons

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A flexible ultrasensitive optoelectronic sensor array for neuromorphic vision systems

Nature Communications ◽

10.1038/s41467-021-22047-w ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Qian-Bing Zhu ◽

Bo Li ◽

Dan-Dan Yang ◽

Chi Liu ◽

Shun Feng ◽

...

Keyword(s):

Sensor Array ◽

Vision System ◽

Vision Systems ◽

Neuromorphic Circuits ◽

Image Sensing ◽

Perovskite Quantum Dots ◽

Optoelectronic Sensor ◽

Weak Light ◽

Do So ◽

Neuromorphic Vision

AbstractThe challenges of developing neuromorphic vision systems inspired by the human eye come not only from how to recreate the flexibility, sophistication, and adaptability of animal systems, but also how to do so with computational efficiency and elegance. Similar to biological systems, these neuromorphic circuits integrate functions of image sensing, memory and processing into the device, and process continuous analog brightness signal in real-time. High-integration, flexibility and ultra-sensitivity are essential for practical artificial vision systems that attempt to emulate biological processing. Here, we present a flexible optoelectronic sensor array of 1024 pixels using a combination of carbon nanotubes and perovskite quantum dots as active materials for an efficient neuromorphic vision system. The device has an extraordinary sensitivity to light with a responsivity of 5.1 × 107 A/W and a specific detectivity of 2 × 1016 Jones, and demonstrates neuromorphic reinforcement learning by training the sensor array with a weak light pulse of 1 μW/cm2.

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