Investigation of non-equilibrium steady-state gain in semiconductor quantum wells

2006 ◽  
Vol 153 (6) ◽  
pp. 299-307 ◽  
Author(s):  
P.J. Bream ◽  
S. Sujecki ◽  
E.C. Larkins
1998 ◽  
Vol 47 (1) ◽  
pp. 131
Author(s):  
JIN SHI-RONG ◽  
ZHENG YAN-LAN ◽  
LIN CHUN ◽  
ZHONG JIN-QUAN ◽  
LI AI-ZHEN

Optik ◽  
2015 ◽  
Vol 126 (19) ◽  
pp. 2003-2008
Author(s):  
Wen-Xing Yang ◽  
Ai-Xi Chen ◽  
Yanfeng Bai ◽  
Ray-Kuang Lee

Author(s):  
Alexey V. Kavokin ◽  
Jeremy J. Baumberg ◽  
Guillaume Malpuech ◽  
Fabrice P. Laussy

Both rich fundamental physics of microcavities and their intriguing potential applications are addressed in this book, oriented to undergraduate and postgraduate students as well as to physicists and engineers. We describe the essential steps of development of the physics of microcavities in their chronological order. We show how different types of structures combining optical and electronic confinement have come into play and were used to realize first weak and later strong light–matter coupling regimes. We discuss photonic crystals, microspheres, pillars and other types of artificial optical cavities with embedded semiconductor quantum wells, wires and dots. We present the most striking experimental findings of the recent two decades in the optics of semiconductor quantum structures. We address the fundamental physics and applications of superposition light-matter quasiparticles: exciton-polaritons and describe the most essential phenomena of modern Polaritonics: Physics of the Liquid Light. The book is intended as a working manual for advanced or graduate students and new researchers in the field.


2020 ◽  
Vol 45 (2) ◽  
pp. 121-132
Author(s):  
Daniel P. Sheehan

AbstractCanonical statistical mechanics hinges on two quantities, i. e., state degeneracy and the Boltzmann factor, the latter of which usually dominates thermodynamic behaviors. A recently identified phenomenon (supradegeneracy) reverses this order of dominance and predicts effects for equilibrium that are normally associated with non-equilibrium, including population inversion and steady-state particle and energy currents. This study examines two thermodynamic paradoxes that arise from supradegeneracy and proposes laboratory experiments by which they might be resolved.


Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 552 ◽  
Author(s):  
Thomas Parr ◽  
Noor Sajid ◽  
Karl J. Friston

The segregation of neural processing into distinct streams has been interpreted by some as evidence in favour of a modular view of brain function. This implies a set of specialised ‘modules’, each of which performs a specific kind of computation in isolation of other brain systems, before sharing the result of this operation with other modules. In light of a modern understanding of stochastic non-equilibrium systems, like the brain, a simpler and more parsimonious explanation presents itself. Formulating the evolution of a non-equilibrium steady state system in terms of its density dynamics reveals that such systems appear on average to perform a gradient ascent on their steady state density. If this steady state implies a sufficiently sparse conditional independency structure, this endorses a mean-field dynamical formulation. This decomposes the density over all states in a system into the product of marginal probabilities for those states. This factorisation lends the system a modular appearance, in the sense that we can interpret the dynamics of each factor independently. However, the argument here is that it is factorisation, as opposed to modularisation, that gives rise to the functional anatomy of the brain or, indeed, any sentient system. In the following, we briefly overview mean-field theory and its applications to stochastic dynamical systems. We then unpack the consequences of this factorisation through simple numerical simulations and highlight the implications for neuronal message passing and the computational architecture of sentience.


1993 ◽  
Vol 47 (20) ◽  
pp. 13880-13883 ◽  
Author(s):  
F. Meseguer ◽  
F. Agulló-Rueda ◽  
C. López ◽  
J. Sánchez-Dehesa ◽  
J. Massies ◽  
...  

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