Rigorous finite-time guarantees for optimization on continuous domains by simulated annealing

Simulated annealing is a popular method for approaching the solution of a global optimization problem. Existing results on its performance apply to discrete combinatorial optimization where the optimization variables can assume only a finite set of possible values. We introduce a new general formulation of simulated annealing which allows one to guarantee finite-time performance in the optimization of functions of continuous variables. The results hold universally for any optimization problem on a bounded domain and establish a connection between simulated annealing and up-to-date theory of convergence of Markov chain Monte Carlo methods on continuous domains. This work is inspired by the concept of finite-time learning with known accuracy and confidence developed in statistical learning theory.

Kinetic model of continuous-wave flow chemical lasers

In this paper an analysis of the kinetic theory of the continuous-wave flow chemical lasers(CWFCL) is presented with emphasis being laid on the effects of inhomogeneous broadeningon CWFCL's performance. The results obtained are applicable to the case where laser fre-quency is either coincident or incoincident with that of the eenter of the line shape. This rela-tion has been,compared with that of the rate model in common use. These two models are almostidentical as the broadening parameter η is larger than 1. The smaller the value of η, thegreater the difference between the results of these two models will be. For fixed η, the dif-ferences between fhe results of the two models increase with the increase of the frequencyshift parameter ξ. When η is about less than 0.2. the kinetic model can predict exactly the in-homogeneous broadening effects,while the rate model cannot.