Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains

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.

Algorithm-based continuous pulse duration tuning and performance control of a mode-locked laser diode.

A control algorithm is presented that addresses the stability issues inherent to the operation of monolithic mode-locked laser diodes. It enables a continuous pulse duration tuning without any onset of Q-switching instabilities. A demonstration of the algorithm performance is presented for two radically different laser diode geometries and continuous pulse duration tuning between 0.5 ps to 2.2 ps and 1.2 ps to 10.2 ps is achieved. With practical applications in mind, this algorithm also facilitates control over performance parameters such as output power and wavelength during pulse duration tuning. The developed algorithm enables the user to harness the operational flexibility from such a laser with 'push-button' simplicity.

Active glass-polymer superlattice structure for photonic integration.

We propose an all-laser processing approach allowing controlled growth of organic-inorganic superlattice structures of rare-earth ion doped tellurium-oxide-based glass and optically transparent polydimethyl siloxane (PDMS) polymer; the purpose of which is to illustrate the structural and thermal compatibility of chemically dissimilar materials at the nanometer scale. Superlattice films with interlayer thicknesses as low as 2 nm were grown using pulsed laser deposition (PLD) at low temperatures (100 °C). Planar waveguides were successfully patterned by femtosecond-laser micro-machining for light propagation and efficient Er(3+)-ion amplified spontaneous emission (ASE). The proposed approach to achieve polymer-glass integration will allow the fabrication of efficient and durable polymer optical amplifiers and lossless photonic devices. The all-laser processing approach, discussed further in this paper, permits the growth of films of a multitude of chemically complex and dissimilar materials for a range of optical, thermal, mechanical and biological functions, which otherwise are impossible to integrate via conventional materials processing techniques.

Reinforcement learning with reference tracking control in continuous state spaces

The contribution described in this paper is an algorithm for learning nonlinear, reference tracking, control policies given no prior knowledge of the dynamical system and limited interaction with the system through the learning process. Concepts from the field of reinforcement learning, Bayesian statistics and classical control have been brought together in the formulation of this algorithm which can be viewed as a form of indirect self tuning regulator. On the task of reference tracking using a simulated inverted pendulum it was shown to yield generally improved performance on the best controller derived from the standard linear quadratic method using only 30 s of total interaction with the system. Finally, the algorithm was shown to work on the simulated double pendulum proving its ability to solve nontrivial control tasks. © 2011 IEEE.