Polarization fine-structure and enhanced single-photon emission of self-assembled lateral InGaAs quantum dot molecules embedded in a planar micro-cavity

Single lateral InGaAs quantum dot molecules have been embedded in a planar micro-cavity in order to increase the luminescence extraction efficiency. Using a combination of metal-organic vapor phase and molecular beam epitaxy samples could be produced that exhibit a 30 times enhanced single-photon emission rate. We also show that the single-photon emission is fully switchable between two different molecular excitonic recombination energies by applying a lateral electric field. Furthermore, the presence of a polarization fine-structure splitting of the molecular neutral excitonic states is reported which leads to two polarization-split classically correlated biexciton exciton cascades. The fine-structure splitting is found to be on the order of 10 micro-eV.Comment: 14 pages, 4 figures; the following article has been submitted to Journal of Applied Physics (29th ICPS - invited paper); after it is published, it will be found at http://jap.aip.org

A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems

In this article we propose a descent method for equality and inequality constrained multiobjective optimization problems (MOPs) which generalizes the steepest descent method for unconstrained MOPs by Fliege and Svaiter to constrained problems by using two active set strategies. Under some regularity assumptions on the problem, we show that accumulation points of our descent method satisfy a necessary condition for local Pareto optimality. Finally, we show the typical behavior of our method in a numerical example

Unifying local-global type properties in vector optimization.

It is well-known that all local minimum points of a semistrictly quasiconvex real-valued function are global minimum points. Also, any local maximum point of an explicitly quasiconvex real-valued function is a global minimum point, provided that it belongs to the intrinsic core of the function’s domain. The aim of this paper is to show that these “local min - global min” and “local max - global min” type properties can be extended and unified by a single general localglobal extremality principle for certain generalized convex vector-valued functions with respect to two proper subsets of the outcome space. For particular choices of these two sets, we recover and refine several local-global properties known in the literature, concerning unified vector optimization (where optimality is defined with respect to an arbitrary set, not necessarily a convex cone) and, in particular, classical vector/multicriteria optimization.Nicolae Popovici’s research was supported by a grant of the Romanian Ministry of Research and Innovation, CNCS-UEFISCDI, project number PN-III-P4-ID-PCE- 2016-0190, within PNCDI III

Inflationary differential evolution for Constrained Multi-Objective Optimisation Problem

In this paper we review several parameter-based scalarisation approaches used within Multi-Objective Optimisation. We propose then a proof-of-concept for a new memetic algorithm designed to solve the Constrained Multi-Objective Optimisation Problem. The algorithm is finally tested on a benchmark with a series of difficulties