Quantum control experiments as a testbed for evolutionary multi-objective algorithms

Experimental multi-objective Quantum Control is an emerging topic within the broad physics and chemistry applications domain of controlling quantum phenomena. This realm offers cutting edge ultrafast laser laboratory applications, which pose multiple objectives, noise, and possibly constraints on the high-dimensional search. In this study we introduce the topic of multi-observable quantum control (MOQC), and consider specific systems to be Pareto optimized subject to uncertainty, either experimentally or by means of simulated systems. The latter include a family of mathematical test-functions with a practical link to MOQC experiments, which are introduced here for the first time. We investigate the behavior of the multi-objective version of the covariance aatrix adaptation evolution strategy (MO-CMA-ES) and assess its performance on computer simulations as well as on laboratory closed-loop experiments. Overall, we propose a comprehensive study on experimental evolutionary Pareto optimization in high-dimensional continuous domains, draw some practical conclusions concerning the impact of fitness disturbance on algorithmic behavior, and raise several theoretical issues in the broad evolutionary multi-objective context.     

Sustained glucagon-like peptide 1 expression from encapsulated transduced cells to treat obese diabetic rats

Obesity and type 2 diabetes (T2D) are two prevalent chronic diseases that have become a major public health concern in industrialized countries. T2D is characterized by hyperglycemia and islet beta cell dysfunction. Glucagon-like peptide 1 (GLP-1) promotes β cell proliferation and neogenesis and has a potent insulinotropic effect. Leptin receptor deficient male rats are obese and diabetic and provide a model of T2D. We hypothesized that their treatment by sustained expression of GLP-1 using encapsulated cells may prevent or delay diabetes onset. Vascular smooth muscle cells (VSMC) retrovirally transduced to secrete GLP-1 were seeded into TheraCyte(TM) encapsulation devices, implanted subcutaneously and rats were monitored for diabetes. Rats that received cell implants showed mean plasma GLP-1 level of 119.3 ± 10.2pM that was significantly elevated over control values of 32.4 ± 2.9pM (P<0.001). GLP-1 treated rats had mean insulin levels of 45.9 ± 2.3ng/ml that were significantly increased over control levels of 7.3±1.5ng/ml (P<0.001). In rats treated before diabetes onset elevations in blood glucose were delayed and rats treated after onset became normoglycemic and showed improved glucose tolerance tests. Untreated diabetic rats possess abnormal islet structures characterized by enlarged islets with α-cell infiltration and multifocal vacuolization. GLP-1 treatment induced normalization of islet structures including a mantle of α-cells and increased islet mass. These data suggest that encapsulated transduced cells may offer a potential long term treatment of patients.     

Phase Stability and Electrical Conductivity in Gd2Ti2O7-Gd2Mo2O7 Solid Solutions

Solid solutions in the Gd₂(Ti1-yMoy)2O7 pyrochlore system, with y = 0.1, 0.3, 0.5, and 0.7, have been investigated as potential candidates for the anode material of solid-oxide fuel cells. The electrical conductivity, stability range, and optimal synthesis conditions of the pyrochlore phase have been explored by electrical, coulometric titration, and X-ray diffractometry techniques. As the molybdenum content increases, the maximum conductivity increases to a value of 70 S/cm for y = 0.7 at 1000°C, whereas the stability range in the oxygen partial pressure (pO2) decreases to just over two orders of magnitude in pO2 in the temperature range of 600°-1000°C. A decomposition reaction that leads to decreased conductivity in oxidizing atmospheres is proposed.     

Estimating forage quantity and quality using aerial hyperspectral imagery for northern mixed-grass prairie

Sustainable rangeland stewardship calls for synoptic estimates of rangeland biomass quantity (kg dry matter ha^− 1) and quality [carbon:nitrogen (C:N) ratio]. These data are needed to support estimates of rangeland crude protein in forage, either by percent (CP_c) or by mass (CP_m). Biomass derived from remote sensing data is often compromised by the presence of both photosynthetically active (PV) and non-photosynthetically active (NPV) vegetation. Here, we explicitly quantify PV and NPV biomass using HyMap hyperspectral imagery. Biomass quality, defined as plant C:N ratio, was also estimated using a previously published algorithm. These independent algorithms for forage quantity and quality (both PV and NPV) were evaluated in two northern mixed-grass prairie ecoregions, one in the Northwestern Glaciated Plains (NGGP) and one in the Northwestern Great Plains (NGP). Total biomass (kg ha^− 1) and C:N ratios were mapped with 18% and 8% relative error, respectively. Outputs from both models were combined to quantify crude protein (kg ha^− 1) on a pasture scale. Results suggest synoptic maps of rangeland vegetation mass (both PV and NPV) and quality may be derived from hyperspectral aerial imagery with greater than 80% accuracy.     

Computational challenges in bounded model checking

We describe several observations regarding the completeness and the complexity of bounded model checking and propose techniques to solve some of the associated computational challenges. We begin by defining the completeness threshold ( ) problem: for every finite model M and an LTL property , there exists a number such that if there is no counterexample to in M of length or less, then M . Finding this number, if it is sufficiently small, offers a practical method for making bounded model checking complete. We describe how to compute an overapproximation to for a general LTL property using Büchi automata, following the Vardi–Wolper LTL model checking framework. This computation is based on finding the initialized diameter and initialized recurrence-diameter (the longest loop-free path from an initial state) of the product automaton. We show a method for finding a recurrence diameter with a formula of size O(klogk) (or O(k(logk)²) in practice), where k is the attempted depth, which is an improvement compared to the previously known method that requires a formula of size in O(k²). Based on the value of , we prove that the complexity of standard SAT-based BMC is doubly exponential and that, consequently, there is a complexity gap of an exponent between this procedure and standard LTL model checking. We discuss ways to bridge this gap.     

Reaction kinetics in a tight spot

The standard analysis of reaction networks based on deterministic rate equations fails in confined geometries, commonly encountered in fields such as astrochemistry, thin-film growth and cell biology. In these systems the small reactant population implies anomalous behavior of reaction rates, which can be accounted for only by following the full distribution of reactant numbers.