Traveling Wave Analysis of Non-Thermal Far-Field Blooming in High-Power Broad-Area Lasers

With rising current, the lateral far-field angle of high-power broad-area lasers widens (far-field blooming), which can be partly attributed to non-thermal effects due to carrier-induced refractive index and gain changes that become the dominant mechanism under pulsed operation. To analyze the non-thermal contribution to far-field blooming, we use a traveling wave-based model that properly describes the injection of the current into and the diffusion of the carriers within the active region. Although no pre-assumptions regarding the modal composition of the field is made and filamentation is automatically accounted for, the highly dynamic time-dependent optical field distribution can be very well represented by only a few modes of the corresponding stationary waveguide equation obtained by a temporal average of the carrier density and field intensity. The reduction of current spreading and spatial holeburning by selecting proper design parameters can substantially improve the beam quality of the laser

Data from: Diminishing-returns epistasis decreases adaptability along an evolutionary trajectory

Populations evolving in constant environments exhibit declining adaptability. Understanding the basis of this pattern could reveal underlying processes determining the repeatability of evolutionary outcomes. In principle, declining adaptability can be due to a decrease in the effect size of beneficial mutations, a decrease in the rate at which they occur, or some combination of both. By evolving Escherichia coli populations started from different steps along a single evolutionary trajectory, we show that declining adaptability is best explained by a decrease in the size of available beneficial mutations. This pattern reflected the dominant influence of negative genetic interactions that caused new beneficial mutations to confer smaller benefits in fitter genotypes. Genome sequencing revealed that starting genotypes that were more similar to one another did not exhibit greater similarity in terms of new beneficial mutations, supporting the view that epistasis acts globally, having a greater influence on the effect than on the identity of available mutations along an adaptive trajectory. Our findings provide support for a general mechanism that leads to predictable phenotypic evolutionary trajectories

PykF time-series analysis

R script analyzing and plotting effect of pykF mutations at steps along evolutionary trajectorie

Data from: Effects of beneficial mutations in pykF gene vary over time and across replicate populations in a long-term experiment with bacteria

The fitness effects of mutations can depend on the genetic backgrounds in which they occur and thereby influence future opportunities for evolving populations. In particular, mutations that fix in a population might change the selective benefit of subsequent mutations, giving rise to historical contingency. We examine these effects by focusing on mutations in a key metabolic gene, pykF, that arose independently early in the history of 12 Escherichia coli populations during a long-term evolution experiment. Eight different evolved nonsynonymous mutations conferred similar fitness benefits of ~10% when transferred into the ancestor, and these benefits were greater than the one conferred by a deletion mutation. By contrast, the same mutations had highly variable fitness effects, ranging from about 0 to 25%, in evolved clones isolated from the populations at 20,000 generations. Two mutations that were moved into these evolved clones conferred similar fitness effects in a given clone, but different effects between the clones, indicating epistatic interactions between the evolved pykF alleles and the other mutations that had accumulated in each evolved clone. We also measured the fitness effects of six evolved pykF alleles in the same populations in which they had fixed, but at seven time points between 0 and 50,000 generations. Variation in fitness effects was high at intermediate time points, and declined to a low level at 50,000 generations, when the mean fitness effect was lowest. Our results demonstrate the importance of genetic context in determining the fitness effects of different beneficial mutations even within the same gene

fig4_mutations_in_founder_also_in_replay

Input file for fig. 4 R script. Summarizes mutations present in founders that also occurred in some replay clones. These mutations are omitted from calculation of the convergence metric

fig4_replay_clone_mutations

Input to fig4 R script. Summary of mutated genes in clones isolated from replay populations

fig4_PI_CI matrix

R script to generate figure 4

fig1.b input data

Input data necessary to generate figure 1