Recently, both simulations and observations have revealed that flybys -fast, one-time interactions between two galaxy halos -are surprisingly common, nearing/comparable to galaxy mergers. Since these are rapid, transient events with the closest approach well outside the galaxy disk, it is unclear if flybys can transform the galaxy in a lasting way. We conduct collisionless N-body simulations of three co-planer flyby interactions between pure-disk galaxies to take a first look at the effects flybys have on disk structure, with particular focus on stellar bar formation. We find that some flybys are capable of inciting a bar with bars forming in both galaxies during our 1:1 interaction and in the secondary during our 10:1 interaction. The bars formed have ellipticities 0.5, sizes on the order of the host disk's scale length, and persist to the end of our simulations, ∼5 Gyr after pericenter. The ability of flybys to incite bar formation implies that many processes associated with secular bar evolution may be more closely tied with interactions than previously though.

SummaryComputational models of plants have identified gaps in our understanding of biological systems, and have revealed ways to optimize cellular processes or organ‐level architecture to increase productivity. Thus, computational models are learning tools that help direct experimentation and measurements. Models are simplifications of complex systems, and often simulate specific processes at single scales (e.g. temporal, spatial, organizational, etc.). Consequently, single‐scale models are unable to capture the critical cross‐scale interactions that result in emergent properties of the system. In this perspective article, we contend that to accurately predict how a plant will respond in an untested environment, it is necessary to integrate mathematical models across biological scales. Computationally mimicking the flow of biological information from the genome to the phenome is an important step in discovering new experimental strategies to improve crops. A key challenge is to connect models across biological, temporal and computational (e.g. CPU versus GPU) scales, and then to visualize and interpret integrated model outputs. We address this challenge by describing the efforts of the international Crops in silico consortium.

The formation of cosmological structure is dominated, especially on large scales, by the force of gravity. In the early Universe, matter is distributed homogeneously, with only small fluctuations about the average density. Overdense regions undergo gravitational collapse to form bound structures, called halos, which will host galaxies within them. Halos grow via accretion of the surrounding material and by merging with other halos. This process of merging to form increasingly massive halos is naturally conceptualized as an inverted tree, where small branches connect up to continually larger ones, leading eventually to a trunk.

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Global population increase coupled with rising urbanization underlies the predicted need for 60% more food by 2050, but produced on the same amount of land as today. Improving photosynthetic efficiency is a largely untapped approach to addressing this problem. Here, we scale modelling processes from gene expression through photosynthetic metabolism to predict leaf physiology in evaluating acclimation of photosynthesis to rising atmospheric concentrations of CO2 ([CO2]). Model integration with the yggdrasil interface enabled asynchronous message passing between models. The multiscale model of soybean (Glycine max) photosynthesis calibrated to physiological measures at ambient [CO2] successfully predicted the acclimatory changes in the photosynthetic apparatus that were observed at 550 ppm [CO2] in the field. We hypothesized that genetic alteration is necessary to achieve optimal photosynthetic efficiency under global change. Flux control analysis in the metabolic system under elevated [CO2] identified enzymes requiring the greatest change to adapt optimally to the new conditions. This predicted that Rubisco was less limiting under elevated [CO2] and should be down-regulated allowing re-allocation of resource to enzymes controlling the rate of regeneration of ribulose-1,5-bisphosphate (RuBP). By linking the Gene Regulatory Network through protein concentration to the metabolic model, it was possible to identify transcription factors (TFs) that matched the up- and down-regulation of genes needed to improve photosynthesis. Most striking was TF Gm-GATA2, which down-regulated genes for Rubisco synthesis while up-regulating key genes controlling RuBP regeneration and starch synthesis. The changes predicted for this TF most closely matched the physiological ideotype that the modelling predicted as optimal for the future elevated [CO2] world.

Observations of the Galactic centre (GC) have accumulated a multitude of "forensic" evidence indicating that several million years ago the centre of the Milky Way galaxy was teeming with star formation and accretion-powered activity -this paints a rather different picture from the GC as we understand it today. We examine a possibility that this epoch of activity could have been triggered by the infall of a satellite galaxy into the Milky-Way which began at the redshift of z = 8 and ended few million years ago with a merger of the Galactic supermassive black hole with an intermediate mass black hole brought in by the inspiralling satellite.

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We present and test TesseRACt, a non-parametric technique for recovering the concentration of simulated dark matter halos using Voronoi tessellation. TesseRACt is tested on idealized N-body halos that are axisymmetric, triaxial, and contain substructure and compared to traditional least-squares fitting as well as two non-parametric techniques that assume spherical symmetry. TesseRACt recovers halo concentrations within 0.3% of the true value regardless of whether the halo is spherical, axisymmetric, or triaxial. Traditional fitting and non-parametric techniques that assume spherical symmetry can return concentrations that are systematically off by as much as 10% from the true value for nonspherical halos. TesseRACt also performs significantly better when there is substructure present outside 0.5R 200 . Given that cosmological halos are rarely spherical and often contain substructure, we discuss implications for studies of halo concentration in cosmological N-body simulations including how choice of technique for measuring concentration might bias scaling relations.