Antenna Simulations and Measurements of Focal Plane Array Facet Reflectors

We present a conceptual prototype model of a focal plane array unit for the STEAMR instrument, highlighting the challenges presented by the required high relative beam proximity of the instrument and focus on how edge-diffraction effects contribute to the array's performance. The analysis was carried out as a comparative process using both PO & PTD and MoM techniques. We first highlight general differences between these computational techniques, with the discussion focusing on diffractive edge effects for near-field imaging reflectors with high truncation. We then present the results of in-depth modeling analyses of the STEAMR focal plane array followed by near-field antenna measurements of a breadboard model of the array. The results of these near-field measurements agree well with both simulation techniques although MoM shows slightly higher complex beam coupling to the measurements than PO & PTD.

Unraveling the Conformational Determinants of Peptide Dendrimers Using Molecular Dynamics Simulations

Peptide dendrimers are synthetic tree-like molecules composed of amino acids. There are at least two kinds of preferential structural behaviors exhibited by these molecules, which acquire either compact or noncompact shapes. However, the key structural determinants of such behaviors remained, until now, unstudied. Herein, we conduct a comprehensive investigation of the structural determinants of peptide dendrimers by employing long molecular dynamics simulations to characterize an extended set of third generation dendrimers. Our results clearly show that a trade-off between electrostatic effects and hydrogen bond formation controls structure acquisition in these systems. Moreover, by selectively changing the dendrimers charge we are able to manipulate the exhibited compactness. In contrast, the length of branching residues does not seem to be a major structural determinant. Our results are in accordance with the most recent experimental evidence and shed some light on the key molecular level interactions controlling structure acquisition in these systems. Thus, the results presented constitute valuable insights that can contribute to the development of truly tailor-made dendritic systems.

Regional climate model simulations for Europe at 6 and 0.2 k BP: sensitivity to changes in anthropogenic deforestation

This study aims to evaluate the direct effects of anthropogenic deforestation on simulated climate at two contrasting periods in the Holocene, ~6 and ~0.2 k BP in Europe. We apply We apply the Rossby Centre regional climate model RCA3, a regional climate model with 50 km spatial resolution, for both time periods, considering three alternative descriptions of the past vegetation: (i) potential natural vegetation (V) simulated by the dynamic vegetation model LPJ-GUESS, (ii) potential vegetation with anthropogenic land use (deforestation) from the HYDE3.1 (History Database of the Global Environment) scenario (V + H3.1), and (iii) potential vegetation with anthropogenic land use from the KK10 scenario (V + KK10). The climate model results show that the simulated effects of deforestation depend on both local/regional climate and vegetation characteristics. At ~6 k BP the extent of simulated deforestation in Europe is generally small, but there are areas where deforestation is large enough to produce significant differences in summer temperatures of 0.5–1 °C. At ~0.2 k BP, extensive deforestation, particularly according to the KK10 model, leads to significant temperature differences in large parts of Europe in both winter and summer. In winter, deforestation leads to lower temperatures because of the differences in albedo between forested and unforested areas, particularly in the snow-covered regions. In summer, deforestation leads to higher temperatures in central and eastern Europe because evapotranspiration from unforested areas is lower than from forests. Summer evaporation is already limited in the southernmost parts of Europe under potential vegetation conditions and, therefore, cannot become much lower. Accordingly, the albedo effect dominates in southern Europe also in summer, which implies that deforestation causes a decrease in temperatures. Differences in summer temperature due to deforestation range from −1 °C in south-western Europe to +1 °C in eastern Europe. The choice of anthropogenic land-cover scenario has a significant influence on the simulated climate, but uncertainties in palaeoclimate proxy data for the two time periods do not allow for a definitive discrimination among climate model results.

The Nature of Scientific Proof in the Age of Simulations. Is numerical mimicry a third way of establishing truth?

Is numerical mimicry a third way of establishing truth? Kevin Heng received his M.S. and Ph.D. in astrophysics from the Joint Institute for Laboratory Astrophysics (JILA) and the University of Colorado at Boulder. He joined the Institute for Advanced Study in Princeton from 2007 to 2010, first as a Member and later as the Frank & Peggy Taplin Member. From 2010 to 2012 he was a Zwicky Prize Fellow at ETH Z¨urich (the Swiss Federal Institute of Technology). In 2013, he joined the Center for Space and Habitability (CSH) at the University of Bern, Switzerland, as a tenure-track assistant professor, where he leads the Exoplanets and Exoclimes Group. He has worked on, and maintains, a broad range of interests in astrophysics: shocks, extrasolar asteroid belts, planet formation, fluid dynamics, brown dwarfs and exoplanets. He coordinates the Exoclimes Simulation Platform (ESP), an open-source set of theoretical tools designed for studying the basic physics and chemistry of exoplanetary atmospheres and climates (www.exoclime.org). He is involved in the CHEOPS (Characterizing Exoplanet Satellite) space telescope, a mission approved by the European Space Agency (ESA) and led by Switzerland. He spends a fair amount of time humbly learning the lessons gleaned from studying the Earth and Solar System planets, as related to him by atmospheric, climate and planetary scientists. He received a Sigma Xi Grant-in-Aid of Research in 2006

Mechanisms of Ligand–Protein Interaction in Sec-14-like Transporters Investigated by Computer Simulations

We review our recent work on protein-ligand interactions in vitamin transporters of the Sec-14-like protein. Our studies focused on the cellular-retinaldehyde binding protein (CRALBP) and the alpha-tocopherol transfer protein (alpha-TTP). CRALBP is responsible for mobilisation and photo-protection of short-chain cis-retinoids in the dim-light visual cycle or rod photoreceptors. alpha-TTP is a key protein responsible for selection and retention of RRR-alpha-tocopherol, the most active isoform of vitamin E in superior animals. Our simulation studies evidence how subtle chemical variations in the substrate can lead to significant distortion in the structure of the complex, and how these changes can either lead to new protein function, or be used to model engineered protein variants with tailored properties. Finally, we show how integration of computational and experimental results can contribute in synergy to the understanding of fundamental processes at the biomolecular scale.

Towards understanding thermal jet quenching via lattice simulations

After reviewing how simulations employing classical lattice gauge theory permit to test a conjectured Euclideanization property of a light-cone Wilson loop in a thermal non-Abelian plasma, we show how Euclidean data can in turn be used to estimate the transverse collision kernel, C(k⊥), characterizing the broadening of a high-energy jet. First results, based on data produced recently by Panero et al, suggest that C(k⊥) is enhanced over the known NLO result in a soft regime k⊥ < a few T. The shape of k3⊥ C(k⊥) is consistent with a Gaussian at small k⊥.

Image-based vs. mesh-based statistical appearance models of the human femur: Implications for finite element simulations.

Statistical appearance models have recently been introduced in bone mechanics to investigate bone geometry and mechanical properties in population studies. The establishment of accurate anatomical correspondences is a critical aspect for the construction of reliable models. Depending on the representation of a bone as an image or a mesh, correspondences are detected using image registration or mesh morphing. The objective of this study was to compare image-based and mesh-based statistical appearance models of the femur for finite element (FE) simulations. To this aim, (i) we compared correspondence detection methods on bone surface and in bone volume; (ii) we created an image-based and a mesh-based statistical appearance models from 130 images, which we validated using compactness, representation and generalization, and we analyzed the FE results on 50 recreated bones vs. original bones; (iii) we created 1000 new instances, and we compared the quality of the FE meshes. Results showed that the image-based approach was more accurate in volume correspondence detection and quality of FE meshes, whereas the mesh-based approach was more accurate for surface correspondence detection and model compactness. Based on our results, we recommend the use of image-based statistical appearance models for FE simulations of the femur.

Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations

Multi-objective optimization algorithms aim at finding Pareto-optimal solutions. Recovering Pareto fronts or Pareto sets from a limited number of function evaluations are challenging problems. A popular approach in the case of expensive-to-evaluate functions is to appeal to metamodels. Kriging has been shown efficient as a base for sequential multi-objective optimization, notably through infill sampling criteria balancing exploitation and exploration such as the Expected Hypervolume Improvement. Here we consider Kriging metamodels not only for selecting new points, but as a tool for estimating the whole Pareto front and quantifying how much uncertainty remains on it at any stage of Kriging-based multi-objective optimization algorithms. Our approach relies on the Gaussian process interpretation of Kriging, and bases upon conditional simulations. Using concepts from random set theory, we propose to adapt the Vorob’ev expectation and deviation to capture the variability of the set of non-dominated points. Numerical experiments illustrate the potential of the proposed workflow, and it is shown on examples how Gaussian process simulations and the estimated Vorob’ev deviation can be used to monitor the ability of Kriging-based multi-objective optimization algorithms to accurately learn the Pareto front.

Are We Sims? How Computer Simulations Represent and What this Means for the Simulation Argument

N. Bostrom’s simulation argument and two additional assumptions imply that we are likely to live in a computer simulation. The argument is based upon the following assumption about the workings of realistic brain simulations: The hardware of a computer on which a brain simulation is run bears a close analogy to the brain itself. To inquire whether this is so, I analyze how computer simulations trace processes in their targets. I describe simulations as fictional, mathematical, pictorial, and material models. Even though the computer hardware does provide a material model of the target, this does not suffice to underwrite the simulation argument because the ways in which parts of the computer hardware interact during simulations do not resemble the ways in which neurons interact in the brain. Further, there are computer simulations of all kinds of systems, and it would be unreasonable to infer that some computers display consciousness just because they simulate brains rather than, say, galaxies.