Experimental simulation of quantum tunneling in small systems

It is well known that quantum computers are superior to classical computers in efficiently simulating quantum systems. Here we report the first experimental simulation of quantum tunneling through potential barriers, a widespread phenomenon of a unique quantum nature, via NMR techniques. Our experiment is based on a digital particle simulation algorithm and requires very few spin-1/2 nuclei without the need of ancillary qubits. The occurrence of quantum tunneling through a barrier, together with the oscillation of the state in potential wells, are clearly observed through the experimental results. This experiment has clearly demonstrated the possibility to observe and study profound physical phenomena within even the reach of small quantum computers.Comment: 17 pages and 8 figure

Integrated Process Chain for Aerostructural Wing Optimization and Application to an NLF Forward Swept Composite Wing

This contribution introduces an integrated process chain for aerostructural wing optimization based on high fidelity simulationmethods. The architecture of this process chain enables two of the most promising future technologies in commercial aircraft design in the context of multidisciplinary design optimization (MDO). These technologies are natural laminar flow (NLF) and aeroelastic tailoring using carbon fiber reinforced plastics (CFRP). With this new approach the application of MDO to an NLF forward swept composite wing will be possible. The main feature of the process chain is the hierarchical decomposition of the optimization problem into two levels. On the highest level the wing planform including twist and airfoil thickness distributions as well as the orthotropy direction of the composite structure will be optimized. The lower optimization level includes the wing box sizing for essential load cases considering the static aeroelastic deformations. Additionally, the airfoil shapes are transferred from a given NLF wing design. The natural laminar flow is considered by prescribing laminar-turbulent transition locations. Results of wing design studies and a wing optimization using the process chain are presented for a forward swept wing aircraft configuration. The wing optimization with 12 design parameters shows a fuel burn reduction in the order of 9% for the design mission

Rapid and Accurate Prediction and Scoring of Water Molecules in Protein Binding Sites

Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity