ERC FUNDED PROJECTS

The global marine ecosystem is being deeply altered by human activity. On the one hand, rising concentrations of atmospheric greenhouse gases are changing the physical and chemical state of the ocean, exerting pressure from the bottom up. Meanwhile, the global fishery has provided large economic benefits, but in so doing has restructured ecosystems by removing most of the large animal biomass, a major top-down change. Although there has been a tremendous amount of research into isolated aspects of these impacts, the development of a holistic understanding of the full interactions between physics, chemistry, ecology and economic activity might appear impossible, given the myriad complexities. This proposal lays out a strategy to assemble a team of trans-disciplinary expertise, that will develop a unified, data-constrained, grid-based modeling framework to represent the most important interactions of the global human-ocean system. Building this framework requires solving a series of fundamental problems that currently hinder the development of the full model. If these problems can be solved, the resulting model will reveal novel emergent properties and open the doors to a range of previously unexplored questions of high impact across a range of disciplines. Key questions include the ways in which animals interact with oxygen minimum zones with implications for fisheries, the impacts fish harvesting may have on nutrient recycling, spatio-temporal interactions between managed and unmanaged fisheries, and fundamental questions about the relationships between fish price, fishing cost, and multiple markets in a changing world. Just as the first coupled ocean-atmosphere models revealed a wealth of new behaviours, the coupled human-ocean model proposed here has the potential to launch multiple new fields of enquiry. It is hoped that the novel approach will contribute to a paradigm shift that treats human activity as one component within the framework of the Earth System.

1 600 000 €

Start date: 2016-07-01, End date: 2021-12-31

The purpose of this project is to develop new methods for solving boundary value problems (BVPs) for nonlinear integrable partial differential equations (PDEs). Integrable PDEs can be analyzed by means of the Inverse Scattering Transform, whose introduction was one of the most important developments in the theory of nonlinear PDEs in the 20th century. Until the 1990s the inverse scattering methodology was pursued almost entirely for pure initial-value problems. However, in many laboratory and field situations, the solution is generated by what corresponds to the imposition of boundary conditions rather than initial conditions. Thus, an understanding of BVPs is crucial. In an exciting sequence of events taking place in the last two decades, new tools have become available to deal with BVPs for integrable PDEs. Although some important issues have already been resolved, several major problems remain open. The aim of this project is to solve a number of these open problems and to find solutions of BVPs which were heretofore not solvable. More precisely, the proposal has eight objectives: 1. Develop methods for solving problems with time-periodic boundary conditions. 2. Answer some long-standing open questions raised by series of wave-tank experiments 35 years ago. 3. Develop a new approach for the study of space-periodic solutions. 4. Develop new approaches for the analysis of BVPs for equations with 3 x 3-matrix Lax pairs. 5. Derive new asymptotic formulas by using a nonlinear version of the steepest descent method. 6. Construct disk and disk/black-hole solutions of the stationary axisymmetric Einstein equations. 7. Solve a BVP in Einstein's theory of relativity describing two colliding gravitational waves. 8. Extend the above methods to BVPs in higher dimensions.

2 000 000 €

Start date: 2016-05-01, End date: 2022-02-28

Visible light photocatalysis and metal-free organocatalytic processes are powerful strategies of modern chemical research with extraordinary potential for the sustainable preparation of organic molecules. However, these environmentally respectful approaches have to date remained largely unrelated. The proposed research seeks to merge these fields of molecule activation to redefine their synthetic potential. Light-driven processes considerably enrich the modern synthetic repertoire, offering a potent way to build complex organic frameworks. In contrast, it is extremely challenging to develop asymmetric catalytic photoreactions that can create chiral molecules with a well-defined three-dimensional arrangement. By developing innovative methodologies to effectively address this issue, I will provide a novel reactivity framework for conceiving light-driven enantioselective organocatalytic processes. I will translate the effective tools governing the success of ground state asymmetric organocatalysis into the realm of photochemical reactivity, exploiting the potential of key organocatalytic intermediates to directly participate in the photoexcitation of substrates. At the same time, the chiral organocatalyst will ensure effective stereochemical control. This single catalyst system, where stereoinduction and photoactivation merge in a sole organocatalyst, will serve for developing novel enantioselective photoreactions. In a complementary dual catalytic approach, the synergistic activities of an organocatalyst and a metal-free photosensitiser will combine to realise asymmetric variants of venerable photochemical processes, which have never before succumbed to a stereocontrolled approach. This proposal challenges the current perception that photochemistry is too unselective to parallel the impressive levels of efficiency reached by the asymmetric catalysis of thermal reactions, expanding the way chemists think about making chiral molecules

2 000 000 €

Start date: 2016-11-01, End date: 2021-10-31

Computer-generated imagery is now ubiquitous in our society, spanning fields such as games and movies, architecture, engineering, or virtual prototyping, while also helping create novel ones such as computational materials. With the increase in computational power and the improvement of acquisition techniques, there has been a paradigm shift in the field towards data-driven techniques, which has yielded an unprecedented level of realism in visual appearance. Unfortunately, this leads to a series of problems, identified in this proposal: First, there is a disconnect between the mathematical representation of the data and any meaningful parameters that humans understand; the captured data is machine-friendly, but not human friendly. Second, the many different acquisition systems lead to heterogeneous formats and very large datasets. And third, real-world appearance functions are usually nonlinear and high-dimensional. As a result, visual appearance datasets are increasingly unfit to editing operations, which limits the creative process for scientists, engineers, artists and practitioners in general. There is an immense gap between the complexity, realism and richness of the captured data, and the flexibility to edit such data. We believe that the current research path leads to a fragmented space of isolated solutions, each tailored to a particular dataset and problem. We propose a research plan at the theoretical, algorithmic and application levels, putting the user at the core. We will learn key relevant appearance features in terms humans understand, from which intuitive, predictable editing spaces, algorithms, and workflows will be defined. In order to ensure usability and foster creativity, we will also extend our research to efficient simulation of visual appearance, exploiting the extra dimensionality of the captured datasets. Achieving our goals will finally enable us to reach the true potential of real-world captured datasets in many aspects of society.

1 629 519 €

Start date: 2016-11-01, End date: 2023-04-30