ERC FUNDED PROJECTS

"Contemporary database query languages are ultimately founded on logic and feature an additive operation – usually a form of (multi)set union or disjunction – that is asymmetric in that additions or updates do not always have an inverse. This asymmetry puts a greater part of the machinery of abstract algebra for equation solving outside the reach of databases. However, such equation solving would be a key functionality that problems such as query equivalence testing and data integration could be reduced to: In the current scenario of the presence of an asymmetric additive operation they are undecidable. Moreover, query languages with a symmetric additive operation (i.e., which has an inverse and is thus based on ring theory) would open up databases for a large range of new scientific and mathematical applications. The goal of the proposed project is to reinvent database management systems with a foundation in abstract algebra and specifically in ring theory. The presence of an additive inverse allows to cleanly define differences between queries. This gives rise to a database analog of differential calculus that leads to radically new incremental and adaptive query evaluation algorithms that substantially outperform the state of the art techniques. These algorithms enable a new class of systems which I call Dynamic Data Management Systems. Such systems can maintain continuously fresh query views at extremely high update rates and have important applications in interactive Large-scale Data Analysis. There is a natural connection between differences and updates, motivating the group theoretic study of updates that will lead to better ways of creating out-of-core data processing algorithms for new storage devices. Basing queries on ring theory leads to a new class of systems, Algebraic Data Management Systems, which herald a convergence of database systems and computer algebra systems."

1 480 548 €

Start date: 2012-01-01, End date: 2016-12-31

Molecular structure elucidation is of great importance in synthetic chemistry, pharmacy, life sciences, energy and environmental sciences, and technology applications. To date structure elucidation by atomic force microscopy (AFM) has been demonstrated for a few, small and mainly planar molecules. In this project high-risk, high-impact scientific questions will be solved using structure elucidation with the AFM employing a novel tool and novel methodologies. A combined low-temperature scanning tunneling microscope/atomic force microscope (LT-STM/AFM) with high throughput and in situ electrospray deposition method will be developed. Chemical resolution will be achieved by novel measurement techniques, in particular the usage of different and novel tip functionalizations and combination with Kelvin probe force microscopy. Elements will be identified using substructure recognition provided by a database that will be erected and by refined theory and simulations. The developed tools and techniques will be applied to molecules of increasing fragility, complexity, size, and three-dimensionality. In particular samples that are challenging to characterize with conventional methods will be studied. Complex molecular mixtures will be investigated molecule-by-molecule taking advantage of the single-molecule sensitivity. The absolute stereochemistry of molecules will be determined, resolving molecules with multiple stereocenters. The operation of single molecular machines as nanocars and molecular gears will be investigated. Reactive intermediates generated with atomic manipulation will be characterized and their on-surface reactivity will be studied by AFM.

2 000 000 €

Start date: 2016-06-01, End date: 2021-05-31

Despite its importance for human health and climate change organic aerosol (OA) remains one of the least understood aspects of atmospheric chemistry. We propose to develop an innovative new framework for the description of OA in chemical transport and climate models that will be able to overcome the challenges posed by the chemical complexity of OA while capturing its essential features. The objectives of ATMOPACS are: (i) The development of a new unified framework for the description of OA based on its two most important parameters: volatility and oxygen content. (ii) The development of measurement techniques for the volatility distribution and oxygen content distribution of OA. This will allow the experimental characterization of OA in this new “coordinate system”. (iii) The study of the major OA processes (partitioning, chemical aging, hygroscopicity, CCN formation, nucleation) in this new framework combining lab and field measurements. (iv) The development and evaluation of the next generation of regional and global CTMs using the above framework. (v) The quantification of the importance of the various sources and formation pathways of OA in Europe and the world, of the sensitivity of OA to emission control strategies, and its role in the direct and indirect effects of aerosols on climate. The proposed work involves a combination of laboratory measurements, field measurements including novel “atmospheric perturbation experiments”, OA model development, and modelling in urban, regional, and global scales. Therefore, it will span the system scales starting from the nanoscale to the global. The modelling tools that will be developed will be made available to all other research groups.

2 496 000 €

Start date: 2011-01-01, End date: 2015-12-31

"The goal of the present proposal is to realize measurements of electronic dynamics in polyatomic molecules with attosecond temporal resolution (1 as = 10^-18s). We propose to study electronic rearrangements following photoexcitation, charge migration in a molecular chain induced by ionization and non-adiabatic multi-electron dynamics in an intense laser field. The grand question addressed by this research is the characterization of electron correlations which control the shape, properties and function of molecules. In all three proposed projects, a time-domain approach appears to be the most suitable since it reduces complex molecular dynamics to the purely electronic dynamics by exploiting the hierarchy of motional time scales. Experimentally, we propose to realize an innovative experimental setup. A few-cycle infrared (IR) pulse will be used to generate attosecond pulses in the extreme-ultraviolet (XUV) by high-harmonic generation. The IR pulse will be separated from the XUV by means of an innovative interferometer. Additionally, it will permit the introduction of a controlled attosecond delay between the two pulses. We propose to use the attosecond pulses as a tool to look inside individual IR- or UV-field cycles to better understand light-matter interactions. Time-resolved pump-probe experiments will be carried out on polyatomic molecules by detecting the energy and angular distribution of photoelectrons in a velocity-map imaging spectrometer. These experiments are expected to provide new insights into the dynamics of multi-electron systems along with new results for the validation and improvement of theoretical models. Multi-electron dynamics is indeed a very complex subject on its own and even more so in the presence of strong laser fields. The proposed experiments directly address theses challenges and are expected to provide new insights that will be beneficial to a wide range of scientific research areas."

1 999 992 €

Start date: 2012-09-01, End date: 2017-08-31

"Many problems in computer science can be cast as state-space search, where the objective is to find a path from an initial state to a goal state in a directed graph called a ""state space"". State-space search is challenging due to the state explosion problem a.k.a. ""curse of dimensionality"": interesting state spaces are often astronomically large, defying brute-force exploration. State-space search has been a core research problem in Artificial Intelligence since its early days and is alive as ever. Every year, a substantial fraction of research published at the ICAPS and SoCS conferences is concerned with state-space search, and the topic is very active at general AI conferences such as IJCAI and AAAI. Algorithms in the A* family, dating back to 1968, are still the go-to approach for state-space search. A* is a graph search algorithm whose only ""intelligence"" stems from a so-called ""heuristic function"", which estimates the distance from a state to the nearest goal state. The efficiency of A* depends on the accuracy of this estimate, and decades of research have pushed the envelope in devising increasingly accurate estimates. In this project, we question the ""A* + distance estimator"" paradigm and explore three new directions that go beyond the classical approach: 1. We propose a new paradigm of declarative heuristics, where heuristic information is not represented as distance estimates, but as properties of solutions amenable to introspection and general reasoning. 2. We suggest moving the burden of creativity away from the human expert by casting heuristic design as a meta-optimization problem that can be solved automatically. 3. We propose abandoning the idea of exploring sequential paths in state spaces, instead transforming state-space search into combinatorial optimization problems with no explicit sequencing aspect. We argue that the ""curse of sequentiality"" is as bad as the curse of dimensionality and must be addressed head-on."

1 997 510 €

Start date: 2019-02-01, End date: 2024-01-31

The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches. These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer. Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language). We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems. We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.

1 500 000 €

Start date: 2016-04-01, End date: 2021-03-31

During the past decades the PI has helped shape the research field of computer simulation of biomolecular systems at the atomic level. He has carried out one of the first molecular dynamics (MD) simulations of proteins, and has since then contributed many different methodological improvements and developed one of the major atomic-level force fields for simulations of proteins, carbohydrates, nucleotides and lipids. Methodology and force field have been implemented in a set of programs called GROMOS (GROningen MOlecular Simulation package), which is currently used in hundreds of academic and industrial research groups from over 50 countries on all continents. It is proposed to develop a next generation of molecular models, force fields, multi-scaling simulation methodology and software for biomolecular simulations which is at least an order of magnitude more accurate in terms of energetics, and which is 1000 times more efficient through the use of coarse-grained molecular models than the currently available software and models.

1 320 000 €

Start date: 2008-11-01, End date: 2014-09-30

Meltwater running off the flanks of the Greenland ice sheet contributes roughly 60% to its mass loss, the rest being due to calving. Only meltwater originating from below the elevation of the runoff limit leaves the ice sheet, contributing to mass loss; melt at higher elevations refreezes in the porous firn and does not drive mass loss. Therefore any shift in the runoff limit modifies mass loss and subsequent sea level rise. New evidence shows surface runoff at increasingly high elevations, outpacing the rate at which the equilibrium line elevation rises. This research proposal focuses on the runoff limit as a powerful yet poorly understood modulator of Greenland mass balance. We will track the runoff limit over the full satellite era using two of the largest and oldest remote sensing archives, Landsat and the Advanced Very High Resolution Radiometer (AVHRR). We will establish time series of the runoff limit for all regions of Greenland to identify the mechanisms driving fluctuations in the runoff limit. This newly gained process understanding and a wealth of in-situ measurements will then be used to build firn hydrology models capable of simulating runoff and the associated runoff limit over time. Eventually, the firn hydrology models will be applied to reconcile estimates of Greenland past, present and future mass balance. Covering the entire satellite era and all of Greenland, the focus on the runoff limit will constitute a paradigm shift leading to major advance in our understanding of how vulnerable the surface of the ice sheet reacts to climate change and how the changing surface impacts runoff and thus Greenland's role in the global sea level budget.

1 989 181 €

Start date: 2019-05-01, End date: 2024-04-30

Transient multivalent interactions are critical for biological processes such as signaling pathways controlling chromatin function. Chromatin, the nucleoprotein complex organizing the genome, is dynamically regulated by post-translational modifications (PTMs) of the chromatin fiber. Protein effectors interact with combinations of these PTMs through multivalent interactions, deposit novel PTMs, thereby propagate signaling cascades and remodel chromatin structure. To reveal the underlying molecular mechanisms, methods outside classical biochemistry are required, in particular due to the combinational complexity of chromatin PTMs and the transient supramolecular interactions crucial for their recognition. Here, we develop a novel approach, where we synthesize arrays of chemically defined designer chromatin fibers and use dynamic multiplex single-molecule imaging to dissect multivalent signaling processes in chromatin. Our studies target a key pathway, the DNA damage response (DDR), which regulates DNA repair processes central to cell survival and is critically implicated in cancer. Detailed knowledge is of utmost importance to develop targeted therapeutic interventions. We thus employ advanced peptide and protein chemistry to generate libraries of chromatin fibers of a defined PTM state that is encoded in the chromatin DNA. With the library immobilized in a flow cell, we use single-molecule detection to directly observe signaling processes by key DDR effectors in real time. Subsequent in situ polony decoding allows the identification of each chromatin fiber’s modification state, enabling broad sampling of signaling outcomes. Finally, we use dynamic computational models to integrate the effector-chromatin interaction network and test key mechanisms in cancer-based cell culture. Together, these methods will yield fundamental insight into chromatin and DDR signaling and will be of broad use for chemical and biomedical research with applications beyond the chromatin field.

1 999 815 €

Start date: 2017-05-01, End date: 2022-04-30