ERC FUNDED PROJECTS

The Tera-Hertz portion of the spectrum presents unique potentials for advanced applications. Currently the THz spectrum is revealing the mechanisms at the origin of our universe and provides the means to monitor the health of our planet via satellite based sensing of critical gases. Potentially time domain sensing of the THz spectrum will be the ideal tool for a vast variety of medical and security applications. Presently, systems in the THz regime are extremely expensive and consequently the THz spectrum is still the domain of only niche (expensive) scientific applications. The main problems are the lack of power and sensitivity. The wide unused THz spectral bandwidth is, herself, the only widely available resource that in the future can compensate for these problems. But, so far, when scientists try to really use the bandwidth, they run into an insurmountable physical limit: antenna dispersion. Antenna dispersion modifies the signal’s spectrum in a wavelength dependent manner in all types of radiation, but is particularly deleterious to THz signals because the spectrum is too wide and with foreseeable technology it cannot be digitized. The goal of this proposal is to introduce break-through antenna technology that will eliminate the dispersion bottle neck and revolutionize Time Domain sensing and Spectroscopic Space Science. Achieving these goals the project will pole vault THz imaging technology into the 21-th century and develop critically important enabling technologies which will satisfy the electrical engineering needs of the next 30 years and in the long run will enable multi Tera-bit wireless communications. In order to achieve these goals, I will first build upon two major breakthrough radiation mechanisms that I pioneered: Leaky Lenses and Connected Arrays. Eventually, ultra wide band imaging arrays constituted by thousands of components will be designed on the bases of the new theoretical findings and demonstrated.

1 499 487 €

Start date: 2011-11-01, End date: 2017-10-31

This project studies several mathematical topics with a related theme, all of them part of the relatively new discipline known as additive combinatorics. We look at approximate, or rough, variants of familiar mathematical notions such as group, polynomial or homomorphism. In each case we seek to describe the structure of these approximate objects, and then to give applications of the resulting theorems. This endeavour has already lead to groundbreaking results in the theory of prime numbers, group theory and combinatorial number theory.

1 000 000 €

Start date: 2011-10-01, End date: 2016-09-30

The emergence of life is one of the most fascinating and yet largely unsolved questions in the natural sciences, and thus a significant challenge for scientists from many disciplines. There is growing evidence that ribonucleic acid (RNA) polymers, which are capable of genetic information storage and self-catalysis, were involved in the early forms of life. But despite recent progress, RNA synthesis without biological machineries is very challenging. The current project aims at understanding how to synthesize RNA in abiotic conditions. I will solve problems associated with three critical aspects of RNA formation that I will rationalize at a molecular level: (i) accumulation of precursors, (ii) formation of a chemical bond between RNA monomers, and (iii) tolerance for alternative backbone sugars or linkages. Because I will study problems ranging from the formation of chemical bonds up to the stability of large biopolymers, I propose an original computational multi-scale approach combining techniques that range from quantum calculations to large-scale all-atom simulations, employed together with efficient enhanced-sampling algorithms, forcefield improvement, cutting-edge analysis methods and model development. My objectives are the following: 1 • To explain why the poorly-understood thermally-driven process of thermophoresis can contribute to the accumulation of dilute precursors. 2 • To understand why linking RNA monomers with phosphoester bonds is so difficult, to understand the molecular mechanism of possible catalysts and to suggest key improvements. 3 • To rationalize the molecular basis for RNA tolerance for alternative backbone sugars or linkages that have probably been incorporated in abiotic conditions. This unique in-silico laboratory setup should significantly impact our comprehension of life’s origin by overcoming major obstacles to RNA abiotic formation, and in addition will reveal significant orthogonal outcomes for (bio)technological applications.

1 497 031 €

Start date: 2018-02-01, End date: 2023-01-31

Antibiotics have contributed to a tremendous increase in human well-being, saving many millions of lives. However, antibiotics become obsolete the more they are used as selection pressure promotes the development of resistant bacteria. The World Health Organization has proclaimed antibiotic resistance as a major global threat to public health. Today, 700,000 deaths per year are due to untreatable infections. To win the battle against antibiotic resistance, new policies affecting the supply and demand of existing and new drugs must be designed. I propose new research to identify and evaluate feasible and effective demand-side policy interventions targeting the relevant decision makers: physicians and patients. ABRSEIST will make use of a broad econometric toolset to identify mechanisms linking antibiotic resistance and consumption exploiting a unique combination of physician-patient-level antibiotic resistance, treatment, and socio-economic data. Using machine learning methods adapted for causal inference, theory-driven structural econometric analysis, and randomization in the field it will provide rigorous evidence on effective intervention designs. This research will improve our understanding of how prescribing, resistance, and the effect of antibiotic use on resistance, are distributed in the general population which has important implications for the design of targeted interventions. It will then estimate a structural model of general practitioners’ acquisition and use of information under uncertainty about resistance in prescription choice, allowing counterfactual analysis of information-improving policies such as mandatory diagnostic testing. The large-scale and structural econometric analyses allow flexible identification of physician heterogeneity, which ABRSEIST will exploit to design and evaluate targeted, randomized information nudges in the field. The result will be improved rational use and a toolset applicable in contexts of antibiotic prescribing.

1 498 920 €

Start date: 2019-01-01, End date: 2023-12-31