ERC FUNDED PROJECTS

The detection of primordial gravity waves created during the Big Bang ranks among the greatest potential intellectual achievements in modern science. During the last few decades, the instrumental progress necessary to achieve this has been nothing short of breathtaking, and we today are able to measure the microwave sky with better than one-in-a-million precision. However, from the latest ultra-sensitive experiments such as BICEP2 and Planck, it is clear that instrumental sensitivity alone will not be sufficient to make a robust detection of gravitational waves. Contamination in the form of astrophysical radiation from the Milky Way, for instance thermal dust and synchrotron radiation, obscures the cosmological signal by orders of magnitude. Even more critically, though, are second-order interactions between this radiation and the instrument characterization itself that lead to a highly non-linear and complicated problem. I propose a ground-breaking solution to this problem that allows for joint estimation of cosmological parameters, astrophysical components, and instrument specifications. The engine of this method is called Gibbs sampling, which I have already applied extremely successfully to basic CMB component separation. The new and ciritical step is to apply this method to raw time-ordered observations observed directly by the instrument, as opposed to pre-processed frequency maps. While representing a ~100-fold increase in input data volume, this step is unavoidable in order to break through the current foreground-induced systematics floor. I will apply this method to the best currently available and future data sets (WMAP, Planck, SPIDER and LiteBIRD), and thereby derive the world's tightest constraint on the amplitude of inflationary gravitational waves. Additionally, the resulting ancillary science in the form of robust cosmological parameters and astrophysical component maps will represent the state-of-the-art in observational cosmology in years to come.

1 999 205 €

Start date: 2018-04-01, End date: 2023-03-31

"We aim to perform academic development of a novel biomedical opportunity: localized synthesis of drugs within biocatalytic therapeutic vascular implants (BVI) for site-specific drug delivery to target organs and tissues. Primary envisioned targets for therapeutic intervention using BVI are atherosclerosis, viral hepatitis, and hepatocellular carcinoma: three of the most prevalent and debilitating conditions which affect hundreds of millions worldwide and which continue to increase in their importance in the era of increasingly aging population. For hepatic applications, we aim to develop drug eluting beads which are equipped with tools of enzyme-prodrug therapy (EPT) and are administered to the liver via trans-arterial catheter embolization. Therein, the beads perform localized synthesis of drugs and imaging reagents for anticancer combination therapy and theranostics, antiviral and anti-inflammatory agents for the treatment of hepatitis. Further, we conceive vascular therapeutic inserts (VTI) as a novel type of implantable biomaterials for treatment of atherosclerosis and re-endothelialization of vascular stents and grafts. Using EPT, inserts will tame “the guardian of cardiovascular grafts”, nitric oxide, for which localized, site specific synthesis and delivery spell success of therapeutic intervention and/or aided tissue regeneration. This proposal is positioned on the forefront of biomedical engineering and its success requires excellence in polymer chemistry, materials design, medicinal chemistry, and translational medicine. Each part of this proposal - design of novel types of vascular implants, engineering novel biomaterials, developing innovative fabrication and characterization techniques – is of high value for fundamental biomedical sciences. The project is target-oriented and once successful, will be of highest practical value and contribute to increased quality of life of millions of people worldwide."

1 996 126 €

Start date: 2014-04-01, End date: 2019-09-30

Advances in technology and methodology over the last decade, have enabled the study of galaxies to the highest redshifts. This has revolutionized our understanding of the origin and evolution of galaxies. I have played a central role in this revolution, by discovering that at z=2, when the universe was only 3 Gyr old, half of the most massive galaxies were extremely compact and had already completed their star formation. During the last five years I have led a successful group of postdocs and students dedicated to investigating the extreme properties of these galaxies and place them into cosmological context. Combining a series of high profile observational studies published by my group and others, I recently proposed an evolutionary sequence that ties together the most extreme galaxies in the universe, from the most intense dusty starburst at cosmic dawn, through quasars: the brightest sources in the universe, driven by feedback from supermassive black holes, and galaxy cores hosting the densest conglomerations of stellar mass known, to the sleeping giants of the local universe, the giant ellipticals. The proposed research program will explore if such an evolutionary sequence exists, with the ultimate goal of reaching, for the first time, a coherent physical understanding of how the most massive galaxies in the universe formed. While there is a chance the rigorous tests may ultimately reveal the proposed sequence to be too simplistic, a guarantied outcome of the program is a significantly improved understanding of the physical mechanisms that shape galaxies and drive their star formation and quenching

1 999 526 €

Start date: 2015-09-01, End date: 2020-08-31

In the aftermath of the high-precision Planck and BICEP2 experiments, cosmology has undergone a critical transition. Before 2014, most breakthroughs came as direct results of improved detector technology and increased noise sensitivity. After 2014, the main source of uncertainty will be due to astrophysical foregrounds, typically in the form of dust or synchrotron emission from the Milky Way. Indeed, this holds as true for the study of reionization and the cosmic dawn as it does for the hunt for inflationary gravitational waves. To break through this obscuring veil, it is of utmost importance to optimally exploit every piece of available information, merging the world's best observational data with the world's most advanced theoretical models. A first step toward this ultimate goal was recently published as the Planck 2015 Astrophysical Baseline Model, an effort led and conducted by myself. Here I propose to build Cosmoglobe, a comprehensive model of the radio, microwave and sub-mm sky, covering 100 MHz to 10 THz in both intensity and polarization, extending existing models by three orders of magnitude in frequency and a factor of five in angular resolution. I will leverage a recent algorithmic breakthrough in multi-resolution component separation to jointly analyze some of the world's best data sets, including C-BASS, COMAP, PASIPHAE, Planck, SPIDER, WMAP and many more. This will result in the best cosmological (CMB, SZ, CIB etc.) and astrophysical (thermal and spinning dust, synchrotron and free-free emission etc.) component maps published to date. I will then use this model to derive the world's strongest limits on, and potentially detect, inflationary gravity waves using SPIDER observations; forecast, optimize and analyze observations from the leading next-generation CMB experiments, including LiteBIRD and S4; and derive the first 3D large-scale structure maps from CO intensity mapping from COMAP, potentially opening up a new window on the cosmic dawn.

1 999 382 €

Start date: 2019-06-01, End date: 2024-05-31

Motivation The enormous growth in the Internet of Things and server farms for cloud services has increased the strain on the optical communication infrastructure. By 2025, our society will require data rates that are physically impossible to implement using current state-of-the-art optical communication technologies. This is because fibre-optic communication systems are rapidly approaching their fundamental capacity limits imposed by the Kerr nonlinearity of the fibre. Nonlinear distortion limits the ability to transport and detect the information stream. This is a very critical problem for increasing the data rates of any optical fibre communication system. Proposed research The only physical quantities not affected by the nonlinearity are eigenvalues, associated with the optical fibre propagation equation. Eigenvalues are thereby ideal candidates for information transport. The concept of eigenvalues is derived under the assumption that the fibre is lossless and that there is no noise in the system which is not strictly correct. Therefore, novel methodologies and concepts for the design of a noise mitigating receiver and a noise robust transmitter are needed to reap the full benefits of optical communication systems employing eigenvalues. This proposal will develop such strategies. This will be achieved by combining, for the first time, the fields of nonlinear optics, optical communication and nonlinear digital signal processing. The results from the project will be verified experimentally, and will form the basis for a new generation of commercial optical communication systems. Preliminary results Our proof-of-concept results demonstrate, for the first time, that noise can be handled by employing novel receiver concepts. An order of magnitude improvement compared to the state-of-the-art is demonstrated. Environment The research will be carried out in close cooperation with leading groups at Stanford University and Technical University of Munich.

2 000 000 €

Start date: 2018-03-01, End date: 2023-02-28

State-of-the-art simulations and observations highlight the self-organization of convective clouds. Our recent work shows two aspects: these clouds are capable of unexpected increase in extreme precipitation when temperature rises; interactions between clouds produce the extremes. As clouds interact, they organize in space and carry a memory of past interaction and precipitation events. This evidence reveals a severe shortcoming of the conventional separation into "forcing" and "feedback" in climate model parameterizations, namely that the "feedback" develops a dynamics of its own, thus driving the extremes. The major scientific challenge tackled in INTERACTION is to make a ground-breaking departure from the established paradigm of "quasi-equilibrium" and instantaneous convective adjustment, traditionally used for parameterization of "sub-grid-scale processes" in general circulation models. To capture convective self-organization and extremes, the out-of-equilibrium cloud field must be described. In INTERACTION, I will produce a conceptual model for the out-of-equilibrium system of interacting clouds. Once triggered, clouds precipitate on a short timescale, but then relax in a "recovery" state where further precipitation is suppressed. Interaction with the surroundings occurs through cold pool outflow,facilitating the onset of new events in the wake. I will perform tailored numerical experiments using cutting-edge large-eddy simulations and very-high-resolution observational analysis to determine the effective interactions in the cloud system. Going beyond traditional forcing-and-feedback descriptions, I emphasize gradual self-organization with explicit temperature dependence. The list of key variables of atmospheric water vapor, temperature and precipitation must therefore be amended by variables describing organization. Capturing the self-organization of convection is essential for understanding of the risk of precipitation extremes today and in a future climate.

1 314 800 €

Start date: 2018-07-01, End date: 2023-06-30

Progress within many contemporary or emergent technologies, including photovoltaics, single-photon light sources, and plasmonics, depends crucially on our ability to control the interactions between light and matter. The complexity of the light-matter interactions has made the development of photonic materials a slow, expensive, and empirical-based science. Of particular importance are the detrimental non-radiative processes mediated by defects and phonons that lead to efficiency losses in photovoltaics, reduce the quantum efficiency of single-photon emitters, and cause Ohmic losses in the metallic components of plasmonic devices. LIMA will develop ground breaking methods for calculating non-radiative relaxation rates in real materials from first principles. These will be used to evaluate key performance parameters such as photo-carrier lifetimes and plasmon propagation lengths and thus facilitate a realistic computational assessment of the application potential of photonic materials. In terms of materials, LIMA will focus on the emergent class of atomically thin two-dimensional (2D) materials. The possibility of combining different 2D materials into van der Waals heterostructures (vdWHs) provides a unique platform for controlling light-matter interactions with atomic scale precision. Multi-scale methods for predicting quasiparticle band structures of general, incommensurable vdWHs will be developed and used to design novel photonic materials with tailored light dispersion and multi-junction solar cells with high absorption and low thermalization losses. High-throughput computational screening will be used to identify novel color centers in 2D materials with potential to act as single-photon sources with high quantum yield and narrow linewidths, which are urgently needed by leading quantum technologies. The possibilities of controlling the color centers via strain engineering and light management will be explored in close collaboration with experimentalists.

1 951 354 €

Start date: 2018-04-01, End date: 2023-03-31

A critical component of computational processing of data sets is the `preprocessing' or `compression' step which is the computation of a \emph{succinct, sufficiently accurate} representation of the given data. Preprocessing is ubiquitous and a rigorous mathematical understanding of preprocessing algorithms is crucial in order to reason about and understand the limits of preprocessing. Unfortunately, there is no mathematical framework to analyze and objectively compare two preprocessing routines while simultaneously taking into account `all three dimensions' -- -- the efficiency of computing the succinct representation, -- the space required to store this representation, and -- the accuracy with which the original data is captured in the succinct representation. ``The overarching goal of this proposal is the development of a mathematical framework for the rigorous analysis of preprocessing algorithms. '' We will achieve the goal by designing new algorithmic techniques for preprocessing, developing a framework of analysis to make qualitative comparisons between various preprocessing routines based on the criteria above and by developing lower bound tools required to understand the limitations of preprocessing for concrete problems. This project will lift our understanding of algorithmic preprocessing to new heights and lead to a groundbreaking shift in the set of basic research questions attached to the study of preprocessing for specific problems. It will significantly advance the analysis of preprocessing and yield substantial technology transfer between adjacent subfields of computer science such as dynamic algorithms, streaming algorithms, property testing and graph theory.

2 000 000 €

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

Web applications that execute in the user's web browser constitute a substantial part of modern software. JavaScript is the main programming language of the web, although alternatives are emerging, in particular, TypeScript and Dart. Despite the advances in design of languages and libraries, it is difficult to prevent errors when programming such web applications. Although the basic principles of software verification have been known for decades and researchers have developed an abundance of techniques for formal reasoning about programs, modern software has lots of errors, as everyday users can testify. The PAW project will create novel automated program analysis algorithms for preventing errors and improving performance of advanced web applications. The project hypothesis is that a scientific breakthrough is within reach, due to recent results in static and dynamic program analysis for JavaScript. The central idea is to combine static and dynamic analysis in new ways. In addition, the project will make program analysis algorithms and infrastructure available in a form that embraces reusability.

1 977 382 €

Start date: 2015-08-01, End date: 2021-07-31

Election pledges are supposedly a vital part of representative democracy. Yet we do not in fact know whether and how pledges matter for vote choice and accountability. This project thus asks: Do election pledges matter for voters’ democratic behavior and beliefs? The role of pledges in citizens’ democratic behavior and beliefs is, surprisingly, virtually unexplored. This project’s ambition is therefore to create a new research agenda that redefines how political scientists think about the link between parties and voters. The project not only advances the research frontier by introducing a new, crucial phenomenon for political scientists to study; it also breaks new ground because it provides original theoretical and methodological tools for this new research agenda. The key empirical contribution of this project is to collect two path-breaking datasets in the United States, France, and Norway that produce an unbiased estimate of voters’ awareness and use of pledges. The first consists of a set of innovative panel surveys with embedded conjoint experiments conducted both before and after national elections. The second dataset codes all pledges; whether or not they are broken; and how the mass media report on them. This project is unique in its scientific ambition: It studies the core mechanism of representative democracy as it happens in real time, and does so in several countries. If successful, we will have much firmer knowledge about how voters select parties that best represent them and sanction those that betray their trust – and what this all implies for people’s trust in democracy.

1 999 255 €

Start date: 2019-08-01, End date: 2024-07-31

This proposal explores the power of quantum information in two respects. The first is the technological power of quantum information in a communication infrastructure, and the second is its descriptive power in many-particle quantum systems. My point of departure is to view quantum information as a resource that can be processed and converted. In quantum communication, a famous resource conversion is provided by the quantum teleportation protocol, which allows us to send one quantum bit (1 qubit) through the transmission of two classical bits (2 cbits) and the use of one entangled pair of quantum bits (1 ebit): 1 ebit + 2 cbits > 1 qubit. Casting quantum protocols in such resource inequalities has proven useful, since the algebraic manipulation of inequalities results in new protocols, but this approach has hitherto largely been limited to point-to-point communication. It is the first goal of this project to overcome this limitation and characterise resource conversion in larger quantum networks. This will result in more efficient communication protocols that will have an impact on the use and design of quantum communication networks, which are currently being built around the globe. A quantum network involving distant communicating labs is mirrored at the small scale by a set of interacting quantum particles. The quantum state arising from pairwise interactions can be strongly entangled, with an underlying entanglement structure given by a graph with entangled pairs along the edges. There is a surprising and close connection between such entanglement structures and tensor research in the context of algebraic complexity theory. The second goal of the project is to exploit this connection and characterise the resource conversion of entanglement structures. The research will lead to more efficient tensor network representations of many-particle quantum states, and to progress on the computational complexity of matrix multiplication, a long-standing unsolved problem.

1 953 750 €

Start date: 2019-12-01, End date: 2024-11-30

Low-mass stars like our Sun are formed in the centers of dark clouds of dust and gas that obscure their visible light. Deep observations at infrared and submillimeter wavelengths are uniquely suited to probe the inner regions of these young stellar objects and unravel their structures, as well as the physical and chemical processes involved. These earliest stages are particularly interesting because the properties of the deeply embedded objects reflect the star formation process itself and how it relates to its environment. It is for example during this stage that the final mass of the star and the properties of its disk – and thus ability to form planets – are determined. It is also during these stages that the first seeds for the chemical evolution of the protoplanetary disk are planted and where some complex organic, possibly prebiotic, molecules may be formed. I here apply for an ERC Consolidator Grant that will support an ambitious program to map the physics and chemistry of the early Solar System. The proposed research program intends to use new high resolution, high sensitivity observations from the Atacama Large Millimeter Array (ALMA) - including a number of recently approved large programs – coupled to state-of-the-art radiative transfer tools and theoretical simulations to address some of the key questions concerning the physics and chemistry of the earliest stages of the Solar System: How is the chemistry of the earliest protostellar stages related to the physical structure and evolution of the young stellar object and its surrounding environment? Which complex organic molecules are present in the inner regions of low-mass protostars? What are the chances the rich chemistry of the earliest stages is incorporated into planetary systems such as our own?

1 999 659 €

Start date: 2015-08-01, End date: 2020-07-31

It was recently realized that lysine acetylation affects a wide variety of cellular processes in addition to the initially recognized histone related gene regulation. Together with recent groundbreaking results, revealing the presence of additional acyllysine modifications, the basis for a paradigm shift in this area was formed. Examples of enzymes formerly thought to be lysine deacetylases, have been shown to cleave these new types of lysine modification and members of the sirtuin class of enzymes play a central role. Development of new tools to investigate the importance of these new modifications as well as the sirtuins that cleave them is required. We therefore propose to adopt an interdisciplinary approach by developing selective inhibitors and so-called activity-based probes (ABPs) and applying these to the investigation of proteins recognizing novel post-translational acylations of lysine residues in cells. Such ABPs will be powerful tools for providing insight regarding this rapidly evolving area of biochemistry; however, the current state-of-the-art in ABP design is endowed with severe limitations because the modifications are inherently cleaved by various hydrolases in human cells. Thus, in the present project, I propose that novel designs accommodating non-cleavable modifications are warranted to maintain structural integrity during experiments. Furthermore, I propose to apply similar mechanism-based designs to develop potent and isoform-selective sirtuin inhibitors, which will serve as chemical probes to investigate links between cancer and metabolism, and may ultimately serve as lead compounds for pre-clinical pharmaceutical development. AIM-I. (a) Development and (b) application of collections of chemical probes for activity-based investigation of enzymes that interact with post-translationally acylated proteins. AIM-II. Utilization of structural and mechanistic insight to design potent and selective inhibitors of sirtuin enzymes.

1 758 742 €

Start date: 2017-04-01, End date: 2022-03-31

Similarity search is the task of identifying, in a collection of items, the ones that are “similar” to a given query item. This task has a range of important applications (e.g. in information retrieval, pattern recognition, statistics, and machine learning) where data sets are often big, high dimensional, and possibly noisy. State-of-the-art methods for similarity search offer only weak guarantees when faced with big data. Either the space overhead is excessive (1000s of times larger than the space for the data itself), or the work needed to report the similar items may be comparable to the work needed to go through all items (even if just a tiny fraction of the items are similar). As a result, many applications have to resort to the use of ad-hoc solutions with only weak theoretical guarantees. This proposal aims at strengthening the theoretical foundation of scalable similarity search, and developing novel practical similarity search methods backed by theory. In particular we will: - Leverage new types of embeddings that are kernelized, asymmetric, and complex-valued. - Consider statistical models of noise in data, and design similarity search data structures whose performance guarantees are phrased in statistical terms. - Build a new theory of the communication complexity of distributed, dynamic similarity search, emphasizing the communication bottleneck present in modern computing infrastructures. The objective is to produce new methods for similarity search that are: 1) Provably robust, 2) scalable to large and high-dimensional data sets, 3) substantially more resource efficient than current state-ofthe- art solutions, and 4) able to provide statistical guarantees on query answers. The study of similarity search has been an incubator for techniques (e.g. locality-sensitive hashing and random projections) that have wide-ranging applications. The new techniques developed in this project are likely to have significant impacts beyond similarity search.

1 889 712 €

Start date: 2014-05-01, End date: 2019-04-30

As far as we know, our solar system is unique. It could, in principle, be the only planetary system in the Universe to harbor intelligent life or, indeed, life at all. As such, attempting to reconstruct its history is one of the most fundamental pursuits in the natural sciences. Whereas astronomical observations of star- forming regions provide a framework for understanding the formation of low-mass stars and the early evolution of planetary systems in general, direct information about the earliest solar system can only come from primitive meteorites and their components and some differentiated meteorites that record the birth of the solar system. The main objective of this proposal is to investigate the timescales and processes – including the role of supernovas – leading to the formation of the solar system by measurement of isotopic variations in meteorites. To achieve our objectives, we will integrate long-lived and short-lived radioisotope chronometers with the presence/absence of nucleosynthetic anomalies in various meteorites and meteoritic components. Our isotopic measurements will be obtained using state-of-the-art technologies such as second-generation mass spectrometers housed in laboratories directed by the PI and fully dedicated to cosmochemistry. This will allow us to: 1) define the mechanism and timescale for the collapse of the protosolar molecular cloud and emergence of the protoplanetary disk, 2) constrain the source and locale of chondrule-forming event(s) as well as the nature of the mechanism(s) required to transport chondrules to the accretion regions of chondrites, and 3) provide robust estimates of the timing and mechanism of asteroidal differentiation. We aim to understand how the variable initial conditions imposed by the range of possible stellar environments and protoplanetary disk properties regulated the formation and assemblage of disk solids into asteroidal and planetary bodies comprising our solar system.

1 910 889 €

Start date: 2014-02-01, End date: 2019-01-31

Biogenic volatile organic compounds (BVOCs) influence atmospheric oxidation causing climate feedback thought to be especially significant in remote areas with low anthropogenic emissions, such as the Arctic. Still, we do not understand the dynamics and impact of climatic and biotic BVOC emission drivers in arctic and alpine tundra, which are highly temperature-sensitive BVOC sources. TUVOLU will redefine tundra BVOC emission estimates to account for rapid and dramatic climate warming accompanied by effects of vegetation change, permafrost thaw, insect outbreaks and herbivory using multidisciplinary, established and novel methodology. We will quantify the relationships between leaf and canopy temperatures and BVOC emissions to improve BVOC emission model predictions of emission rates in low-statured tundra vegetation, which efficiently heats up. We will experimentally determine the contribution of induced BVOC emissions from insect herbivory in the warming Arctic by field manipulation experiments addressing basal herbivory and insect outbreaks and by stable isotope labelling to identify sources of the induced emission. Complementary laboratory assessment will determine if permafrost thaw leads to significant BVOC emissions from thawing processes and newly available soil processes, or if released BVOCs are largely taken up by soil microbes. We will also use a global network of existing climate warming experiments in alpine tundra to assess how the BVOC emissions from tundra vegetation world-wide respond to climate change. Measurement data will help develop and parameterize BVOC emission models to produce holistic enhanced predictions for global tundra emissions. Finally, modelling will be used to estimate emission impact on tropospheric ozone concentrations and secondary organic aerosol levels, producing the first assessment of arctic BVOC-mediated feedback on regional air quality and climate.

2 347 668 €

Start date: 2018-04-01, End date: 2023-03-31