ERC FUNDED PROJECTS

Some of the most fascinating physical phenomena are experimentally observed in strongly correlated electron systems and, on the theoretical side, only poorly understood hitherto. The aim of the ERC project AbinitioDGA is the development, implementation and application of a new, 21th century method for the ab initio calculation of materials with such strong electronic correlations. AbinitioDGA includes strong electronic correlations on all time and length scales and hence is a big step beyond the state-of-the-art methods, such as the local density approximation, dynamical mean field theory, and the GW approach (Green function G times screened interaction W). It has the potential for an extraordinary high impact not only in the field of computational materials science but also for a better understanding of quantum critical heavy fermion systems, high-temperature superconductors, and transport through nano- and heterostructures. These four physical problems and related materials will be studied within the ERC project, besides the methodological development. On the technical side, AbinitioDGA realizes Hedin's idea to include vertex corrections beyond the GW approximation. All vertex corrections which can be traced back to a fully irreducible local vertex and the bare non-local Coulomb interaction are included. This way, AbinitioDGA does not only contain the GW physics of screened exchange and the strong local correlations of dynamical mean field theory but also non-local correlations beyond on all length scales. Through the latter, AbinitioDGA can prospectively describe phenomena such as quantum criticality, spin-fluctuation mediated superconductivity, and weak localization corrections to the conductivity. Nonetheless, the computational effort is still manageable even for realistic materials calculations, making the considerable effort to implement AbinitioDGA worthwhile.

1 491 090 €

Start date: 2013-01-01, End date: 2018-07-31

Diabetes, stroke and coronary artery disease (cardiometabolic diseases) are the leading cause of death in Europe. Given that effective pharmacological and lifestyle interventions are available, it is important to identify high risk individuals at an early stage. Traditionally, this is done using clinical prediction models. However, the established models have substantial limitations: they are often used by doctors only when an underlying disease is already suspected, they are not developed on updated nationally-representative data and they require time-consuming clinical measurements. Thus, a substantial part of the population is not provided with risk assessment. I propose to revolutionize the existing approaches to primary prevention by providing risk assessment of cardiometabolic diseases before an individual even steps into the doctor’s office for a visit. To this end my project has three main objectives: 1) Development of artificial intelligence (AI) approaches to model health trajectories based on nationwide registry data on medications, diagnoses, familial risk and socio-demographic information to obtain accurate risk estimates for cardiometabolic disease. I will integrate high quality data from selected countries that have long traditions of registry data (Finland and Sweden, over 7.5 million individuals). 2) To identify health trajectories that maximize the clinical utility of genetic scores by integrating genetic and registry-based data on > 1 million people to identify subgroups of individuals for whom genetic information might improve risk prediction. 3) Validation of AI and genetic-based risk assessment as first-stage screening via a clinical study in 2800 individuals. My project leverages the latest developments in AI and high-quality data of unprecedented scale to deliver a paradigm shift with important public health consequences by potentially changing the way cardiometabolic disease risk is assessed.

1 550 057 €

Start date: 2021-01-01, End date: 2025-12-31

AQSuS aims at experimentally implementing analogue quantum simulation of interacting spin models in two-dimensional geometries. The proposed experimental approach paves the way to investigate a broad range of currently inaccessible quantum phenomena, for which existing analytical and numerical methods reach their limitations. Developing precisely controlled interacting quantum systems in 2D is an important current goal well beyond the field of quantum simulation and has applications in e.g. solid state physics, computing and metrology. To access these models, I propose to develop a novel circuit quantum-electrodynamics (cQED) platform based on the 3D transmon qubit architecture. This platform utilizes the highly engineerable properties and long coherence times of these qubits. A central novel idea behind AQSuS is to exploit the spatial dependence of the naturally occurring dipolar interactions between the qubits to engineer the desired spin-spin interactions. This approach avoids the complicated wiring, typical for other cQED experiments and reduces the complexity of the experimental setup. The scheme is therefore directly scalable to larger systems. The experimental goals are: 1) Demonstrate analogue quantum simulation of an interacting spin system in 1D & 2D. 2) Establish methods to precisely initialize the state of the system, control the interactions and readout single qubit states and multi-qubit correlations. 3) Investigate unobserved quantum phenomena on 2D geometries e.g. kagome and triangular lattices. 4) Study open system dynamics with interacting spin systems. AQSuS builds on my backgrounds in both superconducting qubits and quantum simulation with trapped-ions. With theory collaborators my young research group and I have recently published an article in PRB [9] describing and analysing the proposed platform. The ERC starting grant would allow me to open a big new research direction and capitalize on the foundations established over the last two years.

1 498 515 €

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

The formation of a functional patterned vascular network is essential for development, tissue growth and organ physiology. Several human vascular disorders arise from the mis-patterning of blood vessels, such as arteriovenous malformations, aneurysms and diabetic retinopathy. Although blood flow is recognised as a stimulus for vascular patterning, very little is known about the molecular mechanisms that regulate endothelial cell behaviour in response to flow and promote vascular patterning. Recently, we uncovered that endothelial cells migrate extensively in the immature vascular network, and that endothelial cells polarise against the blood flow direction. Here, we put forward the hypothesis that vascular patterning is dependent on the polarisation and migration of endothelial cells against the flow direction, in a continuous flux of cells going from low-shear stress to high-shear stress regions. We will establish new reporter mouse lines to observe and manipulate endothelial polarity in vivo in order to investigate how polarisation and coordination of endothelial cells movements are orchestrated to generate vascular patterning. We will manipulate cell polarity using mouse models to understand the importance of cell polarisation in vascular patterning. Also, using a unique zebrafish line allowing analysis of endothelial cell polarity, we will perform a screen to identify novel regulators of vascular patterning. Finally, we will explore the hypothesis that defective flow-dependent endothelial polarisation underlies arteriovenous malformations using two genetic models. This integrative approach, based on high-resolution imaging and unique experimental models, will provide a unifying model defining the cellular and molecular principles involved in vascular patterning. Given the physiological relevance of vascular patterning in health and disease, this research plan will set the basis for the development of novel clinical therapies targeting vascular disorders.

1 618 750 €

Start date: 2016-09-01, End date: 2022-02-28