Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SOLMAG (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 2418750.0 €

For life on Earth, the Sun is the most important astrophysical object in the universe. For astrophysicists, the atmosphere of the Sun presents an intriguing, complex and extremely varied environment generated by continuous dynamic, small-scale interactions between plasma and intricately structured magnetic fields. The purpose of this proposal is to elucidate the physics underlying the structure and dynamics of the solar magnetic field that is responsible for the Sun’s varied activity and its variability. This goal is to be achieved by following an integral approach combining new observational facilities, novel instruments developed in the group of the PI, the next generation of inversion techniques for data analysis and state-of-the-art magnetohydrodynamic simulations. This wide range of expertise present in the group of the PI is unique and well suited to such an approach. The research proposed here will provide measurements of the Sun’s magnetic field at high spatial and temporal resolution at unprecedented sensitivity to Zeeman splitting and to magnetic flux. Also, the use of a novel polarimetric hyperspectral imager, combined with the next generation of inversion techniques will allow following the 3D structure of the magnetic field and of other physical parameters in time through a sequence of snapshots. This will enable following the build-up of magnetic tension and of waves following the field lines and will set important constraints on the heating mechanism of the solar chromosphere and corona. The proposed work, in particular the comparison of measurements with simulations, will also set constraints on the presence and properties of a small-scale turbulent dynamo as well as other fundamental physical processes taking place in the solar atmosphere. The techniques introduced here will enable reliable and robust measurements of chromospheric magnetic fields, shedding new light on this enigmatic but centrally important layer of the solar atmosphere.

Mots-clés : solar magnetic field,solar variability,solar atmosphere
Projet ERC : CALI (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : École française d'Extrême-Orient — Pays : France — Rôle : PI
Acronyme de l'entité : EFEO
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1482843.77 €

For over half a millennium, the great medieval capital of Angkor lay at the heart of a vast empire stretching across much of mainland SE Asia. Recent research has revealed that the famous monuments of Angkor were merely the epicentre of an immense settlement complex, with highly elaborate engineering works designed to manage water and mitigate the uncertainty of monsoon rains. Compelling evidence is now emerging that other temple complexes of the medieval Khmer Empire may also have formed the urban cores of dispersed, low-density settlements with similar systems of hydraulic engineering. Using innovative airborne laser scanning (‘lidar’) technology, CALI will uncover, map and compare archaeological landscapes around all the major temple complexes of Cambodia, with a view to understanding what role these complex and vulnerable water management schemes played in the growth and decline of early civilisations in SE Asia. CALI will evaluate the hypothesis that the Khmer civilisation, in a bid to overcome the inherent constraints of a monsoon environment, became locked into rigid and inflexible traditions of urban development and large-scale hydraulic engineering that constrained their ability to adapt to rapidly-changing social, political and environmental circumstances. By integrating data and techniques from fast-developing archaeological sciences like remote sensing, palaeoclimatology and geoinformatics, this work will provide important insights into the reasons for the collapse of inland agrarian empires in the middle of the second millennium AD, a transition that marks the emergence of modern mainland SE Asia. The lidar data will provide a comprehensive and internally-consistent archive of urban form at a regional scale, and offer a unique experimental space for evaluating socio-ecological resilience, persistence and transformation over two thousand years of human history, with clear implications for our understanding of contemporary urbanism and of urban futures.

Mots-clés : lidar,remote sensing,water management,palaeoenvironment,urbanism,resilience,angkor,southeast asia
Projet ERC : SNOWISO (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : University of Bergen — Pays : Norvège — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1497260.0 €

For the past 50 years, our use of ice core records as climate archives has relied on the fundamental assumption that the isotopic composition of precipitation deposited on the ice sheet surface determines the ice core water isotopic composition. Since the isotopic composition in precipitation is assumed to be governed by the state of the climate this has made ice core isotope records one of the most important proxies for reconstructing the past climate. New simultaneous measurements of snow and water vapor isotopes have shown that the surface snow exchanges with the atmospheric water vapor isotope signal, altering the deposited precipitation isotope signal. This severely questions the standard paradigm for interpreting the ice core proxy record and gives rise to the hypothesis that the isotope record from an ice core is determined by a combination of the atmospheric water vapor isotope signal and the precipitation isotope signal. The SNOWISO project will verify this new hypothesis by combining laboratory and field experiments with in-situ observations of snow and water vapor isotopes in Greenland and Antarctica. This will enable me to quantify and parameterize the snow-air isotope exchange and post-depositional processes. I will implement these results into an isotope-enabled Regional Climate Model with a snowpack module and benchmarked against in-situ observations. Using the coupled snow-atmosphere isotope model I will establish the isotopic shift due to post-depositional processes under different climate conditions. This will facilitate the use of the full suite of water isotopes to infer past changes in the climate system, specifically changes in ocean sea surface temperature and relative humidity. By establishing how the water isotope signal is recorded in the snow, the SNOWISO project will build the foundation for future integration of isotope-enabled General Circulation Models with ice core records; this opens a new frontier in climate reconstruction.

Mots-clés : ice core records,water stable isotopes,snow air exchange,post depositional snow processes
Projet ERC : SPANC (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Utrecht University — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

Forecasting the magnitude of future global warming is among the great scientific challenges. Model estimates of long-term warming resulting from a doubling of the CO2 concentration relative to the pre-industrial era range between 1.5 and 4.5 °C. The large uncertainty in this Equilibrium Climate Sensitivity (ECS) may represent the difference between the melting or conservation of large continental ice sheets, and between habitable and inhabitable regions. SPANC will quantify ECS through accurate reconstructions of past climate change. Existing ECS studies largely focus on periods that were colder than present. Importantly, however, my development of a reliable method to reconstruct past CO2 concentrations now allows for estimates of past warm climates that can serve as analogs for the future. First, I will calibrate the new CO2 proxy for high CO2 levels. Uniquely, my new approach allows CO2 and temperature reconstructions to be based on the same samples, implying optimal time control. This provides the outstanding opportunity to generate high-quality coupled CO2 and temperature reconstructions for the ice-free early Eocene and the warm but glaciated middle Miocene at unprecedented resolution. This allows ECS to be calculated based on long and short-term variability in CO2 and temperature. The combination of ice-free and glaciated periods will also determine the extent to which the presence of ice governs climate response to CO2. Study locations will be carefully selected across pole-equator transects. This allows for quantification of the amplification of temperature changes towards polar regions, crucial for ice sheet extent and volume and hence global sea levels. SPANC will provide a breakthrough regarding the ECS of warm climates. It will provide crucial new constraints on the ability of climate models to correctly simulate warm climates and climate variability forced by changes in CO2 concentrations, which is vital for reliable future climate projections.
Projet ERC : DiDip (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : University of Graz — Pays : Autriche — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2812500.0 €

From Digital to Distant Diplomatics (DiDip) will bring modern computational methods to the transregional study of late medieval charters. It will answer questions about the spread and development of pan-European documentary practices and documentary culture in the later medieval period (c. 1300-1500). The project's novelty lies in 1. the scale of the endeavour, building upon a database of over half a million digitized charters from medieval and early modern Europe (the PI's Monasterium.net) and expanding it both numerically and qualitatively and 2. the application of cutting-edge ‘distant’ macroanalysis practices (Jockers 2013) to a Europe-wide dataset, producing findings that go beyond the traditional regional and single-institution related scope of diplomatics projects. At the core of this project is the observation that the preponderance of studies in diplomatics have been and remain focused on smaller units, such as individual chanceries, collections of single institutions, or the practices of one country, language group or region (Jarret 2013) and the resignation of diplomatics scholars in the face of the large amount of documentation in the 14th and 15th century. How can we truly make an integrated study of European diplomatics in this period when it is largely addressed as a variety of hyperlocalized phenomena, without meaningful study of the relation of the practices of one area to another? The DiDip project answers this question by building a digital research environment to study the issue on a macro scale, improving the quality of research data and the methods available to enable greater breadth of study and provide findings that will point us towards a better understanding of the relationship of the various regional documentary cultures across Europe in the period.

Mots-clés : diplomatics,later middle ages,virtual research environment,macroanalysis,distant reading,europe
Projet ERC : SYGMA (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : Italian Institute of Technology — Pays : Italie — Rôle : Partner
Type d'entité : Recherche
Financement ERC de l'entité : 710000.0 €

From a Physics and Engineering standpoint, swimming bacteria are a formidable example of self-propelled micro-machines. Together with their synthetic counterpart, self-propelled colloids, they represent the “living” atoms of active matter, an exciting branch of contemporary soft matter and statistical mechanics. Differently from synthetic colloids, however, each bacterial cell contains all the molecular machinery that is required to self-replicate, sense the environment, process information and compute responses. Breaking down these biological functions into basic genetic parts has been one of the greatest triumphs of molecular biology. Today, synthetic biologists are assembling these parts into new genetic programs and exploiting bacteria as computing micro-machines. Project SYGMA will employ the synthetic biology toolkit to provide the building blocks for a light controllable active matter having reliable, reconfigurable and interactively tunable dynamical properties. We will first engineer transmembrane photoreceptors to wire RGB external light signals to cellular physical responses like speed, tumbling, growth and death rates. These genetic parts will allow the modular design of customized active particles to build active materials with unprecedented optical control capabilities. Using these new tools we will address, with experiments and theory, fundamental questions like: how fast can we drive particle density using spatio-temporal motility modulations? what is the force on a body suspended in a bath of bacteria with non uniform motility? how do physical forces contribute to morphogenesis in bacterial colonies? Finding quantitative and experimentally validated answers will eventually allow us to engineer structured illumination protocols to mold living microstructures, transport colloidal cargos by shaping active pressure, control swarms of biohybrid microcars and shape bacterial microcolonies.

Mots-clés : active matter
Projet ERC : DynASoAr (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : University of Salzburg — Pays : Autriche — Rôle : PI
Acronyme de l'entité : PLUS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499843.0 €

From a procedural viewpoint, an algorithm is a list of instructions that transforms a given input into the desired output. While this paradigm has been successfully applied in theory and practice, it completely neglects the fact that in many scenarios the input is not given to the algorithm in its entirety at the beginning and might undergo changes that the algorithm needs to react to. Formally, such a situation can be modeled as a game between an adversary creating the sequence of updates to the input and an algorithm that tries to process each of these updates as fast as possible. Researchers have studied such dynamic problems with increasing interest in the past years. However, many state-of-the-art solutions suffer from at least one of the following drawbacks: (1) Many dynamic algorithms are randomized and assume that the sequence of updates is independent of the random choices made by the algorithm. This is not justified in situations where the next update to the input naturally depends on the previous outputs of the algorithm. (2) Many dynamic algorithms achieve amortized running time guarantees where the stated guarantee on processing each update only holds on average and occasionally significantly more time might be needed. This is insufficient for real-time systems requiring hard worst-case guarantees. The goal of this project is to design dynamic algorithms free from these two shortcomings. Formally, this amounts to giving the adversary the following additional powers: (1) adapting its update sequence to the outputs of the algorithm and (2) discarding the algorithm if some update is not processed in time. While isolated results in this direction exist, with some of them obtained by the PI, the unique feature of this project is the systematic study of these stronger adversarial models for otherwise well-studied dynamic problems. Our results will facilitate the use of dynamic algorithms in both real-world applications and in the design of static algorithms.

Mots-clés : efficient algorithms,dynamic graph algorithms
Projet ERC : TACCAMA (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Technical University of Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499375.0 €

From fine chemical synthesis over combustion control to electrode design – the majority of chemical reactions rely on catalysts to improve energy and material efficiency. Yet, the atomic-scale processes underlying a catalytic reaction at elevated pressures are far less well-understood than one might expect. Indeed, the successful optimization of industrial catalysts is typically achieved by ‘trial and error’. If we precisely understood the correlation between catalyst dynamics and activity, we could instead design stable, yet intrinsically dynamic (i.e. structurally fluxional) catalysts, drastically reduce our waste of noble metals by using only the most active particles and replace rare and toxic materials. This project constitutes a fundamental and systematic investigation of heterogeneous catalysis in action. My aim is to map the pressure and temperature range in which supported particle catalysts are stable, and correlate particle size and support morphology with dynamics and stability. To do so, I will combine my experience with surface dynamics studies, video-rate scanning tunneling microscopy (STM), ambient pressure (AP) surface science and cluster research. State-of-the-art video-rate APSTM will enable me to observe catalyst dynamics such as sintering, adsorbate spillover onto the support, dynamic structural fluxionality of clusters and support roughening as a function of reactant partial pressure and temperature. The novelty of this project lies in the direct observation of catalyst particles, defined to the exact number of atoms, under realistic reaction conditions in order to tune reactivity by controlling their dynamics and stability on structurally and electronically optimized oxide supports. AP X-ray photoelectron spectroscopy (APXPS) will supply complementary information about chemical changes occurring in cluster and support. The knowledge gained will contribute to the targeted design of more active and efficient catalysts for specific applications.

Mots-clés : catalyst dynamics,metal clusters,dynamic structural fluxionality,size effects,sintering,support effects,apstm,apxps
Projet ERC : DYNAMICSS (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1049855.0 €

From pension reforms to UI extensions, the optimal tax and program design literature is often ill-equipped to provide clear guidance in policy debates on the reform of social insurance and tax-and-benefit systems. The reason is that this literature is mostly focused on static settings, while these programs are inherently dynamic: they specify a schedule of tax and benefits that is time or state dependent and they affect individuals’ decisions throughout their lifetime. DYNAMICSS will offer a simple and general approach to the analysis of optimal dynamic policies that connects to the data. The key idea of DYNAMICSS is to extend the sufficient statistics (SS) approach to dynamic settings and characterize the full time profile, rather than the average generosity, of social insurance and transfer policies. By expressing optimal policy as a function of a limited set of statistics, the SS approach has the advantage of making clear the trade-offs implied in optimal tax or benefit formulae and of tightly integrating the theory and the empirics of optimal policy analysis, to offer robust policy guidance. DYNAMICSS will use unique administrative data and cutting-edge econometric techniques to exploit compelling variations in policy profiles and offer significant contributions to the empirical analysis of dynamic behavioural responses to policies. A central contribution will be to create a unique measure of consumption expenditures based on leveraging complete administrative information on income, transfers and wealth to offer ground-breaking evidence of the effect of social insurance on consumption dynamics. Part I will use and extend the SS framework to analyse the optimal time profile of UI benefits. Part II will develop this approach for analysing the optimal design of retirement pension systems. Part III will address optimal family policies with a focus on understanding the different dynamics of men and women in the labour market, and exploring the role of cultural norm
Projet ERC : IntScOmics (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : University Medical Center Utrecht — Pays : Pays-Bas — Rôle : Partner
Acronyme de l'entité : UMC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 500000.0 €

From populations of unicellular organisms to complex tissues, cell-to-cell variability in phenotypic traits seems to be universal. To study this heterogeneity and its biological consequences, researchers have used advanced microscopy-based approaches that provide exquisite spatial and temporal resolution, but these methods are typically limited to measuring a few properties in parallel. On the other hand, next generation sequencing technologies allow for massively parallel genome-wide approaches but have, until recently, relied on studying population averages obtained from pooling thousands to millions of cells, precluding genome-wide analysis of cell-to-cell variability. Very excitingly, in the last few years there has been a revolution in single-cell sequencing technologies allowing genome-wide quantification of mRNA and genomic DNA in thousands of individual cells leading to the convergence of genomics and single-cell biology. However, during this convergence the spatial and temporal information, easily accessed by microscopy-based approaches, is often lost in a single-cell sequencing experiment. The overarching goal of this proposal is to develop single-cell sequencing technology that retains important aspects of the spatial-temporal information. In particular I will focus on integrating single-cell transcriptome and epigenome measurements with the physical cell-to-cell interaction network (spatial information) and lineage information (temporal information). These tools will be utilized to (i) explore the division symmetry of intestinal stem cells in vivo; (ii) to reconstruct the cell lineage history during zebrafish regeneration; and (iii) to determine lineage relations and the physical cell-to-cell interaction network of progenitor cells in the murine bone marrow.

Mots-clés : single cell sequencing,single cell genomics,single cell transcriptomics,single cell epigenetics