Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : UBIQGAP (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Durham University — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1437055.0 €

Spectral gap is a fundamental concept in mathematics, physics, and computer science as it governs the exponential rate at which a process converges towards its stationary state. It informs the spectral lines of hydrogen, how we shuffle cards, the behavior of semiconductors, and web search algorithms. Moreover, some of the most prominent issues of contemporary mathematics, including the Ramanujan-Petersson conjecture and the Yang-Mills mass gap, revolve around spectral gap. This proposal seeks to investigate the nature of the spectral gap for hyperbolic surfaces and unitary representations of fundamental groups of surfaces. In the former case, the spectral gap occurs in the spectrum of the Laplace-Beltrami operator on the surface, and in the latter, it occurs in the spectrum of a Hecke operator attached to the representation. The two main motifs of the proposal are ubiquity and optimality. Is the spectral gap ubiquitous? Does it exist for random surfaces and random representations? Is it easy to construct surfaces with a large spectral gap? In what cases can one prove that the spectral gap is close to optimal? The sharpest and most ambitious questions discussed in this proposal combine these two aspects and ask whether objects with (almost) optimal spectral gap appear with high frequency. My main technical tool is the development of new formulas for integration over representation varieties of fundamental groups of surfaces. These integral formulas are of high independent interest. For example, I propose to establish estimates that extend important results in Voiculescu's Free Probability Theory from the context of free groups, to fundamental groups of closed compact surfaces, and beyond. The proposal is extremely timely, as it builds on two separate breakthroughs that I have achieved in 2019. I am uniquely placed to tackle the questions of the proposal due to my broad background in geometry, analysis, and representation theory.

Mots-clés : spectral gap,hyperbolic surfaces,representation varieties
Projet ERC : SPECGEO (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Sapienza University of Rome — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1434000.0 €

Spectral geometry concerns the study of the geometric properties of data domains, such as surfaces or graphs, via the spectral decomposition of linear operators defined upon them. Due to their valuable properties analogous to Fourier theory, such methods find widespread use in several branches of computer science, ranging from computer vision to machine learning and network analysis. Despite their pervasive presence, very little efforts have been devoted to the design and application of spectral techniques that deal with corrupted, missing, high-dimensional or abstract data undergoing complex transformations. This lack of focus is mainly motivated by the widespread acceptance, supported in part by theoretical results, that an ε-perturbation to the geometry of the data (as small as the removal of a single point) can induce arbitrary changes in the operator’s eigendecomposition – leading to a limited adoption of spectral models in real-world applications. This project challenges this view, contending that such presumption of instability is primarily due to a suboptimal choice of the analytical tools that are currently being employed, and which only provide part of the picture. In fact, strong evidence largely contradicts the expected behavior on real geometric data. The reason behind this apparent inconsistency lies in the different focus of current methods, which provide crude bounds and are directed toward other kinds of perturbation than those observed in real settings. The ambitious goal of this project is to develop a novel theoretical and computational framework that will fundamentally change the way spectral techniques are constructed, interpreted, and applied. These tools will enable a range of currently infeasible uses of spectral methods on real data. They will deal with strong incompleteness, corruption and cross-modality, and they will be applied to outstanding problems in geometry processing, computer vision, machine learning, and computational biology.

Mots-clés : spectral geometry,shape analysis
Projet ERC : BRAINGAIT (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Board of the Swiss Federal Institutes of Technology — Pays : Suisse — Rôle : PI
Acronyme de l'entité : ETH Zurich
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Spinal cord injury (SCI) leads to severe motor impairments that significantly alter the quality of life of affected people and incur substantial cost for families and society. The ideas developed within the framework of our ERC starting and Consolidator grants led to the development of neurotechnologies that restored walking in paralyzed individuals. This treatment involves the delivery of targeted electrical spinal cord stimulation protocols that reactivate the spinal cord below the injury and amplify the residual commands from the brain. Crucial to the recovery of voluntary movements is the temporal coincidence between the location of the stimulation and the residual command from the brain. To achieve a perfect synchronization, we directly linked decoding of motor intention from brain recordings to the modulation of spinal cord stimulation protocols. We validated the therapeutic efficacy of this wireless brain-spine interface in a nonhuman primate model of SCI. Here, we aim to establish the technical and regulatory feasibility of this wireless brain-spine interface in humans, develop additional intellectual property, and prepare the path to the commercialization of this revolutionary neurotechnology.

Mots-clés : spinal cord injury,brain computer interface,electrocorticogram,clinical study
Projet ERC : LOQO-MOTIONS (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
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 : 2264167.0 €

Spins have long been appreciated as versatile tools for studying coherent quantum phenomena in a range of materials and have emerged as powerful components for the development of technologies such as quantum information processors and sensors. Results from the past 5 years have shown that spins can exhibit exceptionally long coherence lifetimes (seconds for the electron spin, hours for the nuclear spin), and can be measured with high fidelity in a single shot and at the single spin level. These achievements provide strong motivation to address what remains an open challenge: how to controllably couple such coherent spins in a scalable manner. This goal is being vigorously pursued by many groups following approaches such as those based on exchange interactions between spins, or coupling spins to optical or microwave photons and measurement-based entanglement. However, each of these approaches carries formidable challenges and a clearly realisable route to a scalable technology is still currently lacking. The aim of LOQO-MOTIONS is to exploit the long coherence times observed in spins of atomic defects in materials and open up a new approach for coupling spins based on dipolar interactions combined with physical motion to achieve local quantum operations. This approach is inspired by a recent blueprint for the implementation of a surface code using donors in silicon, permitting fault-tolerant operation even with the limited positional accuracy of ion implantation. LOQO-MOTIONS assembles a comprehensive set of tools required to explore and exploit physically mobile spins, including: versatile single- donor spin measurement, coupling of donor spins and optically-addressable defect spins, and cryogenic scanning of probe spins over static spins to generate entanglement. In addition to developing a new platform for engineering spin-spin couplings, LOQO-MOTIONS has strong synergies with spin-based magnetometry and nano-scale quantum sensing applications will be explored.
Projet ERC : AGEMEC (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Universität Innsbruck — Pays : Autriche — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499565.0 €

Sporadic Alzheimer’s Disease (AD) accounts for the overwhelming majority of all AD cases and exclusively affects people at old age. However, mechanistic links between aging and AD pathology remain elusive. We recently discovered that in contrast to iPSC models, direct conversion of human fibroblasts into induced neurons (iNs) preserves signatures of aging, and we have started to develop a patient-based iN model system for AD. Our preliminary data suggests that AD iNs show a neuronal but de-differentiated transcriptome signature. In this project, we first combine cellular neuroscience assays and epigenetic landscape profiling to understand how neurons in AD fail to maintain their fully mature differentiated state, which might be key in permitting disease development. Next, using metabolome analysis including mass spec metabolite assessment, we explore a profound metabolic switch in AD iNs that shows surprisingly many aspects of aerobic glycolysis observed also in cancer. While this link might represent an interesting connection between two age-dependent and de-differentiation-associated diseases, it also opens new avenues to harness knowledge from the cancer field to better understand sporadic AD. We further focus on identifying and manipulating key metabolic regulators that appear to malfunction in an age-dependent manner, with the ultimate goal to define potential targets and treatment strategies. Finally, we will focus on early AD mechanisms by extending our model to mild cognitive impairment (MCI) patients. An agnostic transcriptome and epigenetic landscape approach of glutamatergic and serotonergic iNs will help to determine the earliest and probably most treatable disease mechanisms of AD, and to better understand the contribution of neuropsychiatric risk factors. We anticipate that this project will help to illuminate the mechanistic interface of cellular aging and the development of AD, and help to define new strategies for AD.

Mots-clés : alzheimer s disease,human disease modeling
Projet ERC : iEXTRACT (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Bar-Ilan University — Pays : Israël — Rôle : PI
Acronyme de l'entité : BIU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499354.0 €

Staggering amounts of information are stored in natural language documents, rendering them unavailable to data-science techniques. Information Extraction (IE), a subfield of Natural Language Processing (NLP), aims to automate the extraction of structured information from text, yielding datasets that can be queried, analyzed and combined to provide new insights and drive research forward. Despite tremendous progress in NLP, IE systems remain mostly inaccessible to non-NLP-experts who can greatly benefit from them. This stems from the current methods for creating IE systems: the dominant machine-learning (ML) approach requires technical expertise and large amounts of annotated data, and does not provide the user control over the extraction process. The previously dominant rule-based approach unrealistically requires the user to anticipate and deal with the nuances of natural language. I aim to remedy this situation by revisiting rule-based IE in light of advances in NLP and ML. The key idea is to cast IE as a collaborative human-computer effort, in which the user provides domain-specific knowledge, and the system is in charge of solving various domain-independent linguistic complexities, ultimately allowing the user to query unstructured texts via easily structured forms. More specifically, I aim develop: (a) a novel structured representation that abstracts much of the complexity of natural language; (b) algorithms that derive these representations from texts; (c) an accessible rule language to query this representation; (d) AI components that infer the user extraction intents, and based on them promote relevant examples and highlight extraction cases that require special attention. The ultimate goal of this project is to democratize NLP and bring advanced IE capabilities directly to the hands of domain-experts: doctors, lawyers, researchers and scientists, empowering them to process large volumes of data and advance their profession.

Mots-clés : information extraction
Projet ERC : INTERACTION (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Leibniz Association — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LG
Type d'entité : Recherche
Financement ERC de l'entité : 1073577.01 €

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.

Mots-clés : precipitation extremes,clausius clapeyron relation,atmospheric convection,self organization
Projet ERC : pCx4All (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Heidelberg University — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499500.0 €

State-of-the-art strategies for p-block element-based bond activations predominantly rely on the activity of low-valent species (e.g., silylenes). However, during bond activation, those species usually collapse into the deep thermodynamic sinks of their standard oxidation states, precluding any catalytic cycles. The present proposal pCX4All develops new concepts that add unique reactivity to the p-block elements Al, Ga, Si, Ge, Sn and P in their stable oxidation states. This is achieved by the generation of planar anti-van’t Hoff/Le Bel configurations, ligand-element cooperativity, and p-block valence isomerism. All those original features are enabled by calix[4]pyrrole – a well-established ligand for transition metals – which has never been used for p-block elements. Challenging bond activations (e.g. dinitrogen) and catalytic transformations (e.g. water splitting and acceptorless dehydrogenative oxidation of alcohols) are tackled with the most abundant elements of the earth crust (e.g. a square-planar, tetracoordinated silicon(IV) or aluminum(III)). The concepts are supplemented by photo-induced reactivity and extended into the field of dynamic covalent chemistry. An integrated synthetic, spectroscopic and theoretical research approach guides the way from fundamental understanding to the application in catalysis and materials. Importantly, general feasibility was recently provided by the successful isolation of the first square-planar coordinated aluminum(III) anion in our laboratories, including the observation of its exciting reactivity. We believe that these objectives will initiate a renaissance of p-block element chemistry in their standard oxidation states, equipped with exceptional reactivity by strong structural constraint and ligand-element cooperativity.

Mots-clés : p block element chemistry,geometrical constraint
Projet ERC : DYNAMIQS (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1500000.0 €

Statistical mechanics, a century-old theory, is probably one of the most powerful constructions of physics. It predicts that the equilibrium properties of any system composed of a large number of particles depend only on a handful of macroscopic parameters, no matter how the particles interact with each other. But the question of how many-body systems relax towards such equilibrium states remains largely unsolved. This problem is especially acute for quantum systems, which evolve in a much larger mathematical space than the classical space-time and obey non-local equations of motion. Despite the formidable complexity of quantum dynamics, recent theoretical advances have put forward a very simple picture: the dynamics of closed quantum many-body systems would be essentially local, meaning that it would take a finite time for correlations between two distant regions of space to reach their equilibrium value. This locality would be an emergent collective property, similar to spontaneous symmetry breaking, and have its origin in the propagation of quasiparticle excitations. The fact is, however, that only few observations directly confirm this scenario. In particular, the role played by the dimensionality and the interaction range is largely unknown. The concept of this project is to take advantage of the great versatility offered by ultracold atom systems to investigate experimentally the relaxation dynamics in regimes well beyond the boundaries of our current knowledge. We will focus our attention on two-dimensional systems with both short- and long-range interactions, when all previous experiments were bound to one-dimensional systems. The realisation of the project will hinge on the construction on a new-generation quantum gas microscope experiment for strontium gases. Amongst the innovative techniques that we will implement is the electronic state hybridisation with Rydberg states, called Rydberg dressing.
Projet ERC : CriBLaM (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Institut des hautes études scientifiques — Pays : France — Rôle : PI
Acronyme de l'entité : IHÉS
Type d'entité : Recherche
Financement ERC de l'entité : 1301459.31 €

Statistical physics is a theory allowing the derivation of the statistical behavior of macroscopic systems from the description of the interactions of their microscopic constituents. For more than a century, lattice models (i.e. random systems defined on lattices) have been introduced as discrete models describing the phase transition for a large variety of phenomena, ranging from ferroelectrics to lattice gas. In the last decades, our understanding of percolation and the Ising model, two classical exam- ples of lattice models, progressed greatly. Nonetheless, major questions remain open on these two models. The goal of this project is to break new grounds in the understanding of phase transition in statistical physics by using and aggregating in a pioneering way multiple techniques from proba- bility, combinatorics, analysis and integrable systems. In this project, we will focus on three main goals: Objective A Provide a solid mathematical framework for the study of universality for Bernoulli percolation and the Ising model in two dimensions. Objective B Advance in the understanding of the critical behavior of Bernoulli percolation and the Ising model in dimensions larger or equal to 3. Objective C Greatly improve the understanding of planar lattice models obtained by general- izations of percolation and the Ising model, through the design of an innovative mathematical theory of phase transition dedicated to graphical representations of classical lattice models, such as Fortuin-Kasteleyn percolation, Ashkin-Teller models and Loop models. Most of the questions that we propose to tackle are notoriously difficult open problems. We believe that breakthroughs in these fundamental questions would reshape significantly our math- ematical understanding of phase transition.

Mots-clés : statistical physics,phase transition,percolation theory,ising model