Project acronym 1st-principles-discs
Project A First Principles Approach to Accretion Discs
Researcher (PI) Martin Elias Pessah
Host Institution (HI) KOBENHAVNS UNIVERSITET
Call Details Starting Grant (StG), PE9, ERC-2012-StG_20111012
Summary Most celestial bodies, from planets, to stars, to black holes; gain mass during their lives by means of an accretion disc. Understanding the physical processes that determine the rate at which matter accretes and energy is radiated in these discs is vital for unraveling the formation, evolution, and fate of almost every type of object in the Universe. Despite the fact that magnetic fields have been known to be crucial in accretion discs since the early 90’s, the majority of astrophysical questions that depend on the details of how disc accretion proceeds are still being addressed using the “standard” accretion disc model (developed in the early 70’s), where magnetic fields do not play an explicit role. This has prevented us from fully exploring the astrophysical consequences and observational signatures of realistic accretion disc models, leading to a profound disconnect between observations (usually interpreted with the standard paradigm) and modern accretion disc theory and numerical simulations (where magnetic turbulence is crucial). The goal of this proposal is to use several complementary approaches in order to finally move beyond the standard paradigm. This program has two main objectives: 1) Develop the theoretical framework to incorporate magnetic fields, and the ensuing turbulence, into self-consistent accretion disc models, and investigate their observational implications. 2) Investigate transport and radiative processes in collision-less disc regions, where non-thermal radiation originates, by employing a kinetic particle description of the plasma. In order to achieve these goals, we will use, and build upon, state-of-the-art magnetohydrodynamic and particle-in-cell codes in conjunction with theoretical modeling. This framework will make it possible to address fundamental questions on stellar and planet formation, binary systems with a compact object, and supermassive black hole feedback in a way that has no counterpart within the standard paradigm.
Summary
Most celestial bodies, from planets, to stars, to black holes; gain mass during their lives by means of an accretion disc. Understanding the physical processes that determine the rate at which matter accretes and energy is radiated in these discs is vital for unraveling the formation, evolution, and fate of almost every type of object in the Universe. Despite the fact that magnetic fields have been known to be crucial in accretion discs since the early 90’s, the majority of astrophysical questions that depend on the details of how disc accretion proceeds are still being addressed using the “standard” accretion disc model (developed in the early 70’s), where magnetic fields do not play an explicit role. This has prevented us from fully exploring the astrophysical consequences and observational signatures of realistic accretion disc models, leading to a profound disconnect between observations (usually interpreted with the standard paradigm) and modern accretion disc theory and numerical simulations (where magnetic turbulence is crucial). The goal of this proposal is to use several complementary approaches in order to finally move beyond the standard paradigm. This program has two main objectives: 1) Develop the theoretical framework to incorporate magnetic fields, and the ensuing turbulence, into self-consistent accretion disc models, and investigate their observational implications. 2) Investigate transport and radiative processes in collision-less disc regions, where non-thermal radiation originates, by employing a kinetic particle description of the plasma. In order to achieve these goals, we will use, and build upon, state-of-the-art magnetohydrodynamic and particle-in-cell codes in conjunction with theoretical modeling. This framework will make it possible to address fundamental questions on stellar and planet formation, binary systems with a compact object, and supermassive black hole feedback in a way that has no counterpart within the standard paradigm.
Max ERC Funding
1 793 697 €
Duration
Start date: 2013-02-01, End date: 2018-01-31
Project acronym 2STEPPARKIN
Project A novel two-step model for neurodegeneration in Parkinson’s disease
Researcher (PI) Emi Nagoshi
Host Institution (HI) UNIVERSITE DE GENEVE
Call Details Starting Grant (StG), LS5, ERC-2012-StG_20111109
Summary Parkinson’s disease (PD) is the second most common neurodegenerative disorder primarily caused by the progressive loss of dopaminergic (DA) neurons in the substantia nigra (SN). Despite the advances in gene discovery associated with PD, the knowledge of the PD pathogenesis is largely limited to the involvement of these genes in the generic cell death pathways, and why degeneration is specific to DA neurons and why the degeneration is progressive remain enigmatic. Broad goal of our work is therefore to elucidate the mechanisms underlying specific and progressive DA neuron degeneration in PD. Our new Drosophila model of PD ⎯Fer2 gene loss-of-function mutation⎯ is unusually well suited to address these questions. Fer2 mutants exhibit specific and progressive death of brain DA neurons as well as severe locomotor defects and short life span. Strikingly, the death of DA neuron is initiated in a small cluster of Fer2-expressing DA neurons and subsequently propagates to Fer2-negative DA neurons. We therefore propose a novel two-step model of the neurodegeneration in PD: primary cell death occurs in a specific subset of dopamindegic neurons that are genetically defined, and subsequently the failure of the neuronal connectivity triggers and propagates secondary cell death to remaining DA neurons. In this research, we will test this hypothesis and investigate the underlying molecular mechanisms. This will be the first study to examine circuit-dependency in DA neuron degeneration. Our approach will use a combination of non-biased genomic techniques and candidate-based screening, in addition to the powerful Drosophila genetic toolbox. Furthermore, to test this hypothesis beyond the Drosophila model, we will establish new mouse models of PD that exhibit progressive DA neuron degeneration. Outcome of this research will likely revolutionize the understanding of PD pathogenesis and open an avenue toward the discovery of effective therapy strategies against PD.
Summary
Parkinson’s disease (PD) is the second most common neurodegenerative disorder primarily caused by the progressive loss of dopaminergic (DA) neurons in the substantia nigra (SN). Despite the advances in gene discovery associated with PD, the knowledge of the PD pathogenesis is largely limited to the involvement of these genes in the generic cell death pathways, and why degeneration is specific to DA neurons and why the degeneration is progressive remain enigmatic. Broad goal of our work is therefore to elucidate the mechanisms underlying specific and progressive DA neuron degeneration in PD. Our new Drosophila model of PD ⎯Fer2 gene loss-of-function mutation⎯ is unusually well suited to address these questions. Fer2 mutants exhibit specific and progressive death of brain DA neurons as well as severe locomotor defects and short life span. Strikingly, the death of DA neuron is initiated in a small cluster of Fer2-expressing DA neurons and subsequently propagates to Fer2-negative DA neurons. We therefore propose a novel two-step model of the neurodegeneration in PD: primary cell death occurs in a specific subset of dopamindegic neurons that are genetically defined, and subsequently the failure of the neuronal connectivity triggers and propagates secondary cell death to remaining DA neurons. In this research, we will test this hypothesis and investigate the underlying molecular mechanisms. This will be the first study to examine circuit-dependency in DA neuron degeneration. Our approach will use a combination of non-biased genomic techniques and candidate-based screening, in addition to the powerful Drosophila genetic toolbox. Furthermore, to test this hypothesis beyond the Drosophila model, we will establish new mouse models of PD that exhibit progressive DA neuron degeneration. Outcome of this research will likely revolutionize the understanding of PD pathogenesis and open an avenue toward the discovery of effective therapy strategies against PD.
Max ERC Funding
1 518 960 €
Duration
Start date: 2013-06-01, End date: 2018-05-31
Project acronym 3DICE
Project 3D Interstellar Chemo-physical Evolution
Researcher (PI) Valentine Wakelam
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Starting Grant (StG), PE9, ERC-2013-StG
Summary At the end of their life, stars spread their inner material into the diffuse interstellar medium. This diffuse medium gets locally denser and form dark clouds (also called dense or molecular clouds) whose innermost part is shielded from the external UV field by the dust, allowing for molecules to grow and get more complex. Gravitational collapse occurs inside these dense clouds, forming protostars and their surrounding disks, and eventually planetary systems like (or unlike) our solar system. The formation and evolution of molecules, minerals, ices and organics from the diffuse medium to planetary bodies, their alteration or preservation throughout this cosmic chemical history set the initial conditions for building planets, atmospheres and possibly the first bricks of life. The current view of interstellar chemistry is based on fragmental works on key steps of the sequence that are observed. The objective of this proposal is to follow the fractionation of the elements between the gas-phase and the interstellar grains, from the most diffuse medium to protoplanetary disks, in order to constrain the chemical composition of the material in which planets are formed. The potential outcome of this project is to get a consistent and more accurate description of the chemical evolution of interstellar matter. To achieve this objective, I will improve our chemical model by adding new processes on grain surfaces relevant under the diffuse medium conditions. This upgraded gas-grain model will be coupled to 3D dynamical models of the formation of dense clouds from diffuse medium and of protoplanetary disks from dense clouds. The computed chemical composition will also be used with 3D radiative transfer codes to study the chemical tracers of the physics of protoplanetary disk formation. The robustness of the model predictions will be studied with sensitivity analyses. Finally, model results will be confronted to observations to address some of the current challenges.
Summary
At the end of their life, stars spread their inner material into the diffuse interstellar medium. This diffuse medium gets locally denser and form dark clouds (also called dense or molecular clouds) whose innermost part is shielded from the external UV field by the dust, allowing for molecules to grow and get more complex. Gravitational collapse occurs inside these dense clouds, forming protostars and their surrounding disks, and eventually planetary systems like (or unlike) our solar system. The formation and evolution of molecules, minerals, ices and organics from the diffuse medium to planetary bodies, their alteration or preservation throughout this cosmic chemical history set the initial conditions for building planets, atmospheres and possibly the first bricks of life. The current view of interstellar chemistry is based on fragmental works on key steps of the sequence that are observed. The objective of this proposal is to follow the fractionation of the elements between the gas-phase and the interstellar grains, from the most diffuse medium to protoplanetary disks, in order to constrain the chemical composition of the material in which planets are formed. The potential outcome of this project is to get a consistent and more accurate description of the chemical evolution of interstellar matter. To achieve this objective, I will improve our chemical model by adding new processes on grain surfaces relevant under the diffuse medium conditions. This upgraded gas-grain model will be coupled to 3D dynamical models of the formation of dense clouds from diffuse medium and of protoplanetary disks from dense clouds. The computed chemical composition will also be used with 3D radiative transfer codes to study the chemical tracers of the physics of protoplanetary disk formation. The robustness of the model predictions will be studied with sensitivity analyses. Finally, model results will be confronted to observations to address some of the current challenges.
Max ERC Funding
1 166 231 €
Duration
Start date: 2013-09-01, End date: 2018-08-31
Project acronym A-BINGOS
Project Accreting binary populations in Nearby Galaxies: Observations and Simulations
Researcher (PI) Andreas Zezas
Host Institution (HI) IDRYMA TECHNOLOGIAS KAI EREVNAS
Call Details Consolidator Grant (CoG), PE9, ERC-2013-CoG
Summary "High-energy observations of our Galaxy offer a good, albeit not complete, picture of the X-ray source populations, in particular the accreting binary sources. Recent ability to study accreting binaries in nearby galaxies has shown that we would be short-sighted if we restricted ourselves to our Galaxy or to a few nearby ones. I propose an ambitious project that involves a comprehensive study of all the galaxies within 10 Mpc for which we can study in detail their X-ray sources and stellar populations. The study will combine data from a unique suite of observatories (Chandra, XMM-Newton, HST, Spitzer) with state-of-the-art theoretical modelling of binary systems. I propose a novel approach that links the accreting binary populations to their parent stellar populations and surpasses any current studies of X-ray binary populations, both in scale and in scope, by: (a) combining methods and results from several different areas of astrophysics (compact objects, binary systems, stellar populations, galaxy evolution); (b) using data from almost the whole electromagnetic spectrum (infrared to X-ray bands); (c) identifying and studying the different sub-populations of accreting binaries; and (d) performing direct comparison between observations and theoretical predictions, over a broad parameter space. The project: (a) will answer the long-standing question of the formation efficiency of accreting binaries in different environments; and (b) will constrain their evolutionary paths. As by-products the project will provide eagerly awaited input to the fields of gravitational-wave sources, γ-ray bursts, and X-ray emitting galaxies at cosmological distances and it will produce a heritage multi-wavelength dataset and library of models for future studies of galaxies and accreting binaries."
Summary
"High-energy observations of our Galaxy offer a good, albeit not complete, picture of the X-ray source populations, in particular the accreting binary sources. Recent ability to study accreting binaries in nearby galaxies has shown that we would be short-sighted if we restricted ourselves to our Galaxy or to a few nearby ones. I propose an ambitious project that involves a comprehensive study of all the galaxies within 10 Mpc for which we can study in detail their X-ray sources and stellar populations. The study will combine data from a unique suite of observatories (Chandra, XMM-Newton, HST, Spitzer) with state-of-the-art theoretical modelling of binary systems. I propose a novel approach that links the accreting binary populations to their parent stellar populations and surpasses any current studies of X-ray binary populations, both in scale and in scope, by: (a) combining methods and results from several different areas of astrophysics (compact objects, binary systems, stellar populations, galaxy evolution); (b) using data from almost the whole electromagnetic spectrum (infrared to X-ray bands); (c) identifying and studying the different sub-populations of accreting binaries; and (d) performing direct comparison between observations and theoretical predictions, over a broad parameter space. The project: (a) will answer the long-standing question of the formation efficiency of accreting binaries in different environments; and (b) will constrain their evolutionary paths. As by-products the project will provide eagerly awaited input to the fields of gravitational-wave sources, γ-ray bursts, and X-ray emitting galaxies at cosmological distances and it will produce a heritage multi-wavelength dataset and library of models for future studies of galaxies and accreting binaries."
Max ERC Funding
1 242 000 €
Duration
Start date: 2014-04-01, End date: 2019-03-31
Project acronym ACDC
Project Algorithms and Complexity of Highly Decentralized Computations
Researcher (PI) Fabian Daniel Kuhn
Host Institution (HI) ALBERT-LUDWIGS-UNIVERSITAET FREIBURG
Call Details Starting Grant (StG), PE6, ERC-2013-StG
Summary "Many of today's and tomorrow's computer systems are built on top of large-scale networks such as, e.g., the Internet, the world wide web, wireless ad hoc and sensor networks, or peer-to-peer networks. Driven by technological advances, new kinds of networks and applications have become possible and we can safely assume that this trend is going to continue. Often modern systems are envisioned to consist of a potentially large number of individual components that are organized in a completely decentralized way. There is no central authority that controls the topology of the network, how nodes join or leave the system, or in which way nodes communicate with each other. Also, many future distributed applications will be built using wireless devices that communicate via radio.
The general objective of the proposed project is to improve our understanding of the algorithmic and theoretical foundations of decentralized distributed systems. From an algorithmic point of view, decentralized networks and computations pose a number of fascinating and unique challenges that are not present in sequential or more standard distributed systems. As communication is limited and mostly between nearby nodes, each node of a large network can only maintain a very restricted view of the global state of the system. This is particularly true if the network can change dynamically, either by nodes joining or leaving the system or if the topology changes over time, e.g., because of the mobility of the devices in case of a wireless network. Nevertheless, the nodes of a network need to coordinate in order to achieve some global goal.
In particular, we plan to study algorithms and lower bounds for basic computation and information dissemination tasks in such systems. In addition, we are particularly interested in the complexity of distributed computations in dynamic and wireless networks."
Summary
"Many of today's and tomorrow's computer systems are built on top of large-scale networks such as, e.g., the Internet, the world wide web, wireless ad hoc and sensor networks, or peer-to-peer networks. Driven by technological advances, new kinds of networks and applications have become possible and we can safely assume that this trend is going to continue. Often modern systems are envisioned to consist of a potentially large number of individual components that are organized in a completely decentralized way. There is no central authority that controls the topology of the network, how nodes join or leave the system, or in which way nodes communicate with each other. Also, many future distributed applications will be built using wireless devices that communicate via radio.
The general objective of the proposed project is to improve our understanding of the algorithmic and theoretical foundations of decentralized distributed systems. From an algorithmic point of view, decentralized networks and computations pose a number of fascinating and unique challenges that are not present in sequential or more standard distributed systems. As communication is limited and mostly between nearby nodes, each node of a large network can only maintain a very restricted view of the global state of the system. This is particularly true if the network can change dynamically, either by nodes joining or leaving the system or if the topology changes over time, e.g., because of the mobility of the devices in case of a wireless network. Nevertheless, the nodes of a network need to coordinate in order to achieve some global goal.
In particular, we plan to study algorithms and lower bounds for basic computation and information dissemination tasks in such systems. In addition, we are particularly interested in the complexity of distributed computations in dynamic and wireless networks."
Max ERC Funding
1 148 000 €
Duration
Start date: 2013-11-01, End date: 2018-10-31
Project acronym ACROSS
Project 3D Reconstruction and Modeling across Different Levels of Abstraction
Researcher (PI) Leif Kobbelt
Host Institution (HI) RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN
Call Details Advanced Grant (AdG), PE6, ERC-2013-ADG
Summary "Digital 3D models are gaining more and more importance in diverse application fields ranging from computer graphics, multimedia and simulation sciences to engineering, architecture, and medicine. Powerful technologies to digitize the 3D shape of real objects and scenes are becoming available even to consumers. However, the raw geometric data emerging from, e.g., 3D scanning or multi-view stereo often lacks a consistent structure and meta-information which are necessary for the effective deployment of such models in sophisticated down-stream applications like animation, simulation, or CAD/CAM that go beyond mere visualization. Our goal is to develop new fundamental algorithms which transform raw geometric input data into augmented 3D models that are equipped with structural meta information such as feature aligned meshes, patch segmentations, local and global geometric constraints, statistical shape variation data, or even procedural descriptions. Our methodological approach is inspired by the human perceptual system that integrates bottom-up (data-driven) and top-down (model-driven) mechanisms in its hierarchical processing. Similarly we combine algorithms operating on different levels of abstraction into reconstruction and modeling networks. Instead of developing an individual solution for each specific application scenario, we create an eco-system of algorithms for automatic processing and interactive design of highly complex 3D models. A key concept is the information flow across all levels of abstraction in a bottom-up as well as top-down fashion. We not only aim at optimizing geometric representations but in fact at bridging the gap between reconstruction and recognition of geometric objects. The results from this project will make it possible to bring 3D models of real world objects into many highly relevant applications in science, industry, and entertainment, greatly reducing the excessive manual effort that is still necessary today."
Summary
"Digital 3D models are gaining more and more importance in diverse application fields ranging from computer graphics, multimedia and simulation sciences to engineering, architecture, and medicine. Powerful technologies to digitize the 3D shape of real objects and scenes are becoming available even to consumers. However, the raw geometric data emerging from, e.g., 3D scanning or multi-view stereo often lacks a consistent structure and meta-information which are necessary for the effective deployment of such models in sophisticated down-stream applications like animation, simulation, or CAD/CAM that go beyond mere visualization. Our goal is to develop new fundamental algorithms which transform raw geometric input data into augmented 3D models that are equipped with structural meta information such as feature aligned meshes, patch segmentations, local and global geometric constraints, statistical shape variation data, or even procedural descriptions. Our methodological approach is inspired by the human perceptual system that integrates bottom-up (data-driven) and top-down (model-driven) mechanisms in its hierarchical processing. Similarly we combine algorithms operating on different levels of abstraction into reconstruction and modeling networks. Instead of developing an individual solution for each specific application scenario, we create an eco-system of algorithms for automatic processing and interactive design of highly complex 3D models. A key concept is the information flow across all levels of abstraction in a bottom-up as well as top-down fashion. We not only aim at optimizing geometric representations but in fact at bridging the gap between reconstruction and recognition of geometric objects. The results from this project will make it possible to bring 3D models of real world objects into many highly relevant applications in science, industry, and entertainment, greatly reducing the excessive manual effort that is still necessary today."
Max ERC Funding
2 482 000 €
Duration
Start date: 2014-03-01, End date: 2019-02-28
Project acronym ACTIVIA
Project Visual Recognition of Function and Intention
Researcher (PI) Ivan Laptev
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Call Details Starting Grant (StG), PE6, ERC-2012-StG_20111012
Summary "Computer vision is concerned with the automated interpretation of images and video streams. Today's research is (mostly) aimed at answering queries such as ""Is this a picture of a dog?"", (classification) or sometimes ""Find the dog in this photo"" (detection). While categorisation and detection are useful for many tasks, inferring correct class labels is not the final answer to visual recognition. The categories and locations of objects do not provide direct understanding of their function i.e., how things work, what they can be used for, or how they can act and react. Such an understanding, however, would be highly desirable to answer currently unsolvable queries such as ""Am I in danger?"" or ""What can happen in this scene?"". Solving such queries is the aim of this proposal.
My goal is to uncover the functional properties of objects and the purpose of actions by addressing visual recognition from a different and yet unexplored perspective. The main novelty of this proposal is to leverage observations of people, i.e., their actions and interactions to automatically learn the use, the purpose and the function of objects and scenes from visual data. The project is timely as it builds upon the two key recent technological advances: (a) the immense progress in visual recognition of objects, scenes and human actions achieved in the last ten years, as well as (b) the emergence of a massive amount of public image and video data now available to train visual models.
ACTIVIA addresses fundamental research issues in automated interpretation of dynamic visual scenes, but its results are expected to serve as a basis for ground-breaking technological advances in practical applications. The recognition of functional properties and intentions as explored in this project will directly support high-impact applications such as detection of abnormal events, which are likely to revolutionise today's approaches to crime protection, hazard prevention, elderly care, and many others."
Summary
"Computer vision is concerned with the automated interpretation of images and video streams. Today's research is (mostly) aimed at answering queries such as ""Is this a picture of a dog?"", (classification) or sometimes ""Find the dog in this photo"" (detection). While categorisation and detection are useful for many tasks, inferring correct class labels is not the final answer to visual recognition. The categories and locations of objects do not provide direct understanding of their function i.e., how things work, what they can be used for, or how they can act and react. Such an understanding, however, would be highly desirable to answer currently unsolvable queries such as ""Am I in danger?"" or ""What can happen in this scene?"". Solving such queries is the aim of this proposal.
My goal is to uncover the functional properties of objects and the purpose of actions by addressing visual recognition from a different and yet unexplored perspective. The main novelty of this proposal is to leverage observations of people, i.e., their actions and interactions to automatically learn the use, the purpose and the function of objects and scenes from visual data. The project is timely as it builds upon the two key recent technological advances: (a) the immense progress in visual recognition of objects, scenes and human actions achieved in the last ten years, as well as (b) the emergence of a massive amount of public image and video data now available to train visual models.
ACTIVIA addresses fundamental research issues in automated interpretation of dynamic visual scenes, but its results are expected to serve as a basis for ground-breaking technological advances in practical applications. The recognition of functional properties and intentions as explored in this project will directly support high-impact applications such as detection of abnormal events, which are likely to revolutionise today's approaches to crime protection, hazard prevention, elderly care, and many others."
Max ERC Funding
1 497 420 €
Duration
Start date: 2013-01-01, End date: 2018-12-31
Project acronym ACUITY
Project Algorithms for coping with uncertainty and intractability
Researcher (PI) Nikhil Bansal
Host Institution (HI) TECHNISCHE UNIVERSITEIT EINDHOVEN
Call Details Consolidator Grant (CoG), PE6, ERC-2013-CoG
Summary The two biggest challenges in solving practical optimization problems are computational intractability, and the presence
of uncertainty: most problems are either NP-hard, or have incomplete input data which
makes an exact computation impossible.
Recently, there has been a huge progress in our understanding of intractability, based on spectacular algorithmic and lower bound techniques. For several problems, especially those with only local constraints, we can design optimum
approximation algorithms that are provably the best possible.
However, typical optimization problems usually involve complex global constraints and are much less understood. The situation is even worse for coping with uncertainty. Most of the algorithms are based on ad-hoc techniques and there is no deeper understanding of what makes various problems easy or hard.
This proposal describes several new directions, together with concrete intermediate goals, that will break important new ground in the theory of approximation and online algorithms. The particular directions we consider are (i) extend the primal dual method to systematically design online algorithms, (ii) build a structural theory of online problems based on work functions, (iii) develop new tools to use the power of strong convex relaxations and (iv) design new algorithmic approaches based on non-constructive proof techniques.
The proposed research is at the
cutting edge of algorithm design, and builds upon the recent success of the PI in resolving several longstanding questions in these areas. Any progress is likely to be a significant contribution to theoretical
computer science and combinatorial optimization.
Summary
The two biggest challenges in solving practical optimization problems are computational intractability, and the presence
of uncertainty: most problems are either NP-hard, or have incomplete input data which
makes an exact computation impossible.
Recently, there has been a huge progress in our understanding of intractability, based on spectacular algorithmic and lower bound techniques. For several problems, especially those with only local constraints, we can design optimum
approximation algorithms that are provably the best possible.
However, typical optimization problems usually involve complex global constraints and are much less understood. The situation is even worse for coping with uncertainty. Most of the algorithms are based on ad-hoc techniques and there is no deeper understanding of what makes various problems easy or hard.
This proposal describes several new directions, together with concrete intermediate goals, that will break important new ground in the theory of approximation and online algorithms. The particular directions we consider are (i) extend the primal dual method to systematically design online algorithms, (ii) build a structural theory of online problems based on work functions, (iii) develop new tools to use the power of strong convex relaxations and (iv) design new algorithmic approaches based on non-constructive proof techniques.
The proposed research is at the
cutting edge of algorithm design, and builds upon the recent success of the PI in resolving several longstanding questions in these areas. Any progress is likely to be a significant contribution to theoretical
computer science and combinatorial optimization.
Max ERC Funding
1 519 285 €
Duration
Start date: 2014-05-01, End date: 2019-04-30
Project acronym ADAPT
Project Theory and Algorithms for Adaptive Particle Simulation
Researcher (PI) Stephane Redon
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Call Details Starting Grant (StG), PE6, ERC-2012-StG_20111012
Summary "During the twentieth century, the development of macroscopic engineering has been largely stimulated by progress in digital prototyping: cars, planes, boats, etc. are nowadays designed and tested on computers. Digital prototypes have progressively replaced actual ones, and effective computer-aided engineering tools have helped cut costs and reduce production cycles of these macroscopic systems.
The twenty-first century is most likely to see a similar development at the atomic scale. Indeed, the recent years have seen tremendous progress in nanotechnology - in particular in the ability to control matter at the atomic scale. Similar to what has happened with macroscopic engineering, powerful and generic computational tools will be needed to engineer complex nanosystems, through modeling and simulation. As a result, a major challenge is to develop efficient simulation methods and algorithms.
NANO-D, the INRIA research group I started in January 2008 in Grenoble, France, aims at developing
efficient computational methods for modeling and simulating complex nanosystems, both natural and artificial. In particular, NANO-D develops SAMSON, a software application which gathers all algorithms designed by the group and its collaborators (SAMSON: Software for Adaptive Modeling and Simulation Of Nanosystems).
In this project, I propose to develop a unified theory, and associated algorithms, for adaptive particle simulation. The proposed theory will avoid problems that plague current popular multi-scale or hybrid simulation approaches by simulating a single potential throughout the system, while allowing users to finely trade precision for computational speed.
I believe the full development of the adaptive particle simulation theory will have an important impact on current modeling and simulation practices, and will enable practical design of complex nanosystems on desktop computers, which should significantly boost the emergence of generic nano-engineering."
Summary
"During the twentieth century, the development of macroscopic engineering has been largely stimulated by progress in digital prototyping: cars, planes, boats, etc. are nowadays designed and tested on computers. Digital prototypes have progressively replaced actual ones, and effective computer-aided engineering tools have helped cut costs and reduce production cycles of these macroscopic systems.
The twenty-first century is most likely to see a similar development at the atomic scale. Indeed, the recent years have seen tremendous progress in nanotechnology - in particular in the ability to control matter at the atomic scale. Similar to what has happened with macroscopic engineering, powerful and generic computational tools will be needed to engineer complex nanosystems, through modeling and simulation. As a result, a major challenge is to develop efficient simulation methods and algorithms.
NANO-D, the INRIA research group I started in January 2008 in Grenoble, France, aims at developing
efficient computational methods for modeling and simulating complex nanosystems, both natural and artificial. In particular, NANO-D develops SAMSON, a software application which gathers all algorithms designed by the group and its collaborators (SAMSON: Software for Adaptive Modeling and Simulation Of Nanosystems).
In this project, I propose to develop a unified theory, and associated algorithms, for adaptive particle simulation. The proposed theory will avoid problems that plague current popular multi-scale or hybrid simulation approaches by simulating a single potential throughout the system, while allowing users to finely trade precision for computational speed.
I believe the full development of the adaptive particle simulation theory will have an important impact on current modeling and simulation practices, and will enable practical design of complex nanosystems on desktop computers, which should significantly boost the emergence of generic nano-engineering."
Max ERC Funding
1 476 882 €
Duration
Start date: 2012-09-01, End date: 2017-08-31
Project acronym ADOS
Project AMPA Receptor Dynamic Organization and Synaptic transmission in health and disease
Researcher (PI) Daniel Georges Gustave Choquet
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Advanced Grant (AdG), LS5, ERC-2013-ADG
Summary AMPA glutamate receptors (AMPAR) play key roles in information processing by the brain as they mediate nearly all fast excitatory synaptic transmission. Their spatio-temporal organization in the post synapse with respect to presynaptic glutamate release sites is a key determinant in synaptic transmission. The activity-dependent regulation of AMPAR organization is at the heart of synaptic plasticity processes underlying learning and memory. Dysfunction of synaptic transmission - hence AMPAR organization - is likely at the origin of a number of brain diseases.
Building on discoveries made during my past ERC grant, our new ground-breaking objective is to uncover the mechanisms that link synaptic transmission with the dynamic organization of AMPAR and associated proteins. For this aim, we have assembled a team of neurobiologists, computer scientists and chemists with a track record of collaboration. We will combine physiology, cellular and molecular neurobiology with development of novel quantitative imaging and biomolecular tools to probe the molecular dynamics that regulate synaptic transmission.
Live high content 3D SuperResolution Light Imaging (SRLI) combined with electron microscopy will allow unprecedented visualization of AMPAR organization in synapses at the scale of individual subunits up to the level of intact tissue. Simultaneous SRLI and electrophysiology will elucidate the intricate relations between dynamic AMPAR organization, trafficking and synaptic transmission. Novel peptide- and small protein-based probes used as protein-protein interaction reporters and modulators will be developed to image and directly interfere with synapse organization.
We will identify new processes that are fundamental to activity dependent modifications of synaptic transmission. We will apply the above findings to understand the causes of early cognitive deficits in models of neurodegenerative disorders and open new avenues of research for innovative therapies.
Summary
AMPA glutamate receptors (AMPAR) play key roles in information processing by the brain as they mediate nearly all fast excitatory synaptic transmission. Their spatio-temporal organization in the post synapse with respect to presynaptic glutamate release sites is a key determinant in synaptic transmission. The activity-dependent regulation of AMPAR organization is at the heart of synaptic plasticity processes underlying learning and memory. Dysfunction of synaptic transmission - hence AMPAR organization - is likely at the origin of a number of brain diseases.
Building on discoveries made during my past ERC grant, our new ground-breaking objective is to uncover the mechanisms that link synaptic transmission with the dynamic organization of AMPAR and associated proteins. For this aim, we have assembled a team of neurobiologists, computer scientists and chemists with a track record of collaboration. We will combine physiology, cellular and molecular neurobiology with development of novel quantitative imaging and biomolecular tools to probe the molecular dynamics that regulate synaptic transmission.
Live high content 3D SuperResolution Light Imaging (SRLI) combined with electron microscopy will allow unprecedented visualization of AMPAR organization in synapses at the scale of individual subunits up to the level of intact tissue. Simultaneous SRLI and electrophysiology will elucidate the intricate relations between dynamic AMPAR organization, trafficking and synaptic transmission. Novel peptide- and small protein-based probes used as protein-protein interaction reporters and modulators will be developed to image and directly interfere with synapse organization.
We will identify new processes that are fundamental to activity dependent modifications of synaptic transmission. We will apply the above findings to understand the causes of early cognitive deficits in models of neurodegenerative disorders and open new avenues of research for innovative therapies.
Max ERC Funding
2 491 157 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
