Project acronym 2DNanoSpec
Project Nanoscale Vibrational Spectroscopy of Sensitive 2D Molecular Materials
Researcher (PI) Renato ZENOBI
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Advanced Grant (AdG), PE4, ERC-2016-ADG
Summary I propose to investigate the nanometer scale organization of delicate 2-dimensional molecular materials using nanoscale vibrational spectroscopy. 2D structures are of great scientific and technological importance, for example as novel materials (graphene, MoS2, WS2, etc.), and in the form of biological membranes and synthetic 2D-polymers. Powerful methods for their analysis and imaging with molecular selectivity and sufficient spatial resolution, however, are lacking. Tip-enhanced Raman spectroscopy (TERS) allows label-free spectroscopic identification of molecular species, with ≈10 nm spatial resolution, and with single molecule sensitivity for strong Raman scatterers. So far, however, TERS is not being carried out in liquids, which is the natural environment for membranes, and its application to poor Raman scatterers such as components of 2D polymers, lipids, or other membrane compounds (proteins, sugars) is difficult. TERS has the potential to overcome the restrictions of other optical/spectroscopic methods to study 2D materials, namely (i) insufficient spatial resolution of diffraction-limited optical methods; (ii) the need for labelling for all methods relying on fluorescence; and (iii) the inability of some methods to work in liquids. I propose to address a number of scientific questions associated with the spatial organization, and the occurrence of defects in sensitive 2D molecular materials. The success of these studies will also rely critically on technical innovations of TERS that notably address the problem of energy dissipation. This will for the first time allow its application to study of complex, delicate 2D molecular systems without photochemical damage.
Summary
I propose to investigate the nanometer scale organization of delicate 2-dimensional molecular materials using nanoscale vibrational spectroscopy. 2D structures are of great scientific and technological importance, for example as novel materials (graphene, MoS2, WS2, etc.), and in the form of biological membranes and synthetic 2D-polymers. Powerful methods for their analysis and imaging with molecular selectivity and sufficient spatial resolution, however, are lacking. Tip-enhanced Raman spectroscopy (TERS) allows label-free spectroscopic identification of molecular species, with ≈10 nm spatial resolution, and with single molecule sensitivity for strong Raman scatterers. So far, however, TERS is not being carried out in liquids, which is the natural environment for membranes, and its application to poor Raman scatterers such as components of 2D polymers, lipids, or other membrane compounds (proteins, sugars) is difficult. TERS has the potential to overcome the restrictions of other optical/spectroscopic methods to study 2D materials, namely (i) insufficient spatial resolution of diffraction-limited optical methods; (ii) the need for labelling for all methods relying on fluorescence; and (iii) the inability of some methods to work in liquids. I propose to address a number of scientific questions associated with the spatial organization, and the occurrence of defects in sensitive 2D molecular materials. The success of these studies will also rely critically on technical innovations of TERS that notably address the problem of energy dissipation. This will for the first time allow its application to study of complex, delicate 2D molecular systems without photochemical damage.
Max ERC Funding
2 311 696 €
Duration
Start date: 2017-09-01, End date: 2022-08-31
Project acronym 4DVIDEO
Project 4DVideo: 4D spatio-temporal modeling of real-world events from video streams
Researcher (PI) Marc Pollefeys
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Starting Grant (StG), PE5, ERC-2007-StG
Summary The focus of this project is the development of algorithms that allow one to capture and analyse dynamic events taking place in the real world. For this, we intend to develop smart camera networks that can perform a multitude of observation tasks, ranging from surveillance and tracking to high-fidelity, immersive reconstructions of important dynamic events (i.e. 4D videos). There are many fundamental questions in computer vision associated with these problems. Can the geometric, topologic and photometric properties of the camera network be obtained from live images? What is changing about the environment in which the network is embedded? How much information can be obtained from dynamic events that are observed by the network? What if the camera network consists of a random collection of sensors that happened to observe a particular event (think hand-held cell phone cameras)? Do we need synchronization? Those questions become even more challenging if one considers active camera networks that can adapt to the vision task at hand. How should resources be prioritized for different tasks? Can we derive optimal strategies to control camera parameters such as pan, tilt and zoom, trade-off resolution, frame-rate and bandwidth? More fundamentally, seeing cameras as points that sample incoming light rays and camera networks as a distributed sensor, how does one decide which rays should be sampled? Many of those issues are particularly interesting when we consider time-varying events. Both spatial and temporal resolution are important and heterogeneous frame-rates and resolution can offer advantages. Prior knowledge or information obtained from earlier samples can be used to restrict the possible range of solutions (e.g. smoothness assumption and motion prediction). My goal is to obtain fundamental answers to many of those question based on thorough theoretical analysis combined with practical algorithms that are proven on real applications.
Summary
The focus of this project is the development of algorithms that allow one to capture and analyse dynamic events taking place in the real world. For this, we intend to develop smart camera networks that can perform a multitude of observation tasks, ranging from surveillance and tracking to high-fidelity, immersive reconstructions of important dynamic events (i.e. 4D videos). There are many fundamental questions in computer vision associated with these problems. Can the geometric, topologic and photometric properties of the camera network be obtained from live images? What is changing about the environment in which the network is embedded? How much information can be obtained from dynamic events that are observed by the network? What if the camera network consists of a random collection of sensors that happened to observe a particular event (think hand-held cell phone cameras)? Do we need synchronization? Those questions become even more challenging if one considers active camera networks that can adapt to the vision task at hand. How should resources be prioritized for different tasks? Can we derive optimal strategies to control camera parameters such as pan, tilt and zoom, trade-off resolution, frame-rate and bandwidth? More fundamentally, seeing cameras as points that sample incoming light rays and camera networks as a distributed sensor, how does one decide which rays should be sampled? Many of those issues are particularly interesting when we consider time-varying events. Both spatial and temporal resolution are important and heterogeneous frame-rates and resolution can offer advantages. Prior knowledge or information obtained from earlier samples can be used to restrict the possible range of solutions (e.g. smoothness assumption and motion prediction). My goal is to obtain fundamental answers to many of those question based on thorough theoretical analysis combined with practical algorithms that are proven on real applications.
Max ERC Funding
1 757 422 €
Duration
Start date: 2008-08-01, End date: 2013-11-30
Project acronym ACCELERATES
Project Acceleration in Extreme Shocks: from the microphysics to laboratory and astrophysics scenarios
Researcher (PI) Luis Miguel De Oliveira E Silva
Host Institution (HI) INSTITUTO SUPERIOR TECNICO
Call Details Advanced Grant (AdG), PE2, ERC-2010-AdG_20100224
Summary What is the origin of cosmic rays, what are the dominant acceleration mechanisms in relativistic shocks, how do cosmic rays self-consistently influence the shock dynamics, how are relativistic collisionless shocks formed are longstanding scientific questions, closely tied to extreme plasma physics processes, and where a close interplay between the micro-instabilities and the global dynamics is critical.
Relativistic shocks are closely connected with the propagation of intense streams of particles pervasive in many astrophysical scenarios. The possibility of exciting shocks in the laboratory will also be available very soon with multi-PW lasers or intense relativistic particle beams.
Computational modeling is now established as a prominent research tool, by enabling the fully kinetic modeling of these systems for the first time. With the fast paced developments in high performance computing, the time is ripe for a focused research programme on simulation-based studies of relativistic shocks. This proposal therefore focuses on using self-consistent ab initio massively parallel simulations to study the physics of relativistic shocks, bridging the gap between the multidimensional microphysics of shock onset, formation, and propagation and the global system dynamics. Particular focus will be given to the shock acceleration mechanisms and the radiation signatures of the various physical processes, with the goal of solving some of the central questions in plasma/relativistic phenomena in astrophysics and in the laboratory, and opening new avenues between theoretical/massive computational studies, laboratory experiments and astrophysical observations.
Summary
What is the origin of cosmic rays, what are the dominant acceleration mechanisms in relativistic shocks, how do cosmic rays self-consistently influence the shock dynamics, how are relativistic collisionless shocks formed are longstanding scientific questions, closely tied to extreme plasma physics processes, and where a close interplay between the micro-instabilities and the global dynamics is critical.
Relativistic shocks are closely connected with the propagation of intense streams of particles pervasive in many astrophysical scenarios. The possibility of exciting shocks in the laboratory will also be available very soon with multi-PW lasers or intense relativistic particle beams.
Computational modeling is now established as a prominent research tool, by enabling the fully kinetic modeling of these systems for the first time. With the fast paced developments in high performance computing, the time is ripe for a focused research programme on simulation-based studies of relativistic shocks. This proposal therefore focuses on using self-consistent ab initio massively parallel simulations to study the physics of relativistic shocks, bridging the gap between the multidimensional microphysics of shock onset, formation, and propagation and the global system dynamics. Particular focus will be given to the shock acceleration mechanisms and the radiation signatures of the various physical processes, with the goal of solving some of the central questions in plasma/relativistic phenomena in astrophysics and in the laboratory, and opening new avenues between theoretical/massive computational studies, laboratory experiments and astrophysical observations.
Max ERC Funding
1 588 800 €
Duration
Start date: 2011-06-01, End date: 2016-07-31
Project acronym ALGILE
Project Foundations of Algebraic and Dynamic Data Management Systems
Researcher (PI) Christoph Koch
Host Institution (HI) ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Call Details Starting Grant (StG), PE6, ERC-2011-StG_20101014
Summary "Contemporary database query languages are ultimately founded on logic and feature an additive operation – usually a form of (multi)set union or disjunction – that is asymmetric in that additions or updates do not always have an inverse. This asymmetry puts a greater part of the machinery of abstract algebra for equation solving outside the reach of databases. However, such equation solving would be a key functionality that problems such as query equivalence testing and data integration could be reduced to: In the current scenario of the presence of an asymmetric additive operation they are undecidable. Moreover, query languages with a symmetric additive operation (i.e., which has an inverse and is thus based on ring theory) would open up databases for a large range of new scientific and mathematical applications.
The goal of the proposed project is to reinvent database management systems with a foundation in abstract algebra and specifically in ring theory. The presence of an additive inverse allows to cleanly define differences between queries. This gives rise to a database analog of differential calculus that leads to radically new incremental and adaptive query evaluation algorithms that substantially outperform the state of the art techniques. These algorithms enable a new class of systems which I call Dynamic Data Management Systems. Such systems can maintain continuously fresh query views at extremely high update rates and have important applications in interactive Large-scale Data Analysis. There is a natural connection between differences and updates, motivating the group theoretic study of updates that will lead to better ways of creating out-of-core data processing algorithms for new storage devices. Basing queries on ring theory leads to a new class of systems, Algebraic Data Management Systems, which herald a convergence of database systems and computer algebra systems."
Summary
"Contemporary database query languages are ultimately founded on logic and feature an additive operation – usually a form of (multi)set union or disjunction – that is asymmetric in that additions or updates do not always have an inverse. This asymmetry puts a greater part of the machinery of abstract algebra for equation solving outside the reach of databases. However, such equation solving would be a key functionality that problems such as query equivalence testing and data integration could be reduced to: In the current scenario of the presence of an asymmetric additive operation they are undecidable. Moreover, query languages with a symmetric additive operation (i.e., which has an inverse and is thus based on ring theory) would open up databases for a large range of new scientific and mathematical applications.
The goal of the proposed project is to reinvent database management systems with a foundation in abstract algebra and specifically in ring theory. The presence of an additive inverse allows to cleanly define differences between queries. This gives rise to a database analog of differential calculus that leads to radically new incremental and adaptive query evaluation algorithms that substantially outperform the state of the art techniques. These algorithms enable a new class of systems which I call Dynamic Data Management Systems. Such systems can maintain continuously fresh query views at extremely high update rates and have important applications in interactive Large-scale Data Analysis. There is a natural connection between differences and updates, motivating the group theoretic study of updates that will lead to better ways of creating out-of-core data processing algorithms for new storage devices. Basing queries on ring theory leads to a new class of systems, Algebraic Data Management Systems, which herald a convergence of database systems and computer algebra systems."
Max ERC Funding
1 480 548 €
Duration
Start date: 2012-01-01, End date: 2016-12-31
Project acronym AlgoRNN
Project Recurrent Neural Networks and Related Machines That Learn Algorithms
Researcher (PI) Juergen Schmidhuber
Host Institution (HI) UNIVERSITA DELLA SVIZZERA ITALIANA
Call Details Advanced Grant (AdG), PE6, ERC-2016-ADG
Summary Recurrent neural networks (RNNs) are general parallel-sequential computers. Some learn their programs or weights. Our supervised Long Short-Term Memory (LSTM) RNNs were the first to win pattern recognition contests, and recently enabled best known results in speech and handwriting recognition, machine translation, etc. They are now available to billions of users through the world's most valuable public companies including Google and Apple. Nevertheless, in lots of real-world tasks RNNs do not yet live up to their full potential. Although universal in theory, in practice they fail to learn important types of algorithms. This ERC project will go far beyond today's best RNNs through novel RNN-like systems that address some of the biggest open RNN problems and hottest RNN research topics: (1) How can RNNs learn to control (through internal spotlights of attention) separate large short-memory structures such as sub-networks with fast weights, to improve performance on many natural short-term memory-intensive tasks which are currently hard to learn by RNNs, such as answering detailed questions on recently observed videos? (2) How can such RNN-like systems metalearn entire learning algorithms that outperform the original learning algorithms? (3) How to achieve efficient transfer learning from one RNN-learned set of problem-solving programs to new RNN programs solving new tasks? In other words, how can one RNN-like system actively learn to exploit algorithmic information contained in the programs running on another? We will test our systems existing benchmarks, and create new, more challenging multi-task benchmarks. This will be supported by a rather cheap, GPU-based mini-brain for implementing large RNNs.
Summary
Recurrent neural networks (RNNs) are general parallel-sequential computers. Some learn their programs or weights. Our supervised Long Short-Term Memory (LSTM) RNNs were the first to win pattern recognition contests, and recently enabled best known results in speech and handwriting recognition, machine translation, etc. They are now available to billions of users through the world's most valuable public companies including Google and Apple. Nevertheless, in lots of real-world tasks RNNs do not yet live up to their full potential. Although universal in theory, in practice they fail to learn important types of algorithms. This ERC project will go far beyond today's best RNNs through novel RNN-like systems that address some of the biggest open RNN problems and hottest RNN research topics: (1) How can RNNs learn to control (through internal spotlights of attention) separate large short-memory structures such as sub-networks with fast weights, to improve performance on many natural short-term memory-intensive tasks which are currently hard to learn by RNNs, such as answering detailed questions on recently observed videos? (2) How can such RNN-like systems metalearn entire learning algorithms that outperform the original learning algorithms? (3) How to achieve efficient transfer learning from one RNN-learned set of problem-solving programs to new RNN programs solving new tasks? In other words, how can one RNN-like system actively learn to exploit algorithmic information contained in the programs running on another? We will test our systems existing benchmarks, and create new, more challenging multi-task benchmarks. This will be supported by a rather cheap, GPU-based mini-brain for implementing large RNNs.
Max ERC Funding
2 500 000 €
Duration
Start date: 2017-10-01, End date: 2022-09-30
Project acronym AMSEL
Project Atomic Force Microscopy for Molecular Structure Elucidation
Researcher (PI) Leo Gross
Host Institution (HI) IBM RESEARCH GMBH
Call Details Consolidator Grant (CoG), PE4, ERC-2015-CoG
Summary Molecular structure elucidation is of great importance in synthetic chemistry, pharmacy, life sciences, energy and environmental sciences, and technology applications. To date structure elucidation by atomic force microscopy (AFM) has been demonstrated for a few, small and mainly planar molecules. In this project high-risk, high-impact scientific questions will be solved using structure elucidation with the AFM employing a novel tool and novel methodologies.
A combined low-temperature scanning tunneling microscope/atomic force microscope (LT-STM/AFM) with high throughput and in situ electrospray deposition method will be developed. Chemical resolution will be achieved by novel measurement techniques, in particular the usage of different and novel tip functionalizations and combination with Kelvin probe force microscopy. Elements will be identified using substructure recognition provided by a database that will be erected and by refined theory and simulations.
The developed tools and techniques will be applied to molecules of increasing fragility, complexity, size, and three-dimensionality. In particular samples that are challenging to characterize with conventional methods will be studied. Complex molecular mixtures will be investigated molecule-by-molecule taking advantage of the single-molecule sensitivity. The absolute stereochemistry of molecules will be determined, resolving molecules with multiple stereocenters. The operation of single molecular machines as nanocars and molecular gears will be investigated. Reactive intermediates generated with atomic manipulation will be characterized and their on-surface reactivity will be studied by AFM.
Summary
Molecular structure elucidation is of great importance in synthetic chemistry, pharmacy, life sciences, energy and environmental sciences, and technology applications. To date structure elucidation by atomic force microscopy (AFM) has been demonstrated for a few, small and mainly planar molecules. In this project high-risk, high-impact scientific questions will be solved using structure elucidation with the AFM employing a novel tool and novel methodologies.
A combined low-temperature scanning tunneling microscope/atomic force microscope (LT-STM/AFM) with high throughput and in situ electrospray deposition method will be developed. Chemical resolution will be achieved by novel measurement techniques, in particular the usage of different and novel tip functionalizations and combination with Kelvin probe force microscopy. Elements will be identified using substructure recognition provided by a database that will be erected and by refined theory and simulations.
The developed tools and techniques will be applied to molecules of increasing fragility, complexity, size, and three-dimensionality. In particular samples that are challenging to characterize with conventional methods will be studied. Complex molecular mixtures will be investigated molecule-by-molecule taking advantage of the single-molecule sensitivity. The absolute stereochemistry of molecules will be determined, resolving molecules with multiple stereocenters. The operation of single molecular machines as nanocars and molecular gears will be investigated. Reactive intermediates generated with atomic manipulation will be characterized and their on-surface reactivity will be studied by AFM.
Max ERC Funding
2 000 000 €
Duration
Start date: 2016-06-01, End date: 2021-05-31
Project acronym AOC
Project Adversary-Oriented Computing
Researcher (PI) Rachid Guerraoui
Host Institution (HI) ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Call Details Advanced Grant (AdG), PE6, ERC-2013-ADG
Summary "Recent technological evolutions, including the cloud, the multicore, the social and the mobiles ones, are turning computing ubiquitously distributed. Yet, building high-assurance distributed programs is notoriously challenging. One of the main reasons is that these systems usually seek to achieve several goals at the same time. In short, they need to be efficient, responding effectively in various average-case conditions, as well as reliable, behaving correctly in severe, worst-case conditions. As a consequence, they typically intermingle different strategies: each to cope with some specific condition, e.g., with or without node failures, message losses, time-outs, contention, cache misses,
over-sizing, malicious attacks, etc. The resulting programs end up hard to design, prove, verify, implement, test and debug. Not surprisingly, there are anecdotal evidences of the fragility of the most celebrated distributed systems.
The goal of this project is to contribute to building high-assurance distributed programs by introducing a new dimension for separating and isolating their concerns, as well as a new scheme for composing and reusing them in a modular manner. In short, the project will explore the inherent power and limitations of a novel paradigm, Adversary-Oriented Computing (AOC). Sub-programs, each implementing a specific strategy to cope with a given adversary, modelling a specific working condition, are designed, proved, verified, implemented, tested and debugged independently. They are then composed, possibly dynamically, as black-boxes within the same global program. The AOC project is ambitious and it seeks to fundamentally revisit the way distributed algorithms are designed and distributed systems are implemented. The gain expected in comparison with today's approaches is substantial, and I believe it will be proportional to the degree of difficulty of the distributed problem at hand."
Summary
"Recent technological evolutions, including the cloud, the multicore, the social and the mobiles ones, are turning computing ubiquitously distributed. Yet, building high-assurance distributed programs is notoriously challenging. One of the main reasons is that these systems usually seek to achieve several goals at the same time. In short, they need to be efficient, responding effectively in various average-case conditions, as well as reliable, behaving correctly in severe, worst-case conditions. As a consequence, they typically intermingle different strategies: each to cope with some specific condition, e.g., with or without node failures, message losses, time-outs, contention, cache misses,
over-sizing, malicious attacks, etc. The resulting programs end up hard to design, prove, verify, implement, test and debug. Not surprisingly, there are anecdotal evidences of the fragility of the most celebrated distributed systems.
The goal of this project is to contribute to building high-assurance distributed programs by introducing a new dimension for separating and isolating their concerns, as well as a new scheme for composing and reusing them in a modular manner. In short, the project will explore the inherent power and limitations of a novel paradigm, Adversary-Oriented Computing (AOC). Sub-programs, each implementing a specific strategy to cope with a given adversary, modelling a specific working condition, are designed, proved, verified, implemented, tested and debugged independently. They are then composed, possibly dynamically, as black-boxes within the same global program. The AOC project is ambitious and it seeks to fundamentally revisit the way distributed algorithms are designed and distributed systems are implemented. The gain expected in comparison with today's approaches is substantial, and I believe it will be proportional to the degree of difficulty of the distributed problem at hand."
Max ERC Funding
2 147 012 €
Duration
Start date: 2014-06-01, End date: 2019-05-31
Project acronym ATLAS
Project Bioengineered autonomous cell-biomaterials devices for generating humanised micro-tissues for regenerative medicine
Researcher (PI) João Felipe Colardelle da Luz Mano
Host Institution (HI) UNIVERSIDADE DE AVEIRO
Call Details Advanced Grant (AdG), PE8, ERC-2014-ADG
Summary New generations of devices for tissue engineering (TE) should rationalize better the physical and biochemical cues operating in tandem during native regeneration, in particular at the scale/organizational-level of the stem cell niche. The understanding and the deconstruction of these factors (e.g. multiple cell types exchanging both paracrine and direct signals, structural and chemical arrangement of the extra-cellular matrix, mechanical signals…) should be then incorporated into the design of truly biomimetic biomaterials. ATLAS proposes rather unique toolboxes combining smart biomaterials and cells for the ground-breaking advances of engineering fully time-self-regulated complex 2D and 3D devices, able to adjust the cascade of processes leading to faster high-quality new tissue formation with minimum pre-processing of cells. Versatile biomaterials based on marine-origin macromolecules will be used, namely in the supramolecular assembly of instructive multilayers as nanostratified building-blocks for engineer such structures. The backbone of these biopolymers will be equipped with a variety of (bio)chemical elements permitting: post-processing chemistry and micro-patterning, specific/non-specific cell attachment, and cell-controlled degradation. Aiming at being applied in bone TE, ATLAS will integrate cells from different units of tissue physiology, namely bone and hematopoietic basic elements and consider the interactions between the immune and skeletal systems. These ingredients will permit to architect innovative films with high-level dialogue control with cells, but in particular sophisticated quasi-closed 3D capsules able to compartmentalise such components in a “globe-like” organization, providing local and long-range order for in vitro microtissue development and function. Such hybrid devices could be used in more generalised front-edge applications, including as disease models for drug discovery or test new therapies in vitro.
Summary
New generations of devices for tissue engineering (TE) should rationalize better the physical and biochemical cues operating in tandem during native regeneration, in particular at the scale/organizational-level of the stem cell niche. The understanding and the deconstruction of these factors (e.g. multiple cell types exchanging both paracrine and direct signals, structural and chemical arrangement of the extra-cellular matrix, mechanical signals…) should be then incorporated into the design of truly biomimetic biomaterials. ATLAS proposes rather unique toolboxes combining smart biomaterials and cells for the ground-breaking advances of engineering fully time-self-regulated complex 2D and 3D devices, able to adjust the cascade of processes leading to faster high-quality new tissue formation with minimum pre-processing of cells. Versatile biomaterials based on marine-origin macromolecules will be used, namely in the supramolecular assembly of instructive multilayers as nanostratified building-blocks for engineer such structures. The backbone of these biopolymers will be equipped with a variety of (bio)chemical elements permitting: post-processing chemistry and micro-patterning, specific/non-specific cell attachment, and cell-controlled degradation. Aiming at being applied in bone TE, ATLAS will integrate cells from different units of tissue physiology, namely bone and hematopoietic basic elements and consider the interactions between the immune and skeletal systems. These ingredients will permit to architect innovative films with high-level dialogue control with cells, but in particular sophisticated quasi-closed 3D capsules able to compartmentalise such components in a “globe-like” organization, providing local and long-range order for in vitro microtissue development and function. Such hybrid devices could be used in more generalised front-edge applications, including as disease models for drug discovery or test new therapies in vitro.
Max ERC Funding
2 498 988 €
Duration
Start date: 2015-12-01, End date: 2020-11-30
Project acronym AtomicGaugeSimulator
Project Classical and Atomic Quantum Simulation of Gauge Theories in Particle and Condensed Matter Physics
Researcher (PI) Uwe-Jens Richard Christian Wiese
Host Institution (HI) UNIVERSITAET BERN
Call Details Advanced Grant (AdG), PE2, ERC-2013-ADG
Summary Gauge theories play a central role in particle and condensed matter physics. Heavy-ion collisions explore the strong dynamics of quarks and gluons, which also governs the deep interior of neutron stars, while strongly correlated electrons determine the physics of high-temperature superconductors and spin liquids. Numerical simulations of such systems are often hindered by sign problems. In quantum link models - an alternative formulation of gauge theories developed by the applicant - gauge fields emerge from discrete quantum variables. In the past year, in close collaboration with atomic physicists, we have established quantum link models as a framework for the atomic quantum simulation of dynamical gauge fields. Abelian gauge theories can be realized with Bose-Fermi mixtures of ultracold atoms in an optical lattice, while non-Abelian gauge fields arise from fermionic constituents embodied by alkaline-earth atoms. Quantum simulators, which do not suffer from the sign problem, shall be constructed to address non-trivial dynamics, including quantum phase transitions in spin liquids, the real-time dynamics of confining strings as well as of chiral symmetry restoration at finite temperature and baryon density, baryon superfluidity, or color-flavor locking. New classical simulation algorithms shall be developed in order to solve severe sign problems, to investigate confining gauge theories, and to validate the proposed quantum simulators. Starting from U(1) and SU(2) gauge theories, an atomic physics tool box shall be developed for quantum simulation of gauge theories of increasing complexity, ultimately aiming at 4-d Quantum Chromodynamics (QCD). This project is based on innovative ideas from particle, condensed matter, and computational physics, and requires an interdisciplinary team of researchers. It has the potential to drastically increase the power of simulations and to address very challenging problems that cannot be solved with classical simulation methods.
Summary
Gauge theories play a central role in particle and condensed matter physics. Heavy-ion collisions explore the strong dynamics of quarks and gluons, which also governs the deep interior of neutron stars, while strongly correlated electrons determine the physics of high-temperature superconductors and spin liquids. Numerical simulations of such systems are often hindered by sign problems. In quantum link models - an alternative formulation of gauge theories developed by the applicant - gauge fields emerge from discrete quantum variables. In the past year, in close collaboration with atomic physicists, we have established quantum link models as a framework for the atomic quantum simulation of dynamical gauge fields. Abelian gauge theories can be realized with Bose-Fermi mixtures of ultracold atoms in an optical lattice, while non-Abelian gauge fields arise from fermionic constituents embodied by alkaline-earth atoms. Quantum simulators, which do not suffer from the sign problem, shall be constructed to address non-trivial dynamics, including quantum phase transitions in spin liquids, the real-time dynamics of confining strings as well as of chiral symmetry restoration at finite temperature and baryon density, baryon superfluidity, or color-flavor locking. New classical simulation algorithms shall be developed in order to solve severe sign problems, to investigate confining gauge theories, and to validate the proposed quantum simulators. Starting from U(1) and SU(2) gauge theories, an atomic physics tool box shall be developed for quantum simulation of gauge theories of increasing complexity, ultimately aiming at 4-d Quantum Chromodynamics (QCD). This project is based on innovative ideas from particle, condensed matter, and computational physics, and requires an interdisciplinary team of researchers. It has the potential to drastically increase the power of simulations and to address very challenging problems that cannot be solved with classical simulation methods.
Max ERC Funding
1 975 242 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym Attoclock
Project Clocking fundamental attosecond electron dynamics
Researcher (PI) Ursula Keller
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Advanced Grant (AdG), PE2, ERC-2012-ADG_20120216
Summary The attoclock is a powerful, new, and unconventional tool to study fundamental attosecond dynamics on an atomic scale. We established its potential by using the first attoclock to measure the tunneling delay time in laser-induced ionization of helium and argon atoms, with surprising results. Building on these first proof-of-principle measurements, I propose to amplify and expand this tool concept to explore the following key questions: How fast can light liberate electrons from a single atom, a single molecule, or a solid-state system? Related are more questions: How fast can an electron tunnel through a potential barrier? How fast is a multi-photon absorption process? How fast is single-photon photoemission? Many of these questions will undoubtedly spark more questions – revealing deeper and more detailed insights on the dynamics of some of the most fundamental and relevant optoelectronic processes.
There are still many unknown and unexplored areas here. Theory has failed to offer definitive answers. Simulations based on the exact time-dependent Schrödinger equation have not been possible in most cases. Therefore one uses approximations and simpler models to capture the essential physics. Such semi-classical models potentially will help to understand attosecond energy and charge transport in larger molecular systems. Indeed the attoclock provides a unique tool to explore different semi-classical models.
For example, the question of whether electron tunneling through an energetically forbidden region takes a finite time or is instantaneous has been subject to ongoing debate for the last sixty years. The tunnelling process, charge transfer, and energy transport all play key roles in electronics, energy conversion, chemical and biological reactions, and fundamental processes important for improved information, health, and energy technologies. We believe the attoclock can help refine and resolve key models for many of these important underlying attosecond processes.
Summary
The attoclock is a powerful, new, and unconventional tool to study fundamental attosecond dynamics on an atomic scale. We established its potential by using the first attoclock to measure the tunneling delay time in laser-induced ionization of helium and argon atoms, with surprising results. Building on these first proof-of-principle measurements, I propose to amplify and expand this tool concept to explore the following key questions: How fast can light liberate electrons from a single atom, a single molecule, or a solid-state system? Related are more questions: How fast can an electron tunnel through a potential barrier? How fast is a multi-photon absorption process? How fast is single-photon photoemission? Many of these questions will undoubtedly spark more questions – revealing deeper and more detailed insights on the dynamics of some of the most fundamental and relevant optoelectronic processes.
There are still many unknown and unexplored areas here. Theory has failed to offer definitive answers. Simulations based on the exact time-dependent Schrödinger equation have not been possible in most cases. Therefore one uses approximations and simpler models to capture the essential physics. Such semi-classical models potentially will help to understand attosecond energy and charge transport in larger molecular systems. Indeed the attoclock provides a unique tool to explore different semi-classical models.
For example, the question of whether electron tunneling through an energetically forbidden region takes a finite time or is instantaneous has been subject to ongoing debate for the last sixty years. The tunnelling process, charge transfer, and energy transport all play key roles in electronics, energy conversion, chemical and biological reactions, and fundamental processes important for improved information, health, and energy technologies. We believe the attoclock can help refine and resolve key models for many of these important underlying attosecond processes.
Max ERC Funding
2 319 796 €
Duration
Start date: 2013-03-01, End date: 2018-02-28
