Project acronym AMADEUS
Project Advancing CO2 Capture Materials by Atomic Scale Design: the Quest for Understanding
Researcher (PI) Christoph Rüdiger MÜLLER
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Consolidator Grant (CoG), PE8, ERC-2018-COG
Summary Carbon dioxide capture and storage is a technology to mitigate climate change by removing CO2 from flue gas streams or the atmosphere and storing it in geological formations. While CO2 removal from natural gas by amine scrubbing is implemented on the large scale, the cost of such process is currently prohibitively expensive. Inexpensive alkali earth metal oxides (MgO and CaO) feature high theoretical CO2 uptakes, but suffer from poor cyclic stability and slow kinetics. Yet, the key objective of recent research on alkali earth metal oxide based CO2 sorbents has been the processing of inexpensive, naturally occurring CO2 sorbents, notably limestone and dolomite, to stabilize their modest CO2 uptake and to establish re-activation methods through engineering approaches. While this research demonstrated a landmark Megawatt (MW) scale viability of the process, our fundamental understanding of the underlying CO2 capture, regeneration and deactivation pathways did not improve. The latter knowledge is, however, vital for the rational design of improved, yet practical CaO and MgO sorbents. Hence this proposal is concerned with obtaining an understanding of the underlying mechanisms that control the ability of an alkali metal oxide to capture a large quantity of CO2 with a high rate, to regenerate and to operate with high cyclic stability. Achieving these aims relies on the ability to fabricate model structures and to characterize in great detail their surface chemistry, morphology, chemical composition and changes therein under reactive conditions. This makes the development of operando and in situ characterization tools an essential prerequisite. Advances in these areas shall allow achieving the overall goal of this project, viz. to formulate a roadmap to fabricate improved CO2 sorbents through their precisely engineered structure, composition and morphology.
Summary
Carbon dioxide capture and storage is a technology to mitigate climate change by removing CO2 from flue gas streams or the atmosphere and storing it in geological formations. While CO2 removal from natural gas by amine scrubbing is implemented on the large scale, the cost of such process is currently prohibitively expensive. Inexpensive alkali earth metal oxides (MgO and CaO) feature high theoretical CO2 uptakes, but suffer from poor cyclic stability and slow kinetics. Yet, the key objective of recent research on alkali earth metal oxide based CO2 sorbents has been the processing of inexpensive, naturally occurring CO2 sorbents, notably limestone and dolomite, to stabilize their modest CO2 uptake and to establish re-activation methods through engineering approaches. While this research demonstrated a landmark Megawatt (MW) scale viability of the process, our fundamental understanding of the underlying CO2 capture, regeneration and deactivation pathways did not improve. The latter knowledge is, however, vital for the rational design of improved, yet practical CaO and MgO sorbents. Hence this proposal is concerned with obtaining an understanding of the underlying mechanisms that control the ability of an alkali metal oxide to capture a large quantity of CO2 with a high rate, to regenerate and to operate with high cyclic stability. Achieving these aims relies on the ability to fabricate model structures and to characterize in great detail their surface chemistry, morphology, chemical composition and changes therein under reactive conditions. This makes the development of operando and in situ characterization tools an essential prerequisite. Advances in these areas shall allow achieving the overall goal of this project, viz. to formulate a roadmap to fabricate improved CO2 sorbents through their precisely engineered structure, composition and morphology.
Max ERC Funding
1 994 900 €
Duration
Start date: 2019-06-01, End date: 2024-05-31
Project acronym BDE
Project Beyond Distance Estimates: A New Theory of Heuristics for State-Space Search
Researcher (PI) Malte HELMERT
Host Institution (HI) UNIVERSITAT BASEL
Call Details Consolidator Grant (CoG), PE6, ERC-2018-COG
Summary "Many problems in computer science can be cast as state-space search, where the
objective is to find a path from an initial state to a goal state in a
directed graph called a ""state space"". State-space search is challenging due
to the state explosion problem a.k.a. ""curse of dimensionality"": interesting
state spaces are often astronomically large, defying brute-force exploration.
State-space search has been a core research problem in Artificial Intelligence
since its early days and is alive as ever. Every year, a substantial fraction
of research published at the ICAPS and SoCS conferences is concerned with
state-space search, and the topic is very active at general AI conferences
such as IJCAI and AAAI.
Algorithms in the A* family, dating back to 1968, are still the go-to approach
for state-space search. A* is a graph search algorithm whose only
""intelligence"" stems from a so-called ""heuristic function"", which estimates
the distance from a state to the nearest goal state. The efficiency of A*
depends on the accuracy of this estimate, and decades of research have pushed
the envelope in devising increasingly accurate estimates.
In this project, we question the ""A* + distance estimator"" paradigm and
explore three new directions that go beyond the classical approach:
1. We propose a new paradigm of declarative heuristics, where heuristic
information is not represented as distance estimates, but as properties of
solutions amenable to introspection and general reasoning.
2. We suggest moving the burden of creativity away from the human expert by
casting heuristic design as a meta-optimization problem that can be solved
automatically.
3. We propose abandoning the idea of exploring sequential paths in state
spaces, instead transforming state-space search into combinatorial
optimization problems with no explicit sequencing aspect. We argue that the
""curse of sequentiality"" is as bad as the curse of dimensionality and must
be addressed head-on."
Summary
"Many problems in computer science can be cast as state-space search, where the
objective is to find a path from an initial state to a goal state in a
directed graph called a ""state space"". State-space search is challenging due
to the state explosion problem a.k.a. ""curse of dimensionality"": interesting
state spaces are often astronomically large, defying brute-force exploration.
State-space search has been a core research problem in Artificial Intelligence
since its early days and is alive as ever. Every year, a substantial fraction
of research published at the ICAPS and SoCS conferences is concerned with
state-space search, and the topic is very active at general AI conferences
such as IJCAI and AAAI.
Algorithms in the A* family, dating back to 1968, are still the go-to approach
for state-space search. A* is a graph search algorithm whose only
""intelligence"" stems from a so-called ""heuristic function"", which estimates
the distance from a state to the nearest goal state. The efficiency of A*
depends on the accuracy of this estimate, and decades of research have pushed
the envelope in devising increasingly accurate estimates.
In this project, we question the ""A* + distance estimator"" paradigm and
explore three new directions that go beyond the classical approach:
1. We propose a new paradigm of declarative heuristics, where heuristic
information is not represented as distance estimates, but as properties of
solutions amenable to introspection and general reasoning.
2. We suggest moving the burden of creativity away from the human expert by
casting heuristic design as a meta-optimization problem that can be solved
automatically.
3. We propose abandoning the idea of exploring sequential paths in state
spaces, instead transforming state-space search into combinatorial
optimization problems with no explicit sequencing aspect. We argue that the
""curse of sequentiality"" is as bad as the curse of dimensionality and must
be addressed head-on."
Max ERC Funding
1 997 510 €
Duration
Start date: 2019-02-01, End date: 2024-01-31
Project acronym CASSANDRA
Project Accelerating mass loss of Greenland: firn and the shifting runoff limit
Researcher (PI) Horst MACHGUTH
Host Institution (HI) UNIVERSITE DE FRIBOURG
Call Details Consolidator Grant (CoG), PE10, ERC-2018-COG
Summary Meltwater running off the flanks of the Greenland ice sheet contributes roughly 60% to its mass loss, the rest being due to calving. Only meltwater originating from below the elevation of the runoff limit leaves the ice sheet, contributing to mass loss; melt at higher elevations refreezes in the porous firn and does not drive mass loss. Therefore any shift in the runoff limit modifies mass loss and subsequent sea level rise. New evidence shows surface runoff at increasingly high elevations, outpacing the rate at which the equilibrium line elevation rises. This research proposal focuses on the runoff limit as a powerful yet poorly understood modulator of Greenland mass balance. We will track the runoff limit over the full satellite era using two of the largest and oldest remote sensing archives, Landsat and the Advanced Very High Resolution Radiometer (AVHRR). We will establish time series of the runoff limit for all regions of Greenland to identify the mechanisms driving fluctuations in the runoff limit. This newly gained process understanding and a wealth of in-situ measurements will then be used to build firn hydrology models capable of simulating runoff and the associated runoff limit over time. Eventually, the firn hydrology models will be applied to reconcile estimates of Greenland past, present and future mass balance. Covering the entire satellite era and all of Greenland, the focus on the runoff limit will constitute a paradigm shift leading to major advance in our understanding of how vulnerable the surface of the ice sheet reacts to climate change and how the changing surface impacts runoff and thus Greenland's role in the global sea level budget.
Summary
Meltwater running off the flanks of the Greenland ice sheet contributes roughly 60% to its mass loss, the rest being due to calving. Only meltwater originating from below the elevation of the runoff limit leaves the ice sheet, contributing to mass loss; melt at higher elevations refreezes in the porous firn and does not drive mass loss. Therefore any shift in the runoff limit modifies mass loss and subsequent sea level rise. New evidence shows surface runoff at increasingly high elevations, outpacing the rate at which the equilibrium line elevation rises. This research proposal focuses on the runoff limit as a powerful yet poorly understood modulator of Greenland mass balance. We will track the runoff limit over the full satellite era using two of the largest and oldest remote sensing archives, Landsat and the Advanced Very High Resolution Radiometer (AVHRR). We will establish time series of the runoff limit for all regions of Greenland to identify the mechanisms driving fluctuations in the runoff limit. This newly gained process understanding and a wealth of in-situ measurements will then be used to build firn hydrology models capable of simulating runoff and the associated runoff limit over time. Eventually, the firn hydrology models will be applied to reconcile estimates of Greenland past, present and future mass balance. Covering the entire satellite era and all of Greenland, the focus on the runoff limit will constitute a paradigm shift leading to major advance in our understanding of how vulnerable the surface of the ice sheet reacts to climate change and how the changing surface impacts runoff and thus Greenland's role in the global sea level budget.
Max ERC Funding
1 989 181 €
Duration
Start date: 2019-05-01, End date: 2024-04-30
Project acronym DYNAPOL
Project Modeling approaches toward bioinspired dynamic materials
Researcher (PI) Giovanni Maria PAVAN
Host Institution (HI) SCUOLA UNIVERSITARIA PROFESSIONALE DELLA SVIZZERA ITALIANA
Call Details Consolidator Grant (CoG), PE4, ERC-2018-COG
Summary Nature uses self-assembly to build fascinating supramolecular materials, such as microtubules and protein filaments, that can self-heal, reconfigure, adapt or respond to specific stimuli in dynamic way. Building synthetic (polymeric) supramolecular materials possessing similar bioinspired properties via the same self-assembly principles is interesting for many applications. But their rational design requires a detailed comprehension of the molecular determinants controlling the assembly (structure, dynamics and properties) that is typically very difficult to reach experimentally.
The aim of this project is to obtain structure-dynamics-property relationships to learn how to control the dynamic bioinspired properties of supramolecular polymers. I propose to unravel the molecular origin of the bioinspired behavior through massive multiscale modeling, advanced simulations and machine learning. First, we will develop ad hoc molecular models to study monomer assembly and the supramolecular structure of various types of self-assembled materials on multiple scales. Second, using advanced simulation approaches we will characterize the supramolecular dynamics of these materials (dynamic exchange of monomers) at high (submolecular) resolution. We will then study bioinspired properties such as the ability of various supramolecular materials to self-heal, adapt or reconfigure dynamically in response to specific stimuli. Our models will be systematically validated by comparison with the experimental evidence from our collaborators. Finally, we will use machine learning approaches to analyze our high-resolution simulations and to identify the key monomer features that control and determine the structure, dynamics and dynamic properties of a supramolecular material (i.e., structure-dynamics-property relationships). This research will produce unprecedented insight and fundamental models for the rational design of artificial dynamic materials with controllable bioinspired properties.
Summary
Nature uses self-assembly to build fascinating supramolecular materials, such as microtubules and protein filaments, that can self-heal, reconfigure, adapt or respond to specific stimuli in dynamic way. Building synthetic (polymeric) supramolecular materials possessing similar bioinspired properties via the same self-assembly principles is interesting for many applications. But their rational design requires a detailed comprehension of the molecular determinants controlling the assembly (structure, dynamics and properties) that is typically very difficult to reach experimentally.
The aim of this project is to obtain structure-dynamics-property relationships to learn how to control the dynamic bioinspired properties of supramolecular polymers. I propose to unravel the molecular origin of the bioinspired behavior through massive multiscale modeling, advanced simulations and machine learning. First, we will develop ad hoc molecular models to study monomer assembly and the supramolecular structure of various types of self-assembled materials on multiple scales. Second, using advanced simulation approaches we will characterize the supramolecular dynamics of these materials (dynamic exchange of monomers) at high (submolecular) resolution. We will then study bioinspired properties such as the ability of various supramolecular materials to self-heal, adapt or reconfigure dynamically in response to specific stimuli. Our models will be systematically validated by comparison with the experimental evidence from our collaborators. Finally, we will use machine learning approaches to analyze our high-resolution simulations and to identify the key monomer features that control and determine the structure, dynamics and dynamic properties of a supramolecular material (i.e., structure-dynamics-property relationships). This research will produce unprecedented insight and fundamental models for the rational design of artificial dynamic materials with controllable bioinspired properties.
Max ERC Funding
1 999 623 €
Duration
Start date: 2019-06-01, End date: 2024-05-31
Project acronym EMPOWER
Project Medium Voltage Direct Current Electronic Transformer
Researcher (PI) Drazen DUJIC
Host Institution (HI) ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Call Details Consolidator Grant (CoG), PE7, ERC-2018-COG
Summary More than a century ago, the invention of alternating current (AC) transformer has made AC the preferred choice over the direct current (DC) technologies. Line AC transformers are bulky but simple and reliable devices, made out of copper and iron, providing voltage adaptation and galvanic isolation in AC power systems.
Currently, DC technology is increasing its presence in AC power systems, enabled by progress in semiconductor devices and power electronics based energy conversion. DC power distribution networks can effectively support energy transformation and high penetration of distributed energy resources and energy storage integration (both increasingly being DC by nature) in future energy systems. Despite this shift towards the DC power distribution networks, DC Transformer, offering AC transformer like features (and beyond) does not exist, either conceptually or practically.
To enable the next (r)evolution in power systems, the EMPOWER project will develop the DC Transformer, a novel, flexible, highly efficient, compact, and reliable conversion principle for seamless energy routing in high-power DC distribution networks. Through a holistic approach, novel concepts, integration and optimization, we will demonstrate new design paradigms for galvanically-isolated power conversion. Our approach relies on resonant conversion utilizing high-voltage semiconductor devices in combination with high-frequency magnetic materials. We propose a new approach for the DC Transformer, avoiding active power flow control and instead utilizing control effort for the safety and protection. The DC Transformer will unify functions of a power converter and a protection device into a single power electronics system, improving drastically the conversion efficiency, reliability and power density in future DC power distribution networks. The success of this project will place Europe at the edge of reliable, efficient and safe energy distribution and transmission technologies.
Summary
More than a century ago, the invention of alternating current (AC) transformer has made AC the preferred choice over the direct current (DC) technologies. Line AC transformers are bulky but simple and reliable devices, made out of copper and iron, providing voltage adaptation and galvanic isolation in AC power systems.
Currently, DC technology is increasing its presence in AC power systems, enabled by progress in semiconductor devices and power electronics based energy conversion. DC power distribution networks can effectively support energy transformation and high penetration of distributed energy resources and energy storage integration (both increasingly being DC by nature) in future energy systems. Despite this shift towards the DC power distribution networks, DC Transformer, offering AC transformer like features (and beyond) does not exist, either conceptually or practically.
To enable the next (r)evolution in power systems, the EMPOWER project will develop the DC Transformer, a novel, flexible, highly efficient, compact, and reliable conversion principle for seamless energy routing in high-power DC distribution networks. Through a holistic approach, novel concepts, integration and optimization, we will demonstrate new design paradigms for galvanically-isolated power conversion. Our approach relies on resonant conversion utilizing high-voltage semiconductor devices in combination with high-frequency magnetic materials. We propose a new approach for the DC Transformer, avoiding active power flow control and instead utilizing control effort for the safety and protection. The DC Transformer will unify functions of a power converter and a protection device into a single power electronics system, improving drastically the conversion efficiency, reliability and power density in future DC power distribution networks. The success of this project will place Europe at the edge of reliable, efficient and safe energy distribution and transmission technologies.
Max ERC Funding
2 198 145 €
Duration
Start date: 2019-06-01, End date: 2024-05-31
Project acronym ICOPT
Project Fundamental Problems at the Interface of Combinatorial Optimization with Integer Programming and Online Optimization
Researcher (PI) Rico Zenklusen
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Consolidator Grant (CoG), PE1, ERC-2018-COG
Summary The goal of this proposal is to leverage and significantly extend techniques from the field of Combinatorial Optimization to address some fundamental open algorithmic questions in other, related areas, namely Integer Programming and Online Optimization. More precisely, we focus on the following three thrusts, which share many combinatorial features:
- Integer programming with bounded subdeterminants.
- Expressive power of mixed-integer linear formulations.
- The matroid secretary conjecture, a key online selection problem.
Recent significant progress, in which the PI played a central role, combined with new ideas, give hope to obtain breakthrough results in these fields. Many of the questions we consider are long-standing open problems in their respective area, and any progress is thus likely to be a significant contribution to Mathematical Optimization and Theoretical Computer Science. However, equally importantly, if progress can be achieved through the suggested methodologies, then this would create intriguing new links between different fields, which was a key driver in the selection of the above research thrusts.
Summary
The goal of this proposal is to leverage and significantly extend techniques from the field of Combinatorial Optimization to address some fundamental open algorithmic questions in other, related areas, namely Integer Programming and Online Optimization. More precisely, we focus on the following three thrusts, which share many combinatorial features:
- Integer programming with bounded subdeterminants.
- Expressive power of mixed-integer linear formulations.
- The matroid secretary conjecture, a key online selection problem.
Recent significant progress, in which the PI played a central role, combined with new ideas, give hope to obtain breakthrough results in these fields. Many of the questions we consider are long-standing open problems in their respective area, and any progress is thus likely to be a significant contribution to Mathematical Optimization and Theoretical Computer Science. However, equally importantly, if progress can be achieved through the suggested methodologies, then this would create intriguing new links between different fields, which was a key driver in the selection of the above research thrusts.
Max ERC Funding
1 443 422 €
Duration
Start date: 2019-11-01, End date: 2024-10-31
Project acronym IMAGINE
Project Non-Invasive Imaging of Nanoscale Electronic Transport
Researcher (PI) Christian Lukas Degen
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Consolidator Grant (CoG), PE3, ERC-2018-COG
Summary Electronic transport in nanostructures and thin films shows a rich variety of physical effects that have been fundamental to the development of modern electronics and communication devices. The standard method for investigating electronic transport – resistance measurements – does not provide any information on the nanoscale current distribution in such structures. The lack of spatial information is unfortunate, because the current distribution plays a key role in many intriguing physical phenomena. Having a technique at hand that could simply look at nanoscale current flow would be immensely valuable.
In this project we propose to exploit sensitive magnetic microscopy to directly access the current distribution in nanostructures with ~15nm spatial resolution. Our approach is based on the recent technique of scanning diamond magnetometry (SDM), a scanned-probe method that utilizes a single spin in a diamond tip as a high-resolution sensor of magnetic field. Conceived in 2008 by the PI, SDM exploits quantum metrology to achieve very high sensitivities, and has recently enabled a breakthrough in the passive analysis of magnetic surfaces. Our proposal has three objectives: (i) Lay the instrumental and conceptual groundwork required for imaging tiny (<10nA) current variations in two-dimensional conductors. (ii) Demonstrate imaging of a variety of mesoscopic transport features on a well-established model system: Mono- and bilayer graphene. (iii) Explore the potential of our technique for probing electronic properties beyond transport, like phase transitions and photoexcitation.
Together, our experiments are designed to establish a powerful new technology for imaging current distributions non-invasively and with nanometer spatial resolution. This capability will provide the unique opportunity for directly looking at electronic transport in nanostructures, with a potentially transformative impact on condensed matter physics, materials science and electrical engineering.
Summary
Electronic transport in nanostructures and thin films shows a rich variety of physical effects that have been fundamental to the development of modern electronics and communication devices. The standard method for investigating electronic transport – resistance measurements – does not provide any information on the nanoscale current distribution in such structures. The lack of spatial information is unfortunate, because the current distribution plays a key role in many intriguing physical phenomena. Having a technique at hand that could simply look at nanoscale current flow would be immensely valuable.
In this project we propose to exploit sensitive magnetic microscopy to directly access the current distribution in nanostructures with ~15nm spatial resolution. Our approach is based on the recent technique of scanning diamond magnetometry (SDM), a scanned-probe method that utilizes a single spin in a diamond tip as a high-resolution sensor of magnetic field. Conceived in 2008 by the PI, SDM exploits quantum metrology to achieve very high sensitivities, and has recently enabled a breakthrough in the passive analysis of magnetic surfaces. Our proposal has three objectives: (i) Lay the instrumental and conceptual groundwork required for imaging tiny (<10nA) current variations in two-dimensional conductors. (ii) Demonstrate imaging of a variety of mesoscopic transport features on a well-established model system: Mono- and bilayer graphene. (iii) Explore the potential of our technique for probing electronic properties beyond transport, like phase transitions and photoexcitation.
Together, our experiments are designed to establish a powerful new technology for imaging current distributions non-invasively and with nanometer spatial resolution. This capability will provide the unique opportunity for directly looking at electronic transport in nanostructures, with a potentially transformative impact on condensed matter physics, materials science and electrical engineering.
Max ERC Funding
2 491 490 €
Duration
Start date: 2019-10-01, End date: 2024-09-30
Project acronym IONPEN
Project Trapped-ion quantum information in 2-dimensional Penning trap arrays
Researcher (PI) Jonathan HOME
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Consolidator Grant (CoG), PE2, ERC-2018-COG
Summary This project will develop a new platform for quantum computation and quantum simulation based on scalable two-dimensional arrays of ions in micro-fabricated Penning traps. It builds upon the rapid advances demonstrating high precision quantum control in micro-fabricated radio-frequency ion traps while eliminating the most problematic element - the radio-frequency potential - using a uniform magnetic field. This offers a significant advantage: since the magnetic field is uniform it provides confinement at any position for which a suitable static quadrupole can be generated. By contrast, r.f. potentials only provide good working conditions along a line. This changed perspective provides access to dense two-dimensional strongly interacting ion lattices, with the possibility to re-configure these lattices in real time. By combining closely-spaced static two-dimensional ion arrays with standard laser control methods, the project will demonstrate previously inaccessible many-body interacting spin Hamiltonians at ion numbers which are out of the reach of classical computers, providing a scalable quantum simulator with the potential to provide new insights into the links between microscopic physics and emergent behavior. Through dynamic control of electrode voltages, reconfigurable two-dimensional arrays will be used to realize a scalable quantum computing architecture, which will be benchmarked through landmark experiments on measurement-based quantum computation and high error-threshold surface codes which are natural to this configuration. Realizing multi-dimensional connectivity between qubits is a major problem facing a number of leading quantum computing architectures including trapped ions. By solving this problem, the proposed project will pave the way to large-scale universal quantum computing with impacts from fundamental physics through to chemistry, materials science and cryptography.
Summary
This project will develop a new platform for quantum computation and quantum simulation based on scalable two-dimensional arrays of ions in micro-fabricated Penning traps. It builds upon the rapid advances demonstrating high precision quantum control in micro-fabricated radio-frequency ion traps while eliminating the most problematic element - the radio-frequency potential - using a uniform magnetic field. This offers a significant advantage: since the magnetic field is uniform it provides confinement at any position for which a suitable static quadrupole can be generated. By contrast, r.f. potentials only provide good working conditions along a line. This changed perspective provides access to dense two-dimensional strongly interacting ion lattices, with the possibility to re-configure these lattices in real time. By combining closely-spaced static two-dimensional ion arrays with standard laser control methods, the project will demonstrate previously inaccessible many-body interacting spin Hamiltonians at ion numbers which are out of the reach of classical computers, providing a scalable quantum simulator with the potential to provide new insights into the links between microscopic physics and emergent behavior. Through dynamic control of electrode voltages, reconfigurable two-dimensional arrays will be used to realize a scalable quantum computing architecture, which will be benchmarked through landmark experiments on measurement-based quantum computation and high error-threshold surface codes which are natural to this configuration. Realizing multi-dimensional connectivity between qubits is a major problem facing a number of leading quantum computing architectures including trapped ions. By solving this problem, the proposed project will pave the way to large-scale universal quantum computing with impacts from fundamental physics through to chemistry, materials science and cryptography.
Max ERC Funding
1 999 375 €
Duration
Start date: 2019-04-01, End date: 2024-03-31
Project acronym Mu-MASS
Project Muonium Laser Spectroscopy
Researcher (PI) Paolo CRIVELLI
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Consolidator Grant (CoG), PE2, ERC-2018-COG
Summary Striking anomalies in the muon sector have accumulated in recent years: notably the famous anomalous muon magnetic moment (g-2) and the muonic hydrogen Lamb shift measurement which prompted the so-called proton charge radius puzzle. These tantalizing results triggered vibrant activity on both experimental and theoretical sides. Different explanations have been put forward including exciting solutions invoking New Physics beyond the Standard Model. To contribute to clarifying the origin of these anomalies, I propose Mu-MASS, an experiment aiming for a 1000-fold improvement in the determination of the 1S-2S transition frequency of Muonium (M), the positive-muon/electron bound state. This substantial improvement beyond the current state-of-the-art relies on the novel cryogenic M converters and confinement techniques developed by the PI, and on the new laser and detection schemes which the PI implemented for positronium spectroscopy. This experiment will be performed at the Paul Scherrer Institute (PSI).
With the Mu-MASS result our knowledge of the muon mass can be improved by almost two orders of magnitude. By using the expected results of the ongoing hyperfine splitting measurement of M in Japan, it will provide one of the most sensitive tests of bound-state Quantum Electrodynamics. It can also be used to extract the muon g-2 from the ongoing experiment at Fermilab. Since M is a unique system composed of two different leptons (point-like particles), the Mu-MASS results will provide the most stringent test of charge equality between the lepton generations. Moreover, it can be used to determine the Rydberg constant free from nuclear and finite-size effects and contribute to solving the proton charge radius puzzle. Mu-MASS is thus very timely and essential to the worldwide effort to understand the interesting observed discrepancies, which could be a hint of New Physics and therefore have profound implications on our understanding of the Universe.
Summary
Striking anomalies in the muon sector have accumulated in recent years: notably the famous anomalous muon magnetic moment (g-2) and the muonic hydrogen Lamb shift measurement which prompted the so-called proton charge radius puzzle. These tantalizing results triggered vibrant activity on both experimental and theoretical sides. Different explanations have been put forward including exciting solutions invoking New Physics beyond the Standard Model. To contribute to clarifying the origin of these anomalies, I propose Mu-MASS, an experiment aiming for a 1000-fold improvement in the determination of the 1S-2S transition frequency of Muonium (M), the positive-muon/electron bound state. This substantial improvement beyond the current state-of-the-art relies on the novel cryogenic M converters and confinement techniques developed by the PI, and on the new laser and detection schemes which the PI implemented for positronium spectroscopy. This experiment will be performed at the Paul Scherrer Institute (PSI).
With the Mu-MASS result our knowledge of the muon mass can be improved by almost two orders of magnitude. By using the expected results of the ongoing hyperfine splitting measurement of M in Japan, it will provide one of the most sensitive tests of bound-state Quantum Electrodynamics. It can also be used to extract the muon g-2 from the ongoing experiment at Fermilab. Since M is a unique system composed of two different leptons (point-like particles), the Mu-MASS results will provide the most stringent test of charge equality between the lepton generations. Moreover, it can be used to determine the Rydberg constant free from nuclear and finite-size effects and contribute to solving the proton charge radius puzzle. Mu-MASS is thus very timely and essential to the worldwide effort to understand the interesting observed discrepancies, which could be a hint of New Physics and therefore have profound implications on our understanding of the Universe.
Max ERC Funding
1 999 150 €
Duration
Start date: 2019-02-01, End date: 2024-01-31
Project acronym Piko
Project Revealing the adaptive internal organization and dynamics of bacteria and mitochondria
Researcher (PI) Suliana MANLEY
Host Institution (HI) ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Call Details Consolidator Grant (CoG), PE3, ERC-2018-COG
Summary Bacteria cells appear to be less complex than our own cells -- yet they are better able to survive harsh conditions. Typically ~1 micron in size, they lack motor proteins; thus, they rely on fluctuations for intracellular transport. Bacteria in the environment often face starvation and exist in a non-proliferating quiescent state, which promotes antibiotic resistance and virulence. Entering quiescence, the bacterial cytoplasm displays signatures of the colloidal glass transition, with increasingly slow and heterogeneous diffusion. Also important for fitness during starvation is the formation of storage granules up to hundreds of nanometers in size. The complex state behavior of the bacterial cytoplasm is therefore important for their survival, but the physical nature of each of these processes is poorly understood. Our own cells are typically tens of microns in size and contain organelles including mitochondria, which originated from ancient bacterial endosymbionts. But little is known about the transport properties of the mitochondrial matrix, or how it responds to changes in mitochondrial membrane potential or energy production.
The goal of this project is to elucidate the organization and dynamics of the bacterial cytoplasm and the mitochondrial matrix. A major obstacle to studying the interior of bacteria and mitochondria is the relevant length scales, which lie below the diffraction limit. Furthermore, to observe and quantify their adaptive response, many cells must be measured. Our strategy to overcome both of these technical challenges is to use high-throughput super-resolution fluorescence microscopy. We have developed new microscopes, capable of capturing thousands of super-resolved cells in each experiment. We propose to translate these developments to dynamic structured illumination and long-term molecular tracking. Broadly applicable, this will also enable the quantitative study of the subcellular properties of single bacteria cells or mitochondria.
Summary
Bacteria cells appear to be less complex than our own cells -- yet they are better able to survive harsh conditions. Typically ~1 micron in size, they lack motor proteins; thus, they rely on fluctuations for intracellular transport. Bacteria in the environment often face starvation and exist in a non-proliferating quiescent state, which promotes antibiotic resistance and virulence. Entering quiescence, the bacterial cytoplasm displays signatures of the colloidal glass transition, with increasingly slow and heterogeneous diffusion. Also important for fitness during starvation is the formation of storage granules up to hundreds of nanometers in size. The complex state behavior of the bacterial cytoplasm is therefore important for their survival, but the physical nature of each of these processes is poorly understood. Our own cells are typically tens of microns in size and contain organelles including mitochondria, which originated from ancient bacterial endosymbionts. But little is known about the transport properties of the mitochondrial matrix, or how it responds to changes in mitochondrial membrane potential or energy production.
The goal of this project is to elucidate the organization and dynamics of the bacterial cytoplasm and the mitochondrial matrix. A major obstacle to studying the interior of bacteria and mitochondria is the relevant length scales, which lie below the diffraction limit. Furthermore, to observe and quantify their adaptive response, many cells must be measured. Our strategy to overcome both of these technical challenges is to use high-throughput super-resolution fluorescence microscopy. We have developed new microscopes, capable of capturing thousands of super-resolved cells in each experiment. We propose to translate these developments to dynamic structured illumination and long-term molecular tracking. Broadly applicable, this will also enable the quantitative study of the subcellular properties of single bacteria cells or mitochondria.
Max ERC Funding
2 366 835 €
Duration
Start date: 2019-10-01, End date: 2024-09-30
