Project acronym 321
Project from Cubic To Linear complexity in computational electromagnetics
Researcher (PI) Francesco Paolo ANDRIULLI
Host Institution (HI) POLITECNICO DI TORINO
Country Italy
Call Details Consolidator Grant (CoG), PE7, ERC-2016-COG
Summary Computational Electromagnetics (CEM) is the scientific field at the origin of all new modeling and simulation tools required by the constantly arising design challenges of emerging and future technologies in applied electromagnetics. As in many other technological fields, however, the trend in all emerging technologies in electromagnetic engineering is going towards miniaturized, higher density and multi-scale scenarios. Computationally speaking this translates in the steep increase of the number of degrees of freedom. Given that the design cost (the cost of a multi-right-hand side problem dominated by matrix inversion) can scale as badly as cubically with these degrees of freedom, this fact, as pointed out by many, will sensibly compromise the practical impact of CEM on future and emerging technologies.
For this reason, the CEM scientific community has been looking for years for a FFT-like paradigm shift: a dynamic fast direct solver providing a design cost that would scale only linearly with the degrees of freedom. Such a fast solver is considered today a Holy Grail of the discipline.
The Grand Challenge of 321 will be to tackle this Holy Grail in Computational Electromagnetics by investigating a dynamic Fast Direct Solver for Maxwell Problems that would run in a linear-instead-of-cubic complexity for an arbitrary number and configuration of degrees of freedom.
The failure of all previous attempts will be overcome by a game-changing transformation of the CEM classical problem that will leverage on a recent breakthrough of the PI. Starting from this, the project will investigate an entire new paradigm for impacting algorithms to achieve this grand challenge.
The impact of the FFT’s quadratic-to-linear paradigm shift shows how computational complexity reductions can be groundbreaking on applications. The cubic-to-linear paradigm shift, which the 321 project will aim for, will have such a rupturing impact on electromagnetic science and technology.
Summary
Computational Electromagnetics (CEM) is the scientific field at the origin of all new modeling and simulation tools required by the constantly arising design challenges of emerging and future technologies in applied electromagnetics. As in many other technological fields, however, the trend in all emerging technologies in electromagnetic engineering is going towards miniaturized, higher density and multi-scale scenarios. Computationally speaking this translates in the steep increase of the number of degrees of freedom. Given that the design cost (the cost of a multi-right-hand side problem dominated by matrix inversion) can scale as badly as cubically with these degrees of freedom, this fact, as pointed out by many, will sensibly compromise the practical impact of CEM on future and emerging technologies.
For this reason, the CEM scientific community has been looking for years for a FFT-like paradigm shift: a dynamic fast direct solver providing a design cost that would scale only linearly with the degrees of freedom. Such a fast solver is considered today a Holy Grail of the discipline.
The Grand Challenge of 321 will be to tackle this Holy Grail in Computational Electromagnetics by investigating a dynamic Fast Direct Solver for Maxwell Problems that would run in a linear-instead-of-cubic complexity for an arbitrary number and configuration of degrees of freedom.
The failure of all previous attempts will be overcome by a game-changing transformation of the CEM classical problem that will leverage on a recent breakthrough of the PI. Starting from this, the project will investigate an entire new paradigm for impacting algorithms to achieve this grand challenge.
The impact of the FFT’s quadratic-to-linear paradigm shift shows how computational complexity reductions can be groundbreaking on applications. The cubic-to-linear paradigm shift, which the 321 project will aim for, will have such a rupturing impact on electromagnetic science and technology.
Max ERC Funding
2 000 000 €
Duration
Start date: 2017-09-01, End date: 2023-08-31
Project acronym 3D-CAP
Project 3D micro-supercapacitors for embedded electronics
Researcher (PI) David Sarinn PECH
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Country France
Call Details Consolidator Grant (CoG), PE7, ERC-2017-COG
Summary The realization of high-performance micro-supercapacitors is currently a big challenge but the ineluctable applications requiring such miniaturized energy storage devices are continuously emerging, from wearable electronic gadgets to wireless sensor networks. Although they store less energy than micro-batteries, micro-supercapacitors can be charged and discharged very rapidly and exhibit a quasi-unlimited lifetime. The global scientific research is consequently largely focused on the improvement of their capacitance and energetic performances. However, to date, they are still far from being able to power sensors or electronic components.
Here I propose a 3D paradigm shift of micro-supercapacitor design to ensure increased energy storage capacities. Hydrous ruthenium dioxide (RuO2) is a pseudocapacitive material for supercapacitor electrode well-known for its high capacitance. A thin-film of ruthenium will be deposited by atomic layer deposition (ALD), followed by an electrochemical oxidation process, onto a high-surface-area 3D current collector prepared via an ingenious dynamic template built with hydrogen bubbles. The structural features of these 3D architectures will be controllably tailored by the processing methodologies. These electrodes will be combined with an innovative electrolyte in solid form (a protic ionogel) able to operate over an extended cell voltage. In a parallel investigation, we will develop a fundamental understanding of electrochemical reactions occurring at the nanoscale with a FIB-patterned (Focused Ion Beam) RuO2 nano-supercapacitor. The resulting 3D micro-supercapacitors should display extremely high power, long lifetime and – for the first time – energy densities competing or even exceeding that of micro-batteries. As a key achievement, prototypes will be designed using a new concept based on a self-adaptative micro-supercapacitors matrix, which arranges itself according to the global amount of energy stored.
Summary
The realization of high-performance micro-supercapacitors is currently a big challenge but the ineluctable applications requiring such miniaturized energy storage devices are continuously emerging, from wearable electronic gadgets to wireless sensor networks. Although they store less energy than micro-batteries, micro-supercapacitors can be charged and discharged very rapidly and exhibit a quasi-unlimited lifetime. The global scientific research is consequently largely focused on the improvement of their capacitance and energetic performances. However, to date, they are still far from being able to power sensors or electronic components.
Here I propose a 3D paradigm shift of micro-supercapacitor design to ensure increased energy storage capacities. Hydrous ruthenium dioxide (RuO2) is a pseudocapacitive material for supercapacitor electrode well-known for its high capacitance. A thin-film of ruthenium will be deposited by atomic layer deposition (ALD), followed by an electrochemical oxidation process, onto a high-surface-area 3D current collector prepared via an ingenious dynamic template built with hydrogen bubbles. The structural features of these 3D architectures will be controllably tailored by the processing methodologies. These electrodes will be combined with an innovative electrolyte in solid form (a protic ionogel) able to operate over an extended cell voltage. In a parallel investigation, we will develop a fundamental understanding of electrochemical reactions occurring at the nanoscale with a FIB-patterned (Focused Ion Beam) RuO2 nano-supercapacitor. The resulting 3D micro-supercapacitors should display extremely high power, long lifetime and – for the first time – energy densities competing or even exceeding that of micro-batteries. As a key achievement, prototypes will be designed using a new concept based on a self-adaptative micro-supercapacitors matrix, which arranges itself according to the global amount of energy stored.
Max ERC Funding
1 673 438 €
Duration
Start date: 2018-04-01, End date: 2023-03-31
Project acronym 3D-VIEW
Project Seeing the invisible: Light-based 3D imaging of opaque nanostructures
Researcher (PI) Stefan WITTE
Host Institution (HI) STICHTING NEDERLANDSE WETENSCHAPPELIJK ONDERZOEK INSTITUTEN
Country Netherlands
Call Details Consolidator Grant (CoG), PE7, ERC-2019-COG
Summary Nanostructures drive the world around us. Every modern electronic device contains integrated circuits and nano-electronics to provide its functionality. Advances in nanotechnology directly impact society by enabling smartphones, autonomous devices, the internet of things, data storage, and essentially all forms of advanced technology. Fabricating such nanostructures crucially depends on having the tools to make them visible without destroying them. Modern nanodevices often have complex three-dimensional architectures with small features in all dimensions. While imaging methods that achieve nanometer-scale resolution exist, there are currently no compact tools that can look inside 3D nanostructures made out of metals and semiconductors without damaging their delicate internal structure. I will address this challenge by developing compact tools to image 3D nanostructures in a non-invasive way. Even though most nanostructures are completely opaque to visible light, I will develop light-based methods, combined with computational imaging techniques developed in my previous ERC project, to look inside them with unprecedented resolution and contrast. Light-based imaging is unparalleled in speed and versatility, and allows contact-free detection. My proposal is to: 1) Use compact laser-produced soft-X-ray sources to image nanostructures with high 3D resolution and element-sensitive contrast; 2) Use laser-induced ultrasound pulses to image complex 3D nanostructures, even through strongly absorbing materials; 3) Employ computational imaging methods to reconstruct high-resolution 3D object images from the resulting complex diffraction signals. I will forge a coordinated research program to bring these concepts to reality. This program provides exciting prospects for fundamental science and industrial metrology. I will go beyond the state-of-the-art in nano-imaging, to extend our vision into the complex interior of the smallest structures found in science and technology.
Summary
Nanostructures drive the world around us. Every modern electronic device contains integrated circuits and nano-electronics to provide its functionality. Advances in nanotechnology directly impact society by enabling smartphones, autonomous devices, the internet of things, data storage, and essentially all forms of advanced technology. Fabricating such nanostructures crucially depends on having the tools to make them visible without destroying them. Modern nanodevices often have complex three-dimensional architectures with small features in all dimensions. While imaging methods that achieve nanometer-scale resolution exist, there are currently no compact tools that can look inside 3D nanostructures made out of metals and semiconductors without damaging their delicate internal structure. I will address this challenge by developing compact tools to image 3D nanostructures in a non-invasive way. Even though most nanostructures are completely opaque to visible light, I will develop light-based methods, combined with computational imaging techniques developed in my previous ERC project, to look inside them with unprecedented resolution and contrast. Light-based imaging is unparalleled in speed and versatility, and allows contact-free detection. My proposal is to: 1) Use compact laser-produced soft-X-ray sources to image nanostructures with high 3D resolution and element-sensitive contrast; 2) Use laser-induced ultrasound pulses to image complex 3D nanostructures, even through strongly absorbing materials; 3) Employ computational imaging methods to reconstruct high-resolution 3D object images from the resulting complex diffraction signals. I will forge a coordinated research program to bring these concepts to reality. This program provides exciting prospects for fundamental science and industrial metrology. I will go beyond the state-of-the-art in nano-imaging, to extend our vision into the complex interior of the smallest structures found in science and technology.
Max ERC Funding
2 000 000 €
Duration
Start date: 2020-10-01, End date: 2025-09-30
Project acronym AGILEFLIGHT
Project Low-latency Perception and Action for Agile Vision-based Flight
Researcher (PI) Davide SCARAMUZZA
Host Institution (HI) UNIVERSITAT ZURICH
Country Switzerland
Call Details Consolidator Grant (CoG), PE7, ERC-2019-COG
Summary Drones are disrupting industries, such as agriculture, package delivery, inspection, and search and rescue. However, they are still either controlled by a human pilot or heavily rely on GPS for navigating autonomously. The alternative to GPS are onboard sensors, such as cameras: from the raw data, a local 3D map of the environment is built, which is then used to plan a safe trajectory to the goal. While the underlying algorithms are well understood, we are still far from having autonomous drones that can navigate through complex environments as good as human pilots. State-of-the-art perception and control algorithms are mature but not robust: coping with unreliable state estimation, low-latency perception, real-time planning in dynamic environments, and tight coupling of perception and action under severe resource constraints are all still unsolved research problems. Another issue is that, because battery energy density is increasing at a very slow rate, drones need to navigate faster in order to accomplish more within their limited flight time. To obtain more agile robots, we need faster sensors and low-latency processing.
The goal of this project is to develop novel scientific methods that would allow me to demonstrate autonomous, vision-based, agile quadrotor navigation in unknown, GPS-denied, and cluttered environments with possibly moving obstacles, which can be as effective in terms of maneuverability and agility as those of professional drone pilots. The outcome would not only be beneficial for disaster response scenarios, but also for other scenarios, such as aerial delivery or inspection. To achieve this ambitious goal, I will first develop robust, low-latency, multimodal perception algorithms that combine the advantages of standard cameras with event cameras. Then, I will develop novel methods that unify perception and state estimation together with planning and control to enable agile maneuvers through cluttered, unknown, and dynamic environments.
Summary
Drones are disrupting industries, such as agriculture, package delivery, inspection, and search and rescue. However, they are still either controlled by a human pilot or heavily rely on GPS for navigating autonomously. The alternative to GPS are onboard sensors, such as cameras: from the raw data, a local 3D map of the environment is built, which is then used to plan a safe trajectory to the goal. While the underlying algorithms are well understood, we are still far from having autonomous drones that can navigate through complex environments as good as human pilots. State-of-the-art perception and control algorithms are mature but not robust: coping with unreliable state estimation, low-latency perception, real-time planning in dynamic environments, and tight coupling of perception and action under severe resource constraints are all still unsolved research problems. Another issue is that, because battery energy density is increasing at a very slow rate, drones need to navigate faster in order to accomplish more within their limited flight time. To obtain more agile robots, we need faster sensors and low-latency processing.
The goal of this project is to develop novel scientific methods that would allow me to demonstrate autonomous, vision-based, agile quadrotor navigation in unknown, GPS-denied, and cluttered environments with possibly moving obstacles, which can be as effective in terms of maneuverability and agility as those of professional drone pilots. The outcome would not only be beneficial for disaster response scenarios, but also for other scenarios, such as aerial delivery or inspection. To achieve this ambitious goal, I will first develop robust, low-latency, multimodal perception algorithms that combine the advantages of standard cameras with event cameras. Then, I will develop novel methods that unify perception and state estimation together with planning and control to enable agile maneuvers through cluttered, unknown, and dynamic environments.
Max ERC Funding
2 000 000 €
Duration
Start date: 2020-09-01, End date: 2025-08-31
Project acronym AMPHIBIANS
Project All Optical Manipulation of Photonic Metasurfaces for Biophotonic Applications in Microfluidic Environments
Researcher (PI) Andrea DI FALCO
Host Institution (HI) THE UNIVERSITY COURT OF THE UNIVERSITY OF ST ANDREWS
Country United Kingdom
Call Details Consolidator Grant (CoG), PE7, ERC-2018-COG
Summary The current trend in biophotonics is to try and replicate the same ease and precision that our hands, eyes and ears offer at the macroscopic level, e.g. to hold, observe, squeeze and pull, rotate, cut and probe biological specimens in microfluidic environments. The bidding to get closer and closer to the object of interest has prompted the development of extremely advanced manipulation techniques at scales comparable to that of the wavelength of light. However, the fact that the optical beam can only access the microfluidic chip from the narrow aperture of a microscopic objective limits the versatility of the photonic function that can be realized.
With this project, the applicant proposes to introduce a new biophotonic platform based on the all optical manipulation of flexible photonic metasurfaces. These artificial two-dimensional materials have virtually arbitrary photonic responses and have an intrinsic exceptional mechanical stability. This cross-disciplinary project, bridging photonics, material sciences and biology, will enable the adoption of the most modern and advanced photonic designs in microfluidic environments, with transformative benefits for microscopy and biophotonic applications at the interface of molecular and cell biology.
Summary
The current trend in biophotonics is to try and replicate the same ease and precision that our hands, eyes and ears offer at the macroscopic level, e.g. to hold, observe, squeeze and pull, rotate, cut and probe biological specimens in microfluidic environments. The bidding to get closer and closer to the object of interest has prompted the development of extremely advanced manipulation techniques at scales comparable to that of the wavelength of light. However, the fact that the optical beam can only access the microfluidic chip from the narrow aperture of a microscopic objective limits the versatility of the photonic function that can be realized.
With this project, the applicant proposes to introduce a new biophotonic platform based on the all optical manipulation of flexible photonic metasurfaces. These artificial two-dimensional materials have virtually arbitrary photonic responses and have an intrinsic exceptional mechanical stability. This cross-disciplinary project, bridging photonics, material sciences and biology, will enable the adoption of the most modern and advanced photonic designs in microfluidic environments, with transformative benefits for microscopy and biophotonic applications at the interface of molecular and cell biology.
Max ERC Funding
1 999 524 €
Duration
Start date: 2019-02-01, End date: 2024-01-31
Project acronym APOLLO
Project Advanced Signal Processing Technologies for Wireless Powered Communications
Researcher (PI) Ioannis Krikidis
Host Institution (HI) UNIVERSITY OF CYPRUS
Country Cyprus
Call Details Consolidator Grant (CoG), PE7, ERC-2018-COG
Summary Wireless power transfer (WPT), pioneered by Tesla, is an idea at least as old as radio communications. However, on the one hand, due to health concerns and the large antenna dimensions required for transmission of high energy levels, until recently WPT has been limited mostly to very short distance applications. On the other hand, recent advances in silicon technology have significantly reduced the energy needs of electronic systems, making WPT over radio waves a potential source of energy for low power devices. Although WPT through radio waves has already found various short-range applications (such as the radio-frequency identification technology, healthcare monitoring etc.), its integration as a building block in the operation of wireless communications systems is still unexploited. On the other hand, conventional radio wave based information and energy transmissions have largely been designed separately. However, many applications can benefit from simultaneous wireless information and power transfer (SWIPT).
The overall objective of the APOLLO project is to study the integration of WPT/SWIPT technology into future wireless communication systems. Compared to past and current research efforts in this area, our technical approach is deeply interdisciplinary and more comprehensive, combining the expertise of wireless communications, control theory, information theory, optimization, and electronics/microwave engineering.
The key outcomes of the project include: 1) a rigorous and complete mathematical theory for WPT/SWIPT via information/communication/control theoretic studies; 2) new physical and cross-layer mechanisms that will enable the integration of WPT/SWIPT into future communication systems; 3) new network architectures that will fully exploit potential benefits of WPT/SWIPT; and 4) development of a proof-of-concept by implementing highly-efficient and multi-band metamaterial energy harvesting sensors for SWIPT.
Summary
Wireless power transfer (WPT), pioneered by Tesla, is an idea at least as old as radio communications. However, on the one hand, due to health concerns and the large antenna dimensions required for transmission of high energy levels, until recently WPT has been limited mostly to very short distance applications. On the other hand, recent advances in silicon technology have significantly reduced the energy needs of electronic systems, making WPT over radio waves a potential source of energy for low power devices. Although WPT through radio waves has already found various short-range applications (such as the radio-frequency identification technology, healthcare monitoring etc.), its integration as a building block in the operation of wireless communications systems is still unexploited. On the other hand, conventional radio wave based information and energy transmissions have largely been designed separately. However, many applications can benefit from simultaneous wireless information and power transfer (SWIPT).
The overall objective of the APOLLO project is to study the integration of WPT/SWIPT technology into future wireless communication systems. Compared to past and current research efforts in this area, our technical approach is deeply interdisciplinary and more comprehensive, combining the expertise of wireless communications, control theory, information theory, optimization, and electronics/microwave engineering.
The key outcomes of the project include: 1) a rigorous and complete mathematical theory for WPT/SWIPT via information/communication/control theoretic studies; 2) new physical and cross-layer mechanisms that will enable the integration of WPT/SWIPT into future communication systems; 3) new network architectures that will fully exploit potential benefits of WPT/SWIPT; and 4) development of a proof-of-concept by implementing highly-efficient and multi-band metamaterial energy harvesting sensors for SWIPT.
Max ERC Funding
1 930 625 €
Duration
Start date: 2019-07-01, End date: 2025-03-31
Project acronym BCINET
Project Non-invasive decoding of brain communication patterns to ease motor restoration after stroke
Researcher (PI) Fabrizio De Vico Fallani
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Country France
Call Details Consolidator Grant (CoG), PE7, ERC-2019-COG
Summary Human-computer interfaces are increasingly explored to facilitate interaction with the external world. Brain-computer interfaces (BCIs), bypassing the skeletomuscular system, are particularly promising for assisting paralyzed people in control and communication, but also for boosting neuromotor rehabilitation.
Despite their potential, the societal impact of BCIs is dramatically limited by the poor usability in real-life applications. While many solutions have been proposed - from the identification of the best classification algorithm to the type of sensory feedback - the accuracy is still highly variable across subjects and BCIs cannot be used by everyone. Critically, these approaches have implicitly assumed that the user’s intent could be decoded by examining the activity of single brain areas. Today, we know that this is not true as the brain functioning essentially depends on a complex network of interactions between differently specialized areas.
The grand challenge of this project is to develop a novel generation of BCIs that integrate the user’s brain network information for enhancing accuracy and usability. Based on this approach, we will experiment innovative BCI prototypes to restore the lost motor functions in patients suffering from stroke.
This project relies on a unifying framework that analyses and models brain networks by means of analytical tools derived from graph theory and complex systems science. By recruiting diverse neuroimaging and experimental methods, within a modern computational framework, we aim to i) identify new control features for enhancing BCI accuracy, ii) study the brain dynamics of human learning for improving adaptive BCI architectures, and iii) optimize brain stimulation techniques for boosting BCI skill acquisition.
This project can significantly improve BCI usability as well as determining how brain lesions compromise brain functioning and which solutions are most effective to unlock motor restoration after stroke.
Summary
Human-computer interfaces are increasingly explored to facilitate interaction with the external world. Brain-computer interfaces (BCIs), bypassing the skeletomuscular system, are particularly promising for assisting paralyzed people in control and communication, but also for boosting neuromotor rehabilitation.
Despite their potential, the societal impact of BCIs is dramatically limited by the poor usability in real-life applications. While many solutions have been proposed - from the identification of the best classification algorithm to the type of sensory feedback - the accuracy is still highly variable across subjects and BCIs cannot be used by everyone. Critically, these approaches have implicitly assumed that the user’s intent could be decoded by examining the activity of single brain areas. Today, we know that this is not true as the brain functioning essentially depends on a complex network of interactions between differently specialized areas.
The grand challenge of this project is to develop a novel generation of BCIs that integrate the user’s brain network information for enhancing accuracy and usability. Based on this approach, we will experiment innovative BCI prototypes to restore the lost motor functions in patients suffering from stroke.
This project relies on a unifying framework that analyses and models brain networks by means of analytical tools derived from graph theory and complex systems science. By recruiting diverse neuroimaging and experimental methods, within a modern computational framework, we aim to i) identify new control features for enhancing BCI accuracy, ii) study the brain dynamics of human learning for improving adaptive BCI architectures, and iii) optimize brain stimulation techniques for boosting BCI skill acquisition.
This project can significantly improve BCI usability as well as determining how brain lesions compromise brain functioning and which solutions are most effective to unlock motor restoration after stroke.
Max ERC Funding
1 999 720 €
Duration
Start date: 2020-10-01, End date: 2025-09-30
Project acronym BEATRICE
Project Beyond Massive MIMO: Living at the Interface of Electromagnetics and Information Theory
Researcher (PI) Michail MATTHAIOU
Host Institution (HI) THE QUEEN'S UNIVERSITY OF BELFAST
Country United Kingdom
Call Details Consolidator Grant (CoG), PE7, ERC-2020-COG
Summary Massive multiple-input multiple-output (MaMi) is now a core technology for 5G networks. With MaMi, we refer to systems with an unconventionally large number (e.g. hundreds or even thousands) of base station antennas simultaneously serving tens (or even hundreds) of users. To date, the development of MaMi has been exclusively based on information theory (IT) tailored towards cellular communications. While IT is undoubtedly a versatile mathematical tool, it is based on mathematical logic. This theoretical framework now needs to be extended and reshaped to: (i) account for the unique electromagnetic (EM) properties and (ii) incorporate the main feature of future MaMi-based communication systems, namely their capability of sensing the system’s response to the radio waves, and thereby informing its modification. Looking ahead, MaMi will have far more general applications: optical communications, radar, and wireless power transfer to name a few. The grand question that the proposed research will address is: Are the existing IT tools sufficient to understand the physical phenomena and develop the upcoming generation of MaMi-based systems in ten years from now? BEATRICE will address this fundamental question by unifying EM theory and IT and pave the way for an extended range of applications supported by massive antenna arrays after 2025.
The specific project objectives are to:
O1) Redefine the information theoretic modelling of concurrent and future MaMi-based systems using knowledge of unique EM characteristics, thereby quantifying their realisable potential.
O2) Develop new topological designs and modulation techniques for robust communication by harnessing knowledge about the EM properties of the transceivers and the propagation medium.
O3) Leverage the world-class T&M facilities at QUB, to design, fabricate and measure novel array topologies which will be able to support a plethora of MaMi-based applications.
Summary
Massive multiple-input multiple-output (MaMi) is now a core technology for 5G networks. With MaMi, we refer to systems with an unconventionally large number (e.g. hundreds or even thousands) of base station antennas simultaneously serving tens (or even hundreds) of users. To date, the development of MaMi has been exclusively based on information theory (IT) tailored towards cellular communications. While IT is undoubtedly a versatile mathematical tool, it is based on mathematical logic. This theoretical framework now needs to be extended and reshaped to: (i) account for the unique electromagnetic (EM) properties and (ii) incorporate the main feature of future MaMi-based communication systems, namely their capability of sensing the system’s response to the radio waves, and thereby informing its modification. Looking ahead, MaMi will have far more general applications: optical communications, radar, and wireless power transfer to name a few. The grand question that the proposed research will address is: Are the existing IT tools sufficient to understand the physical phenomena and develop the upcoming generation of MaMi-based systems in ten years from now? BEATRICE will address this fundamental question by unifying EM theory and IT and pave the way for an extended range of applications supported by massive antenna arrays after 2025.
The specific project objectives are to:
O1) Redefine the information theoretic modelling of concurrent and future MaMi-based systems using knowledge of unique EM characteristics, thereby quantifying their realisable potential.
O2) Develop new topological designs and modulation techniques for robust communication by harnessing knowledge about the EM properties of the transceivers and the propagation medium.
O3) Leverage the world-class T&M facilities at QUB, to design, fabricate and measure novel array topologies which will be able to support a plethora of MaMi-based applications.
Max ERC Funding
1 997 797 €
Duration
Start date: 2021-06-01, End date: 2026-05-31
Project acronym BNYQ
Project Breaking the Nyquist Barrier: A New Paradigm in Data Conversion and Transmission
Researcher (PI) Yonina Eldar
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Country Israel
Call Details Consolidator Grant (CoG), PE7, ERC-2014-CoG
Summary Digital signal processing (DSP) is a revolutionary paradigm shift enabling processing of physical data in the digital domain where design and implementation are considerably simplified. However, state-of-the-art analog-to-digital convertors (ADCs) preclude high-rate wideband sampling and processing with low cost and energy consumption, presenting a major bottleneck. This is mostly due to a traditional assumption that sampling must be performed at the Nyquist rate, that is, twice the signal bandwidth. Modern applications including communications, medical imaging, radar and more use signals with high bandwidth, resulting in prohibitively large Nyquist rates.
Our ambitious goal is to introduce a paradigm shift in ADC design that will enable systems capable of low-rate, wideband sensing and low-rate DSP.
While DSP has a rich history in exploiting structure to reduce dimensionality and perform efficient parameter extraction, current ADCs do not exploit such knowledge.
We challenge current practice that separates the sampling stage from the processing stage and exploit structure in analog signals already in the ADC, to drastically reduce the sampling and processing rates.
Our preliminary data shows that this allows substantial savings in sampling and processing rates --- we show rate reduction of 1/28 in ultrasound imaging, and 1/30 in radar detection.
To achieve our overreaching goal we focus on three interconnected objectives -- developing the 1) theory 2) hardware and 3) applications of sub-Nyquist sampling.
Our methodology ties together two areas on the frontier of signal processing: compressed sensing (CS), focused on finite length vectors, and analog sampling. Our research plan also inherently relies on advances in several other important areas within signal processing and combines multi-disciplinary research at the intersection of signal processing, information theory, optimization, estimation theory and hardware design.
Summary
Digital signal processing (DSP) is a revolutionary paradigm shift enabling processing of physical data in the digital domain where design and implementation are considerably simplified. However, state-of-the-art analog-to-digital convertors (ADCs) preclude high-rate wideband sampling and processing with low cost and energy consumption, presenting a major bottleneck. This is mostly due to a traditional assumption that sampling must be performed at the Nyquist rate, that is, twice the signal bandwidth. Modern applications including communications, medical imaging, radar and more use signals with high bandwidth, resulting in prohibitively large Nyquist rates.
Our ambitious goal is to introduce a paradigm shift in ADC design that will enable systems capable of low-rate, wideband sensing and low-rate DSP.
While DSP has a rich history in exploiting structure to reduce dimensionality and perform efficient parameter extraction, current ADCs do not exploit such knowledge.
We challenge current practice that separates the sampling stage from the processing stage and exploit structure in analog signals already in the ADC, to drastically reduce the sampling and processing rates.
Our preliminary data shows that this allows substantial savings in sampling and processing rates --- we show rate reduction of 1/28 in ultrasound imaging, and 1/30 in radar detection.
To achieve our overreaching goal we focus on three interconnected objectives -- developing the 1) theory 2) hardware and 3) applications of sub-Nyquist sampling.
Our methodology ties together two areas on the frontier of signal processing: compressed sensing (CS), focused on finite length vectors, and analog sampling. Our research plan also inherently relies on advances in several other important areas within signal processing and combines multi-disciplinary research at the intersection of signal processing, information theory, optimization, estimation theory and hardware design.
Max ERC Funding
2 400 000 €
Duration
Start date: 2015-08-01, End date: 2021-06-30
Project acronym BrightEyes
Project Multi-Parameter Live-Cell Observation of Biomolecular Processes with Single-Photon Detector Array
Researcher (PI) Giuseppe Vicidomini
Host Institution (HI) FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA
Country Italy
Call Details Consolidator Grant (CoG), PE7, ERC-2018-COG
Summary Fluorescence single-molecule (SM) detection techniques have the potential to provide insights into the complex functions, structures and interactions of individual, specifically labelled biomolecules. However, current SM techniques work properly only when the biomolecule is observed in controlled environments, e.g., immobilized on a glass surface. Observation of biomolecular processes in living (multi)cellular environments – which is fundamental for sound biological conclusion – always comes with a price, such as invasiveness, limitations in the accessible information and constraints in the spatial and temporal scales.
The overall objective of the BrightEyes project is to break the above limitations by creating a novel SM approach compatible with the state-of-the-art biomolecule-labelling protocols, able to track a biomolecule deep inside (multi)cellular environments – with temporal resolution in the microsecond scale, and with hundreds of micrometres tracking range – and simultaneously observe its structural changes, its nano- and micro-environments.
Specifically, by exploring a novel single-photon detectors array, the BrightEyes project will implement an optical system, able to continuously (i) track in real-time the biomolecule of interest from which to decode its dynamics and interactions; (ii) measure the nano-environment fluorescence spectroscopy properties, such as lifetime, photon-pair correlation and intensity, from which to extract the biochemical properties of the nano-environment, the structural properties of the biomolecule – via SM-FRET and anti-bunching – and the interactions of the biomolecule with other biomolecular species – via STED-FCS; (iii) visualize the sub-cellular structures within the micro-environment with sub-diffraction spatial resolution – via STED and image scanning microscopy.
This unique paradigm will enable unprecedented studies of biomolecular behaviours, interactions and self-organization at near-physiological conditions.
Summary
Fluorescence single-molecule (SM) detection techniques have the potential to provide insights into the complex functions, structures and interactions of individual, specifically labelled biomolecules. However, current SM techniques work properly only when the biomolecule is observed in controlled environments, e.g., immobilized on a glass surface. Observation of biomolecular processes in living (multi)cellular environments – which is fundamental for sound biological conclusion – always comes with a price, such as invasiveness, limitations in the accessible information and constraints in the spatial and temporal scales.
The overall objective of the BrightEyes project is to break the above limitations by creating a novel SM approach compatible with the state-of-the-art biomolecule-labelling protocols, able to track a biomolecule deep inside (multi)cellular environments – with temporal resolution in the microsecond scale, and with hundreds of micrometres tracking range – and simultaneously observe its structural changes, its nano- and micro-environments.
Specifically, by exploring a novel single-photon detectors array, the BrightEyes project will implement an optical system, able to continuously (i) track in real-time the biomolecule of interest from which to decode its dynamics and interactions; (ii) measure the nano-environment fluorescence spectroscopy properties, such as lifetime, photon-pair correlation and intensity, from which to extract the biochemical properties of the nano-environment, the structural properties of the biomolecule – via SM-FRET and anti-bunching – and the interactions of the biomolecule with other biomolecular species – via STED-FCS; (iii) visualize the sub-cellular structures within the micro-environment with sub-diffraction spatial resolution – via STED and image scanning microscopy.
This unique paradigm will enable unprecedented studies of biomolecular behaviours, interactions and self-organization at near-physiological conditions.
Max ERC Funding
1 861 250 €
Duration
Start date: 2019-09-01, End date: 2024-08-31
