Project acronym INVPROB
Project Inverse Problems
Researcher (PI) Lassi Juhani Päivärinta
Host Institution (HI) TALLINNA TEHNIKAULIKOOL
Call Details Advanced Grant (AdG), PE1, ERC-2010-AdG_20100224
Summary Inverse problems constitute an interdisciplinary field of science concentrating on the mathematical theory and practical interpretation of indirect measurements. Their applications include medical imaging, atmospheric remote sensing, industrial process monitoring, and astronomical imaging. The common feature is extreme sensitivity to measurement noise. Computerized tomography, MRI, and exploration of the interior of earth by using earthquake data are typical inverse problems where mathematics has played an important role. By using the methods of inverse problems it is possible to bring modern mathematics to a vast number of applied fields. Genuine scientific innovations that are found in mathematical research, say in geometry, stochastics, or analysis, can be brought to real life applications through modelling. The solutions are often found by combining recent theoretical and computational advances. The study of inverse problems is one of the most active and fastest growing areas of modern applied mathematics, and the most interdisciplinary field of mathematics or even science in general.
The exciting but high risk problems in the research plan of the PI include mathematics of invisibility cloaking, invisible patterns, practical algorithms for imaging, and random quantum systems. Progress in these problems could have a considerable impact in applications such as construction of metamaterials for invisible optic fibre cables, scopes for MRI devices, and early screening for breast cancer. The progress here necessitates international collaboration. This will be realized in upcoming programs on inverse problems. The PI is involved in organizing semester programs in inverse problems at MSRI in 2010, Isaac Newton Institute in 2011, and Mittag-Leffler -institute in 2012.
Summary
Inverse problems constitute an interdisciplinary field of science concentrating on the mathematical theory and practical interpretation of indirect measurements. Their applications include medical imaging, atmospheric remote sensing, industrial process monitoring, and astronomical imaging. The common feature is extreme sensitivity to measurement noise. Computerized tomography, MRI, and exploration of the interior of earth by using earthquake data are typical inverse problems where mathematics has played an important role. By using the methods of inverse problems it is possible to bring modern mathematics to a vast number of applied fields. Genuine scientific innovations that are found in mathematical research, say in geometry, stochastics, or analysis, can be brought to real life applications through modelling. The solutions are often found by combining recent theoretical and computational advances. The study of inverse problems is one of the most active and fastest growing areas of modern applied mathematics, and the most interdisciplinary field of mathematics or even science in general.
The exciting but high risk problems in the research plan of the PI include mathematics of invisibility cloaking, invisible patterns, practical algorithms for imaging, and random quantum systems. Progress in these problems could have a considerable impact in applications such as construction of metamaterials for invisible optic fibre cables, scopes for MRI devices, and early screening for breast cancer. The progress here necessitates international collaboration. This will be realized in upcoming programs on inverse problems. The PI is involved in organizing semester programs in inverse problems at MSRI in 2010, Isaac Newton Institute in 2011, and Mittag-Leffler -institute in 2012.
Max ERC Funding
1 800 000 €
Duration
Start date: 2011-03-01, End date: 2016-02-29
Project acronym Kerr
Project How do chiral superconductors break time-reversal symmetry? – Kerr spectroscopy study
Researcher (PI) Girsh Blumberg
Host Institution (HI) KEEMILISE JA BIOLOOGILISE FUUSIKA INSTITUUT
Call Details Advanced Grant (AdG), PE3, ERC-2019-ADG
Summary Unconventional superconductivity is extensively sought for in contemporary research. Of particular interest are chiral superconductors which possess non-trivial topological properties resulting in superconducting (SC) order parameters (OPs) that may break time-reversal symmetry (TRS). The possibility of applications to topological quantum computation have placed such materials at the forefront of condensed matter research. Recent measurements of the polar Kerr effect (PKE), in which a rotation of polarization is detected for a beam of light reflected from the surface of a superconductor, have emerged as a key experimental probe of TRS breaking. Here we propose the development of a new generation of spectroscopic instrumentation for the PKE spectroscopy in the sub-THz frequency range, the energy scale that is comparable with the SC gap magnitude of unconventional superconductors. The THz range PKE spectroscopy will enable to study the broken symmetries, the origin of unconventional pairing, the in-gap collective modes, and the structures of the SC OPs. We plan to measure the PKE at sub-THz frequencies and with sub-milli-radian angular resolution from a variety of unconventional superconductors that are cooled to 100 mK, deep into SC state. The aim is to understand the basic mechanisms leading to unconventional superconductivity in these systems in order to find answers to the fundamental questions, such as: What is the structure of the SC gap in Sr2RuO4, URu2Si2, and UPt3? Is the TRS broken in (a) the Hidden Order state and in (b) SC state of URu2Si2? Which symmetries are broken at the transition from the HO state into the unconventional SC state? – and to elucidate the microscopic origin of superconductivity in the new families of unconventional superconductors. In a broader view, the project will keep Estonian physics on the forefront of science through new scientific contacts and will promote physics education by engaging students and postdocs in the research.
Summary
Unconventional superconductivity is extensively sought for in contemporary research. Of particular interest are chiral superconductors which possess non-trivial topological properties resulting in superconducting (SC) order parameters (OPs) that may break time-reversal symmetry (TRS). The possibility of applications to topological quantum computation have placed such materials at the forefront of condensed matter research. Recent measurements of the polar Kerr effect (PKE), in which a rotation of polarization is detected for a beam of light reflected from the surface of a superconductor, have emerged as a key experimental probe of TRS breaking. Here we propose the development of a new generation of spectroscopic instrumentation for the PKE spectroscopy in the sub-THz frequency range, the energy scale that is comparable with the SC gap magnitude of unconventional superconductors. The THz range PKE spectroscopy will enable to study the broken symmetries, the origin of unconventional pairing, the in-gap collective modes, and the structures of the SC OPs. We plan to measure the PKE at sub-THz frequencies and with sub-milli-radian angular resolution from a variety of unconventional superconductors that are cooled to 100 mK, deep into SC state. The aim is to understand the basic mechanisms leading to unconventional superconductivity in these systems in order to find answers to the fundamental questions, such as: What is the structure of the SC gap in Sr2RuO4, URu2Si2, and UPt3? Is the TRS broken in (a) the Hidden Order state and in (b) SC state of URu2Si2? Which symmetries are broken at the transition from the HO state into the unconventional SC state? – and to elucidate the microscopic origin of superconductivity in the new families of unconventional superconductors. In a broader view, the project will keep Estonian physics on the forefront of science through new scientific contacts and will promote physics education by engaging students and postdocs in the research.
Max ERC Funding
2 489 976 €
Duration
Start date: 2021-01-01, End date: 2025-12-31
Project acronym PIX
Project The Process Improvement Explorer: Automated Discovery and Assessment of Business Process Improvement Opportunities
Researcher (PI) Marlon DUMAS
Host Institution (HI) TARTU ULIKOOL
Call Details Advanced Grant (AdG), PE6, ERC-2018-ADG
Summary Business processes are the operational backbone of modern organizations. Their continuous improvement is key to the achievement of business objectives, be it with respect to efficiency, quality, compliance, or agility. Accordingly, a common task for process analysts is to discover and assess process improvement opportunities, i.e. changes to one or more processes, which are likely to improve them with respect to one or more performance measures. Current approaches to discover process improvement opportunities are expert-driven. In these approaches, data are used to assess opportunities derived from experience and intuition rather than to discover them in the first place. Moreover, as the assessment of opportunities is manual, analysts can only explore a fraction thereof.
PIX will build the foundations of a new generation of process improvement methods that do not exclusively rely on guidelines and heuristics, but rather on a systematic exploration of a space of possible changes derived from process execution data. Specifically, PIX will develop conceptual frameworks and algorithms to analyze process execution data in order to discover process changes corresponding to possible improvement opportunities, including changes in the control-flow dependencies between activities, partial automation of activities, changes in resource allocation rules, or changes in decision rules that may reduce wastes or negative outcomes. Each change will be associated with a multi-dimensional utility, thus allowing us to map a process improvement problem to an optimization problem over a multidimensional space. Given this mapping, PIX will develop efficient and incremental methods to search through said spaces in order to find Pareto-optimal groups of changes. The outputs will be embodied in a first-of-its-kind tool for automated process improvement discovery, which will lift the focus in the field of process mining from analyzing as-is processes to designing to-be processes.
Summary
Business processes are the operational backbone of modern organizations. Their continuous improvement is key to the achievement of business objectives, be it with respect to efficiency, quality, compliance, or agility. Accordingly, a common task for process analysts is to discover and assess process improvement opportunities, i.e. changes to one or more processes, which are likely to improve them with respect to one or more performance measures. Current approaches to discover process improvement opportunities are expert-driven. In these approaches, data are used to assess opportunities derived from experience and intuition rather than to discover them in the first place. Moreover, as the assessment of opportunities is manual, analysts can only explore a fraction thereof.
PIX will build the foundations of a new generation of process improvement methods that do not exclusively rely on guidelines and heuristics, but rather on a systematic exploration of a space of possible changes derived from process execution data. Specifically, PIX will develop conceptual frameworks and algorithms to analyze process execution data in order to discover process changes corresponding to possible improvement opportunities, including changes in the control-flow dependencies between activities, partial automation of activities, changes in resource allocation rules, or changes in decision rules that may reduce wastes or negative outcomes. Each change will be associated with a multi-dimensional utility, thus allowing us to map a process improvement problem to an optimization problem over a multidimensional space. Given this mapping, PIX will develop efficient and incremental methods to search through said spaces in order to find Pareto-optimal groups of changes. The outputs will be embodied in a first-of-its-kind tool for automated process improvement discovery, which will lift the focus in the field of process mining from analyzing as-is processes to designing to-be processes.
Max ERC Funding
2 349 965 €
Duration
Start date: 2019-09-01, End date: 2024-08-31
Project acronym Sip-Vol+
Project Stress-Induced Plant Volatiles in Biosphere-Atmosphere System
Researcher (PI) Ülo Niinemets
Host Institution (HI) EESTI MAAULIKOOL
Call Details Advanced Grant (AdG), LS8, ERC-2012-ADG_20120314
Summary Vegetation forms a key interface between Earth surface and atmosphere. The important role of vegetation carbon, water and energy exchanges is well established, but the overall impact of plant trace gas (VOC) emission for large-scale Earth processes is poorly understood. Although it is widely accepted that VOCs play major roles in the formation of ozone, secondary organic aerosols (SOA) and cloud condensation nuclei (CNN) with potentially profound impacts on air quality and Earth radiative balance, the research has so far focused only on constitutive emissions from species considered “emitters”. However, differently from constitutive VOCs emitted only by certain species, all plant species can be triggered to emit induced VOCs under abiotic and biotic stress. So far, induced high-reactivity VOCs are not considered in global VOC budget, and thus, this proposal tests the key assumption that VOC emissions worldwide have been vastly underestimated. As global change is resulting in higher level of stress in Earth ecosystems, the relevance of induced emissions is further expected to gain in importance. The current project has the overall objective to evaluate the effect of plant-generated VOC emissions on air composition and environment under global change, with particular emphasis on the role of VOCs induced in response to environmental stress. The study first quantifies the VOC production vs. stress severity relationships across species with differing stress tolerance and advances and parameterizes the qualitative induced VOC model developed by PI. The novel quantitative model is further verified by flux measurements and scaled up to regional and global scales to assess the contribution of induced emissions to overall VOC budget, and study the feedbacks between stress, ozone, SOA and CNN formation and the Earth climate using an hierarchy of available models. This highly cross-disciplinary project is expected to result in key contributions in two research fields of major significance: plant stress tolerance from molecules to globe and the role of vegetation component in atmospheric reactivity and Earth climate. The first part of the study provides fundamental insight into the stress responsiveness of plants with differing tolerance to environmental limitations, extending “leaf economics spectrum”, a hotspot of current plant ecology research. The second part provides quantitative information on large-scale importance of plant VOCs in globally changing climates with major relevance for understanding the role of plants in the Earth’s large scale processes.
Summary
Vegetation forms a key interface between Earth surface and atmosphere. The important role of vegetation carbon, water and energy exchanges is well established, but the overall impact of plant trace gas (VOC) emission for large-scale Earth processes is poorly understood. Although it is widely accepted that VOCs play major roles in the formation of ozone, secondary organic aerosols (SOA) and cloud condensation nuclei (CNN) with potentially profound impacts on air quality and Earth radiative balance, the research has so far focused only on constitutive emissions from species considered “emitters”. However, differently from constitutive VOCs emitted only by certain species, all plant species can be triggered to emit induced VOCs under abiotic and biotic stress. So far, induced high-reactivity VOCs are not considered in global VOC budget, and thus, this proposal tests the key assumption that VOC emissions worldwide have been vastly underestimated. As global change is resulting in higher level of stress in Earth ecosystems, the relevance of induced emissions is further expected to gain in importance. The current project has the overall objective to evaluate the effect of plant-generated VOC emissions on air composition and environment under global change, with particular emphasis on the role of VOCs induced in response to environmental stress. The study first quantifies the VOC production vs. stress severity relationships across species with differing stress tolerance and advances and parameterizes the qualitative induced VOC model developed by PI. The novel quantitative model is further verified by flux measurements and scaled up to regional and global scales to assess the contribution of induced emissions to overall VOC budget, and study the feedbacks between stress, ozone, SOA and CNN formation and the Earth climate using an hierarchy of available models. This highly cross-disciplinary project is expected to result in key contributions in two research fields of major significance: plant stress tolerance from molecules to globe and the role of vegetation component in atmospheric reactivity and Earth climate. The first part of the study provides fundamental insight into the stress responsiveness of plants with differing tolerance to environmental limitations, extending “leaf economics spectrum”, a hotspot of current plant ecology research. The second part provides quantitative information on large-scale importance of plant VOCs in globally changing climates with major relevance for understanding the role of plants in the Earth’s large scale processes.
Max ERC Funding
2 259 366 €
Duration
Start date: 2013-05-01, End date: 2018-04-30
