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Project acronym LEARN
Project Limitations, Estimation, Adaptivity, Reinforcement and Networks in System Identification
Researcher (PI) Lennart Ljung
Host Institution (HI) LINKOPINGS UNIVERSITET
Summary The objective with this proposal is to provide design tools and algorithms for model management in robust, adaptive and autonomous engineering systems. The increasing demands on reliable models for systems of ever greater complexity have pointed to several insufficiencies in today's techniques for model construction. The proposal addresses key areas where new ideas are required. Modeling a central issue in many scientific fields. System Identification is the term used in the Automatic Control Community for the area of building mathematical models of dynamical systems from observed input and output signals, but several other research communities work with the same problem under different names, such as (data-driven) learning. We have identified five specific themes where progress is both acutely needed and feasible: 1.	Encounters with Convex Programming Techniques: How to capitalize on the remarkable recent progress in convex and semidefinite programming to obtain efficient, robust and reliable algorithmic solutions. 2.	Fundamental Limitations: To develop and elucidate what are the limits of model accuracy, regardless of the modeling method. This can be seen as a theory rooted in the Cramer-Rao inequality in the spirit of invariance results and lower bounds characterizing, e.g., Information Theory. 3.	Experiment Design and Reinforcement Techniques: Study how well tailored and ``cheap'' experiments can extract essential information about isolated model properties. Also study how such methods may relate to general reinforcement techniques. 4.	Potentials of Non-parametric Models: How to incorporate and adjust techniques from adjacent research communities, e.g. concerning manifold learning and Gaussian Processes in machine learning. 5.	Managing Structural Constraints: To develop structure preserving identification methods for networked and decentralized systems. We have ideas how to approach each of these themes, and initial attempts are promising.
The objective with this proposal is to provide design tools and algorithms for model management in robust, adaptive and autonomous engineering systems. The increasing demands on reliable models for systems of ever greater complexity have pointed to several insufficiencies in today's techniques for model construction. The proposal addresses key areas where new ideas are required. Modeling a central issue in many scientific fields. System Identification is the term used in the Automatic Control Community for the area of building mathematical models of dynamical systems from observed input and output signals, but several other research communities work with the same problem under different names, such as (data-driven) learning. We have identified five specific themes where progress is both acutely needed and feasible: 1.	Encounters with Convex Programming Techniques: How to capitalize on the remarkable recent progress in convex and semidefinite programming to obtain efficient, robust and reliable algorithmic solutions. 2.	Fundamental Limitations: To develop and elucidate what are the limits of model accuracy, regardless of the modeling method. This can be seen as a theory rooted in the Cramer-Rao inequality in the spirit of invariance results and lower bounds characterizing, e.g., Information Theory. 3.	Experiment Design and Reinforcement Techniques: Study how well tailored and ``cheap'' experiments can extract essential information about isolated model properties. Also study how such methods may relate to general reinforcement techniques. 4.	Potentials of Non-parametric Models: How to incorporate and adjust techniques from adjacent research communities, e.g. concerning manifold learning and Gaussian Processes in machine learning. 5.	Managing Structural Constraints: To develop structure preserving identification methods for networked and decentralized systems. We have ideas how to approach each of these themes, and initial attempts are promising.
Project acronym QGPDYN
Project Dynamics of the Quark-Gluon Plasma: A Journey into new phases of the Strong Interaction
Researcher (PI) Vincenzo Greco
Host Institution (HI) UNIVERSITA DEGLI STUDI DI CATANIA
Summary The study of the fundamental theory of the strong interaction, Quantum Chromo Dynamics (QCD), under extreme conditions of temperature and density has captured an increasing interest due to its very rich dynamical content and its relation to the Early Universe physics. Heavy-Ion Collisions (HIC) at ultra-relativistic energy (above ~10 AGeV) provide the possibility to scrutiny the QCD phase diagram reaching energy densities high enough to cause a phase transition of the hadronic matter into a quark-gluon plasma (QGP). The experiments conducted at the Brookhaven National Laboratory have shown that such a state of matter behaves like a nearly perfect fluid with a very small shear viscosity, a very high opacity at high transverse momentum pT (>6 GeV) and manifesting evidences for a modification of the hadronization process at intermediate pT (2-6 GeV) . Interestingly and surprisingly enough, also in the heavy quark sector there are hints that viscosity is similarly small. Furthermore some evidence of a new phase of QCD, the color glass condensate (CGC), has been found while its relevance should increase in the upcoming LHC program at CERN. These are the main physics subjects that we deal with in our project. The main objective of the project is to determine the value of the shear viscosity to entropy ratio h/s of the perfect fluid and the implications of a possible primordial CGC phase on the dynamical evolution of the system. The research gains strength from a comprehensive study of the rich phenomenology including both inclusive and more exclusive observables (like the two-three particles correlations triggered by hadronic jets) and from the inclusion of hadronization effects. In addition the study will be conducted considering also the heavy flavor sector where a fluid behaviour similar to the light one is observed. The microscopic origin of such a similarity will be investigated together with its relation to the suppression/regeneration of quarkonia.
The study of the fundamental theory of the strong interaction, Quantum Chromo Dynamics (QCD), under extreme conditions of temperature and density has captured an increasing interest due to its very rich dynamical content and its relation to the Early Universe physics. Heavy-Ion Collisions (HIC) at ultra-relativistic energy (above ~10 AGeV) provide the possibility to scrutiny the QCD phase diagram reaching energy densities high enough to cause a phase transition of the hadronic matter into a quark-gluon plasma (QGP). The experiments conducted at the Brookhaven National Laboratory have shown that such a state of matter behaves like a nearly perfect fluid with a very small shear viscosity, a very high opacity at high transverse momentum pT (>6 GeV) and manifesting evidences for a modification of the hadronization process at intermediate pT (2-6 GeV) . Interestingly and surprisingly enough, also in the heavy quark sector there are hints that viscosity is similarly small. Furthermore some evidence of a new phase of QCD, the color glass condensate (CGC), has been found while its relevance should increase in the upcoming LHC program at CERN. These are the main physics subjects that we deal with in our project. The main objective of the project is to determine the value of the shear viscosity to entropy ratio h/s of the perfect fluid and the implications of a possible primordial CGC phase on the dynamical evolution of the system. The research gains strength from a comprehensive study of the rich phenomenology including both inclusive and more exclusive observables (like the two-three particles correlations triggered by hadronic jets) and from the inclusion of hadronization effects. In addition the study will be conducted considering also the heavy flavor sector where a fluid behaviour similar to the light one is observed. The microscopic origin of such a similarity will be investigated together with its relation to the suppression/regeneration of quarkonia.