Springer Emerging Frontiers in Nonlinear Science: 32 (Nonlinear Systems and Complexity, 32)

This book explores the impact of nonlinearity on a broad range of areas, including time-honored fields such as biology, geometry, and topology, but also modern ones such as quantum mechanics, networks, metamaterials and artificial intelligence. The concept of nonlinearity is a universal feature in mathematics, physics, chemistry and biology, and is used to characterize systems whose behavior does not amount to a superposition of simple building blocks, but rather features complex and often chaotic patterns and phenomena. Each chapter of the book features a synopsis that not only recaps the recent progress in each field but also charts the challenges that lie ahead.    This interdisciplinary book presents contributions from a diverse group of experts from various fields to provide an overview of each field’s past, present and future. It will appeal to both beginners and seasoned researchers in nonlinear science, numerous areas of physics (optics, quantum physics, biophysics), and applied mathematics (ODEs, PDEs, dynamical systems, machine learning) as well as engineering. From the Back Cover This book explores the impact of nonlinearity on a broad range of areas, including time-honored fields such as biology, geometry, and topology, but also modern ones such as quantum mechanics, networks, metamaterials and artificial intelligence. The concept of nonlinearity is a universal feature in mathematics, physics, chemistry and biology, and is used to characterize systems whose behavior does not amount to a superposition of simple building blocks, but rather features complex and often chaotic patterns and phenomena. Each chapter of the book features a synopsis that not only recaps the recent progress in each field but also charts the challenges that lie ahead.    This interdisciplinary book presents contributions from a diverse group of experts from various fields to provide an overview of each field’s past, present and future. It will appeal to both beginners and seasoned researchers in nonlinear science, numerous areas of physics (optics, quantum physics, biophysics), and applied mathematics (ODEs, PDEs, dynamical systems, machine learning) as well as engineering. About the Author Prof. Panayotis Kevrekidis earned his B.Sc. Degree from the Department of Physics of the University of Athens in 1996. He subsequently joined the Physics Department of Rutgers University from where he earned a M.S. (1998), an M.Phil. (2000) and a Ph.D. (2000) in Physics working under the supervision of Profs. J.L. Lebowitz (Mathematics and Physics) and P.G. Georgopoulos (Environmental Science). His Ph.D. thesis was entitled “Lattice Dynamics of Solitary Wave Excitations.” He then assumed a postdoctoral research post for a year split between the Program in Applied and Computational Mathematics of Princeton University (10/2000-02/2001) and the Theoretical Division and the Center for Nonlinear Studies of the Los Alamos National Laboratory (03/2001-08/2001). From September 2001, he joined the Faculty ranks of the Department of Mathematics and Statistics of the University of Massachusetts (UMass), Amherst, as an Assistant Professor. He was awarded tenure and was promoted to Associate Professor in June 2005. Between September 2010 and September 2015, he was a Full Professor at UMass, Amherst, and since then, he holds a Distinguished University Professorship.  Kevrekidis has received numerous awards and distinctions for his work during his time at UMass. These include, among others, a CAREER award in Applied Mathematics from the US NSF (in 2003), a Humboldt Research Fellowship from the Humboldt Foundation and an Outstanding Paper Prize from the Society for Industrial and Applied Mathematics (SIAM), the 2008 International Stephanos Pnevmatikos Award for research in Nonlinear Phenomena, the 2013 J.D. Crawford Prize of the Activity Group on Dynamical Systems of SIAM and the A.F. Pallas award from the Academy