@phdthesis{Zoeller1999,
  author    = {Z{\"o}ller, Gert},
  title     = {Analyse raumzeitlicher Muster in Erdbebendaten},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-0000122},
  school      = {Universit{\"a}t Potsdam},
  year      = {1999},
  abstract  = {Die vorliegende Arbeit besch{\"a}ftigt sich mit der Charakterisierung von Seismizit{\"a}t anhand von Erdbebenkatalogen. Es werden neue Verfahren der Datenanalyse entwickelt, die Aufschluss dar{\"u}ber geben sollen, ob der seismischen Dynamik ein stochastischer oder ein deterministischer Prozess zugrunde liegt und was daraus f{\"u}r die Vorhersagbarkeit starker Erdbeben folgt. Es wird gezeigt, dass seismisch aktive Regionen h{\"a}ufig durch nichtlinearen Determinismus gekennzeichent sind. Dies schließt zumindest die M{\"o}glichkeit einer Kurzzeitvorhersage ein. Das Auftreten seismischer Ruhe wird h{\"a}ufig als Vorl{\"a}uferphaenomen f{\"u}r starke Erdbeben gedeutet. Es wird eine neue Methode pr{\"a}sentiert, die eine systematische raumzeitliche Kartierung seismischer Ruhephasen erm{\"o}glicht. Die statistische Signifikanz wird mit Hilfe des Konzeptes der Ersatzdaten bestimmt. Als Resultat erh{\"a}lt man deutliche Korrelationen zwischen seismischen Ruheperioden und starken Erdbeben. Gleichwohl ist die Signifikanz daf{\"u}r nicht hoch genug, um eine Vorhersage im Sinne einer Aussage {\"u}ber den Ort, die Zeit und die St{\"a}rke eines zu erwartenden Hauptbebens zu erm{\"o}glichen.},
  language  = {en}
}
@misc{ŚlęzakBurneckiMetzler2019,
  author    = {Ślęzak, Jakub and Burnecki, Krzysztof and Metzler, Ralf},
  title     = {Random coefficient autoregressive processes describe Brownian yet non-Gaussian diffusion in heterogeneous systems},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {765},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-43792},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-437923},
  pages     = {18},
  year      = {2019},
  abstract  = {Many studies on biological and soft matter systems report the joint presence of a linear mean-squared displacement and a non-Gaussian probability density exhibiting, for instance, exponential or stretched-Gaussian tails. This phenomenon is ascribed to the heterogeneity of the medium and is captured by random parameter models such as 'superstatistics' or 'diffusing diffusivity'. Independently, scientists working in the area of time series analysis and statistics have studied a class of discrete-time processes with similar properties, namely, random coefficient autoregressive models. In this work we try to reconcile these two approaches and thus provide a bridge between physical stochastic processes and autoregressive models.Westart from the basic Langevin equation of motion with time-varying damping or diffusion coefficients and establish the link to random coefficient autoregressive processes. By exploring that link we gain access to efficient statistical methods which can help to identify data exhibiting Brownian yet non-Gaussian diffusion.},
  language  = {en}
}
@article{ŚlęzakBurneckiMetzler2019,
  author    = {Ślęzak, Jakub and Burnecki, Krzysztof and Metzler, Ralf},
  title     = {Random coefficient autoregressive processes describe Brownian yet non-Gaussian diffusion in heterogeneous systems},
  series = {New Journal of Physics},
  volume    = {21},
  journal   = {New Journal of Physics},
  publisher = {Deutsche Physikalische Gesellschaft ; IOP, Institute of Physics},
  address   = {Bad Honnef und London},
  issn      = {1367-2630},
  doi       = {10.1088/1367-2630/ab3366},
  pages     = {18},
  year      = {2019},
  abstract  = {Many studies on biological and soft matter systems report the joint presence of a linear mean-squared displacement and a non-Gaussian probability density exhibiting, for instance, exponential or stretched-Gaussian tails. This phenomenon is ascribed to the heterogeneity of the medium and is captured by random parameter models such as 'superstatistics' or 'diffusing diffusivity'. Independently, scientists working in the area of time series analysis and statistics have studied a class of discrete-time processes with similar properties, namely, random coefficient autoregressive models. In this work we try to reconcile these two approaches and thus provide a bridge between physical stochastic processes and autoregressive models.Westart from the basic Langevin equation of motion with time-varying damping or diffusion coefficients and establish the link to random coefficient autoregressive processes. By exploring that link we gain access to efficient statistical methods which can help to identify data exhibiting Brownian yet non-Gaussian diffusion.},
  language  = {en}
}
@misc{ŚlęzakMetzlerMagdziarz2019,
  author    = {Ślęzak, Jakub and Metzler, Ralf and Magdziarz, Marcin},
  title     = {Codifference can detect ergodicity breaking and non-Gaussianity},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {748},
  doi       = {10.25932/publishup-43617},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-436178},
  pages     = {25},
  year      = {2019},
  abstract  = {We show that the codifference is a useful tool in studying the ergodicity breaking and non-Gaussianity properties of stochastic time series. While the codifference is a measure of dependence that was previously studied mainly in the context of stable processes, we here extend its range of applicability to random-parameter and diffusing-diffusivity models which are important in contemporary physics, biology and financial engineering. We prove that the codifference detects forms of dependence and ergodicity breaking which are not visible from analysing the covariance and correlation functions. We also discuss a related measure of dispersion, which is a nonlinear analogue of the mean squared displacement.},
  language  = {en}
}
@misc{ŚlęzakMetzlerMagdziarz2018,
  author    = {Ślęzak, Jakub and Metzler, Ralf and Magdziarz, Marcin},
  title     = {Superstatistical generalised Langevin equation},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-409315},
  pages     = {25},
  year      = {2018},
  abstract  = {Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.},
  language  = {en}
}
@article{ŚlęzakMetzlerMagdziarz2018,
  author    = {Ślęzak, Jakub and Metzler, Ralf and Magdziarz, Marcin},
  title     = {Superstatistical generalised Langevin equation},
  series = {New Journal of Physics},
  volume    = {20},
  journal   = {New Journal of Physics},
  number    = {023026},
  publisher = {Deutsche Physikalische Gesellschaft / Institute of Physics},
  address   = {Bad Honnef und London},
  issn      = {1367-2630},
  doi       = {10.1088/1367-2630/aaa3d4},
  pages     = {1 -- 25},
  year      = {2018},
  abstract  = {Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.},
  language  = {en}
}
@article{ŚlęzakMetzlerMagdziarz2019,
  author    = {Ślęzak, Jakub and Metzler, Ralf and Magdziarz, Marcin},
  title     = {Codifference can detect ergodicity breaking and non-Gaussianity},
  series = {New Journal of Physics},
  volume    = {21},
  journal   = {New Journal of Physics},
  publisher = {Deutsche Physikalische Gesellschaft},
  address   = {Bad Honnef},
  issn      = {1367-2630},
  doi       = {10.1088/1367-2630/ab13f3},
  pages     = {25},
  year      = {2019},
  abstract  = {We show that the codifference is a useful tool in studying the ergodicity breaking and non-Gaussianity properties of stochastic time series. While the codifference is a measure of dependence that was previously studied mainly in the context of stable processes, we here extend its range of applicability to random-parameter and diffusing-diffusivity models which are important in contemporary physics, biology and financial engineering. We prove that the codifference detects forms of dependence and ergodicity breaking which are not visible from analysing the covariance and correlation functions. We also discuss a related measure of dispersion, which is a nonlinear analogue of the mean squared displacement.},
  language  = {en}
}
@inproceedings{OPUS4-1412,
  title     = {The 3rd international IEEE scientific conference on physics and control (PhysCon 2007) : September 3rd-7th 2007 at the University of Potsdam},
  editor    = {Kurths, J{\"u}rgen and Fradkov, Alexander and Chen, Guanrong},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-15228},
  pages     = {345},
  year      = {2007},
  abstract  = {During the last few years there was a tremendous growth of scientific activities in the fields related to both Physics and Control theory: nonlinear dynamics, micro- and nanotechnologies, self-organization and complexity, etc. New horizons were opened and new exciting applications emerged. Experts with different backgrounds starting to work together need more opportunities for information exchange to improve mutual understanding and cooperation. The Conference "Physics and Control 2007" is the third international conference focusing on the borderland between Physics and Control with emphasis on both theory and applications. With its 2007 address at Potsdam, Germany, the conference is located for the first time outside of Russia. The major goal of the Conference is to bring together researchers from different scientific communities and to gain some general and unified perspectives in the studies of controlled systems in physics, engineering, chemistry, biology and other natural sciences. We hope that the Conference helps experts in control theory to get acquainted with new interesting problems, and helps experts in physics and related fields to know more about ideas and tools from the modern control theory.},
  language  = {en}
}
@misc{OPUS4-5024,
  title     = {T{\"a}tigkeitsbericht 1994-2000},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-48483},
  year      = {2004},
  abstract  = {Das Interdisziplin{\"a}re Zentrum f{\"u}r Nichtlineare Dynamik an der Universit{\"a}t Potsdam verbindet theoretisch-methodische Untersuchungen in Mathematik und theoretischer Physik mit einer Vielzahl anderer Wissenschaften und zielt auf eine fruchtbare Wechselwirkung zwischen Theorie und Experiment. Unter Einbezug von Instituten und Großforschungseinrichtungen, die insbesondere im Potsdamer Raum angesiedelt sind, soll sich ein {\"u}berregional bedeutender Schwerpunkt entwickeln, wie er an keiner anderen deutschen Universit{\"a}t in gleicher Weise interdisziplin{\"a}r angelegt ist.},
  language  = {de}
}