TY - JOUR A1 - Voss, Henning U. A1 - Kurths, Jürgen A1 - Schwarz, Udo T1 - Reconstruction of grand minima of solar activity from radiocarbon data : linear and nonlinear signal analysis N2 - Using a special technique of data analysis, we have found out 34 grand minima of solar activity in a 7,700 years long C14 record. The method used rests on a proper filtering of the C14 record and the extrapolation of verifiable results for the later history back in time. Additionally, we have applied a method of nonlinear dynamics, the recurrence rate, to back up the results. Our findings are not contradictory to the record of grand minima by Eddy, but constitute a considerable extension. Hence, it has become possible to look closer at the validity of models. This way, we have tested esp. the model of Barnes et al. There are hints for that the grand minima might solely be driven by the 209--year period found in the C14 record. Y1 - 1996 UR - http://www.agnld.uni-potsdam.de/~shw/Paper/vks.ps.gz ER - TY - JOUR A1 - Wessel, Niels A1 - Konvicka, Jan A1 - Weidermann, Frank A1 - Nestmann, S. A1 - Neugebauer, R. A1 - Schwarz, U. A1 - Wessel, A. A1 - Kurths, Jürgen T1 - Predicting thermal displacements in modular tool systems N2 - In the last decade, there has been an increasing interest in compensating thermally induced errors to improve the manufacturing accuracy of modular tool systems. These modular tool systems are interfaces between spindle and workpiece and consist of several complicatedly formed parts. Their thermal behavior is dominated by nonlinearities, delay and hysteresis effects even in tools with simpler geometry and it is difficult to describe it theoretically. Due to the dominant nonlinear nature of this behavior the so far used linear regression between the temperatures and the displacements is insufficient. Therefore, in this study we test the hypothesis whether we can reliably predict such thermal displacements via nonlinear temperature-displacement regression functions. These functions are estimated firstly from learning measurements using the alternating conditional expectation (ACE) algorithm and then tested on independent data sets. First, we analyze data that were generated by a finite element spindle model. We find that our approach is a powerful tool to describe the relation between temperatures and displacements for simulated data. Next, we analyze the temperature-displacement relationship in a silent real experimental setup, where the tool system is thermally forced. Again, the ACE-algorithm is powerful to estimate the deformation with high precision. The corresponding errors obtained by using the nonlinear regression approach are 10-fold lower in comparison to multiple linear regression analysis. Finally, we investigate the thermal behavior of a modular tool system in a working milling machine and get again promising results. The thermally inducedaccuracy using this nonlinear regression analysis. Therefore, this approach seems to be very useful for the development of new modular tool systems. errors can be estimated with 1-2 micrometer Y1 - 2004 SN - 1054-1500 ER - TY - JOUR A1 - Thiel, Marco A1 - Romano, Maria Carmen A1 - Schwarz, Udo A1 - Kurths, Jürgen A1 - Hasinger, Günther A1 - Belloni, Tomaso T1 - Nonlinear Time series analysis of the X-ray flux of compact objects N2 - We analyse the X-ray light curves of compact objects using linear and nonlinear time series analysis methods. A Power Density Spectrum (PDS) describes the overall second order properties of the observed data well. To look beyond we propose the nonlinear Q-statistic to detect an asymmetry of the time series. This allows us to find relevant time scales. This method even grants a subclassification of the known states of X-ray sources. Y1 - 2001 SN - 0004-640x ER - TY - JOUR A1 - Kurths, Jürgen A1 - Schwarz, Udo A1 - Witt, Annette T1 - Non-linear data analysis in solar radio astronomy N2 - We have discussed some tools from nonlinear dynamics which may help to analyze transient phenomena, such as solar bursts. The structure function known from turbulence theory is an appropriate method to find out some scaling behavior of fluctuations in time. More generally, the wavelet analysis, which is some generalization of the power spectrum, exhibits information on the location as well as the size of hidden characteristic features. Applying both techniques to microwave bursts, we have found some scaling properties that refer to the existence of hierarchic time structures. This is in good accordance with the electric circuit model for describing the flare-particle energization process. Y1 - 1995 UR - http://www.agnld.uni-potsdam.de/~shw/Paper/lnp.ps.gz ER - TY - JOUR A1 - Kurths, Jürgen A1 - Schwarz, Udo T1 - Nichtlineare Wissenschaften - neue Paradigmen und Konzepte N2 - In den letzten 2 Jahrzehnten des 20. Jahrhunderts hat sich mit der rasanten Entwicklung der Nichtlinearen Wissenschaften ein weiterer Umbruch vollzogen, der eine ausgepraegte Nachhaltigkeit in Wissenschaft und Technik ebenso wie in der Gesellschaft erwarten laesst. Die Nichtlinearen Wissenschaften werden auch als Nichtlineare Dynamik, Wissenschaft Komplexer Systeme oder etwas eingegrenzt Chaostheorie bezeichnet. Y1 - 2001 UR - http://www.agnld.uni-potsdam.de/~shw/Paper/2001ArtChaos.pdf SN - 0177- 3674 ER - TY - JOUR A1 - Wessel, Niels A1 - Aßmus, Joerg A1 - Weidermann, Frank A1 - Konvicka, Jan A1 - Nestmann, S. A1 - Neugebauer, R. A1 - Schwarz, Udo A1 - Kurths, Jürgen T1 - Modeling thermal displacements in modular tool systems N2 - In the last decade, there has been an increasing interest in compensating thermally induced errors to improve the manufacturing accuracy of modular tool systems. These modular tool systems are interfaces between spindle and workpiece and consist of several complicatedly formed parts. Their thermal behavior is dominated by nonlinearities, delay and hysteresis effects even in tools with simpler geometry and it is difficult to describe it theoretically. Due to the dominant nonlinear nature of this behavior the so far used linear regression between the temperatures and the displacements is insufficient. Therefore, in this study we test the hypothesis whether we can reliably predict such thermal displacements via nonlinear temperature-displacement regression functions. These functions are estimated firstly from learning measurements using the alternating conditional expectation (ACE) algorithm and then tested on independent data sets. First, we analyze data that were generated by a finite element spindle model. We find that our approach is a powerful tool to describe the relation between temperatures and displacements for simulated data. Next, we analyze the temperature-displacement relationship in a silent real experimental setup, where the tool system is thermally forced. Again, the ACE-algorithm is powerful to estimate the deformation with high precision. The corresponding errors obtained by using the nonlinear regression approach are 10-fold lower in comparison to multiple linear regression analysis. Finally, we investigate the thermal behavior of a modular tool system in a working milling machine and get again promising results. The thermally induced errors can be estimated with 1-2${mu m}$ accuracy using this nonlinear regression analysis. Therefore, this approach seems to be very useful for the development of new modular tool systems. Y1 - 2004 ER - TY - JOUR A1 - Voss, Henning U. A1 - Timmer, Jens A1 - Kurths, Jürgen T1 - Modeling and identification of nonlinear systems Y1 - 2004 SN - 0218-1274 ER - TY - JOUR A1 - Zolotova, Nadezhda V. A1 - Ponyavin, Dmitri I. A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Long-term asymmetry in the wings of the butterfly diagram N2 - Aims. Sunspot distribution in the northern and southern solar hemispheres exibit striking synchronous behaviour on the scale of a Schwabe cycle. However, sometimes the bilateral symmetry of the Butterfly diagram relative to the solar equatorial plane breaks down. The investigation of this phenomenon is important to explaining the almost-periodic behaviour of solar cycles. Methods. We use cross-recurrence plots for the study of the time-varying phase asymmetry of the northern and southern hemisphere and compare our results with the latitudinal distribution of the sunspots. Results. We observe a long-term persistence of phase leading in one of the hemispheres, which lasts almost 4 solar cycles and probably corresponds to the Gleissberg cycle. Long-term variations in the hemispheric-leading do not demonstrate clear periodicity but are strongly anti-correlated with the long-term variations in the magnetic equator. Y1 - 2009 UR - http://www.aanda.org/ U6 - https://doi.org/10.1051/0004-6361/200811430 SN - 0004-6361 ER - TY - JOUR A1 - Timmer, Jens A1 - Schwarz, Udo A1 - Voss, Henning U. A1 - Wardinski, Ingo A1 - Belloni, Tomaso A1 - Hasinger, Günther A1 - VanDerKlis, Michael A1 - Kurths, Jürgen T1 - Linear and Nonlinear Time Series Analysis of the Black Hole Candidate Cygnus X-1 N2 - We analyze the variability in the x-ray lightcurves of the black hole candidate Cygnus X-1 by linear and nonlinear time series analysis methods. While a linear model describes the overall second order properties of the observed data well, surrogate data analysis reveals a significant deviation from linearity. We discuss the relation between shot noise models usually applied to analyze these data and linear stochastic autoregressive models. We debate statistical and interpretational issues of surrogate data testing for the present context. Finally, we suggest a combination of tools from linear and nonlinear time series analysis methods as a procedure to test the predictions of astrophysical models on observed data. Y1 - 2000 UR - http://pre.aps.org/ ER - TY - JOUR A1 - Braun, Holger A1 - Ditlevsen, Peter D. A1 - Kurths, Jürgen A1 - Mudelsee, Manfred T1 - Limitations of red noise in analysing Dansgaard-Oeschger events N2 - During the last glacial period, climate records from the North Atlantic region exhibit a pronounced spectral component corresponding to a period of about 1470 years, which has attracted much attention. This spectral peak is closely related to the recurrence pattern of Dansgaard-Oeschger (DO) events. In previous studies a red noise random process, more precisely a first-order autoregressive (AR1) process, was used to evaluate the statistical significance of this peak, with a reported significance of more than 99%. Here we use a simple mechanistic two-state model of DO events, which itself was derived from a much more sophisticated ocean-atmosphere model of intermediate complexity, to numerically evaluate the spectral properties of random (i.e., solely noise-driven) events. This way we find that the power spectral density of random DO events differs fundamentally from a simple red noise random process. These results question the applicability of linear spectral analysis for estimating the statistical significance of highly non-linear processes such as DO events. More precisely, to enhance our scientific understanding about the trigger of DO events, we must not consider simple "straw men" as, for example, the AR1 random process, but rather test against realistic alternative descriptions. Y1 - 2010 UR - http://www.clim-past.net/volumes_and_issues.html U6 - https://doi.org/10.5194/cp-6-85-2010 SN - 1814-9324 ER -