TY - INPR A1 - Buchholz, Thilo A1 - Schulze, Bert-Wolfgang T1 - Volterra operators and parabolicity : anisotropic pseudo-differential operators N2 - Parabolic equations on manifolds with singularities require a new calculus of anisotropic pseudo-differential operators with operator-valued symbols. The paper develops this theory along the lines of sn abstract wedge calculus with strongly continuous groups of isomorphisms on the involved Banach spaces. The corresponding pseodo-diferential operators are continuous in anisotropic wedge Sobolev spaces, and they form an alegbra. There is then introduced the concept of anisotropic parameter-dependent ellipticity, based on an order reduction variant of the pseudo-differential calculus. The theory is appled to a class of parabolic differential operators, and it is proved the invertibility in Sobolev spaces with exponential weights at infinity in time direction. T3 - Preprint - (1998) 11 Y1 - 1998 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-25231 ER - TY - GEN A1 - Bruttel, Lisa Verena A1 - Stolley, Florian T1 - Gender differences in the response to decision power and responsibility BT - Framing effects in a dictator game T2 - Postprints der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - This paper studies the effects of two different frames on decisions in a dictator game. Before making their allocation decision, dictators read a short text. Depending on the treatment, the text either emphasizes their decision power and freedom of choice or it stresses their responsibility for the receiver’s payoff. Including a control treatment without such a text, three treatments are conducted with a total of 207 dictators. Our results show a different reaction to these texts depending on the dictator’s gender. We find that only men react positively to a text that stresses their responsibility for the receiver, while only women seem to react positively to a text that emphasizes their decision power and freedom of choice. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 135 KW - dictator game KW - framing KW - gender KW - experiment Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-473068 SN - 1867-5808 IS - 135 ER - TY - JOUR A1 - Brungs, Hans H. A1 - Gräter, Joachim T1 - On central extensions of SL(2, F) admitting left-orderings JF - Journal of Algebra N2 - For an arbitrary euclidean field F we introduce a central extension (G(F), Phi) of SL(2, F) admitting a left-ordering and study its algebraic properties. The elements of G(F) are order preserving bijections of the convex hull of Q in F. If F = R then G(F) is isomorphic to the classical universal covering group of the Lie group SL(2, R). Among other results we show that G(F) is a perfect group which possesses a rank 1 cone of exceptional type. We also prove that its centre is an infinite cyclic group and investigate its normal subgroups. KW - Universal covering group KW - Central extensions of groups KW - Perfect groups KW - Ordered fields KW - Left-ordered groups KW - Order-preserving bijections KW - Euclidean fields Y1 - 2017 U6 - https://doi.org/10.1016/j.jalgebra.2017.05.025 SN - 0021-8693 SN - 1090-266X VL - 486 SP - 288 EP - 327 PB - Elsevier CY - San Diego ER - TY - INPR A1 - Brauer, Uwe A1 - Karp, Lavi T1 - Local existence of classical solutions for the Einstein-Euler system using weighted Sobolev spaces of fractional order N2 - We prove the existence of a class of local in time solutions, including static solutions, of the Einstein-Euler system. This result is the relativistic generalisation of a similar result for the Euler-Poisson system obtained by Gamblin [8]. As in his case the initial data of the density do not have compact support but fall off at infinity in an appropriate manner. An essential tool in our approach is the construction and use of weighted Sobolev spaces of fractional order. Moreover, these new spaces allow us to improve the regularity conditions for the solutions of evolution equations. The details of this construction, the properties of these spaces and results on elliptic and hyperbolic equations will be presented in a forthcoming article. T3 - Preprint - (2006) 17 Y1 - 2006 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-30175 ER - TY - INPR A1 - Brauer, Uwe A1 - Karp, Lavi T1 - Well-posedness of Einstein-Euler systems in asymptotically flat spacetimes N2 - We prove a local in time existence and uniqueness theorem of classical solutions of the coupled Einstein{Euler system, and therefore establish the well posedness of this system. We use the condition that the energy density might vanish or tends to zero at infinity and that the pressure is a certain function of the energy density, conditions which are used to describe simplified stellar models. In order to achieve our goals we are enforced, by the complexity of the problem, to deal with these equations in a new type of weighted Sobolev spaces of fractional order. Beside their construction, we develop tools for PDEs and techniques for hyperbolic and elliptic equations in these spaces. The well posedness is obtained in these spaces. T3 - Preprint - (2008) 07 Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-30347 ER - TY - THES A1 - Branding, Volker T1 - The evolution equations for Dirac-harmonic Maps T1 - Die Evolutionsgleichungen für Dirac-harmonische Abbildungen N2 - This thesis investigates the gradient flow of Dirac-harmonic maps. Dirac-harmonic maps are critical points of an energy functional that is motivated from supersymmetric field theories. The critical points of this energy functional couple the equation for harmonic maps with spinor fields. At present, many analytical properties of Dirac-harmonic maps are known, but a general existence result is still missing. In this thesis the existence question is studied using the evolution equations for a regularized version of Dirac-harmonic maps. Since the energy functional for Dirac-harmonic maps is unbounded from below the method of the gradient flow cannot be applied directly. Thus, we first of all consider a regularization prescription for Dirac-harmonic maps and then study the gradient flow. Chapter 1 gives some background material on harmonic maps/harmonic spinors and summarizes the current known results about Dirac-harmonic maps. Chapter 2 introduces the notion of Dirac-harmonic maps in detail and presents a regularization prescription for Dirac-harmonic maps. In Chapter 3 the evolution equations for regularized Dirac-harmonic maps are introduced. In addition, the evolution of certain energies is discussed. Moreover, the existence of a short-time solution to the evolution equations is established. Chapter 4 analyzes the evolution equations in the case that the domain manifold is a closed curve. Here, the existence of a smooth long-time solution is proven. Moreover, for the regularization being large enough, it is shown that the evolution equations converge to a regularized Dirac-harmonic map. Finally, it is discussed in which sense the regularization can be removed. In Chapter 5 the evolution equations are studied when the domain manifold is a closed Riemmannian spin surface. For the regularization being large enough, the existence of a global weak solution, which is smooth away from finitely many singularities is proven. It is shown that the evolution equations converge weakly to a regularized Dirac-harmonic map. In addition, it is discussed if the regularization can be removed in this case. N2 - Die vorliegende Dissertation untersucht den Gradientenfluss von Dirac-harmonischen Abbildungen. Dirac-harmonische Abbildungen sind kritische Punkte eines Energiefunktionals, welches aus supersymmetrischen Feldtheorien motiviert ist. Die kritischen Punkte dieses Energiefunktionals koppeln die Gleichung für harmonische Abbildungen mit Spinorfeldern. Viele analytische Eigenschaften von Dirac-harmonischen Abbildungen sind bereits bekannt, ein allgemeines Existenzresultat wurde aber noch nicht erzielt. Diese Dissertation untersucht das Existenzproblem, indem der Gradientenfluss von einer regularisierten Version Dirac-harmonischer Abbildungen untersucht wird. Die Methode des Gradientenflusses kann nicht direkt angewendet werden, da das Energiefunktional für Dirac-harmonische Abbildungen nach unten unbeschränkt ist. Daher wird zunächst eine Regularisierungsvorschrift für Dirac-harmonische Abbildungen eingeführt und dann der Gradientenfluss betrachtet. Kapitel 1 stellt für die Arbeit wichtige Resultate über harmonische Abbildungen/harmonische Spinoren zusammen. Außerdem werden die zur Zeit bekannten Resultate über Dirac-harmonische Abbildungen zusammengefasst. In Kapitel 2 werden Dirac-harmonische Abbildungen im Detail eingeführt, außerdem wird eine Regularisierungsvorschrift präsentiert. Kapitel 3 führt die Evolutionsgleichungen für regularisierte Dirac-harmonische Abbildungen ein. Zusätzlich wird die Evolution von verschiedenen Energien diskutiert. Schließlich wird die Existenz einer Kurzzeitlösung bewiesen. In Kapitel 4 werden die Evolutionsgleichungen für den Fall analysiert, dass die Ursprungsmannigfaltigkeit eine geschlossene Kurve ist. Die Existenz einer Langzeitlösung der Evolutionsgleichungen wird bewiesen. Es wird außerdem gezeigt, dass die Evolutionsgleichungen konvergieren, falls die Regularisierung groß genug gewählt wurde. Schließlich wird diskutiert, ob die Regularisierung wieder entfernt werden kann. Kapitel 5 schlussendlich untersucht die Evolutionsgleichungen für den Fall, dass die Ursprungsmannigfaltigkeit eine geschlossene Riemannsche Spin Fläche ist. Es wird die Existenz einer global schwachen Lösung bewiesen, welche bis auf endlich viele Singularitäten glatt ist. Die Lösung konvergiert im schwachen Sinne gegen eine regularisierte Dirac-harmonische Abbildung. Auch hier wird schließlich untersucht, ob die Regularisierung wieder entfernt werden kann. KW - Dirac-harmonische Abbildungen KW - Gradientenfluss KW - Wärmefluss KW - Spin Geometrie KW - nichtlineare partielle Differentialgleichung KW - Dirac-harmonic maps KW - Gradient flow KW - Heat Flow KW - Spin Geometry KW - nonlinear partial differential equations Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-64204 ER - TY - JOUR A1 - Bourne, D. P. A1 - Cushing, D. A1 - Liu, S. A1 - Münch, Florentin A1 - Peyerimhoff, Norbert T1 - Ollivier-Ricci idleness functions of graphs JF - SIAM Journal on Discrete Mathematics N2 - We study the Ollivier-Ricci curvature of graphs as a function of the chosen idleness. We show that this idleness function is concave and piecewise linear with at most three linear parts, and at most two linear parts in the case of a regular graph. We then apply our result to show that the idleness function of the Cartesian product of two regular graphs is completely determined by the idleness functions of the factors. KW - Ollivier-Ricci KW - idleness KW - optimal transport Y1 - 2018 U6 - https://doi.org/10.1137/17M1134469 SN - 0895-4801 SN - 1095-7146 VL - 32 IS - 2 SP - 1408 EP - 1424 PB - Society for Industrial and Applied Mathematics CY - Philadelphia ER - TY - JOUR A1 - Boldrighini, Carlo A1 - Frigio, Sandro A1 - Maponi, Pierluigi A1 - Pellegrinotti, Alessandro A1 - Sinai, Yakov G. T1 - 3-D incompressible Navier-Stokes equations: Complex blow-up and related real flows JF - Lectures in pure and applied mathematics KW - random point processes KW - statistical mechanics KW - stochastic analysis Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-472201 SN - 978-3-86956-485-2 SN - 2199-4951 SN - 2199-496X IS - 6 SP - 185 EP - 194 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Blanchard, Gilles A1 - Zadorozhnyi, Oleksandr T1 - Concentration of weakly dependent Banach-valued sums and applications to statistical learning methods JF - Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability N2 - We obtain a Bernstein-type inequality for sums of Banach-valued random variables satisfying a weak dependence assumption of general type and under certain smoothness assumptions of the underlying Banach norm. We use this inequality in order to investigate in the asymptotical regime the error upper bounds for the broad family of spectral regularization methods for reproducing kernel decision rules, when trained on a sample coming from a tau-mixing process. KW - Banach-valued process KW - Bernstein inequality KW - concentration KW - spectral regularization KW - weak dependence Y1 - 2019 U6 - https://doi.org/10.3150/18-BEJ1095 SN - 1350-7265 SN - 1573-9759 VL - 25 IS - 4B SP - 3421 EP - 3458 PB - International Statistical Institute CY - Voorburg ER - TY - GEN A1 - Blanchard, Gilles A1 - Scott, Clayton T1 - Corrigendum to: Classification with asymmetric label noise BT - Consistency and maximal denoising T2 - Electronic journal of statistics N2 - We point out a flaw in Lemma 15 of [1]. We also indicate how the main results of that section are still valid using a modified argument. Y1 - 2018 U6 - https://doi.org/10.1214/18-EJS1422 SN - 1935-7524 VL - 12 IS - 1 SP - 1779 EP - 1781 PB - Institute of Mathematical Statistics CY - Cleveland ER - TY - JOUR A1 - Blanchard, Gilles A1 - Mücke, Nicole T1 - Optimal rates for regularization of statistical inverse learning problems JF - Foundations of Computational Mathematics N2 - We consider a statistical inverse learning (also called inverse regression) problem, where we observe the image of a function f through a linear operator A at i.i.d. random design points X-i , superposed with an additive noise. The distribution of the design points is unknown and can be very general. We analyze simultaneously the direct (estimation of Af) and the inverse (estimation of f) learning problems. In this general framework, we obtain strong and weak minimax optimal rates of convergence (as the number of observations n grows large) for a large class of spectral regularization methods over regularity classes defined through appropriate source conditions. This improves on or completes previous results obtained in related settings. The optimality of the obtained rates is shown not only in the exponent in n but also in the explicit dependency of the constant factor in the variance of the noise and the radius of the source condition set. KW - Reproducing kernel Hilbert space KW - Spectral regularization KW - Inverse problem KW - Statistical learning KW - Minimax convergence rates Y1 - 2018 U6 - https://doi.org/10.1007/s10208-017-9359-7 SN - 1615-3375 SN - 1615-3383 VL - 18 IS - 4 SP - 971 EP - 1013 PB - Springer CY - New York ER - TY - JOUR A1 - Blanchard, Gilles A1 - Mücke, Nicole T1 - Kernel regression, minimax rates and effective dimensionality BT - beyond the regular case JF - Analysis and applications N2 - We investigate if kernel regularization methods can achieve minimax convergence rates over a source condition regularity assumption for the target function. These questions have been considered in past literature, but only under specific assumptions about the decay, typically polynomial, of the spectrum of the the kernel mapping covariance operator. In the perspective of distribution-free results, we investigate this issue under much weaker assumption on the eigenvalue decay, allowing for more complex behavior that can reflect different structure of the data at different scales. KW - Kernel regression KW - minimax optimality KW - eigenvalue decay Y1 - 2020 U6 - https://doi.org/10.1142/S0219530519500258 SN - 0219-5305 SN - 1793-6861 VL - 18 IS - 4 SP - 683 EP - 696 PB - World Scientific CY - New Jersey ER - TY - INPR A1 - Blanchard, Gilles A1 - Mücke, Nicole T1 - Optimal rates for regularization of statistical inverse learning problems N2 - We consider a statistical inverse learning problem, where we observe the image of a function f through a linear operator A at i.i.d. random design points X_i, superposed with an additional noise. The distribution of the design points is unknown and can be very general. We analyze simultaneously the direct (estimation of Af) and the inverse (estimation of f) learning problems. In this general framework, we obtain strong and weak minimax optimal rates of convergence (as the number of observations n grows large) for a large class of spectral regularization methods over regularity classes defined through appropriate source conditions. This improves on or completes previous results obtained in related settings. The optimality of the obtained rates is shown not only in the exponent in n but also in the explicit dependence of the constant factor in the variance of the noise and the radius of the source condition set. T3 - Preprints des Instituts für Mathematik der Universität Potsdam - 5 (2016) 5 KW - statistical inverse problem KW - minimax rate KW - kernel method Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-89782 SN - 2193-6943 VL - 5 IS - 5 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - INPR A1 - Blanchard, Gilles A1 - Mathé, Peter T1 - Discrepancy principle for statistical inverse problems with application to conjugate gradient iteration N2 - The authors discuss the use of the discrepancy principle for statistical inverse problems, when the underlying operator is of trace class. Under this assumption the discrepancy principle is well defined, however a plain use of it may occasionally fail and it will yield sub-optimal rates. Therefore, a modification of the discrepancy is introduced, which takes into account both of the above deficiencies. For a variety of linear regularization schemes as well as for conjugate gradient iteration this modification is shown to yield order optimal a priori error bounds under general smoothness assumptions. A posteriori error control is also possible, however at a sub-optimal rate, in general. This study uses and complements previous results for bounded deterministic noise. T3 - Preprints des Instituts für Mathematik der Universität Potsdam - 1 (2012) 7 Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-57117 ER - TY - INPR A1 - Blanchard, Gilles A1 - Krämer, Nicole T1 - Convergence rates of kernel conjugate gradient for random design regression N2 - We prove statistical rates of convergence for kernel-based least squares regression from i.i.d. data using a conjugate gradient algorithm, where regularization against overfitting is obtained by early stopping. This method is related to Kernel Partial Least Squares, a regression method that combines supervised dimensionality reduction with least squares projection. Following the setting introduced in earlier related literature, we study so-called "fast convergence rates" depending on the regularity of the target regression function (measured by a source condition in terms of the kernel integral operator) and on the effective dimensionality of the data mapped into the kernel space. We obtain upper bounds, essentially matching known minimax lower bounds, for the L^2 (prediction) norm as well as for the stronger Hilbert norm, if the true regression function belongs to the reproducing kernel Hilbert space. If the latter assumption is not fulfilled, we obtain similar convergence rates for appropriate norms, provided additional unlabeled data are available. T3 - Preprints des Instituts für Mathematik der Universität Potsdam - 5 (2016) 8 KW - nonparametric regression KW - reproducing kernel Hilbert space KW - conjugate gradient KW - partial least squares KW - minimax convergence rates Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-94195 SN - 2193-6943 VL - 5 IS - 8 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Blanchard, Gilles A1 - Hoffmann, Marc A1 - Reiss, Markus T1 - Optimal adaptation for early stopping in statistical inverse problems JF - SIAM/ASA Journal on Uncertainty Quantification N2 - For linear inverse problems Y = A mu + zeta, it is classical to recover the unknown signal mu by iterative regularization methods ((mu) over cap,(m) = 0,1, . . .) and halt at a data-dependent iteration tau using some stopping rule, typically based on a discrepancy principle, so that the weak (or prediction) squared-error parallel to A((mu) over cap (()(tau)) - mu)parallel to(2) is controlled. In the context of statistical estimation with stochastic noise zeta, we study oracle adaptation (that is, compared to the best possible stopping iteration) in strong squared- error E[parallel to((mu) over cap (()(tau)) - mu)parallel to(2)]. For a residual-based stopping rule oracle adaptation bounds are established for general spectral regularization methods. The proofs use bias and variance transfer techniques from weak prediction error to strong L-2-error, as well as convexity arguments and concentration bounds for the stochastic part. Adaptive early stopping for the Landweber method is studied in further detail and illustrated numerically. KW - linear inverse problems KW - early stopping KW - discrepancy principle KW - adaptive estimation KW - oracle inequality KW - Landweber iteration Y1 - 2018 U6 - https://doi.org/10.1137/17M1154096 SN - 2166-2525 VL - 6 IS - 3 SP - 1043 EP - 1075 PB - Society for Industrial and Applied Mathematics CY - Philadelphia ER - TY - JOUR A1 - Blanchard, Gilles A1 - Hoffmann, Marc A1 - Reiss, Markus T1 - Early stopping for statistical inverse problems via truncated SVD estimation JF - Electronic journal of statistics N2 - We consider truncated SVD (or spectral cut-off, projection) estimators for a prototypical statistical inverse problem in dimension D. Since calculating the singular value decomposition (SVD) only for the largest singular values is much less costly than the full SVD, our aim is to select a data-driven truncation level (m) over cap is an element of {1, . . . , D} only based on the knowledge of the first (m) over cap singular values and vectors. We analyse in detail whether sequential early stopping rules of this type can preserve statistical optimality. Information-constrained lower bounds and matching upper bounds for a residual based stopping rule are provided, which give a clear picture in which situation optimal sequential adaptation is feasible. Finally, a hybrid two-step approach is proposed which allows for classical oracle inequalities while considerably reducing numerical complexity. KW - Linear inverse problems KW - truncated SVD KW - spectral cut-off KW - early stopping KW - discrepancy principle KW - adaptive estimation KW - oracle inequalities Y1 - 2018 U6 - https://doi.org/10.1214/18-EJS1482 SN - 1935-7524 VL - 12 IS - 2 SP - 3204 EP - 3231 PB - Institute of Mathematical Statistics CY - Cleveland ER - TY - INPR A1 - Blanchard, Gilles A1 - Delattre, Sylvain A1 - Roquain, Étienne T1 - Testing over a continuum of null hypotheses N2 - We introduce a theoretical framework for performing statistical hypothesis testing simultaneously over a fairly general, possibly uncountably infinite, set of null hypotheses. This extends the standard statistical setting for multiple hypotheses testing, which is restricted to a finite set. This work is motivated by numerous modern applications where the observed signal is modeled by a stochastic process over a continuum. As a measure of type I error, we extend the concept of false discovery rate (FDR) to this setting. The FDR is defined as the average ratio of the measure of two random sets, so that its study presents some challenge and is of some intrinsic mathematical interest. Our main result shows how to use the p-value process to control the FDR at a nominal level, either under arbitrary dependence of p-values, or under the assumption that the finite dimensional distributions of the p-value process have positive correlations of a specific type (weak PRDS). Both cases generalize existing results established in the finite setting, the latter one leading to a less conservative procedure. The interest of this approach is demonstrated in several non-parametric examples: testing the mean/signal in a Gaussian white noise model, testing the intensity of a Poisson process and testing the c.d.f. of i.i.d. random variables. Conceptually, an interesting feature of the setting advocated here is that it focuses directly on the intrinsic hypothesis space associated with a testing model on a random process, without referring to an arbitrary discretization. T3 - Preprints des Instituts für Mathematik der Universität Potsdam - 1 (2012) 1 Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-56877 ER - TY - JOUR A1 - Blanchard, Gilles A1 - Carpentier, Alexandra A1 - Gutzeit, Maurilio T1 - Minimax Euclidean separation rates for testing convex hypotheses in R-d JF - Electronic journal of statistics N2 - We consider composite-composite testing problems for the expectation in the Gaussian sequence model where the null hypothesis corresponds to a closed convex subset C of R-d. We adopt a minimax point of view and our primary objective is to describe the smallest Euclidean distance between the null and alternative hypotheses such that there is a test with small total error probability. In particular, we focus on the dependence of this distance on the dimension d and variance 1/n giving rise to the minimax separation rate. In this paper we discuss lower and upper bounds on this rate for different smooth and non-smooth choices for C. KW - Minimax hypothesis testing KW - Gaussian sequence model KW - nonasymptotic minimax separation rate Y1 - 2018 U6 - https://doi.org/10.1214/18-EJS1472 SN - 1935-7524 VL - 12 IS - 2 SP - 3713 EP - 3735 PB - Institute of Mathematical Statistics CY - Cleveland ER - TY - JOUR A1 - Biskaborn, Boris A1 - Smith, Sharon L. A1 - Noetzli, Jeannette A1 - Matthes, Heidrun A1 - Vieira, Goncalo A1 - Streletskiy, Dmitry A. A1 - Schoeneich, Philippe A1 - Romanovsky, Vladimir E. A1 - Lewkowicz, Antoni G. A1 - Abramov, Andrey A1 - Allard, Michel A1 - Boike, Julia A1 - Cable, William L. A1 - Christiansen, Hanne H. A1 - Delaloye, Reynald A1 - Diekmann, Bernhard A1 - Drozdov, Dmitry A1 - Etzelmueller, Bernd A1 - Grosse, Guido A1 - Guglielmin, Mauro A1 - Ingeman-Nielsen, Thomas A1 - Isaksen, Ketil A1 - Ishikawa, Mamoru A1 - Johansson, Margareta A1 - Johannsson, Halldor A1 - Joo, Anseok A1 - Kaverin, Dmitry A1 - Kholodov, Alexander A1 - Konstantinov, Pavel A1 - Kroeger, Tim A1 - Lambiel, Christophe A1 - Lanckman, Jean-Pierre A1 - Luo, Dongliang A1 - Malkova, Galina A1 - Meiklejohn, Ian A1 - Moskalenko, Natalia A1 - Oliva, Marc A1 - Phillips, Marcia A1 - Ramos, Miguel A1 - Sannel, A. Britta K. A1 - Sergeev, Dmitrii A1 - Seybold, Cathy A1 - Skryabin, Pavel A1 - Vasiliev, Alexander A1 - Wu, Qingbai A1 - Yoshikawa, Kenji A1 - Zheleznyak, Mikhail A1 - Lantuit, Hugues T1 - Permafrost is warming at a global scale JF - Nature Communications N2 - Permafrost warming has the potential to amplify global climate change, because when frozen sediments thaw it unlocks soil organic carbon. Yet to date, no globally consistent assessment of permafrost temperature change has been compiled. Here we use a global data set of permafrost temperature time series from the Global Terrestrial Network for Permafrost to evaluate temperature change across permafrost regions for the period since the International Polar Year (2007-2009). During the reference decade between 2007 and 2016, ground temperature near the depth of zero annual amplitude in the continuous permafrost zone increased by 0.39 +/- 0.15 degrees C. Over the same period, discontinuous permafrost warmed by 0.20 +/- 0.10 degrees C. Permafrost in mountains warmed by 0.19 +/- 0.05 degrees C and in Antarctica by 0.37 +/- 0.10 degrees C. Globally, permafrost temperature increased by 0.29 +/- 0.12 degrees C. The observed trend follows the Arctic amplification of air temperature increase in the Northern Hemisphere. In the discontinuous zone, however, ground warming occurred due to increased snow thickness while air temperature remained statistically unchanged. Y1 - 2019 U6 - https://doi.org/10.1038/s41467-018-08240-4 SN - 2041-1723 VL - 10 PB - Nature Publ. Group CY - London ER -