Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
967
result(s) for
"Gottwald, A"
Sort by:
Rembrandt's light
Rembrandt's Light' brings together paintings, etchings and drawings that focus on Rembrandt's mastery of visual storytelling through light, concentrating on the period from 1639-58, when he lived in his 'dream house' on the Breestraat in the heart of Amsterdam (today the Museum Het Rembrandthuis). The rooms on the first floor of the house, with their large windows and exceptional quality of light, offered new possibilities for the creation of art works.00Arranged thematically the book traces Rembrandt's innovation: from evoking a meditative mood, to lighting people, to creating impact and drama. Highlights include 'The Denial of St Peter', 'Pilgrims at Emmaus' and three of the artist's most famous images of women: 'A Woman Bathing in a Stream', 'A Woman in Bed' and 'Girl at a Window'.00Published to coincide with an exhibition at Dulwich Picture Gallery, and the celebrations taking place throughout Europe to mark 350 years since the artist's death (1669), Rembrandt's Light aims to refresh the way we look at works by this incomparable Dutch Master. 00Exhibition: Dulwich Picture Gallery, London, UK (04.10.2019-02.02.2020).
Book
Learning dynamical systems with hit-and-run random feature maps
We show how random feature maps can be used to forecast dynamical systems with excellent forecasting skill. We consider the tanh activation function and judiciously choose the internal weights in a data-driven manner such that the resulting features explore the nonlinear, non-saturated regions of the activation function. We introduce skip connections and construct a deep variant of random feature maps by combining several units. To mitigate the curse of dimensionality, we introduce localization where we learn local maps, employing conditional independence. Our modified random feature maps provide excellent forecasting skill for both single trajectory forecasts as well as long-time estimates of statistical properties, for a range of chaotic dynamical systems with dimensions up to 512. In contrast to other methods such as reservoir computers which require extensive hyperparameter tuning, we effectively need to tune only a single hyperparameter, and are able to achieve state-of-the-art forecasting skill with much smaller networks.
Learning chaotic dynamical systems from data is notoriously hard. Here, authors refine random feature maps via judicious weight sampling, skip connections, localization and a deep architecture, producing forecasts at a fraction of previous computational costs.
Journal Article
Experimental search for the low-energy nuclear transition in 229Th with undulator radiation
To search for the lowest energy nuclear isomeric transition in 229Th in solid samples, a novel adsorption technique which prepares 229Th atoms on a surface of CaF2 is developed. Adsorbed 229Th is exposed to highly intensive undulator radiation in the wavelength range between 130 and 320 nm, which includes the indirectly measured nuclear resonance wavelength 160(10) nm. After the excitation, fluorescence from the sample is detected with a VUV sensitive photomultiplier tube. No clear signal relating to the nuclear transition is observed and possible reasons are discussed.
Journal Article
On the Implementation of the 0–1 Test for Chaos
In this paper we address practical aspects of the implementation of the 0-1 test for chaos in deterministic systems. In addition, we present a new formulation of the test which significantly increases its sensitivity. The test can be viewed as a method for distilling a binary quantity from the power spectrum. The implementation is guided by recent results from the theoretical justification of the test as well as by exploring better statistical methods for determining the binary quantities. We give several examples to illustrate the improvement.
Journal Article
A new test for chaos in deterministic systems
We describe a new test for determining whether a given deterministic dynamical system is chaotic or non-chaotic. In contrast to the usual method of computing the maximal Lyapunov exponent, our method is applied directly to the time-series data and does not require phase-space reconstruction. Moreover, the dimension of the dynamical system and the form of the underlying equations are irrelevant. The input is the time-series data and the output is 0 or 1, depending on whether the dynamics is non-chaotic or chaotic. The test is universally applicable to any deterministic dynamical system, in particular to ordinary and partial differential equations, and to maps. Our diagnostic is the real valued function p(t)= t 0 (x(s))cos(θ(s))ds, where φ is an observable on the underlying dynamicsx(t) and θ(t)=ct+ ∫ 0 t (x(s))ds. The constant c > 0 is fixed arbitrarily. We define the mean-square displacement M(t) for p(t) and set K=limt→∞logM(t)/logt. Using recent developments in ergodic theory, we argue that, typically, K=0, signifying non-chaotic dynamics, or K=1, signifying chaotic dynamics.
Journal Article
Huygens principle for diffusion and anomalous diffusion in spatially extended systems
We present a universal view on diffusive behavior in chaotic spatially extended systems for anisotropic and isotropic media. For anisotropic systems, strong chaos leads to diffusive behavior (Brownian motion with drift) and weak chaos leads to superdiffusive behavior (Lévy processes with drift). For isotropic systems, the drift term vanishes and strong chaos again leads to Brownian motion. We establish the existence of a nonlinear Huygens principle for weakly chaotic systems in isotropic media whereby the dynamics behaves diffusively in even space dimension and exhibits superdiffusive behavior in odd space dimensions.
Journal Article
A model for Dansgaard–Oeschger events and millennial-scale abrupt climate change without external forcing
We propose a conceptual model which generates abrupt climate changes akin to Dansgaard–Oeschger events. In the model these abrupt climate changes are not triggered by external perturbations but rather emerge in a dynamic self-consistent way through complex interactions of the ocean, the atmosphere and an intermittent process. The abrupt climate changes are caused in our model by intermittencies in the sea-ice cover. The ocean is represented by a Stommel two-box model, the atmosphere by a Lorenz-84 model and the sea-ice cover by a deterministic approximation of a correlated additive and multiplicative noise (CAM) process. The key dynamical ingredients of the model are given by stochastic limits of deterministic multi-scale systems and recent results in deterministic homogenisation theory. The deterministic model reproduces statistical features of actual ice-core data such as non-Gaussian
α
-stable behaviour. The proposed mechanism for abrupt millenial-scale climate change only relies on the existence of a quantity, which exhibits intermittent dynamics on an intermediate time scale. We consider as a particular mechanism intermittent sea-ice cover where the intermittency is generated by emergent atmospheric noise. However, other mechanisms such as freshwater influxes may also be formulated within the proposed framework.
Journal Article
Exploring three-dimensional orbital imaging with energy-dependent photoemission tomography
Recently, it has been shown that experimental data from angle-resolved photoemission spectroscopy on oriented molecular films can be utilized to retrieve real-space images of molecular orbitals in two dimensions. Here, we extend this orbital tomography technique by performing photoemission initial state scans as a function of photon energy on the example of the brickwall monolayer of 3,4,9,10-perylene tetracarboxylic dianhydride (PTCDA) on Ag(110). The overall dependence of the photocurrent on the photon energy can be well accounted for by assuming a plane wave for the final state. However, the experimental data, both for the highest occupied and the lowest unoccupied molecular orbital of PTCDA, exhibits an additional modulation attributed to final state scattering effects. Nevertheless, as these effects beyond a plane wave final state are comparably small, we are able, with extrapolations beyond the attainable photon energy range, to reconstruct three-dimensional images for both orbitals in agreement with calculations for the adsorbed molecule.
Experimental data from angle-resolved photoemission spectroscopy can be utilized on molecular films to retrieve real-space images of molecular orbitals in two dimensions. Here, by scanning initial states as a function of photon energy, the authors can reconstruct three-dimensional orbital images.
Journal Article
The new PTB beamline for vacuum-ultraviolet radiometry
At the Metrology Light Source, a 630 MeV electron storage ring for the use of synchrotron radiation for metrology applications, a new beamline is dedicated to radiometry in the vacuum-ultraviolet spectral range. The emphasis lies on the traceability of measurements and profound uncertainty analysis. To replace the previously existing normal incidence monochromator beamline which serviced for more than 20 years now at different facilities, a newly designed 2 m off-plane Eagle monochromator beamline concept was developed. Different reflective coatings for mirrors and gratings in combination with order-sorting filters ensure highest spectral purity of the monochromatized radiation in combination with optimized photon flux characteristics. The beamline is planned to go into full operation in late 2022.
Journal Article
Stochastic partial differential fluid equations as a diffusive limit of deterministic Lagrangian multi-time dynamics
In Holm (Holm 2015 Proc. R. Soc. A 471, 20140963. (doi:10.1098/rspa.2014.0963)), stochastic fluid equations were derived by employing a variational principle with an assumed stochastic Lagrangian particle dynamics. Here we show that the same stochastic Lagrangian dynamics naturally arises in a multi-scale decomposition of the deterministic Lagrangian flow map into a slow large-scale mean and a rapidly fluctuating small-scale map. We employ homogenization theory to derive effective slow stochastic particle dynamics for the resolved mean part, thereby obtaining stochastic fluid partial equations in the Eulerian formulation. To justify the application of rigorous homogenization theory, we assume mildly chaotic fast small-scale dynamics, as well as a centring condition. The latter requires that the mean of the fluctuating deviations is small, when pulled back to the mean flow.
Journal Article