Optomechanics

We review recent progress in the field of optomechanics, where one studies the effects of radiation on mechanical motion. The paradigmatic example is an optical cavity with a movable mirror, where the radiation pressure can induce cooling, amplification and nonlinear dynamics of the mirror.Comment: 12 pages, 4 figures, submitted to the proceedings of the NATO Advanced Research Workshop 'Recent Advances in Nonlinear Dynamics and Complex System Physics', Tashkent, Uzbekistan, 200

The optomechanical instability in the quantum regime

We consider a generic optomechanical system, consisting of a driven optical cavity and a movable mirror attached to a cantilever. Systems of this kind (and analogues) have been realized in many recent experiments. It is well known that those systems can exhibit an instability towards a regime where the cantilever settles into self-sustained oscillations. In this paper, we briefly review the classical theory of the optomechanical instability, and then discuss the features arising in the quantum regime. We solve numerically a full quantum master equation for the coupled system, and use it to analyze the photon number, the cantilever's mechanical energy, the phonon probability distribution and the mechanical Wigner density, as a function of experimentally accessible control parameters. We observe and discuss the quantum-to-classical transition as a function of a suitable dimensionless quantum parameter.Comment: 23 pages, 6 figures, subm. to focus issue of New Journal of Physics on "Mechanical Systems at the Quantum Limit

Novel methodological approaches in loess research – interrogating biomarkers and compound-specific stable isotopes

Löss-Paläoboden Sequenzen sind wichtige terrestrische Archive für die Rekonstruktion der quartären Landschafts- und Klimageschichte. Die Entwicklung neuer, quantitativerer Paläoklima-Proxies könnte in den kommenden Jahren eine neue Ära in der Lössforschung einleiten. Dieser Review-Artikel stellt die Prinzipien, die zugrunde liegende Analytik, und erste Anwendungsbeispiele für einige dieser Proxies vor, welche derzeit entwickelt werden. Wir diskutieren das Potential von (i) pflanzenwachsbürtigen n-Alkanen als Biomarker für die Rekonstruktion der Vegetationsgeschichte, (ii) Aminosäure Razemisierung und Glycerin-Dialkyl-Glycerin-Tetraether (GDGT) Indizes als Proxies für die Rekonstruktion der Paläotemperatur und (iii) substanzspezifischen δD and δ18O Analysen an pflanzenbürtigen n-Alkanen bzw. Zuckern für die Entwicklung von Proxies zur Rekonstruktion von Paläoklima/-aridität. Während wir versuchen, die Leserschaft für die methodischen und analytischen Neuentwicklungen und deren Potential für die Lössforschung zu begeistern, verweisen wir gleichzeitig auch auf die Limitierungen und Schwächen der jeweiligen Methoden. So müssen beispielsweise Degradationseffekte oder postsedimentäre ‚Kontamination’ bei der Interpretation von Biomarker-Rekords berücksichtigt und weiter untersucht werden. Des Weiteren könnte sich die Quantifizierung der unterschiedlichen Einflussfaktoren auf Deuterium- und 18O-Rekords als herausfordernd erweisen.researc

Collective dynamics in optomechanical arrays

The emerging field of optomechanics seeks to explore the interaction between nanomechanics and light. Recently, the exciting concept of optomechanical crystals has been introduced, where defects in photonic crystal structures are used to generate both localized optical and mechanical modes that interact with each other. Here we start exploring the collective dynamics of arrays consisting of many coupled optomechanical cells. We show that such "optomechanical arrays" can display synchronization and that they can be described by a modified Kuramoto model that allows to explain and predict most of the features that will be observable in future experiments.Comment: 6 pages, 5 figure

Automated Processing of Webcam Images for Phenological Classification

Along with the global climate change, there is an increasing interest for its effect on phenological patterns such as start and end of the growing season. Scientific digital webcams are used for this purpose taking every day one or more images from the same natural motive showing for example trees or grassland sites. To derive phenological patterns from the webcam images, regions of interest are manually defined on these images by an expert and subsequently a time series of percentage greenness is derived and analyzed with respect to structural changes. While this standard approach leads to satisfying results and allows to determine dates of phenological change points, it is associated with a considerable amount of manual work and is therefore constrained to a limited number of webcams only. In particular, this forbids to apply the phenological analysis to a large network of publicly accessible webcams in order to capture spatial phenological variation. In order to be able to scale up the analysis to several hundreds or thousands of webcams, we propose and evaluate two automated alternatives for the definition of regions of interest, allowing for efficient analyses of webcam images. A semi-supervised approach selects pixels based on the correlation of the pixels’ time series of percentage greenness with a few prototype pixels. An unsupervised approach clusters pixels based on scores of a singular value decomposition. We show for a scientific webcam that the resulting regions of interest are at least as informative as those chosen by an expert with the advantage that no manual action is required. Additionally, we show that the methods can even be applied to publicly available webcams accessed via the internet yielding interesting partitions of the analyzed images. Finally, we show that the methods are suitable for the intended big data applications by analyzing 13988 webcams from the AMOS database. All developed methods are implemented in the statistical software package R and publicly available in the R package phenofun. Executable example code is provided as supplementary material