Stochastic optimization of a cold atom experiment using a genetic algorithm

We employ an evolutionary algorithm to automatically optimize different stages of a cold atom experiment without human intervention. This approach closes the loop between computer based experimental control systems and automatic real time analysis and can be applied to a wide range of experimental situations. The genetic algorithm quickly and reliably converges to the most performing parameter set independent of the starting population. Especially in many-dimensional or connected parameter spaces the automatic optimization outperforms a manual search.Comment: 4 pages, 3 figure

RF-MEMS switch actuation pulse optimization using Taguchi's method

Copyright @ 2011 Springer-VerlagReliability and longevity comprise two of the most important concerns when designing micro-electro-mechanical-systems (MEMS) switches. Forcing the switch to perform close to its operating limits underlies a trade-off between response bandwidth and fatigue life due to the impact force of the cantilever touching its corresponding contact point. This paper presents for first time an actuation pulse optimization technique based on Taguchi’s optimization method to optimize the shape of the actuation pulse of an ohmic RF-MEMS switch in order to achieve better control and switching conditions. Simulation results show significant reduction in impact velocity (which results in less than 5 times impact force than nominal step pulse conditions) and settling time maintaining good switching speed for the pull down phase and almost elimination of the high bouncing phenomena during the release phase of the switch

Klimapolitische Entwicklungspfade deutscher Groß- und Mittelstädte

Dieser Forschungsbericht bietet vertiefte klimapolitische Pfadanalysen von 17 Groß- und Mittelstädten in den Bundesländern Baden-Württemberg, Bayern, Brandenburg und Nordrhein-Westfalen. Die Pfadanalysen basieren auf umfangreichen Analysen zahlreicher Policy-Dokumente und Interviews mit Vertreter:innen aus Stadtverwaltungen, Kommunalpolitik und Zivilgesellschaft. Die Fallstädte sind im Hinblick auf Klimapolitik unterschiedlich aktiv und lassen sich fünf verschiedenen Stadttypen zuordnen, die anhand von strukturellen Merkmalen definiert sind. Im Fokus des Berichts steht der Einfluss dieser Stadttypen auf die klimapolitische Aktivität einer Stadt. Dabei kommt die Studie zu folgenden zentralen Ergebnissen: - Städte, die seit Jahrzehnten ein Image als Grüne Städte pflegen und als Vorreiter in den Bereichen Umweltschutz und Nachhaltigkeit gelten, sind auch im Bereich Klimaschutz und meist auch im Bereich Klimaanpassung weit fortgeschritten. - Wissenschaftsstädten fällt es deutlich leichter klimapolitische Akzente zu setzen als anderen Städten. Dies liegt unter anderem an den oft günstigeren ökonomischen, sozio-ökonomischen und sozio-demographischen Rahmenbedingungen. - Industriestädten (im Wandel), bei denen es sich oft um schrumpfende Städte handelt, fällt es schwerer, klimapolitische Erfolge zu erzielen als etwa innovativen und wachsenden Wissenschaftsstädten. - In Welterbestädten kommt es oft zu Konflikten zwischen Klimapolitik und Denkmalschutz. Dennoch können je nach Art des Welterbes auch Synergien entstehen, da beide Aspekte Bestandteil einer nachhaltigen Stadtentwicklung sein können. - In Städteregionen kommt es oft zu fruchtbaren Kooperationen zwischen Städten (z.B. gemeinsame Klimastrategien). Bestätigen können wir dies aber nur für die Kooperation zwischen Großstädten innerhalb einer Städteregion

Icebergs in the North Atlantic: Modelling circulation changes and glacio-marine deposition

In order to investigate meltwater events in the North Atlantic, a simple iceberg generation, drift, and melting routine was implemented in a high-resolution OGCM. Starting from the modelled last glacial state, every 25th day cylindrical model icebergs 300 meters high were released at 32 specific points along the coasts. Icebergs launched at the Barents Shelf margin spread a light meltwater lid over the Norwegian and Greenland Seas, shutting down the deep convection and the anti-clockwise circulation in this area. Due to the constraining ocean circulation, the icebergs produce a tongue of relatively cold and fresh water extending eastward from Hudson Strait that must develop at this location, regardless of iceberg origin. From the total amount of freshwater inferred by the icebergs, the thickness of the deposited IRD could be calculated in dependance of iceberg sediment concentration. In this way, typical extent and thickness of Heinrich layers could be reproduced, running the model for 250 years of steady state with constant iceberg meltwater inflow

Restricted Isometries for Partial Random Circulant Matrices

In the theory of compressed sensing, restricted isometry analysis has become a standard tool for studying how efficiently a measurement matrix acquires information about sparse and compressible signals. Many recovery algorithms are known to succeed when the restricted isometry constants of the sampling matrix are small. Many potential applications of compressed sensing involve a data-acquisition process that proceeds by convolution with a random pulse followed by (nonrandom) subsampling. At present, the theoretical analysis of this measurement technique is lacking. This paper demonstrates that the $s$th order restricted isometry constant is small when the number $m$ of samples satisfies $m \gtrsim (s \log n)^{3/2}$, where $n$ is the length of the pulse. This bound improves on previous estimates, which exhibit quadratic scaling

Feasibility of detecting single atoms using photonic bandgap cavities

We propose an atom-cavity chip that combines laser cooling and trapping of neutral atoms with magnetic microtraps and waveguides to deliver a cold atom to the mode of a fiber taper coupled photonic bandgap (PBG) cavity. The feasibility of this device for detecting single atoms is analyzed using both a semi-classical treatment and an unconditional master equation approach. Single-atom detection seems achievable in an initial experiment involving the non-deterministic delivery of weakly trapped atoms into the mode of the PBG cavity.Comment: 11 pages, 5 figure

Anisotropy of the Topopah Spring Member Tuff

Mechanical properties of the tuffaceous rocks within Yucca Mountain are needed for near and far-field modeling of the potential nuclear waste repository. If the mechanical properties are significantly anisotropic (i.e., direction-dependent), a more complex model is required. Relevant data from tuffs tested in earlier studies indicate that elastic and strength properties are anisotropic. This scoping study confirms the elastic anisotropy and concludes some tuffs are transversely isotropic. An approach for sampling and testing the rock to determine the magnitude of the anisotropy is proposed

Far-infrared absorption in parallel quantum wires with weak tunneling

We study collective and single-particle intersubband excitations in a system of quantum wires coupled via weak tunneling. For an isolated wire with parabolic confinement, the Kohn's theorem guarantees that the absorption spectrum represents a single sharp peak centered at the frequency given by the bare confining potential. We show that the effect of weak tunneling between two parabolic quantum wires is twofold: (i) additional peaks corresponding to single-particle excitations appear in the absorption spectrum, and (ii) the main absorption peak acquires a depolarization shift. We also show that the interplay between tunneling and weak perpendicular magnetic field drastically enhances the dispersion of single-particle excitations. The latter leads to a strong damping of the intersubband plasmon for magnetic fields exceeding a critical value.Comment: 18 pages + 6 postcript figure

An improved constraint satisfaction adaptive neural network for job-shop scheduling

Copyright @ Springer Science + Business Media, LLC 2009This paper presents an improved constraint satisfaction adaptive neural network for job-shop scheduling problems. The neural network is constructed based on the constraint conditions of a job-shop scheduling problem. Its structure and neuron connections can change adaptively according to the real-time constraint satisfaction situations that arise during the solving process. Several heuristics are also integrated within the neural network to enhance its convergence, accelerate its convergence, and improve the quality of the solutions produced. An experimental study based on a set of benchmark job-shop scheduling problems shows that the improved constraint satisfaction adaptive neural network outperforms the original constraint satisfaction adaptive neural network in terms of computational time and the quality of schedules it produces. The neural network approach is also experimentally validated to outperform three classical heuristic algorithms that are widely used as the basis of many state-of-the-art scheduling systems. Hence, it may also be used to construct advanced job-shop scheduling systems.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01 and in part by the National Nature Science Fundation of China under Grant 60821063 and National Basic Research Program of China under Grant 2009CB320601