Magnetic trapping for an atom-chip-based gravimeter

In the past century, the development of gravimeters with low uncertainty and long-term stability has led to new fields of research in geodesy and geoscience. Decreasing the instrumental measurement uncertainty further will enable observations of previously inaccessible phenomena, for instance, mass transport in hydrology and volcanology. During the last decades, quantum sensors based on the interference of cold atoms have been developed. Using a cold atomic gas as test mass, the accuracy of these sensors is not limited by mechanical properties but by effects caused by the thermal expansion of the atomic ensemble. The application of ultra-cold atomic ensembles with lower expansion rates in atom interferometer gravimeters is projected to reduce the leading order uncertainties by more than an order of magnitude. At the same time, atom chip technology makes it possible to prepare ultra-cold atomic ensembles at a high repetition rate and to miniaturise the sensor size. These advancements promise the realisation of an absolute gravimeter with unprecedented accuracy. This thesis describes the design considerations and the assembly of the transportable Quantum Gravimeter (QG-1) based on light-pulse atom interferometry of Bose-Einstein condensates (BEC) prepared on an atom chip. It is estimated, that the two leading order uncertainties of systematic biases governing the instrumental measurement uncertainty of current generation cold atom gravimeters are reduced to less than 1 nm/s² in the QG-1 apparatus. The established design of an atom-chip-based BEC source pioneered in the Quantus collaboration is modified to meet the requirements of QG-1. A free optical aperture of 18 mm for the interferometry laser beam is realised by changing the orientation of the atom-chip-based BEC source. Therefore, a new layout of the mesoscopic wire structure of the atom chip is required. The design described in this thesis enables atom interferometry with a free falling test mass with a baseline of 330 mm. The retro-reflection mirror is placed inside the vacuum chamber to eliminate optical elements in the atom interferometer beam path. It is mounted on a custom designed tip/tilt-stage with compact size and a large dynamic range of up to a hundredfold of the Earth's rotation rate for characterisation. Furthermore, a compact, robust and transportable fibre based laser system with modular electronics and a computer control system are set up. The key result of this thesis is the reliable operation of the ultra-cold atomic source on the atom chip. After optimisation of the trap loading procedure for a high atom number and low excitation of oscillations, it was shown that the necessary design change of the atom chip allows for efficient operation. The compressed magnetic trap has a geometrically averaged trap frequency of 2π · 256 Hz and the trapped ensemble has a lifetime of 3.2 s. The evaporative cooling procedure starts with 3.3 · 10⁷ atoms at a temperature of 166 μK. Within 1.3 s, or 2.3 s for the complete sequence, 3000 atoms are prepared at a temperature of 160 nK close to the critical temperature for Bose-Einstein condensation

AMR Dependency Parsing with a Typed Semantic Algebra

We present a semantic parser for Abstract Meaning Representations which learns to parse strings into tree representations of the compositional structure of an AMR graph. This allows us to use standard neural techniques for supertagging and dependency tree parsing, constrained by a linguistically principled type system. We present two approximative decoding algorithms, which achieve state-of-the-art accuracy and outperform strong baselines.Comment: This paper will be presented at ACL 2018 (see https://acl2018.org/programme/papers/

Forecast Performance, Disagreement, and Heterogeneous Signal-to-Noise Ratios

We propose an imperfect information model for the expectations of macroeconomic forecasters that explains differences in average disagreement levels across forecasters by means of cross sectional heterogeneity in the variance of private noise signals. We show that the forecaster-specific signal-to-noise ratios determine both the average individual disagreement level and an individuals' forecast performance: forecasters with very noisy signals deviate strongly from the average forecasts and report forecasts with low accuracy. We take the model to the data by empirically testing for this implied correlation. Evidence based on data from the Surveys of Professional Forecasters for the US and for the Euro Area supports the model for short- and medium-run forecasts but rejects it based on its implications for long-run forecasts

Human myocardial protein pattern reveals cardiac diseases

Proteomic profiles of myocardial tissue in two different etiologies of heart failure were investigated using high performance liquid chromatography (HPLC)/Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Right atrial appendages from 10 patients with hemodynamically significant isolated aortic valve disease and from 10 patients with isolated symptomatic coronary heart disease were collected during elective cardiac surgery. As presented in an earlier study by our group (Baykut et al., 2006), both disease forms showed clearly different pattern distribution characteristics. Interesting enough, the classification patterns could be used for correctly sorting unknown test samples in their correct categories. However, in order to fully exploit and also validate these findings there is a definite need for unambiguous identification of the differences between different etiologies at molecular level. In this study, samples representative for the aortic valve disease and coronary heart disease were prepared, tryptically digested, and analyzed using an FT-ICR MS that allowed collision-induced dissociation (CID) of selected classifier masses. By using the fragment spectra, proteins were identified by database searches. For comparison and further validation, classifier masses were also fragmented and analyzed using HPLC-/Matrix-assisted laser desorption ionization (MALDI) time-of-flight/time-of-flight (TOF/TOF) mass spectrometry. Desmin and lumican precursor were examples of proteins found in aortic samples at higher abundances than in coronary samples. Similarly, adenylate kinase isoenzyme was found in coronary samples at a higher abundance. The described methodology could also be feasible in search for specific biomarkers in plasma or serum for diagnostic purposes

Sky View Factor footprints for urban climate modeling

Urban morphology is an important multidimensional variable to consider in climate modeling and observations, because it significantly drives the local and micro-scale climatic variability in cities. Urban form can be described through urban canopy parameters (UCPs) that resolve the spatial heterogeneity of cities by specifying the 3-dimensional geometry, arrangement, and materials of urban features. The sky view factor (SVF) is a dimension-reduced UCP capturing 3-dimensional form through horizon limitation fractions. SVF has become a popular metric to parameterize urban morphology, but current approaches are difficult to scale up to global coverage. This study introduces a Big-Data approach to calculate SVFs for urban areas from Google Street View (GSV). 90-degree field-of-view GSV photos are retrieved and converted into hemispherical views through equiangular projection. The fisheyes are segmented into sky and non-sky pixels using image processing, and the SVF is calculated using an annulus method. Results are compared to SVFs retrieved from GSV images segmented using deep learning. SVF footprints are presented for urban areas around the world tallying 15,938,172 GSV locations. Two use cases are introduced: (1) an evaluation of a Google Earth Engine classified Local Climate Zone map for Singapore; (2) hourly sun duration maps for New York and San Francisco

Organizational Water Footprint to Support Decision Making: a Case Study for a German Technological Solutions Provider for the Plumbing Industry

With water scarcity representing an increasing threat to humans, the environment and the economy, companies are interested in exploring how their operations and supply chains affect water resources globally. To allow for systematically compiling the water footprint at the company level, the organizational water footprint method based on ISO 14046 and ISO/TS 14072 was developed. This paper presents the first complete organizational water scarcity footprint case study carried out for Neoperl GmbH, a German company that offers innovative solutions regarding drinking water for the plumbing industry. The cradle-to-gate assessment for one year includes, besides facility-based production activities, purchased materials, electricity and fuels, and supporting activities, such as company vehicles and infrastructure. Neoperl’s total freshwater consumption amounts to approximately 110,000 m3, 96% thereof being attributable to the supply chain, with freshwater consumption through purchased metals playing the predominant role. Metals (mainly stainless steel and brass) are major hotspots, also when considering the water scarcity-related local impacts resulting from freshwater consumption, which mainly affect China and Chile. These results can be used to improve the company’s supply chain water use in cooperation with internal and external stakeholders by means of, e.g., sustainable purchase strategies or eco-design options to substitute water intensive materials.BMBF, 02WGR1429, GROW - Verbundprojekt WELLE: Wasserfußabdruck für Unternehmen - Lokale Maßnahmen in Globalen WertschöpfungskettenDFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli