High-fidelity, near-field microwave gates in a cryogenic surface trap

We present a novel dynamical decoupling strategy for near field microwave gradient driven, Mølmer-Sørensen style, two-ion quantum logic gates, which suppresses errors from both fluctuations in the qubit frequency and imperfection in the decoupling drive itself. Using a microwave-integrated surface-trap which is operated cryogenically at 25 K and a magnetically insensitive 43-Ca+ qubit at 288 G, we demonstrate a 331 us two-ion quantum logic gates, with 4.9(11)e-3 logic error probability. This is below the 1% error threshold required for quantum error correction and represents a ~10x gate time reduction when compared to previously demonstrated near field gradient driven microwave gates below the 1% error probability threshold. Additionally, two faster gates were demonstrated without the use of dynamical decoupling. Respectively, these two gates had gate operation durations of 216.8 us & 153.8 us and measured gate error probabilities of 8.5(20)e-3 & 9.8(21)e-3. Further, we develop a method for rapid calculation of ion transport operations. We successfully demonstrate ion transport as well as crystal splitting and merging operations within two different ion traps using the waveforms calculated by this ion transport toolbox

Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps

Grid maps are widely used in robotics to represent obstacles in the environment and differentiating dynamic objects from static infrastructure is essential for many practical applications. In this work, we present a methods that uses a deep convolutional neural network (CNN) to infer whether grid cells are covering a moving object or not. Compared to tracking approaches, that use e.g. a particle filter to estimate grid cell velocities and then make a decision for individual grid cells based on this estimate, our approach uses the entire grid map as input image for a CNN that inspects a larger area around each cell and thus takes the structural appearance in the grid map into account to make a decision. Compared to our reference method, our concept yields a performance increase from 83.9% to 97.2%. A runtime optimized version of our approach yields similar improvements with an execution time of just 10 milliseconds.Comment: This is a shorter version of the masters thesis of Florian Piewak and it was accapted at IV 201

Results from the Farm Behaviour Component of the Integrated Economic-Hydrologic Model for the Watershed Evaluation of Beneficial Management Practices Program

This report summarizes preliminary results from the Farm Behavior component of the South Tobacco Creek Integrated Modeling Project (STC Project) which is being undertaken as part of the Watershed Evaluation of BMPs (WEBs) Program. WEBS is a partnership between Agriculture and Agri-Food Canada (AAFC) and Ducks Unlimited Canada (DUC) established to evaluate the economic and environmental performance of BMPs for water quality at the watershed scale. Water draining from South Tobacco Creek eventually enters to Lake Winnipeg which is degraded from the cumulative effects of nutrient loading, particularly phosphorous. Many jurisdictions across the world, including Canada, use payments programs to encourage land owners to change land management practices in order to reduce non-point source pollution. BMP incentive programs in Canada, such as Greencover, rely on fixed payment schemes which pay producers a set amount for BMPs, regardless of costs or benefits. In order to improve the performance of payment programs many jurisdictions have instituted auction type mechanisms. The purpose of the Farm Behavior component of the STC project is to examine the performance of various types of payment programs for BMPs relative to reducing phosphorous loads from STC. Theoretical and empirical evidence from conservation auctions suggest that the performance of auctions depends on several factors which affect the bidding behavior of producers during the auction, and therefore the cost-effectiveness of auctions over other types of payment programs. In particular, some producers actually benefit from BMPs, however under certain auction rules these producers would be paid the same amount as high cost producers; alternatively, producers with low costs of adopting BMPs may not always provide the greatest benefits in terms of pollution abatement depending on their location in the watershed, and physical features of their land. We assessed the relative performance of different payment programs by developing producer response functions for adoption of Beneficial Management Practices (BMPs). Producer adoption responses under different incentive schemes were tested using experiments with student subjects and limited trials with producers. We examined four BMPs: construction of holding ponds, riparian management, forage conversion, and conservation till. The results of the adoption response experiments conducted under WEBS were used to draw preliminary observations on BMP policy design and form the basis for recommendations for further research. The farm behavior project focuses on addressing the following two questions: 1. Does BMP adoption at a given farm make the individual farm household better or worse off from an economic perspective? 2. How much will it cost the government to get farms to adopt BMPs under different payment programs? Since producer heterogeneity is key to understanding the performance of conservation auctions, we examined the costs and benefits of BMPs at the individual farm level and developed on-farm costs for each BMP for each producer in the watershed. The basic components of the model are described below, however the details including underlying assumptions regarding baseline farm behavior, are outlined within the body of the report. We used the on-farm cost model to generate aggregate cost functions for BMPs for the watershed and to parameterize the policy experiments related to conservation auctions. Preliminary estimates of environmental benefits of individual BMP adoption were provided by Dr. Wanhong Yang using results from a SWAT model developed under a separate component of the South Tobacco Creek WEBS project. Based on this information, we were able to evaluate the performance of various auction formats in terms of cost effectiveness, distribution of payments amongst producers, and environmental benefit. The results from the Farm behavior component of the South Tobacco Creek project are preliminary, and are currently being refined. Therefore it is difficult to draw generalized conclusions at this point. Further experiments are being conducted to complete the data collection during FY 08-09 through Interim WEBS funding. Nonetheless main findings to date are summarized below: 1. The four BMPs assessed differ in terms of their cost as well as their ability to deliver environmental benefits. Unfortunately, there is no BMP that dominates across farms at all abatement levels. Farms have heterogeneous costs in terms of BMPs, and some farms are cost effective at supplying abatement using one BMP, but not another. 2. This suggests that if water quality benefits (e.g. phosphorous reduction) can be quantified through modeling by BMP and by farm, then water quality should be the contracting unit for the auction rather than the BMP. This would allow producers to select the most cost effective BMP for supplying water quality benefits, and then decision makers could allocate contracts based on ranking the costs of abatement. 3. At the next stage of the research we will test for synergies between farms – ie., whether the joint production function for water quality between farms differs from the sum of individual production functions. This will have implications for how the payment scheme should be designed. 4. Incorporating „fairness‟ types of allocation rules for conservation dollars, such as maximum participation in conservation programs is inefficient in terms of cost and environmental benefits. If fairness, or using conservation payments as a form of extension to learn about on farm costs of BMPs is the goal of the auction, then fixed payment programs which are open to everyone may be more desirable. 5. The performance of the auction depends on the shape of the cost function for BMPs and/or pollution abatement, as well as whether uniform (pay everyone the highest bid) or discriminatory pricing (pay everyone their own bid) rules are applied. In future research we will be investigating to what extent we can generalize results about the performance of uniform versus discriminatory pricing rules in this context. In conclusion, this research has allowed us to investigate individually the performance of incentive payments for individual BMPs. The results of the analysis provide us with a baseline of information by which we can begin to assess more complex conservation program issues, such as how to optimally select multiple BMPs within the watershed, and whether/how to spatially target BMPs.watersheds, South Tobacco Creek, water quality, Environmental Economics and Policy, Land Economics/Use, Resource /Energy Economics and Policy, Q12,Q52,D44,

Transforming 2D Radar Remote Sensor Information from a UAV into a 3D World-View

[EN] Since unmanned aerial vehicles (UAVs) have been established in geoscience as a key and accessible tool, a wide range of applications are currently being developed. However, not only the design of UAVs themselves is vital to carry out an accurate investigation, but also the sensors and the data processing are key parts to be considered. Several publications including accurate sensors are taking part in pioneer research programs, but less is explained about how they were designed. Besides the commonly used sensors such as a camera, one of the most popular ones is radar. The advantages of a radar sensor to perform research in geosciences are the robustness, the ability to consider large distances and velocity measurements. Unfortunately, these sensors are often expensive and there is a lack of methodological papers that explain how to reduce these costs. To fill this gap, this article aims to show how: (i) we used a radar sensor from the automotive field; and (ii) it is possible to reconstruct a three-dimensional scenario with a UAV and a radar sensor. Our methodological approach proposes a total of eleven stages to process the radar data. To verify and validate the process, a real-world scenario reconstruction is presented with a system resolution reaching from two to three times the radar resolution. We conclude that this research will help the scientific community to include the use of radars in their research projects and programs, reducing costs and increasing accuracy.This research work was supported by the "European Regional Development Fund" (EFRE) in the context of the aim of "Investment in Growth and Employment" (IWB) in Rhineland-Palatinate, Germany.Weber, C.; Eggert, M.; Rodrigo-Comino, J.; Udelhoven, T. (2022). Transforming 2D Radar Remote Sensor Information from a UAV into a 3D World-View. Remote Sensing. 14(7). https://doi.org/10.3390/rs1407163314

High Temperature Solid Oxide Electrolysis – Technology and Modeling

In the global quest to renounce from fossil fuels, a large demand for the renewable production of hydrogen via water electrolysis exists. In this context, the solid oxide electrolyzer (SOE) is an interesting technology due to its high efficiency resulting from elevated operating temperatures of up to 900 °C. Physical modeling plays a vital role in the development of SOEs, as it lowers experimental costs and provides insight where measurements reach limits. A main challenge for modeling SOEs is the multitude of physical effects, occurring and interacting on various spatial and temporal scales. This requires assumptions and simplifications, particularly when increasing scope and dimensions of a model. In this review, we discuss the different approaches currently available in literature

Virtual Reality Technologies in Health Care: A Literature Review of Theoretical Foundations

The digitization of health care promises an improvement of medical care through the adoption of virtual reality (VR) related technologies. Although most undergoing mechanisms of clinical effectiveness are yet not defined theoretically, research approaches have already taken place in several empirical settings. To structure current and upcoming scientific work in this field, we conducted a literature review with regard to theoretical implications of both IS-related and healthcare-related research. We found several theoretical bases to build upon in the field of psychology, but expressed a need for enrichment of theoretical foundations in the field of IS research. We therefore plead for a theoretical foundation enriched by synergetic concepts of clinically effective VR related technologies. Finally, we conclude that VR related technologies appear as a promising approach worth further theoretical and empirical research in order to improve medical care

Countrywide mapping of shrub forest using multi-sensor data and bias correction techniques

The continual increase of shrub forest in the Swiss Alps over the past few decades impacts biodiversity, forest succession and the protective function of forests. Therefore, up-to-date and area-wide information on its distribution is of great interest. To detect the shrub forest areas for the whole of Switzerland (41,285 km2), we developed an approach that uses Random Forest (RF), bias correction techniques and data from multiple remote sensing sources. Manual aerial orthoimage interpretation of shrub forest areas was conducted in a non-probabilistic way to derive initial training data. The multi-sensor and open access predictor data included digital terrain and vegetation height models obtained from Airborne Laser Scanning (ALS) and stereo-imagery, as well as Synthetic Aperture Radar (SAR) backscatter from Sentinel-1 and multispectral imagery from Sentinel-2. To mitigate the expected bias due to the training data sampling strategy, two techniques using RF probability estimates were tested to improve mapping accuracy. 1) an iterative and semi-automated active learning technique was used to generate further training data and 2) threshold-moving related object growing was applied. Both techniques facilitated the production of a shrub forest map for the whole of Switzerland at a spatial resolution of 10 m. An accuracy assessment was performed using independent data covering 7640 regularly distributed National Forest Inventory (NFI) plots. We observed the influence of the bias correction techniques and found higher accuracies after each performed iteration. The Mean Absolute Error (MAE) for the predicted shrub forest proportion was reduced from 6.04% to 2.68% while achieving a Mean Bias Error (MBE) of close to 0. The present study underscores the potential of combining multi-sensor data with bias correction techniques to provide cost-effective and accurate countrywide detection of shrub forest. Moreover, the map complements currently available NFI plot sample point data