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Geographic dispersion of depositors, borrowers, and banks may prevent funding from flowing to high loan demand areas, limiting credit access. Using bank-county-year level data, we provide evidence of the geographic imbalance of deposits and loans and develop a methodology for investigating the contribution to this imbalance of branch networks, market power, and scope economies. Results are based on a novel measure of imbalance and estimation of a structural model of bank competition that admits interconnections across locations and between deposit and loan markets. Counterfactual experiments show branch networks and competition contribute importantly to credit flow but benefit more affluent markets., Comment: 75 pages

There is a growing trend among statistical agencies to explore non-probability data sources for producing more timely and detailed statistics, while reducing costs and respondent burden. Coverage and measurement error are two issues that may be present in such data. The imperfections may be corrected using available information relating to the population of interest, such as a census or a reference probability sample. In this paper, we compare a wide range of existing methods for producing population estimates using a non-probability dataset through a simulation study based on a realistic business population. The study was conducted to examine the performance of the methods under different missingness and data quality assumptions. The results confirm the ability of the methods examined to address selection bias. When no measurement error is present in the non-probability dataset, a screening dual-frame approach for the probability sample tends to yield lower sample size and mean squared error results. The presence of measurement error and/or nonignorable missingness increases mean squared errors for estimators that depend heavily on the non-probability data. In this case, the best approach tends to be to fall back to a model-assisted estimator based on the probability sample., Comment: Submitted to the Journal of Official Statistics, and is currently under review

Cosmic rays are energetic nuclei and elementary particles that originate from stars and intergalactic events. The interaction of these particles with the upper atmosphere produces a range of secondary particles that reach the surface of the earth, of which muons are the most prominent. With enough energy, muons can travel up to a few kilometers beneath the surface of the earth before being stopped completely. The terrestrial muon flux profile and associated zenith angle can be utilized to determine geological characteristics of a location without having to use conventional methods. This work intends to use a low-power plastic scintillator-based muon detection system for this non-destructive geological assay methodology. 4 custom designed plastic scintillation panels are used to realize two orthogonal detection planes. Simultaneous triggers between detectors from two planes indicate a coincidence event which is recorded using a data acquisition system from FNAL. In order to quantify the systematic uncertainties associated with the detector, such as energy depositions and angular resolution of the detector design, a Monte Carlo simulation using Geant4 is being developed. Simulated and experimental data will drive the development and validation of a reconstruction algorithm that, upon completion, is expected to predict average overburden and rock density. Extended detector exposure to muons can be used as a means to understand changes in the surrounding environment like rock porosity. On the experimental front, the measured flux data will be used to benchmark independent and established models. Successful proof-of-concept demonstration of this technology can open doors for long term non-invasive geological monitoring. The detector design, and experimental methodology are detailed in this work., Comment: American Nuclear Society 2022 International High-Level Radioactive Waste Management Conference (https://www.ans.org/pubs/proceedings/article-52770/)

Ion transport is an essential operation in some models of quantum information processing, where fast ion shuttling with minimal motional excitation is necessary for efficient, high-fidelity quantum logic. While fast and cold ion shuttling has been demonstrated, the dynamics and specific trajectory of an ion during diabatic transport have not been studied in detail. Here we describe a position-dependent optical deshelving technique useful for sampling an ion's position throughout its trajectory, and we demonstrate the technique on fast linear transport of a $^{40}\text{Ca}^+$ ion in a surface-electrode ion trap. At high speed, the trap's electrode filters strongly distort the transport potential waveform. With this technique, we observe deviations from the intended constant-velocity (100 m/s) transport: we measure an average speed of 83(2) m/s and a peak speed of 251(6) m/s over a distance of 120 $\mu$m