Quasiparticle trapping in Meissner and vortex states of mesoscopic superconductors

Nowadays superconductors serve in numerous applications, from high-field magnets to ultra-sensitive detectors of radiation. Mesoscopic superconducting devices, i.e. those with nanoscale dimensions, are in a special position as they are easily driven out of equilibrium under typical operating conditions. The out-of-equilibrium superconductors are characterized by non-equilibrium quasiparticles. These extra excitations can compromise the performance of mesoscopic devices by introducing, e.g., leakage currents or decreased coherence times in quantum devices. By applying an external magnetic field, one can conveniently suppress or redistribute the population of excess quasiparticles. In this article we present an experimental demonstration and a theoretical analysis of such effective control of quasiparticles, resulting in electron cooling both in the Meissner and vortex states of a mesoscopic superconductor. We introduce a theoretical model of quasiparticle dynamics which is in quantitative agreement with the experimental data

Multi-scale movement of demersal fishes in Alaska

Thesis (Ph.D.) University of Alaska Fairbanks, 2019Information on the movement of migratory demersal fishes such as Pacific halibut, Pacific cod, and sablefish is needed for management of these valuable fisheries in Alaska, yet available methods such as conventional tagging are too coarse to provide detailed information on migration characteristics. In this dissertation, I present methods for characterizing seasonal and annual demersal fish movement at multiple scales in space and time using electronic archival and acoustic tags. In Chapter 1, acoustic telemetry and the Net Squared Displacement statistic were used to identify and characterize small-scale movement of adult female Pacific halibut during summer foraging in a Marine Protected Area (MPA). The dominant movement pattern was home range behavior at spatial scales of less than 1 km, but a more dispersive behavioral state was also observed. In Chapter 2, Pop-up Satellite Archival Tags (PSATs) and acoustic tags were deployed on adult female Pacific halibut to determine annual movement patterns relative to MPA boundaries. Based on observations of summer home range behavior, high rates of year-round MPA residency, migration timing that largely coincided with winter commercial fisheries closures, and the demonstrated ability of migratory fish to return to previously occupied summer foraging areas, the MPA is likely to be effective for protecting both resident and migrant Pacific halibut brood stock year-round. In Chapter 3, I adapted a Hidden Markov Model (HMM) originally developed for geolocation of Atlantic cod in the North Sea for use on demersal fishes in Alaska, where maximum daily depth is the most informative and reliable geolocation variable. Because depth is considerably more heterogeneous in many regions of Alaska compared to the North Sea, I used simulated trajectories to determine that the degree of bathymetry heterogeneity affected model performance for different combinations of likelihood specification methods and model grid sizes. In Chapter 4, I added a new geolocation variable, geomagnetic data, to the HMM in a small-scale case study. The results suggest that the addition of geomagnetic data could increase model performance over depth alone, but more research is needed to continue validation of the method over larger areas in Alaska. In general, the HMM is a flexible tool for characterizing movement at multiple spatial scales and its use is likely to enrich our knowledge about migratory demersal fish movement in Alaska. The methods developed in this dissertation can provide valuable insights into demersal fish spatial dynamics that will benefit fisheries management activities such as stock delineation, stock assessment, and design of space-time closures.Rasmuson Fisheries Research Center and the Pollock Conservation Cooperative Research CenterChapter 1: Characterizing Pacific halibut movement and habitat in a Marine Protected Area using net squared displacement analysis methods -- Chapter 2: Interannual site fidelity of Pacific halibut: potential utility of protected areas for management of a migratory demersal fish -- Chapter 3 Effect of study area bathymetric heterogeneity on parameterization and performance of a depth depth-based geolocation model for demersal fishes -- Chapter 4 Potential utility of geomagnetic data for geolocation of demersal fish in the North Pacific Ocean -- General conclusion -- References -- Appendix A: Geolocation of demersal fishes in the North Pacific Ocean: Hidden Markov model framework and data likelihood models

Multimodal Image Fusion and Its Applications.

Image fusion integrates different modality images to provide comprehensive information of the image content, increasing interpretation capabilities and producing more reliable results. There are several advantages of combining multi-modal images, including improving geometric corrections, complementing data for improved classification, and enhancing features for analysis...etc. This thesis develops the image fusion idea in the context of two domains: material microscopy and biomedical imaging. The proposed methods include image modeling, image indexing, image segmentation, and image registration. The common theme behind all proposed methods is the use of complementary information from multi-modal images to achieve better registration, feature extraction, and detection performances. In material microscopy, we propose an anomaly-driven image fusion framework to perform the task of material microscopy image analysis and anomaly detection. This framework is based on a probabilistic model that enables us to index, process and characterize the data with systematic and well-developed statistical tools. In biomedical imaging, we focus on the multi-modal registration problem for functional MRI (fMRI) brain images which improves the performance of brain activation detection.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120701/1/yuhuic_1.pd

CMB-S4 Science Book, First Edition

This book lays out the scientific goals to be addressed by the next-generation ground-based cosmic microwave background experiment, CMB-S4, envisioned to consist of dedicated telescopes at the South Pole, the high Chilean Atacama plateau and possibly a northern hemisphere site, all equipped with new superconducting cameras. CMB-S4 will dramatically advance cosmological studies by crossing critical thresholds in the search for the B-mode polarization signature of primordial gravitational waves, in the determination of the number and masses of the neutrinos, in the search for evidence of new light relics, in constraining the nature of dark energy, and in testing general relativity on large scales

Analysis of aeromagnetic filtering techniques in locating the primary target in sedimentary terrain: A review

This article analyzes some aeromagnetic filtering techniques for mitigating deceptive geophysical conceptions that may result in a distorted range of geological information from aeromagnetic data. The implication of using the aeromagnetic method, data processing, and enhancement to distinguish sediment-produced anomalies was considered. Two methods to locate buried faults in aeromagnetic data were compared: Edge and fault detection were considered using the magnetic contrast and horizontal gradient methods, whereas rapid depth estimation was considered using the Euler deconvolution method and Signum method. The general challenge to find the magnetic anomaly depth and delineate edges relies on geophysical filtering techniques discussed in order to maintain its geological relevance. The magnetic- contrast layer model signatures help clarify the existence of intra-sedimentary faults. The horizontal gradient approach relative to other derivative methods has better noise stability and fast adaptation to grids without modifying parameters. However, the Signum transform (ST) approach offers a more special solution in depth estimation than the Euler’s deconvolution approach whose solution relies on the required choice of default shape parameters and windows. The Euler deconvolution procedure may not be able to detect structures found by the ST approach and vice versa. As a result, these techniques may be used in conjunction with one another during analysis, as complementary interpretation tools. This review will however aid in the analysis of informatio

Search methods for an autonomous underwater vehicle using scalar measurements

Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution July 1996The continuing development of the autonomous underwater vehicle as an oceanographic research tool has opened up the realm of scientific possibility in the field of deep ocean research. The ability of a vehicle to travel to the ocean floor untethered, collect data for an extended period of time and return to the surface for recovery can make precise oceanographic surveying more economically practical and more efficient. This thesis investigates several scalar parameter searching techniques which have their basis in mathematical optimization algorithms and their applicability for use specifically within the context of autonomous underwater vehicle dynamics. In particular, a modified version of the circular gradient evaluation in the simulated environment of a hydrothermal plume is examined as a test case. Using a priori knowledge of the expected structure of the scalar parameter contour is shown to be advantageous in optimizing the search

Complex Dielectric Permittivity Measurements from Ground-Penetrating Radar Data to Estimate Snow Liquid Water Content in the Pendular Regime

Monitoring the snow water equivalent (SWE) is critical to effective management of water resources in many parts of the world that depend on the mountain snowpack for water storage. There are currently no methods to remotely sense SWE with accuracy over large lateral distances in the steep and often forested terrain of mountain basins. Previous studies have shown that measurements of ground-penetrating radar (GPR) velocity can provide accurate estimates of SWE in dry snow. Introduction of liquid water into the snowpack results in a three-phase system that cannot be accurately characterized with GPR velocity alone. We show that measuring the frequency-dependent GPR signal attenuation and velocity provides a direct estimate of the complex dielectric permittivity. Because the imaginary component is a function only of liquid water content, we can utilize both the real and imaginary components of the permittivity to estimate liquid water content, snow density, and SWE using existing empirical relationships that are valid in the pendular regime. We tested this new method at two field sites and found that the estimates were accurate to within 12% of gravimetric methods in both a moist and a dry snowpack. GPR has the potential to provide SWE estimates across large lateral distances over a broad range of snow conditions

Advanced Geoscience Remote Sensing

Nowadays, advanced remote sensing technology plays tremendous roles to build a quantitative and comprehensive understanding of how the Earth system operates. The advanced remote sensing technology is also used widely to monitor and survey the natural disasters and man-made pollution. Besides, telecommunication is considered as precise advanced remote sensing technology tool. Indeed precise usages of remote sensing and telecommunication without a comprehensive understanding of mathematics and physics. This book has three parts (i) microwave remote sensing applications, (ii) nuclear, geophysics and telecommunication; and (iii) environment remote sensing investigations

Using a Ladder of Seeps with computer decision processes to explore for and evaluate cold seeps on the Costa Rica active margin

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Vrolijk, P., Summa, L., Ayton, B., Nomikou, P., Huepers, A., Kinnaman, F., Sylva, S., Valentine, D., & Camilli, R. Using a Ladder of Seeps with computer decision processes to explore for and evaluate cold seeps on the Costa Rica active margin. Frontiers in Earth Science, 9, (2021): 601019, https://doi.org/10.3389/feart.2021.601019.Natural seeps occur at the seafloor as loci of fluid flow where the flux of chemical compounds into the ocean supports unique biologic communities and provides access to proxy samples of deep subsurface processes. Cold seeps accomplish this with minimal heat flux. While individual expertize is applied to locate seeps, such knowledge is nowhere consolidated in the literature, nor are there explicit approaches for identifying specific seep types to address discrete scientific questions. Moreover, autonomous exploration for seeps lacks any clear framework for efficient seep identification and classification. To address these shortcomings, we developed a Ladder of Seeps applied within new decision-assistance algorithms (Spock) to assist in seep exploration on the Costa Rica margin during the R/V Falkor 181210 cruise in December, 2018. This Ladder of Seeps [derived from analogous astrobiology criteria proposed by Neveu et al. (2018)] was used to help guide human and computer decision processes for ROV mission planning. The Ladder of Seeps provides a methodical query structure to identify what information is required to confirm a seep either: 1) supports seafloor life under extreme conditions, 2) supports that community with active seepage (possible fluid sample), or 3) taps fluids that reflect deep, subsurface geologic processes, but the top rung may be modified to address other scientific questions. Moreover, this framework allows us to identify higher likelihood seep targets based on existing incomplete or easily acquired data, including MBES (Multi-beam echo sounder) water column data. The Ladder of Seeps framework is based on information about the instruments used to collect seep information (e.g., are seeps detectable by the instrument with little chance of false positives?) and contextual criteria about the environment in which the data are collected (e.g., temporal variability of seep flux). Finally, the assembled data are considered in light of a Last-Resort interpretation, which is only satisfied once all other plausible data interpretations are excluded by observation. When coupled with decision-making algorithms that incorporate expert opinion with data acquired during the Costa Rica experiment, the Ladder of Seeps proved useful for identifying seeps with deep-sourced fluids, as evidenced by results of geochemistry analyses performed following the expedition.Support for this research was provided through NASA PSTAR Grant #NNX16AL08G and National Science Foundation Navigating the New Arctic grant #1839063. Use of the R/V Falkor and ROV SuBastian were provided through a grant from the Schmidt Ocean Institute. The AUG Nemesis and the Aurora in-situ mass spectrometer was provided through in-kind support from Teledyne Webb Research and Navistry Corp, respectively