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  • Quantifying X-ray Diffraction Reconstruction Fidelity

    Luo, Bobing (The University of Arizona., 2022)
    With increasing transport security awareness and the demand for threat detection, X-ray diffraction (XRD) technology is developing continuously [1]. X-ray diffraction imaging refers to the method of using X-rays, namely beams with photon energy between 1keV to 150keV , to detect the scattered light from the interaction between objects with different materials and X-ray photons, to infer the type of material by measuring momentum transfer of photons. Unlike computed tomography (CT), X-ray diffraction not only provides the spatial distribution of objects, but also the molecular material composition. As such X-ray diffraction requires complex computations and a challenging measurement. A variety of XRD reconstruction algorithm have been developed, such as state-of-the-art Group Total Variation. The goal of this work is to quantify XRD reconstruction algorithm performance with respect to signal-to-noise ratio (SNR), material categories and collimation/coding schemes.
  • Revealing Earth science code and data-use practices using the Throughput Graph Database

    Thomer, Andrea K.; Wofford, Morgan F.; Lenard, Michael C.; Dominguez Vidana, Socorro; Goring, Simon J.; School of Information (Geological Society of America, 2023)
    The increased use of complex programmatic workflows and open data within the Earth sciences has led to an increase in the need to find and reuse code, whether as examples, templates, or code snippets that can be used across projects. The “Throughput Graph Database” project offers a platform for discovery that links research objects by using structured annotations. Throughput was initially populated by scraping GitHub for code repositories that reference the names or URLs of data archives listed on the Registry of Research Data Repositories (https://re3data.org). Throughput annotations link the research data archives to public code repositories, which makes data-relevant code repositories easier to find. Linking code repositories in a queryable, machine-readable way is only the first step to improving discoverability. A better understanding of the ways in which data is used and reused in code repositories is needed to better support code reuse. In this paper, we examine the data practices of Earth science data reusers through a classification of GitHub repositories that reference geology and paleontology data archives. A typology of seven reuse classes was developed to describe how data were used within a code repository, and it was applied to a subset of 129 public code repositories on GitHub. Code repositories could have multiple typology assignments. Data use for Software Development dominated (n = 44), followed by Miscellaneous Links to Data Archives (n = 41), Analysis (n = 22), and Educational (n = 20) uses. GitHub repository features show some relationships to the assigned typologies, which indicates that these characteristics may be leveraged to systematically predict a code repository’s category or discover potentially useful code repositories for certain data archives.
  • The University of Arizona 2022 Cotton Variety Testing Program - Trial Results

    Norton, Randy; University of Arizona, Extension Agronomist (College of Agriculture, Life & Veterinary Sciences & Cooperative Extension, University of Arizona (Tucson, AZ), 2023-02)
    Variety selection is one of the most important decisions a grower will make contributing to the success of a cotton crop. It is critical, that a grower have as much information as possible in order to make an informed decision regarding variety selection. In an effort to help supply reliable variety performance information, the University of Arizona conducts a statewide cotton variety testing program. The 2022 cotton season variety trials were conducted in 3 locations across Arizona including Yuma, Maricopa, and Safford. This testing program is called the University of Arizona Upland Cotton Advanced Strains Testing Program.
  • The Phase-Space Distribution of Galaxy Clusters

    Rozo, Eduardo; Wolfe, Brandon; Su, Shufang; Krause, Elisabeth; Dienes, Keith; Behroozi, Peter (The University of Arizona., 2023)
    We provide the modeling framework to enable a proposed new measurement of the Hubble constant, using the radial extent of galaxy clusters as a standard ruler. Observationally, we plan to measure the angular extent of the cluster and the velocity of galaxies around the cluster. More massive clusters have galaxies that orbit faster, so we can use the velocity of galaxies within clusters to estimate an effective cluster mass. To enable this, we have calibrated the relation between line-of-sight galaxy velocity and cluster mass using cosmological simulations. With an estimate of halo mass now in hand, we can infer the radius of the dark matter halo containing it. To enable this, we have also calibrated the relationship between halo mass and radius with simulations. We find that a halo whose mass is $1\times10^{14}$ $M_\odot/h$ has a physical radius of $596\pm3$ kPc/h, better than $1\%$ precision. Comparing the halo radius inferred from galaxies' velocities to their angular extent allows us to estimate the distance to the cluster, which in turn can be used to assemble a Hubble diagram for galaxy clusters. The high level of precision in the halo radius needed to establish this measurement is founded on a recent insight in halo modeling: galaxies in halos can be split into two populations: those orbiting their host dark matter halo, and those falling into the host for the first time. Here, we present an algorithm that uses the galaxies' accretion history to distinguish between them. We use our split catalog to generate fits for the orbiting and infalling galaxy phase space densities. Importantly, each can be described as depending on a single fundamental scale, the halo radius $r_h$. Both the orbiting and density profiles can be described with 5$\%$ accuracy using $r_h$ as the length scale. In velocity space, we show that the infalling velocity distribution has a bimodal appearance due to the impact of the Hubble flow on galaxy velocities. Our model of the distribution of galaxy line-of-sight velocities is also 5\% accurate. Finally, to prepare the calibration for application to galaxy clusters, we characterize the impact of cluster selection effects the phase space distribution of galaxies. To do so, we select clusters based on the galaxy counts in cylinders of height $\pm$20 h$^{-1}$~Mpc and $\pm$60 h$^{-1}$~Mpc along the line of sight. The distributions of line-of-sight velocities for both orbiting and infalling galaxies are robust to cluster selection; so is the projected orbiting surface density. The projected surface density of the infalling population, however, exhibits a strong scale-dependent bias, where the scale is set by the aperture used in the process of cluster selection. Finally, we suggest the next steps needed to characterize the dependence of the halo radius on the assumed cosmology, as well as the possible influence of baryonic processes on it. As a coda, we also include work on the broadband emission of galaxy clusters, and examine the possible detection of extra-solar neutrinos (via the ICECUBE and Auger experiments) from the Coma cluster of galaxies, as well as for $\gamma$-ray-bright clusters.
  • Ultrafast Carrier Dynamics in Two-Dimensional Materials

    LeRoy, Brian; Brasington, Alexandra; Sandhu, Arvinder; Schaibley, John; Binder, Rolf; Monti, Oliver (The University of Arizona., 2022)
    The discovery of graphene led to an eruption of research into the expansive collection of two-dimensional materials. The ability to fabricate stacked heterostructures with van der Waals materials layer-by-layer has allowed the production of unique devices and has rapidly advanced research in electronics and optics. Understanding the dynamics of carrier and phonon interactions within these systems is crucial for the development of optoelectronic devices. This thesis explores the dynamics of photo-excited carriers in two-dimensional systems: the effects of substrate choice on carrier relaxation in graphene and phonon induced bandgap renormalization in monolayer tungsten disulfide at high carrier densities. Graphene-hBN (hexagonal boron nitride) heterostructures show promising use in electronics applications due to high carrier mobility. We first explore the effect of the hBN substrate on the relaxation rates of photo-excited carriers in these heterostructures using femtosecond pump-probe spectroscopy. Time dynamics of photo-excited carriers in graphene-hBN heterostructures show a cooling rate approximately four times faster on hBN substrates compared to silicon oxide substrates. We next study the effect of variation in isotopic concentration in hBN substrates on the relaxation rates of photo-excited carriers. We measure and compare the time dynamics of photo-excited carriers in graphene-hBN heterostructures using naturally occurring hBN (containing 20% 10B and 80% 11B) and isotopically pure hBN (containing 100% 10B or 100% 11B). We observed a carrier relaxation rate ~1.7 times faster for isotopically pure hBN substrate. Isotopically pure hBN substrates samples allow more efficient decay of optical phonons from graphene into acoustic phonons in the substrate, while the isotopic disorder in naturally occurring hBN causes isotope-phonon scattering. Monolayer transition metal dichalcogenides are another van der Waals material which have garnered a lot of interest due to their direct optical band gap and strongly bound excitonic states in the visible light range. We utilize non-degenerate femtosecond pump-probe spectroscopy to measure the differential reflectivity in monolayer WS2 to investigate the interactions between carriers, defects, and phonons in the high carrier density regime. We find photo-excited carriers are trapped by defect states, which act as non-radiative recombination sites and emit phonons, which cause a phonon-induced band gap renormalization up to 23 meV.

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