2 resultados para Near Infrared (NIR) Spectroscopy

em DRUM (Digital Repository at the University of Maryland)


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Ɣ-ray bursts (GRBs) are the Universe's most luminous transient events. Since the discovery of GRBs was announced in 1973, efforts have been ongoing to obtain data over a broader range of the electromagnetic spectrum at the earliest possible times following the initial detection. The discovery of the theorized ``afterglow'' emission in radio through X-ray bands in the late 1990s confirmed the cosmological nature of these events. At present, GRB afterglows are among the best probes of the early Universe (z ≳ 9). In addition to informing theories about GRBs themselves, observations of afterglows probe the circum-burst medium (CBM), properties of the host galaxies and the progress of cosmic reionization. To explore the early-time variability of afterglows, I have developed a generalized analysis framework which models near-infrared (NIR), optical, ultra-violet (UV) and X-ray light curves without assuming an underlying model. These fits are then used to construct the spectral energy distribution (SED) of afterglows at arbitrary times within the observed window. Physical models are then used to explore the evolution of the SED parameter space with time. I demonstrate that this framework produces evidence of the photodestruction of dust in the CBM of GRB 120119A, similar to the findings from a previous study of this afterglow. The framework is additionally applied to the afterglows of GRB 140419A and GRB 080607. In these cases the evolution of the SEDs appears consistent with the standard fireball model. Having introduced the scientific motivations for early-time observations, I introduce the Rapid Infrared Imager-Spectrometer (RIMAS). Once commissioned on the 4.3 meter Discovery Channel Telescope (DCT), RIMAS will be used to study the afterglows of GRBs through photometric and spectroscopic observations beginning within minutes of the initial burst. The instrument will operate in the NIR, from 0.97 μm to 2.37 μm, permitting the detection of very high redshift (z ≳ 7) afterglows which are attenuated at shorter wavelengths by Lyman-ɑ absorption in the intergalactic medium (IGM). A majority of my graduate work has been spent designing and aligning RIMAS's cryogenic (~80 K) optical systems. Design efforts have included an original camera used to image the field surrounding spectroscopic slits, tolerancing and optimizing all of the instrument's optics, thermal modeling of optomechanical systems, and modeling the diffraction efficiencies for some of the dispersive elements. To align the cryogenic optics, I developed a procedure that was successfully used for a majority of the instrument's sub-assemblies. My work on this cryogenic instrument has necessitated experimental and computational projects to design and validate designs of several subsystems. Two of these projects describe simple and effective measurements of optomechanical components in vacuum and at cryogenic temperatures using an 8-bit CCD camera. Models of heat transfer via electrical harnesses used to provide current to motors located within the cryostat are also presented.

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Maps depicting spatial pattern in the stability of summer greenness could advance understanding of how forest ecosystems will respond to global changes such as a longer growing season. Declining summer greenness, or “greendown”, is spectrally related to declining near-infrared reflectance and is observed in most remote sensing time series to begin shortly after peak greenness at the end of spring and extend until the beginning of leaf coloration in autumn,. Understanding spatial patterns in the strength of greendown has recently become possible with the advancement of Landsat phenology products, which show that greendown patterns vary at scales appropriate for linking these patterns to proposed environmental forcing factors. This study tested two non-mutually exclusive hypotheses for how leaf measurements and environmental factors correlate with greendown and decreasing NIR reflectance across sites. At the landscape scale, we used linear regression to test the effects of maximum greenness, elevation, slope, aspect, solar irradiance and canopy rugosity on greendown. Secondly, we used leaf chemical traits and reflectance observations to test the effect of nitrogen availability and intrinsic water use efficiency on leaf-level greendown, and landscape-level greendown measured from Landsat. The study was conducted using Quercus alba canopies across 21 sites of an eastern deciduous forest in North America between June and August 2014. Our linear model explained greendown variance with an R2=0.47 with maximum greenness as the greatest model effect. Subsequent models excluding one model effect revealed elevation and aspect were the two topographic factors that explained the greatest amount of greendown variance. Regression results also demonstrated important interactions between all three variables, with the greatest interaction showing that aspect had greater influence on greendown at sites with steeper slopes. Leaf-level reflectance was correlated with foliar δ13C (proxy for intrinsic water use efficiency), but foliar δ13C did not translate into correlations with landscape-level variation in greendown from Landsat. Therefore, we conclude that Landsat greendown is primarily indicative of landscape position, with a small effect of canopy structure, and no measureable effect of leaf reflectance. With this understanding of Landsat greendown we can better explain the effects of landscape factors on vegetation reflectance and perhaps on phenology, which would be very useful for studying phenology in the context of global climate change