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The aim of this project was to study what mixed cluster fragments were formed in the interaction between radiation and H2O-CO2 clusters formed by adiabatic expansion, both experimentally and using simulations. The experiment was done using a mass spectrometer at the MAX IV synchrotron facility and by studying the time-of-flight of the ionic fragments. All peaks in the mass spectrum were identified by converting the time-of-flight to mass/charge, and the spectrum for two different photon energies (307 eV and 550 eV ) and two different stagnation pressures (1.5 bar and 2.2 bar) were compared. The data showed that mixed clusters were formed, including fragments with extra hydrogen atoms. The mass spectra showed a larger change in peak height and width with increasing pressure than with increasing photon energy. Molecular dynamics simulations were used to study the stability of the identified clusters. The simulated clusters contained CO2, H2O and H2O+. As a measure of stability, the largest centre of mass distance between the H2O+ molecule and any other molecule in the cluster in every time step of the simulation was determined. The structure of the more stable clusters was also studied visually. The simulations showed that the clusters vary greatly in stability, but generally clusters with many H2O molecules were more stable. The stable structures had the H2O+ molecule on one end of the cluster, with its hydrogen atoms directed towards the rest of the molecules. Although the clusters with many H2O molecules were more stable in the simulations, clusters with many CO2 molecules were more abundant in the experimental data. This was most likely due to a high amount of CO2 in the gas used to create the clusters. / Målet med projektet var att experimentellt och med simuleringar studera de klusterfragment som bildas i interaktionen mellan strålning och blandade H2O-CO2-kluster skapade genom adiabatisk expansion. I experimentet studerades flygtiden hos de laddade fragmenten genom mätningar med en masspektrometer vid synkrotronanläggningen MAX IV. Topparna i masspektrumet identifierades genom att konvertera flygtiden till massa/laddning. Två olika strålenergier (307 eV och 550 eV) samt två stagnationstryck (1.5 bar och 2.2 bar) jämfördes. Datan visade att blandade kluster bildades, bland annat identifierades fragment med extra väteatomer. Skillnaden i spektrumen var större mellan de olika trycken än mellan de olika energierna, framför allt så producerade det högre trycket fler och större klusterfragment. Molekyldynamiksimuleringar användes för att undersöka stabiliteten hos de identifierade klustren. De kluster som simulerades innehöll CO2, H2O och H2O+. För att mäta stabiliteten av klustren bestämdes det största avståndet mellan H2O+ molekylen och någon annan molekyl i klustret i varje tidssteg av simuleringen. Strukturen hos de mer stabila klustern undersöktes också visuellt. Simuleringarna visade att stabiliteten hos klustren varierade mycket, men generellt så var kluster med många H2O molekyler mer stabila. I de stabila klusterstrukturerna var H2O+ molekylen placerad på kanten av klustret, med dess väteatomer riktade mot resterande molekyler. Kluster med många H2O molekyler var mer stabila i simuleringarna, men experimentellt förekom fler kluster med många CO2 molekyler. Detta beror troligtvis på att gasen som användes för att skapa klustren till stor del bestod av CO2 gas.

With the rising costs of large scale distributed systems many researchers have began looking at utilizing low power architectures for clusters. In this paper, we describe our Astro cluster, which consists of 46 NVIDIA Jetson TK1 nodes each equipped with an ARM Cortex A15 CPU, 192 core Kepler GPU, 2 GB of RAM, and 16 GB of flash storage. The cluster has a number of advantages when compared to conventional clusters including lower power usage, ambient cooling, shared memory between the CPU and GPU, and affordability. The cluster is built using commodity hardware and can be setup for relatively low costs while providing up to 190 single precision GFLOPS of computing power per node due to its combined GPU/CPU architecture. The cluster currently uses one 48-port Gigabit Ethernet switch and runs Linux for Tegra, a modified version of Ubuntu provided by NVIDIA as its operating system. Common file systems such as PVFS, Ceph, and NFS are supported by the cluster and benchmarks such as HPL, LAPACK, and LAMMPS are used to evaluate the system. At peak performance, the cluster is able to produce 328 GFLOPS of double precision and a peak of 810W using the LINPACK benchmark placing the cluster at 324th place on the Green500. Single precision benchmarks result in a peak performance of 6800 GFLOPs. The Astro cluster aims to be a proof-of-concept for future low power clusters that utilize a similar architecture. The cluster is installed with many of the same applications used by top supercomputers and is validated using the several standard supercomputing benchmarks. We show that with the rise of low-power CPUs and GPUs, and the need for lower server costs, this cluster provides insight into how ARM and CPU-GPU hybrid chips will perform in high-performance computing.

Cabernet sauvignon is the most widely planted red wine grape in California and is valued in the hundreds of millions of dollars. Cabernet sauvignon grapes, when severely vigorous or overcropped, can contain vegetal aromas and flavors when harvested. 3-alkyl-methoxypyrazines are the volatile compounds responsible for this effect and can lower the perceived quality of the wine. Resveratrol is a phytoalexin that has many medical and health benefits and can be found in red wines. An experiment was conducted in Paso Robles, CA to assess the effects of five yield levels, manipulated through cluster thinning, on methoxypyrazine and resveratrol concentrations. Berry weights and chemistry were also measured, in the form of ºBrix, pH, and TA. In 2009 and 2010, no significant statistical differences were found in methoxypyrazines in the harvested grapes. In 2009, resveratrol concentrations were below the detection limits in the wine produced. In 2010, berry weight and chemistry measurements were not significantly different, except for grapes from lightly- and greatly-thinned vines which varied in pH at harvest. The 2009 wines were subjected to discrimination and preference testing by trained tasters. No significant difference was found in the discrimination test and no difference was found using the Friedman and Kramer’s Rank test for the preference test. Only a very slight difference was found between the wines made from unthinned and greatly-thinned vines according to Tukey’s Multiple Comparison Test. The findings of this thesis suggest that cluster thinning does not affect methoxypyrazine and resveratrol concentrations or sensory analysis in Cabernet sauvignon grown on the east side of Paso Roble, CA.

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The classical Extreme Value Theory deals with independent random variables. If random variables are dependent, large values tend to cluster (that is, one large value is followed by a series of large values). It is of interest to describe probabilistically the clustering and estimate the relevant cluster functionals. We consider disjoint blocks, sliding blocks and runs estimators of cluster indices. Using a modern theory of multivariate, regularly varying time series, we obtain consistency results and central limit theorems under conditions that can be easily verified for a large class of short-range dependent models. In particular, we show that in the Peak-over-Threshold framework, all the estimators have the same limiting variances. This solves a longstanding open problem and is in contrast to the Block Maxima method. Our findings are illustrated by simulation experiments.

Optical and spectroscopic molecular properties are key to characterizing the behavior of molecules interacting with an applied electromagnetic field of light. Response theory has been used for a long time to calculate such properties in the frequency domain. Real-time (RT) methods solve for the frequency-dependent properties in the time domain by explicitly propagating the time-dependent wave function. Various quantum chemical methods can be incorporated with the RT formalism, including Hartree-Fock, density functional theory, configurational interaction, coupled cluster, etc. Among these, coupled cluster (CC) methods provide high accuracy for systems with strong electron correlation, making RT-CC implementations intriguing. All applications of CC methods face a substantial challenge due to their high-order polynomial scaling. For RT-CC methods, two aspects may be explored to improve the efficiency, the numerical techniques regarding the RT propagation and the reduced-scaling methods regarding CC itself. In this work, we start with the exploration of the hardware used for the calculations and the numerical integration methods for propagating the wave function parameters. Firstly, a GPU-enabled Python implementation has been developed by conducting the tensor contractions on GPUs utilizing PyTorch, a machine learning package, that has similar syntax as NumPy for tensor operations. A speedup of a factor of 14 is obtained for the RT-CCSD/cc-pVDZ absorption spectrum calculation of the water tetramer. Furthermore, to optimize the performance on GPUs, single-precision arithmetic is added to the implementation to achieve an additional speedup of a factor of two. Lastly, a group of integrators for solving differential equations are introduced to the RT framework, including regular explicit integrators, adaptive integrators, and a mixed-step-size approach customized for strong-field simulations. The optimal choice of the integrator depends on the requiring accuracy, stability and efficiency. In addition to being highly accurate, CC methods are also systematically improvable and provide a hierarchy of accuracy. Based upon the RT-CCSD implementation, the coupled cluster singles, doubles and approximate triples (CC3) method, favorable for calculating frequency-dependent properties, is tailored to the RT framework for high excitation and approximate orbital relaxation. The calculation is tested on both CPUs and GPUs, with a significant speedup gained from GPUs for the water cluster test cases. To further expand the range of applications of our RT-CC implementation, dynamic polarizabilities, first hyperpolarizabilities, and the G' tensor are calculated from induced electric and magnetic dipole moments using finite-difference methods. A discussion has also been conducted to compare RT-CC3 with RT-CCSD, and time-dependent nonorthogonal orbital-optimized coupled cluster doubles (TDNOCCD) method. Additionally, electron dynamics, including the Rabi oscillation and exited state to excited state transitions, have also been explored utilizing the well-developed RT-CC framework. / Doctor of Philosophy / Theoretical studies aim to match experiments, but more importantly, provide insights to interpret and predict experimental data. Calculating optical properties related to light-matter interactions is one of the most crucial tasks for characterizing molecular properties. In experiments, electromagnetic radiation in the form of light is applied to the system. The absorption or emission of light can be measured to identify, for example, the electronic structure of the molecule. In theoretical simulations, this applied radiation is represented by a perturbation operator that is added to the Hamiltonian in the Schrödinger equation. Quantum chemists are dedicated to developing methods that provide a better description of the spectroscopy. In the current work, the frequency, shape and the intensity of the radiation can all be finely-tuned, similar to experimental setups. The framework for extracting optical properties from time-dependent trajectories of induced dipole moments is established for accurate and efficient simulations. To improve efficiency and make the method feasible for real-world applications, a strong understanding of light-matter interactions on a quantum level and proper utilization of computational resources are both necessary. Improvements achieved and presented in this dissertation demonstrate a powerful tool for a better understanding of the nature of the interaction between the system and the electromagnetic radiation.

To effectively implement climate change mitigation and carbon sequestration activities in the southern US, nonindustrial private forest (NIPF) landowner participation is necessary because of the significant number of acres of forest land under their ownership. This study intended to develop a typology of NIPF landowners based on their reasons of owning forestland, assess their attitude toward climate change and carbon sequestration, and evaluate their participation behavior toward forest carbon sequestration in the southern US. A mail survey of NIPF landowners in the southern US was used to collect the data necessary for this study. Study results indicated that landowners in the southern US could be segmented into multi-objective, timber and amenity oriented landowners; and landowner groups differed in terms of their ownership characteristics, management behavior, and interest toward forest carbon sequestration. Additionally, the southern landowner attitudes toward climate change and carbon sequestration could be grouped into positive, negative, and undecided types; with the undecided group composing the largest proportion of landowners. However, few landowners indicated having a good understanding of forest carbon sequestration, indicating the need for more education and outreach activities in this region. In addition, landowner willingness to participate in carbon sequestration practices was different when such practices were more profitable, revenue neutral or less profitable than timber management only. Although many landowners would require a significant profit to participate in carbon sequestration programs, others would participate with little or no incentives. Those having recreational goals for their property were the most likely landowners to participate in carbon sequestration. Similarly, positive attitudes toward climate change (i.e., with a belief that climate change is scientifically proven) and a good understanding of forest carbon sequestration positively affected landowner participation in forest carbon sequestration. Economic implementation of climate change policy could be achieved by designing education, incentives, or assistance programs to connect with recreational goal landowners in the southern US.

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