Plasma density gradients in a gas jet were used to control the wake phase velocity and trapping threshold in a laser wakefield accelerator, producing stable electron bunches with longitudinal and transverse momentum spreads more than ten times lower than in previous experiments (0.17 and 0.02 MeV/c FWHM, respectively) and with central momenta of 0.76 +- 0.02 MeV/c. Transition radiation measurements combined with simulations indicated that the bunches can be used as a wakefield accelerator injector to produce stable beams with 0.2 MeV/c-class momentum spread at high energies.

Laser- and particle beam-driven plasma wakefield accelerators produce accelerating fields thousands of times higher than radio-frequency accelerators, offering compactness and ultrafast bunches to extend the frontiers of high energy physics and to enable laboratory-scale radiation sources. Large-scale kinetic simulations provide essential understanding of accelerator physics to advance beam performance and stability and show and predict the physics behind recent demonstration of narrow energy spread bunches. Benchmarking between codes is establishing validity of the models used and, by testing new reduced models, is extending the reach of simulations to cover upcoming meter-scale multi-GeV experiments. This includes new models that exploit Lorentz boosted simulation frames to speed calculations. Simulations of experiments showed that recently demonstrated plasma gradient injection of electrons can be used as an injector to increase beam quality by orders of magnitude. Simulations are now also modeling accelerator stages of tens of GeV, staging of modules, and new positron sources to design next-generation experiments and to use in applications in high energy physics and light sources.

Design of efficient, high gradient laser driven wakefield accelerator (LWFA) stages using explicit particle-incell simulations with physical parameters scaled by plasma density is presented. LWFAs produce few percent energy spread electron bunches at 0.1-1 GeV with high accelerating gradients. Design tools are now required to predict and improve performance and efficiency of future LWFA stages. Scaling physical parameters extends the reach of explicit simulations to address applications including 10 GeV stages and stages for radiation sources, and accurately resolves deep laser depletion to evaluate efficient stages.

Advances in and physics of the acceleration of particles using underdense plasma structures driven by lasers were the topics of presentations and discussions in Working Group 1 of the 2010 Advanced Accelerator Concepts Workshop. Such accelerators have demonstrated gradients several orders beyond conventional machines, with quasi-monoenergetic beams at MeV-GeV energies, making them attractive candidates for next generation accelerators. Workshop discussions included advances in control over injection and laser propagation to further improve beam quality and stability, detailed diagnostics and physics models of the acceleration process, radiation generation as a source and diagnostic, and technological tools and upcoming facilities to extend the reach of laser-plasma accelerators.

Laser-plasma collider designs point to staging of multiple accelerator stages at the 10 GeV level, which are to be developed on the upcoming BELLA laser, while Thomson Gamma source designs use GeV stages, both requiring efficiency and low emittance. Design and scaling of stages operating in the quasi-linear regime to address these needs are presented using simulations in the VORPAL framework. In addition to allowing symmetric acceleration of electrons and positrons, which is important for colliders, this regime has the property that the plasma wakefield is proportional to the transverse gradient of the laser intensity profile. We demonstrate use of higher order laser modes to tailor the laser pulse and hence the transverse focusing forces in the plasma. In particular, we show that by using higher order laser modes, we can reduce the focusing fields and hence increase the matched electron beam radius, which is important to increased charge and efficiency, while keeping the low bunch emittance required for applications.

Modern autocrats depend on at least some support and cooperation from the business sector to sustain their rule. To efficiently mobilize business support, they are incentivized to (1) build a reputation of rewarding loyal supporters, and (2) create a minimum check so that they will not renege on their promises when business elites spend costly effort in supporting the regime. I argue that autocrats may achieve the two goals by incorporating loyal business elites into existing formal institutions and visibly channeling economic privileges to them. As these politically incorporated business elites are in the spotlight, the private benefits that they gain from holding political office become public signals to other business elites. The visibility then enables the state to showcase that it rewards loyal supporters and to mitigate the usual commitment problem underlying bilateral business-state interactions, both of which enhance state-business exchanges.

Drawing on a range of data, this dissertation provides evidence that the Chinese ruling party incorporates private entrepreneurs into high-level political institutions, such as the National People’s Congress (NPC), to take advantage of the visible nature of these institutions. Specifically, the ruling party selects loyal business supporters to the formal institutions while also channeling substantial economic privileges to the incorporated entrepreneurs. These private benefits, when becoming public signals, help the party build a reputation of credibly rewarding supporters. The reputation then mobilizes private entrepreneurs to support the regime in exchange for a profitable seat in formal institutions in the future. The enhanced regime support from the business sector may explain why the party made the noticeable switch from rewarding business supporters through informal (and often “invisible”) interactions to formally incorporating them into political institutions in the early 2000s.

How does new information affect citizens' political attitudes and personal beliefs? Past research has explored this question with mixed results: while some suggest that information can alter beliefs and policy positions, others argue that political opinions are stubbornly resistant to change, regardless of the potential value of new information. Building on this expansive body of research, I argue that both individual-level uncertainty and the information medium play a critical role in shaping when information matters. While I expect citizens who are more uncertain to be more likely to reevaluate their beliefs in the face of new information, I argue that in specific contents, this is particularly true if that information comes from a source that is viewed as trustworthy, like their community.

Using data from two survey experiments and a large-N original dataset of Facebook community pages, my dissertation explores this dynamic in Brazil with information about violence, a persistent development challenge. Conditional on respondents uncertainty about community violence, I find that community-based information shared through social media has significant and countervailing effects: (1) it significantly decreases anxiety about crime and support for the police among more ``uncertain" individuals, but increases it for less ``uncertain" individuals. I find no such heterogenous effects among respondents who receive information about violence in their community from government sources. Examining the divergence in high and low certainty individuals who receive the social media information is beyond the scope of this dissertation, but what is clear from these findings is that the source of the information plays a central role in shaping whether people are willing to update their beliefs.\

I argue that this observed shift in beliefs is due to respondents' willingness to trust information that comes from ``people like them" over more traditional purveyors of information, such as their government. I test this through a conjoint experiment, which randomly varies features of information about violence and government services and asks participants to select which they would trust more. Across both types of information, participants are significantly less likely to trust information that comes from a government source, and more willing to believe information that has a wide reach on social media and that is shared in real time. Uncertainty appears to play little role in respondents' weighting of these various attributes.

In the final chapter of my dissertation, I investigate how the transition from traditional to social media sources for information shapes individuals’ beliefs about violence in their communities, which in turn shape their political preferences. Although respondents appear more willing to update their beliefs based on information from social media, that information does not accurately reflect real world instances in violence. An analysis of content from community level Facebook groups reveals clear biases in the content shared on these platforms. Social media users based in areas that are neither very violent nor very peaceful are more likely to share content about violence. This finding suggests that those who have less certain information about particular aspects of the real world will be more likely to increase the inaccuracy of their understanding if they rely mostly on social media for information. This research not only complicates existing theories about information processing, but also explores these dynamics in an understudied and rapidly transforming political environment where social media usage is rapidly accelerating.

The dissertation has a methodological and a substantive contribution. First, it develops a method of measurement that serves to directly test specific hypothesis about the simultaneous interaction of classes in a multivariate regression environment. I show how compositional analysis can be applied to the same data that are used to construct the Gini coefficient serving to further investigate and adjudicate the class effects that are only suggested in the Gin results. I show that because identical Gini calculations result from drastically different land distributions it is wrong to narrow its interpretation to theories relating only the very rich and the very poor while ignoring the middle class. Second, it shows that municipalities in Colombia with relatively large numbers of middle-sized farmers versus large landowners provide larger proportions of their citizens with piped water, electricity, and other public services. I argue that middle-sized farmers play this role because they have the income and other resources needed to travel to local urban areas to gather relevant information and to lead local Communal Action Boards in bargaining with local elected officials, but they are poor enough to need the public provision of such services. On the other hand, large landowners live in urban areas, and find more efficient to pay privately for their own services than paying for everyone’s via local taxes.

Compared to conventional particle accelerators, plasmas can sustain accelerating fields that are thousands of times higher. To exploit this ability, massively parallel SciDAC particle simulations provide physical insight into the development of next-generation accelerators that use laser-driven plasma waves. These plasma-based accelerators offer a path to more compact, ultra-fast particle and radiation sources for probing the subatomic world, for studying new materials and new technologies, and for medical applications.