THREE ESSAYS ON THE HIGH-SPEED RAIL NETWORK IN CHINA

My dissertation consists of three essays that study the economic consequences of China’s high-speed rail (HSR) expansion. In the first essay, I use the college admission cutoff scores to reveal students’ college preferences under the enrollment quota. By exploiting the quasi-experimental variation in whether or not college cities are connected by the HSR network, I document a two-point increase in the cutoff scores following a HSR station opening in the college city using difference-in-difference (DD) approach. Colleges in the megacities experience a larger increase in cutoff scores after the station opening. These findings suggest that the HSR network stimulates “brain drain” from unconnected cities to connected cities, especially connected megacities. The second essay examines the impact of better HSR accessibility on housing prices in Jiangsu Province. Using transaction data of new houses aggregated to the complex level, I compare the housing prices of properties close to the new HSR stations to those close to pre-existing HSR stations, before and after the new station openings. In a DD specification, I document that housing prices decrease by twenty percent in the areas where the station distance reduces due to the station opening outside the city. The third essay investigates the impacts on household income. Using DD approach, I document that urban households experience a significant increase in total household income following the opening of HSR station in their city. While labor earnings increase, the probability of having business income decreases. Moreover, labor income of the households whose heads work in the manufacturing sector increases little, but for households whose heads work in the transport or communications sectors increases much more than other households, suggesting that the HSR network facilitates urban industry specialization

Cooperative Perception for Safe Control of Autonomous Vehicles under LiDAR Spoofing Attacks

Autonomous vehicles rely on LiDAR sensors to detect obstacles such as pedestrians, other vehicles, and fixed infrastructures. LiDAR spoofing attacks have been demonstrated that either create erroneous obstacles or prevent detection of real obstacles, resulting in unsafe driving behaviors. In this paper, we propose an approach to detect and mitigate LiDAR spoofing attacks by leveraging LiDAR scan data from other neighboring vehicles. This approach exploits the fact that spoofing attacks can typically only be mounted on one vehicle at a time, and introduce additional points into the victim's scan that can be readily detected by comparison from other, non-modified scans. We develop a Fault Detection, Identification, and Isolation procedure that identifies non-existing obstacle, physical removal, and adversarial object attacks, while also estimating the actual locations of obstacles. We propose a control algorithm that guarantees that these estimated object locations are avoided. We validate our framework using a CARLA simulation study, in which we verify that our FDII algorithm correctly detects each attack pattern

Single T gate in a Clifford circuit drives transition to universal entanglement spectrum statistics

Clifford circuits are insufficient for universal quantum computation or creating $t$-designs with $t\ge 4$. While the entanglement entropy is not a telltale of this insufficiency, the entanglement spectrum is: the entanglement levels are Poisson-distributed for circuits restricted to the Clifford gate-set, while the levels follow Wigner-Dyson statistics when universal gates are used. In this paper we show, using finite-size scaling analysis of different measures of level spacing statistics, that in the thermodynamic limit, inserting a single T $(\pi/8)$ gate in the middle of a random Clifford circuit is sufficient to alter the entanglement spectrum from a Poisson to a Wigner-Dyson distribution.Comment: 14 pages, 8 figures; Submission to SciPos

Utilizing the Systematic Literature Review in Aviation -- A Case Study for Runway Incursions

This research presents the process for a systematic literature review examining factors that contribute to runway incursions (RIs). A systematic literature review uses other research results as data for systematic analysis. Runway safety is a top priority. In the US, RIs have been increasing and typically three RIs occur every day. This paper identified 134 articles using 22 databases. Filtering criteria and analysis identified six contributing categories: human factors, airport geometry, technical factors, airport characteristics, environmental factors, and organizational factors. Recommendations for reduction of RIs and suggestions for further studies are presented based on these factors