Browsing by Author "Vezvaee, Arian"
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- CS5604 Fall 2017 Classification Team SubmissionAzizi, Ahmadreza; Mulchandani, Deepika; Naik, Amit; Ngo, Khai; Patil, Suraj; Vezvaee, Arian; Yang, Robin (Virginia Tech, 2018-01-03)This project submission includes the work of the 'Classification' team of the CS5604 'Information Storage and Retrieval' course of Fall 2017 towards the GETAR project. Classification of the GETAR data would allow users to analyze, visualize, and explore content related to crises, disasters, human rights, inequality, population growth, shootings, violence, etc. Binary classification models were trained for different events for both tweet and webpage collections. Word2Vec was used as the feature selection technique and the Word2Vec model was trained on the entire corpus available. Logistic Regression was used as our classification technique. As part of this submission, we detail our classification framework and the experiments that we conducted. We also give an insight into the challenges we faced, how we overcame those challenges, and also what we learned in the process. We also provide the code that we implemented and the models that were built to classify 1,562,215 tweets and 4,366 webpages.
- Quantum spins in semiconductor nanostructures: Hyperfine interactions and optical controlVezvaee, Arian (Virginia Tech, 2021-08-30)Quantum information technologies offer significantly more computational power for certain tasks and secure communication lines compared to the available classical machines. In recent years there have been numerous proposals for the implementation of quantum computers in several different systems that each come with their own advantages and challenges. This dissertation primarily focuses on challenges, specifically interactions with the environment, and applications of two of such systems: Semiconductor quantum dots and topological insulators. The first part of the dissertation is devoted to the study of semiconductor quantum dots as candidates for quantum information storage and sources of single-photon emission. The spin of the electron trapped in a self-assembled quantum dot can be used as a quantum bit of information for quantum technology applications. This system possesses desirable photon emission properties, including efficiency and tunability, which make it one of the most advanced single-photon emitters. This interface is also actively explored for the generation of complex entangled photonic states with applications in quantum computing, networks, and sensing. First, an overview of the relevant developments in the field will be discussed and our recent contributions, including protocols for the control of the spin and a scheme for the generation of entangled photon states from coupled quantum dots, will be presented. We then look at the interaction between the electron and the surrounding nuclear spins and describe how its interplay with optical driving can lead to dynamic nuclear polarization. The second part of the dissertation follows a similar study in topological insulators: The role of time-reversal breaking magnetic impurities in topological materials and how spinful impurities enable backscattering mechanisms by lifting the topological protection of edge modes. I will present a model that allows for an analytical study of the effects of magnetic impurities within an experimental framework. It will be discussed how the same platform also enables a novel approach for applications of spintronics and quantum information, such as studying the entanglement entropy between the impurities and chiral modes of the system.