Mikhail's Research

Research Contents

Network Science

University of California, Davis
Department of Political Science
Social and Political Interacting Networks Group

The Social and Political Interacting Networks group is an interdisciplinary working group devoted to the study of network science, social network analysis, and the study of international processes. Our group includes faculty, post doctoral fellows, and graduate students from political science, communications, computer science, applied math, and physics. Our goal is to explore the effect of shocks on networks, the causes and consequences of network spillover, and methods for analyzing social and political networks.

One of my research projects is on writing a simulation of a network formed in a social experiment conducted on campus. The research question asks about the effects of shocks on the system in the form of changes in the costs of ties formed in the network. The experiment consisted of subjects playing a game of maximizing utility in a network within a set number of rounds. Each round consists of two stages. In the first stage, players can form or drop links with other players. In the second stage, players play a prisoner's dilemma game with those they have a tie from the previous stage. The following image shows a few rounds of the simulation where the player highlighted in red uses a strategy in which they always choose to defect in the prisoner's dilemma game. The code to the simulation can be found here.


Cornell University
Cornell Laboratory for Accelerator-Based Sciences and Education

REU Project: Innovations in optimization and control of accelerators using methods of differential geometry and genetic algorithms
Abstract: This research laid the foundation of the code to be used for the online optimization for the Cornell Electron Storage Ring (CESR). A standalone virtual simulation of CESR written in Fortran using the BMAD library was used and edited for use with a python wrapper to interface with several different optimization codes written in python. These optimization methods included the Nelder-Mead, Powell, Levenberg-Marquardt, and genetic algorithms. We were successful in optimizing the virtual machine code, thus allowing further study using our code to develop better optimization methods suited for online control of accelerators.
Presentation and Final Report

Nuclear Physics

Mississippi State University
Department of Physics

Honor's Thesis: Meaurement of Material Thickness Using X-ray Attenuation
Abstract: This project aims to use x-rays produced from radioactive Americium-241 (241Am) source to measure the thickness of the target cell window used in the recently completed Qweak experiment at the Thomas Jefferson National Accelerator in Virginia. The aluminum windows that will be measured are very thin, on the scale of a tenth of a millimeter. The advantage of using x-rays to measure thickness is that the measurement requires minimal physical and mechanical interference with the material and should be capable of sub-1% accuracy on the thickness measurement. Reducing this uncertainty on the window thickness is very important to the Jefferson Lab Qweak final result. In addition, one could consider this project as a seed program to building the capacity at MSU to potentially measure all future target windows for Jefferson Lab experiments.
Defense and Thesis

Dark Matter

Mississippi State University
Department of Physics
Mississippi State Axion Search

Project: Monte Carlo Simulation of the Mississippi State Axion Search
Abstract: The study of dark matter has been of interest to physicists, and a candidate dark matter particle called the axion has been theorized. The Mississippi State Axion Search (MASS) project will use a light shining through a wall technique to search for the particle. The MASS project will search in the meV range. This range was estimated by the Polarizzazione del Vuoto con LASer (PVLAS) in Italy in 2008. A beam of photons will be fired at a wall through a vacuum within a magnetic field. If this produces axions, they will pass through the wall and decay into photons which will be detected by sensors. Before the completion of the experiment, a Monte Carlo simulation written in Mathematica will model the experiment using known theories regarding the experiment. The Monte Carlo generates “fake” data based on certain random statistical methods that will be used to test the analysis package to be used for the experimental data. The data generated by the Monte Carlo will also be used to compare against the experimental data.

Computational Fluid Dynamics

Mississippi State University
Center for Advanced Vehicular Systems

Project: Coupled Discrete Element/Lattice Boltzmann Model (DEM/LBM) for Large Particle Assemblies in Fluid

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