https://ar.iub.edu.bd/handle/11348/502 2026-06-27T09:48:27Z https://ar.iub.edu.bd/handle/11348/1165 Theoretical Analysis of Electromagnetic Modes in Stratified Media Islam, Md. Ariful Electromagnetic wave propagation in stratified conducting media is a fundamental problem in underwater wireless communication and geophysical exploration. However, the accurate modeling of such environments is computationally challenging due to the highly oscillatory nature of the Bessel functions within the Sommerfeld integrals. This thesis develops a numerical method for analyzing electromagnetic modes in a three- layer model consisting of air, seawater, and seabed. The Global Matrix Method (GMM) is employed to formulate the boundary value problem, allowing for the rigorous treatment of multiple reflections at the interfaces. To resolve the numerical instability associated with the Sommerfeld integrals, a cus- tom integration solver was developed utilizing Romberg integration accelerated by the Shanks transformation (Wynn’s ε-algorithm)[1]. This hybrid approach ensures sta- ble convergence for the oscillatory integrands, overcoming the limitations of standard quadrature methods. Using this solver, the electromagnetic field components generated by a submerged Horizontal Magnetic Dipole (HMD) were explicitly calculated. The results confirm the transition from direct wave dominance in the near-field to lateral wave propaga- tion in the far-field, demonstrating the efficacy of the proposed method for modeling propagation in lossy stratified environments. 2026-02-26T00:00:00Z https://ar.iub.edu.bd/handle/11348/1164 Page Curve Like Entanglement Dynamics in Many-Body Quantum Systems: A Study of a Free Fermionic Model Bhakta, Prosanto This thesis investigates entanglement dynamics in open quantum many-body systems, focusing on a one-dimensional free-fermion model in which a finite system is coupled to a large environment. We study the model introduced in Ref. [1], which becomes exactly solvable in the weak-coupling limit. Using resonant-level-model factorization, we derive analytical expressions for the entanglement dynamics and validate them with numerical simulations based on the correlation matrix formalism. We show that the system exhibits Page-curve-like behavior: the entanglement entropy grows at early times, reaches a maximum at the Page time (proportional to system size), and then decreases at late times. In the appropriate scaling regime, data for different system sizes collapse onto a single curve when plotted against the emitted-particle fraction. These results provide an analytically controlled and numerically validated framework for understanding Page-curve dynamics in open free-fermion systems. 2026-02-01T00:00:00Z https://ar.iub.edu.bd/handle/11348/1000 The LHCb Detector and Testing and Performance Evaluation of AdePT in Gaussino Gomes, James Peter To meet the increasing computational demands of LHC experiments, this study explores the potential of GPU acceleration for electromagnetic simulations. The AdePT proto- type is integrated into the Gaussino framework and compared to the standard GEANT4. Initial results show that AdePT, while requiring optimization, demonstrates promising performance gains, especially with larger workloads. The successful simulation of elec- trons using AdePT highlights its potential for accelerating LHCb simulations and contributing to future physics analysis. Furthermore, a brief review of the LHCb detector is provided, encompassing its key subdetectors: the Vertex Locator (VELO), the tracking system (including the Trigger Tracker, Inner Tracker, and Outer Tracker), the Ring Imaging Cherenkov (RICH) detectors, the electromagnetic and hadronic calorimeters (ECAL and HCAL), and the muon system. 2025-02-01T00:00:00Z https://ar.iub.edu.bd/handle/11348/524 Modeling Chaotic Behavior of Dhaka Stock Market Index Values Using the Neuro-fuzzy Model Banik, Shipra; Chanchary, Farah Habib; Habib, Farah; Khan, AFM Khodadad Stock market prediction is an important area of financial forecasting, which attracts great interest of stock investors, stock buyers/sellers, policy makers, applied researchers and many others who are involved in the capital market. This paper aims to develop an efficient model to predict the Dhaka Stock Market Index (DSPI) values using the appropriate forecasting model. It is widely believed that stock data are nonlinear, dynamic and chaotic. In this paper, we propose an adaptive network based fuzzy inference system (ANFIS) to predict DSPI values. We used the daily general DSPI values for the period of March 2003 to October 10, 2006 for the learning and October 11, 2006 to May 31, 2007 for validation. Results obtained by this model are also compared to the back-propagation ANN model and the traditional ARIMA model to show advantages of the proposed ANFIS model. The findings suggest that the ANFIS model can be used as a better predictor for daily general DSPI values as compared to the ANN and the ARIMA models. The review also discussed relevant patents related to our research. 2020-10-24T00:00:00Z