DEPARTMENT OF PHYSICS

This study develops a machine learning model to predict abnormalities in commercial airplanes using real-world Automatic Dependent Surveillance-Broadcast (ADS-B) data, focusing on altitude changes exceeding 100 feet in 10 seconds. Following the methodology established by Passarella et al. (2024), this research implements and compares 25 different machine learning algorithms, ultimately selecting Quadratic Discriminant Analysis (QDA) as the optimal approach. The dataset comprises 167,844 records, including 84,074 normal and 83,770 abnormal instances, with features such as altitude, velocity, heading, latitude, and longitude. The theoretical foundation covers the comprehensive taxonomy of machine learning methods, from supervised learning algorithms like Support Vector Machines and Decision Trees to unsupervised approaches such as K-Means clustering. The QDA model achieves superior performance with 93-97% accuracy, 0.96-0.97 ROC-AUC, validated through stratified 5-fold cross-validation. Visualizations, including altitude plots and ROC curves, enhance interpretability for aviation professionals. This research demonstrates that QDA's ability to model non-linear decision boundaries with class-specific covariance matrices makes it particularly suitable for complex aviation data patterns, supporting enhanced flight safety and operational efficiency.

Nanotechnology has gained significant attention in various fields due to its potential in developing advanced materials with unique properties. Silver nanoparticles (AgNPs) are widely used in medicine, electronics, and environmental applications due to their antibacterial and catalytic properties. This study explores a practical approach to synthesizing AgNPs using a chemical method, where silver salts are reduced in the presence of stabilizing and reducing agents. By adjusting factors such as precursor concentration, temperature, and reaction time, the size and stability of AgNPs can be controlled. Common chemical techniques like the Turkevich and polyol methods provide efficient and scalable synthesis. The resulting nanoparticles are analyzed using UV-Vis Spectroscopy, DLS, XRD, and TEM to confirm their size and structure. While chemical synthesis is effective, challenges like toxicity and environmental impact must be considered for safe and sustainable use

Quantum computing represents a revolutionary paradigm shift in computation, promising exponential speedup over classical computers in solving certain problems. This project delves into the realm of quantum computing, aiming to provide a comprehensive understanding of its principles, applications, and implications. The introductory chapter sets the stage by delineating the motivation and objectives of the study. Following this, the literature review offers a historical overview and examines key concepts in quantum mechanics, classical computing limitations, landmark quantum algorithms, recent advancements, and existing challenges. Methodologically, a qualitative approach is adopted, integrating literature review, experimental data, and simulations. Ethical considerations are carefully accounted for throughout the research process. Results and findings are then presented, encompassing analysis of experimental data or simulation outcomes, comparison of classical and quantum computing performance, and implications for the field. This project serves as a foundational resource for understanding quantum computing, offering insights into its current state, potential applications, and future trajectories. It contributes to the ongoing discourse surrounding quantum computing, guiding future research endeavors and technological advancements in this transformative field.

n the research of Determining the size and geometry of the universe, we noticed some challenges. It is challenging to estimate the size and shape of the universe. Sheer scale means that light from distant areas has not had time to reach us, truncating observations. Further, the accelerating expansion due to dark energy complicates measurement. Dark matter, which is unseen, affects the universe's gravitational structure in a complex way. It is hard to measure distances due to enormous scales and the need for calibration. Observations rely on visible matter and radiation, so the picture is incomplete and uncertain. In determining the size and geometry of the universe relies on important methods. Astronomers observe cosmic microwave background (CMB) radiation for data about its structure. They use large-scale structures like the distribution of galaxies to comprehend the universe's shape. Techniques like redshift surveys quantify the expanding universe through light from distant galaxies to determine distances and scale. Gravitational lensing, with deflection of light by massive bodies, indicates where visible and dark matter are. Combining these methods with theoretical models, scientists can develop a coherent picture of the universe's size and shape. From integrating data from these diverse approaches, we were able to determine the value of the parameters for the scale factor of the universe (a), the curvature of space (k), Hubble's constant (H). I was able to calculate to get the value for the scale factor of the universe (a) to be 9 × 1010 light years, and for the value for k which is the curvature of space, to be 1. When k is 1, the universe will be spherical. And also, for the value of the Hubble’s constant to be 69.8km/s/mpc.

This research is concerned with neutrino physics in general, and specifically with neutrino mixing and oscillations. Neutrinos are massless in the standard model of particle physics, so they do not mix or oscillate. However, many experimental results now appear to support neutrino oscillations, necessitating the extension of the standard model to include neutrino masses and mixing among different neutrino flavors. In calculating the probability of electron neutrino oscillating into muon neutrino, the model equation below was used: � �� → �� = 𝑠� 2 2�13 𝑠� 2 �23 𝑠� 2 1.27∆�2 2 3 �� 2 � �� � ��� The probability was calculated using the model equation by taking arbitrary values for L/E ranging from 100-10000, using the Microsoft excel spreadsheet. The value of the probability varies between 0.093-0.24 and a graph of probability, P against ranging values of L/E was also plotted using the Microsoft excel spreadsheet. The probability of a neutrino changing type is related to the distance travelled by the neutrino from its point of production to its point of detection. As a general rule, neutrinos travelling greater distances will exhibit greater depletion from oscillation. Moreover, the oscillation varies smoothly over increasing distance.

Zinc sulphide (ZnS) thin films were successfully deposited on glass substrates using an improved solution growth technique (SGT) at a constant temperature of 50 °C for three hours, with bath molarity varied between 0.03 M and 0.15 M. The optical and solid-state characteristics of the films were systematically investigated to evaluate the influence of precursor concentration on their structural and optoelectronic performance. Spectral analyses revealed that absorbance increased while transmittance generally decreased with rising molarity, indicating enhanced light absorption due to improved film density. The absorption coefficient (α) and refractive index (n) exhibited molarity-dependent variations consistent with changes in surface uniformity and crystallinity. Calculated optical band gaps (Eg) ranged between 3.47 eV and 3.77 eV, signifying direct allowed transitions typical of ZnS semiconductors. Notably, films prepared at 0.12 M displayed optimal optical properties, balancing high transmittance with suitable band gap energy for potential application in solar cells and other optoelectronic devices.
The results confirm that controlled bath concentration in SGT offers a simple and effective route to tailoring ZnS thin films with desirable optical and solid-state characteristics for functional material applications.

This research explores the photon (γ) as the gauge boson responsible for mediating the electromagnetic force, framed within Yang–Mills gauge field theory. The work investigates how U(1) gauge symmetry naturally gives rise to the electromagnetic field and explains the masslessness, spin-1 nature, and non-self-interaction of the photon as direct consequences of unbroken gauge invariance.

Through comparative analysis between Abelian and non-Abelian gauge theories, the study demonstrates that while Yang–Mills fields (SU(2), SU(3)) yield self-interacting gauge bosons, the Abelian U(1) symmetry of electromagnetism produces a linear, non-self-interacting field—the classical Maxwell equations emerging as a special case.

The findings confirm that the photon’s existence and properties are not empirical accidents but logical necessities of gauge principles. Ultimately, this project underscores the profound unity between electromagnetism and the broader framework of modern gauge theory, situating the photon as a fundamental manifestation of symmetry in nature.

Perovskite materials made of lead telluride (PbTe) have gained a lot of attention from researchers because of its potential uses in photovoltaics, optoelectronics, and thermoelectrics. They cannot, however, be fully utilized in device applications due to issues such as structural instability, mechanical constraints, electronic flaws, and suboptimal optical performance. In order to solve these problems, we comprehensively examine the structural, mechanical, electronic, and optical characteristics of PbTe perovskite using first-principles density functional theory (DFT) computations. Through the analysis of elastic constants, and formation energies, our study unveils the basic stability criteria. The mechanical resilience of the material is assessed by evaluating its mechanical properties, such as bulk modulus, shear modulus, and Poisson's ratio. Additionally, the nature of bandgap engineering and defect tolerance can be understood through the use of density of states and electronic band structure simulations. The dielectric function and absorption coefficient are examples of optical response functions that are calculated to maximize light-harvesting efficiency. Our findings point to potential strain engineering and doping techniques to improve PbTe's stability, electrical performance, and optical activity, hence increasing its suitability for use in next-generation energy and optoelectronic applications.

This research focuses on the design and implementation of a wireless resistivity meter using discrete components. The system addresses the limitations of traditional wired resistivity meters by integrating a wireless transmitter and receiver for efficient data acquisition and portability. The transmitter processes sinusoidal and square wave signals from a signal generator and wirelessly transmits the data to the receiver for analysis. The wireless resistivity meter was evaluated through experimental tests to validate its accuracy, reliability, and operational range. Results demonstrate that the system effectively captures and transmits geophysical data with high precision, making it a significant advancement over conventional wired systems. Key features of the system include real-time data storage and export capabilities, compatibility with modern software tools like LabVIEW Signal Express, and robust performance across varying field conditions.

This study has used the recently established combination between EAM and
the TB-SMA scheme to determine the n, p, q parameters values needed for the
calculation of total energy of the three FCC metals which include Ag, Pd and Pt. The EAM and TB-SMA was established to replace the old approach of determining parameters for calculating total energy because of its improved computational efficiency and accurate results. The Microsoft excel programming language has been employed in this study to reproduce results with good accuracy as compared with previous studies using other programming software.