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AMITY BSc MATHEMATICS PROJECT IDEAS

Amity University BSc Mathematics Projects

Mathematical Modeling of Population Dynamics

Develop mathematical models to study population growth, migration patterns, and demographic changes, exploring implications for public policy and urban planning.

Computational Fluid Dynamics Simulations

Perform numerical simulations of fluid flow phenomena using computational fluid dynamics (CFD) methods, analyzing turbulence, heat transfer, and fluid-structure interactions.

Fractal Geometry and Chaos Theory Analysis

Explore fractal geometry and chaos theory concepts, studying fractal patterns, strange attractors, and nonlinear dynamics using mathematical algorithms and simulations.

Optimization Algorithms and Operations Research

Implement optimization algorithms such as linear programming, genetic algorithms, or simulated annealing to solve complex optimization problems in logistics, finance, or engineering.

Cryptography and Information Security Analysis

Analyze cryptographic algorithms, protocols, and security mechanisms, exploring their strengths and vulnerabilities for protecting digital data and communications.

Mathematical Finance and Risk Management Models

Develop mathematical models for financial markets, portfolio optimization, and risk assessment, applying stochastic calculus and Monte Carlo simulations.

Graph Theory and Network Analysis

Investigate graph theory concepts and network properties, analyzing complex networks like social networks, transportation networks, or biological networks.

Mathematical Biology and Epidemiology Models

Model biological systems and disease dynamics using mathematical equations, studying epidemiological patterns, vaccination strategies, and disease spread control measures.

Quantum Information Theory and Quantum Computing

Explore quantum information theory concepts such as quantum entanglement, quantum cryptography, and quantum algorithms for quantum computing applications.

Numerical Analysis and Scientific Computing

Implement numerical methods for solving differential equations, numerical integration, and approximation algorithms for scientific computing applications.

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