Numerical study
Noise Effects on Periodic Soliton
Tracking how stochastic noise intensity κ reshapes the amplitude of a periodic soliton across space and time.
Publications
Research & publications
Working studies on soliton dynamics under noise and fractional order, alongside three peer-reviewed publications, thesis work, and applied computational modelling.
Research projects
Soliton dynamics under noise & fractional order
Built with Maple for the analytics and MATLAB / Python for the numerics — the same pipeline used across the applied projects further down this page.
Numerical study
Fractional Order & Noise Affect Soliton
Combining fractional-order derivatives with stochastic noise to see how the two effects compound in soliton evolution.
Numerical study
Modulation Instability with Noise
Growth-rate analysis of modulation instability as a function of noise intensity σ, tracked across real and imaginary components.
Numerical study
Fractional Effect on Solitons
Comparing soliton solutions Q(x,t) across fractional orders α, from integer order down to near-integer fractional dynamics.
Peer-reviewed
Publications
Solitons, bifurcation, chaos, and stability of the fractional Schrödinger-Hirota equation with beta derivative
From Hertzian contact to Pochhammer-Chree dynamics: solitons, chaos, and bifurcation in granular metamaterials
Soliton solutions, chaotic dynamics, and stability analysis of the (2+1)-dimensional time-space fractional nonlinear Schrödinger equation
Comprehensive soliton solutions of fractional stochastic Kraenkel–Manna–Merle equations in ferromagnetic materials
Exclusive soliton solutions arise in mono-mode optical fibre connecting to nonlinear Fokas system
Thesis
Land use & land cover change — Gazipur District
A full thesis report on detecting and predicting land use / land cover change across Gazipur District, Bangladesh, using multi-epoch Landsat and Sentinel-2 imagery.
Random Forest classification
Google Earth Engine
ArcGIS Pro
CA-Markov projection
Landsat / Sentinel-2
EDIT
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Applied computational work
Flood dynamics modelling — Dinajpur
Adapting a fractional stochastic PDE model — originally developed in Maple — into MATLAB and Python, iteratively resolving symbolic-to-numeric conversion issues to recover stable solution families for flood behaviour.