Skip to content
View debansuadhikary's full-sized avatar
☁️
☁️

Block or report debansuadhikary

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
debansuadhikary/README.md



Hi, I'm Debansu Adhikary

Physics Student & Undergraduate Researcher

Exploring Quantum Foundations & Scientific Computing

Investigating fundamental physical principles through theoretical analysis and computational simulations.




// ABOUT ME


Monochrome Visual

I am a physics undergrad, focusing on quantum foundations, theoretical models, and computational physics.

My academic journey involves investigating fundamental physical principles through both theoretical analysis and computational simulations. I actively participate in research programs and physics colloquia to explore foundational problems in modern physics.

  • Focus Areas: Quantum Foundations, Theoretical Physics, Computational Modeling, Fusion Reactors
  • Methods: Mathematical Proofs, Numerical Simulations, Algorithmic Analysis



// FEATURED PROJECT


Charged Particle Dynamics in a Dipole Magnetic Field

High-performance RK4 numerical simulation investigating single-particle confinement, nested multiscale periodicity (gyration, bounce, azimuthal drift), and numerical conservation of the first adiabatic invariant $\mu = \frac{m v_\perp^2}{2|B|}$.

  • Core Implementation: Modular, field-agnostic 4th-order Runge-Kutta integrator engineered in C for high-throughput ODE stepping, paired with an adaptive-window running gyro-average algorithm.
  • Analysis & Visualization: Post-processing pipeline in Python (Matplotlib) for 3D drift shell reconstruction and $\Delta t$ convergence sweeps across 40× step-size variations.
  • Physics Insights: Distinguishes physical finite-Larmor-radius ripple from secular numerical drift, benchmarking invariant conservation against high-order truncation limits.



// COMPUTATIONAL TOOLSET


Applied computational tools while continuously learning and deepening my understanding through physics projects.


Languages & Typesetting

Scientific Computing & Modeling

Environment & Version Control



"Equipped with five senses, man explores the universe around him and calls the adventure Science." — Edwin Hubble

Pinned Loading

  1. computational_physics-journalcomputational_physics-journalPublic

    Sharing my college computational physics coursework here to create a clear, accessible foundational reference for anyone interested in the subject.

    Python 1

  2. dipole_field_adiabatic_invariantsdipole_field_adiabatic_invariantsPublic

    Charged particle trapped in a magnetic dipole field: gyration, bounce, and drift motion, plus the first adiabatic invariant and its numerical conservation.

    C 1