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  • University of York
  • United Kingdom
  • 14:49 (UTC +01:00)

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scott-lynn/README.md

About Me

I am a computational physicist with a background in theoretical physics and scientific computing, having earned a first-class MPhys in Theoretical Physics from the University of York. My Master's research focused on the computational simulation and security analysis of entanglement-based quantum key distribution (QKD).

I am particularly interested in high performance computing (HPC), parallel programming, distributed computing, and GPU acceleration for complex scientific workloads.

Core Stack: C++, Modern Fortran, Python

HPC: MPI, OpenMP, CUDA.

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  1. hybrid-mpi-sor-solver hybrid-mpi-sor-solver Public

    High-performance, hybrid-parallelised (MPI + OpenMP) Successive Over-Relaxation (SOR) solver for coaxial potentials

    Fortran

  2. waterfowl-CNN waterfowl-CNN Public

    CNN classifying ducks, geese, and swans from images — built in TensorFlow/Keras, tuned via Bayesian optimisation, on a small, imbalanced dataset.

    Jupyter Notebook

  3. 2D-heat-solver-MPI 2D-heat-solver-MPI Public

    A modern Fortran 2D heat equation solver utilising MPI for distributed-memory parallelisation, featuring hardware topology and latency analysis on AMD EPYC architectures.

    Fortran

  4. bb84_sim bb84_sim Public

    End-to-end C++23 BB84 quantum key distribution simulator for cryptographic key generation under realistic optical channel physics.

    C++

  5. iDEA iDEA Public

    Forked from iDEA-org/iDEA

    interacting Dynamic Electrons Approach

    Jupyter Notebook 1