{"id":23589444,"url":"https://github.com/ewdlop/computational-physcis-notes","last_synced_at":"2026-04-20T05:34:06.195Z","repository":{"id":49354034,"uuid":"363988908","full_name":"ewdlop/Computational-Physcis-Notes","owner":"ewdlop","description":"Computational Physics written in Python","archived":false,"fork":false,"pushed_at":"2025-01-13T20:41:23.000Z","size":43712,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-13T21:33:16.027Z","etag":null,"topics":["maple","matlab","numpy","physics-simulation","python","qsharp","scipy","wolfram-mathematica"],"latest_commit_sha":null,"homepage":"","language":"Mathematica","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ewdlop.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2021-05-03T16:15:30.000Z","updated_at":"2025-01-13T20:41:26.000Z","dependencies_parsed_at":"2024-04-16T09:14:47.222Z","dependency_job_id":null,"html_url":"https://github.com/ewdlop/Computational-Physcis-Notes","commit_stats":null,"previous_names":["ewdlop/computational-physics-notes","ewdlop/computational-physcis-notes"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ewdlop%2FComputational-Physcis-Notes","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ewdlop%2FComputational-Physcis-Notes/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ewdlop%2FComputational-Physcis-Notes/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ewdlop%2FComputational-Physcis-Notes/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ewdlop","download_url":"https://codeload.github.com/ewdlop/Computational-Physcis-Notes/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239420152,"owners_count":19635518,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["maple","matlab","numpy","physics-simulation","python","qsharp","scipy","wolfram-mathematica"],"created_at":"2024-12-27T06:14:07.487Z","updated_at":"2025-11-03T22:30:26.185Z","avatar_url":"https://github.com/ewdlop.png","language":"Mathematica","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Computational-Physcis-Notes\n\n![alt text](Doge.jpeg)\n![alt text](ExpZ.jpg)\n![alt text](Less\u0026#32;points.gif)\n![alt text](Lmao.jpg)\n![alt text](Maple\u0026#32;Code.png)\n![alt text](OpOp.png)\n![alt text](OpOpX2.png)\n![alt text](OpOpX3.gif)\n![alt text](OpOpX4.png)\n![alt text](Poordoge.jpg)\n![alt text](Spin.gif)\n![alt text](Too\u0026#32;many\u0026#32;circles.jpg)\n![alt text](Too\u0026#32;many\u0026#32;circles.jpg)\n![alt text](Trajectories.PNG)\n![alt text](WeirdAngle.PNG)\n![alt text](Wow.gif)\n![alt text](op.jpg)\n![alt text](opopx5.PNG)\n\n## Purpose of the Repository\n\nThis repository contains various computational physics scripts and notebooks. The purpose is to provide examples and notes on different computational physics problems and methods.\n\n## Main Files and Their Purposes\n\n- `Python/calculate_trajectory.py`: Calculates the trajectory of a projectile.\n- `Python/Cooper_Pairing(BCS Theory).py`: Implements the BCS theory for Cooper pairing.\n- `Python/Logic/logic.ipynb`: Contains logic gates and quantum logic examples.\n- `Python/lanczos_tridiagonalisation.ipynb`: Demonstrates the Lanczos tridiagonalization method.\n- `Python/boundary-value-problem-in-electrostatics_ConformalMap.py`: Solves a boundary value problem in electrostatics using conformal mapping.\n- `Python/casimir_force.py`: Calculates the Casimir force between two plates.\n- `Python/components-in-series-or-parallel.py`: Calculates equivalent capacitance, resistance, inductance, and spring constants for components in series or parallel.\n- `Python/derivative.ipynb`: Demonstrates numerical differentiation methods.\n- `Python/discretised_fourier_transform.ipynb`: Demonstrates the discretized Fourier transform.\n- `Python/dispersion relation_for_diatomic_chain.py`: Calculates the dispersion relation for a diatomic chain.\n- `Python/double_pendulum_LagrangianMechanics.py`: Simulates the double pendulum using Lagrangian mechanics.\n- `Python/double_pendulum.py`: Simulates the double pendulum.\n- `Python/eigenvalue_problem.ipynb`: Solves eigenvalue problems.\n- `Python/finding_roots.ipynb`: Demonstrates numerical root-finding methods.\n- `Python/ground_state_quantum_harmonic_oscillator.ipynb`: Solves the ground state of a quantum harmonic oscillator.\n- `Python/Hamilton-Jacobi.md`: Notes on the Hamilton-Jacobi equation.\n- `Python/Impedances.py`: Calculates impedances in series and parallel circuits.\n- `Python/kernel_density_function.ipynb`: Demonstrates kernel density estimation.\n- `Python/kirchhoff's-laws.py`: Solves circuits using Kirchhoff's laws.\n- `Python/lattice-QCD.py`: Simulates lattice QCD.\n- `Python/Logic/logic.ipynb`: Contains logic gates and quantum logic examples.\n- `Python/modelling_lithium.ipynb`: Models lithium atoms.\n- `Python/numeric_integration.ipynb`: Demonstrates numerical integration methods.\n- `Python/Numpy/basic.ipynb`: Basic examples of using NumPy.\n- `Python/parton_distribution.py`: Models parton distribution functions.\n- `Python/phonon_dispersion.py`: Calculates the phonon dispersion relation.\n- `Python/qBits.ipynb`: Demonstrates quantum bits (qubits).\n- `Python/runge_kutta_method.ipynb`: Demonstrates the Runge-Kutta method for solving ODEs.\n- `Python/Scipy/basic.ipynb`: Basic examples of using SciPy.\n- `Python/semiconductor-band-structure.py`: Models the band structure of a semiconductor.\n- `Python/simple-harmonic-oscillator_Hamilton-Jacobi_Symbolically.py`: Solves the simple harmonic oscillator using the Hamilton-Jacobi equation symbolically.\n- `Python/simple-harmonic-oscillator_Hamilton-Jacobi.py`: Solves the simple harmonic oscillator using the Hamilton-Jacobi equation.\n- `Python/simple-harmonic-oscillator_Path Integral_Numerical.py`: Solves the simple harmonic oscillator using the path integral method numerically.\n- `Python/simple-harmonic-oscillator_Path Integral_Symbolically.py`: Solves the simple harmonic oscillator using the path integral method symbolically.\n- `Python/simple-pendulum_elliptic-integral-of-the-first-kind.py`: Solves the simple pendulum using the elliptic integral of the first kind.\n- `Python/simple-pendulum_Hamiltonian-Mechanics.py`: Solves the simple pendulum using Hamiltonian mechanics.\n- `Python/stress-strain_curve.py`: Plots the stress-strain curve for elastic and nonelastic materials.\n- `Python/symplectic-form.md`: Notes on the symplectic form.\n- `Python/three_body_equations.py`: Solves the three-body problem.\n- `Python/truncated normal distribution.ipynb`: Demonstrates the truncated normal distribution.\n- `Python/two-body-problem.py`: Solves the two-body problem.\n- `Python/Type I and Type II-superconductors.py`: Notes on Type I and Type II superconductors.\n- `Python/wave_packet_spreading.ipynb`: Demonstrates wave packet spreading.\n- `Python/wave_packet_spreading.py`: Demonstrates wave packet spreading.\n- `Python/workspace.code-workspace`: VS Code workspace configuration.\n\n## How to Run the Code\n\n1. Clone the repository:\n   ```\n   git clone https://github.com/ewdlop/Computational-Physcis-Notes.git\n   cd Computational-Physcis-Notes\n   ```\n\n2. Install the required dependencies. For Python scripts, you can use `pip` to install the necessary packages. For example:\n   ```\n   pip install numpy matplotlib scipy sympy\n   ```\n\n3. Navigate to the desired script or notebook and run it. For example, to run a Python script:\n   ```\n   python Python/calculate_trajectory.py\n   ```\n\n4. For Jupyter notebooks, you can use Jupyter Lab or Jupyter Notebook to open and run the notebooks. For example:\n   ```\n   jupyter lab Python/Logic/logic.ipynb\n   ```\n\n5. Follow the instructions and comments within each script or notebook for specific usage details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fewdlop%2Fcomputational-physcis-notes","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fewdlop%2Fcomputational-physcis-notes","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fewdlop%2Fcomputational-physcis-notes/lists"}