STEM AI & Physics Simulations

A comprehensive collection of Jupyter notebooks and Python tools for simulating physics systems, implementing AI models, and exploring AGI frameworks. This project covers a wide range of topics from quantum mechanics and astrophysics to deep reinforcement learning and symbolic mathematics.

Installation

Ensure you have Python 3.8+ installed. You can install the required dependencies using pip:

pip install -r requirements.txt

Additional system-level dependencies may be required for specific simulations (e.g., imagemagick for animations).

Usage

Quickstart

import asyncio
from main import AGISystemSTEM

async def run():
    agi = AGISystemSTEM()
    print("AGI System Initialized")

if __name__ == "__main__":
    asyncio.run(run())

Running Notebooks

Most of the functionality is contained within Jupyter notebooks. You can start a Jupyter server to explore them:

jupyter notebook

Core System

The project includes a unified AGI system entry point in main.py:

python3 main.py

Core Features

Physics Simulations

Astrophysics: N-Body simulations, Black Hole accretion disks, Gravitational lensing, and Galaxy dynamics.
Quantum Mechanics: Schrödinger equation solvers, Quantum Harmonic Oscillators, and Lattice QCD.
Statistical Mechanics: Ising models and Monte Carlo simulations.
Fluid Dynamics: Relativistic Burgers equation and Plasma dynamics.

Artificial Intelligence & Machine Learning

Deep Learning: CNNs, LSTMs, Autoencoders, and GANs.
Reinforcement Learning: PPO, Q-Learning, REINFORCE, and Multi-Agent RL.
Generative AI: Text-to-Image Diffusion models, StyleGAN, and Wav2Lip.
Symbolic AI: Integration with SymPy and Z3 Solver.

AGI Frameworks

Integrated AGI systems combining NLP, memory, and symbolic reasoning.
Multi-modal AGI training and neuroevolution strategies.

Project Structure

main.py: Core application entry point.
requirements.txt: Python dependencies.
*.ipynb: Specialized notebooks for various simulations and models.
LICENSE: Project license (MIT).

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for details.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Citation

If you use this software in your research, please cite it using the metadata in CITATION.cff.

Navigation Menu

Repository files navigation

STEM AI & Physics Simulations

Table of Contents

Installation

Usage

Quickstart

Running Notebooks

Core System

Core Features

Physics Simulations

Artificial Intelligence & Machine Learning

AGI Frameworks

Project Structure

Contributing

License

Citation

About

Releases

Packages

Used by

Contributors

Languages

Name		Name	Last commit message	Last commit date
Latest commit History 517 Commits
.github/ISSUE_TEMPLATE		.github/ISSUE_TEMPLATE
REPORTS		REPORTS
omni_sentinel		omni_sentinel
src		src
tests		tests
.deepsource.toml		.deepsource.toml
.gitignore		.gitignore
A2C_Architecture.ipynb		A2C_Architecture.ipynb
AGI_model_frameworks.ipynb		AGI_model_frameworks.ipynb
AI_Assisted_Poetic_Composition_Using_Neural_Language_Models.ipynb		AI_Assisted_Poetic_Composition_Using_Neural_Language_Models.ipynb
AI_Driven_Adaptive_Storytelling_with_Multiple_User_Inputs.ipynb		AI_Driven_Adaptive_Storytelling_with_Multiple_User_Inputs.ipynb
AI_Driven_Personal_Assistant_for_Creative_Brainstorming.ipynb		AI_Driven_Personal_Assistant_for_Creative_Brainstorming.ipynb
A_basic_MD_simulation_with_Lennard_Jones_potential_using_Python.ipynb		A_basic_MD_simulation_with_Lennard_Jones_potential_using_Python.ipynb
A_simple_Variational_Monte_Carlo_for_a_single_particle_wavefunction_with_a_variational_parameter.ipynb		A_simple_Variational_Monte_Carlo_for_a_single_particle_wavefunction_with_a_variational_parameter.ipynb
Active_Learning_Implementation.ipynb		Active_Learning_Implementation.ipynb
Adaptive_Composition_Rules.ipynb		Adaptive_Composition_Rules.ipynb
Adaptive_Composition_Rules_(using_the_golden_ratio_to_position_elements).ipynb		Adaptive_Composition_Rules_(using_the_golden_ratio_to_position_elements).ipynb
Adding_a_Gradient_Background.ipynb		Adding_a_Gradient_Background.ipynb
Advanced_Astrophysical_Visualization_3D_Star_Cluster_Visualization.ipynb		Advanced_Astrophysical_Visualization_3D_Star_Cluster_Visualization.ipynb
Advanced_Bayesian_Inference_with_Hierarchical_Models.ipynb		Advanced_Bayesian_Inference_with_Hierarchical_Models.ipynb
Advanced_Computational_Modeling_in_Cosmology_Dark_Matter_Halo_Distribution.ipynb		Advanced_Computational_Modeling_in_Cosmology_Dark_Matter_Halo_Distribution.ipynb
Advanced_Numerical_Relativity.ipynb		Advanced_Numerical_Relativity.ipynb
Advanced_Reinforcement_Learning_with_OpenAI_Gym.ipynb		Advanced_Reinforcement_Learning_with_OpenAI_Gym.ipynb
Agent_Communication_with_ZeroMQ.ipynb		Agent_Communication_with_ZeroMQ.ipynb
Algorithmic_Music_Composition_and_Remixing.ipynb		Algorithmic_Music_Composition_and_Remixing.ipynb
Analyzing_Astronomical_Data_(using_Gaia_Catalog_Data).ipynb		Analyzing_Astronomical_Data_(using_Gaia_Catalog_Data).ipynb
Applying_PCA_to_Spectral_Data.ipynb		Applying_PCA_to_Spectral_Data.ipynb
Approximate_solution_for_a_simple_scalar_field_theory_using_SDEs.ipynb		Approximate_solution_for_a_simple_scalar_field_theory_using_SDEs.ipynb
Astrophysics_N_Body_Simulation_of_Galaxy_Formation.ipynb		Astrophysics_N_Body_Simulation_of_Galaxy_Formation.ipynb
Augmented_Reality_(AR)_Filters_Using_Computer_Vision.ipynb		Augmented_Reality_(AR)_Filters_Using_Computer_Vision.ipynb
Basic_3D_Rendering_with_PyOpenGL_and_GLUT.ipynb		Basic_3D_Rendering_with_PyOpenGL_and_GLUT.ipynb
Basic_FEM_for_a_1D_Poisson_equation,_relevant_to_gravitational_potentials.ipynb		Basic_FEM_for_a_1D_Poisson_equation,_relevant_to_gravitational_potentials.ipynb
Basic_GAN_Structure_for_Galaxy_Image_Generation.ipynb		Basic_GAN_Structure_for_Galaxy_Image_Generation.ipynb
Basic_N_body_Code_Structure.ipynb		Basic_N_body_Code_Structure.ipynb
Basic_Sound_Reactive_Visualization.ipynb		Basic_Sound_Reactive_Visualization.ipynb
Basic_finite_difference_implementation_for_solving_a_1D_wave_equation_as_a_simplified_model.ipynb		Basic_finite_difference_implementation_for_solving_a_1D_wave_equation_as_a_simplified_model.ipynb
Basic_hybrid_quantum_classical_variational_circuit_for_binary_classification_of_quantum_states.ipynb		Basic_hybrid_quantum_classical_variational_circuit_for_binary_classification_of_quantum_states.ipynb
Basic_implementation_of_the_Einstein_tensor_in_2D_to_demonstrate_curvature_in_a_simplified_gravitational_model.ipynb		Basic_implementation_of_the_Einstein_tensor_in_2D_to_demonstrate_curvature_in_a_simplified_gravitational_model.ipynb
Basic_setup_for_a_simulation_with_a_falling_cube.ipynb		Basic_setup_for_a_simulation_with_a_falling_cube.ipynb
Bayesian_Inference_for_Cosmological_Parameters.ipynb		Bayesian_Inference_for_Cosmological_Parameters.ipynb
Bayesian_Inference_for_Orbital_Parameters.ipynb		Bayesian_Inference_for_Orbital_Parameters.ipynb
Bayesian_Modeling_of_Hubble_Constant_Estimation.ipynb		Bayesian_Modeling_of_Hubble_Constant_Estimation.ipynb
Bias_Evaluation_Example.ipynb		Bias_Evaluation_Example.ipynb
Blackboard_Implementation.ipynb		Blackboard_Implementation.ipynb
Blending_the_Face_Using_Poisson_Blending.ipynb		Blending_the_Face_Using_Poisson_Blending.ipynb
Body_Language_and_Posture_Recognition.ipynb		Body_Language_and_Posture_Recognition.ipynb
Building_a_CNN_for_Galaxy_Classification.ipynb		Building_a_CNN_for_Galaxy_Classification.ipynb
Building_a_Custom_Galaxy_Clustering_Algorithm.ipynb		Building_a_Custom_Galaxy_Clustering_Algorithm.ipynb
Building_an_RNN_for_Gravitational_Wave_Signal_Detection.ipynb		Building_an_RNN_for_Gravitational_Wave_Signal_Detection.ipynb
CITATION.cff		CITATION.cff
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
Calculating_the_scale_factor_over_time_for_a_universe_dominated_by_matter_and_dark_energy.ipynb		Calculating_the_scale_factor_over_time_for_a_universe_dominated_by_matter_and_dark_energy.ipynb
Calculating_the_trajectory_of_an_object_in_a_Schwarzschild_black_hole’s_gravitational_field.ipynb		Calculating_the_trajectory_of_an_object_in_a_Schwarzschild_black_hole’s_gravitational_field.ipynb
Causal_Reinforcement_Learning.ipynb		Causal_Reinforcement_Learning.ipynb
Climate_Modeling_with_Xarray.ipynb		Climate_Modeling_with_Xarray.ipynb
Code_Example_for_Collaborative_Filtering.ipynb		Code_Example_for_Collaborative_Filtering.ipynb
Code_Example_for_Incremental_Learning.ipynb		Code_Example_for_Incremental_Learning.ipynb
Code_Example_for_Quantum_Circuit_Creation.ipynb		Code_Example_for_Quantum_Circuit_Creation.ipynb
Code_Example_for_Speech_Recognition.ipynb		Code_Example_for_Speech_Recognition.ipynb
Code_Example_for_Task_Progress_Tracking.ipynb		Code_Example_for_Task_Progress_Tracking.ipynb
Code_Skeleton_for_Coordination.ipynb		Code_Skeleton_for_Coordination.ipynb
Code_Skeleton_for_Ethereum_Smart_Contract_Interaction.ipynb		Code_Skeleton_for_Ethereum_Smart_Contract_Interaction.ipynb
Code_Snippet_for_Image_Analysis.ipynb		Code_Snippet_for_Image_Analysis.ipynb
Code_for_3D_Recursive_Spheres.ipynb		Code_for_3D_Recursive_Spheres.ipynb
Code_for_Animation.ipynb		Code_for_Animation.ipynb
Code_for_Dynamic_Color_Gradients.ipynb		Code_for_Dynamic_Color_Gradients.ipynb
Code_for_Interactive_Generative_Art.ipynb		Code_for_Interactive_Generative_Art.ipynb
Code_for_Layered_Transparency.ipynb		Code_for_Layered_Transparency.ipynb
Code_for_Multi_Layered_Animation.ipynb		Code_for_Multi_Layered_Animation.ipynb
Code_for_Named_Entity_Recognition_(NER).ipynb		Code_for_Named_Entity_Recognition_(NER).ipynb
Code_for_TFLite_Conversion.ipynb		Code_for_TFLite_Conversion.ipynb
Complete_MAML_Example_Code.ipynb		Complete_MAML_Example_Code.ipynb
Compressing_Spectral_Data_with_an_Autoencoder.ipynb		Compressing_Spectral_Data_with_an_Autoencoder.ipynb
Computing_Cosmological_Distances.ipynb		Computing_Cosmological_Distances.ipynb
Construct_a_simple_Matrix_Product_State_(MPS)_for_a_one_dimensional_quantum_system.ipynb		Construct_a_simple_Matrix_Product_State_(MPS)_for_a_one_dimensional_quantum_system.ipynb
Context_Aware_Reasoning_with_LLMs.ipynb		Context_Aware_Reasoning_with_LLMs.ipynb
Cosmic_Expansion_Modeling.ipynb		Cosmic_Expansion_Modeling.ipynb
Cosmic_Ray_Detection_using_Machine_Learning.ipynb		Cosmic_Ray_Detection_using_Machine_Learning.ipynb
Cosmological_Parameter_Estimation_with_Markov_Chain_Monte_Carlo_(MCMC).ipynb		Cosmological_Parameter_Estimation_with_Markov_Chain_Monte_Carlo_(MCMC).ipynb
Create_a_basic_MPS_representation_for_a_1D_spin_chain_using_PyTorch.ipynb		Create_a_basic_MPS_representation_for_a_1D_spin_chain_using_PyTorch.ipynb
Create_a_basic_gravitational_wave_simulation_using_a_wave_equation_model_as_a_stand_in_for_the_full_BSSN_equations.ipynb		Create_a_basic_gravitational_wave_simulation_using_a_wave_equation_model_as_a_stand_in_for_the_full_BSSN_equations.ipynb
Creating_Conversational_Agents_with_Memory.ipynb		Creating_Conversational_Agents_with_Memory.ipynb
Creating_a_3D_Solar_System_Visualization_with_Python_(using_plotly).ipynb		Creating_a_3D_Solar_System_Visualization_with_Python_(using_plotly).ipynb
Creative_Data_Visualization_with_D3_js_and_Python.ipynb		Creative_Data_Visualization_with_D3_js_and_Python.ipynb
Curator_Controls.ipynb		Curator_Controls.ipynb
DQN_implementation_with_the_`CuriosityModule`_and_the_`replay`_method.ipynb		DQN_implementation_with_the_`CuriosityModule`_and_the_`replay`_method.ipynb
Dark_Matter_Halo_Simulation.ipynb		Dark_Matter_Halo_Simulation.ipynb
Data_Analysis_Techniques_for_Large_Scale_Physics_Data.ipynb		Data_Analysis_Techniques_for_Large_Scale_Physics_Data.ipynb
Data_Driven_Models_for_Material_Science.ipynb		Data_Driven_Models_for_Material_Science.ipynb
Data_Logging_for_Further_Research.ipynb		Data_Logging_for_Further_Research.ipynb
Data_Sonification_for_Scientific_or_Artistic_Exploration.ipynb		Data_Sonification_for_Scientific_or_Artistic_Exploration.ipynb
Deep_Learning_for_Quantum_Systems.ipynb		Deep_Learning_for_Quantum_Systems.ipynb
Detect_Emotions_via_Computer_Vision.ipynb		Detect_Emotions_via_Computer_Vision.ipynb
Different_components_into_a_comprehensive_research_pipeline.ipynb		Different_components_into_a_comprehensive_research_pipeline.ipynb
Digital_Twins_and_Generative_Design_for_Sustainable_Innovation.ipynb		Digital_Twins_and_Generative_Design_for_Sustainable_Innovation.ipynb
Double_DQN_(DDQN).ipynb		Double_DQN_(DDQN).ipynb
Dueling_DQN.ipynb		Dueling_DQN.ipynb
Dynamic_Chat_Flows_with_FSM.ipynb		Dynamic_Chat_Flows_with_FSM.ipynb
EAIP_Technical_Specification.xml		EAIP_Technical_Specification.xml

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Latest commit

History

Repository files navigation

STEM AI & Physics Simulations

Table of Contents

Installation

Usage

Quickstart

Running Notebooks

Core System

Core Features

Physics Simulations

Artificial Intelligence & Machine Learning

AGI Frameworks

Project Structure

Contributing

License

Citation

About

Resources

Code of conduct

Contributing

Security policy

Stars

Watchers

Forks

Releases

Packages

Used by

Contributors

Languages