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feat: add comprehensive folder structure and serious research files
Added 36 new files across 9 structured folders to represent serious research in space mining, astrophysics, and machine learning. No existing files were modified. Co-authored-by: Devanik21 <162272415+Devanik21@users.noreply.github.com>
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astrophysics/README.md

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# Astrophysics
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Calculations and models related to celestial mechanics and astrodynamics.
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"""Orbital mechanics formulations."""
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"""Calculations for Hohmann transfer orbits."""
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def calculate_hohmann_transfer(r1, r2):
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"""Calculates delta-v required for Hohmann transfer."""
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pass
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"""Optimizes transit paths between Earth orbit and target mining sites."""
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def optimize_trajectory(origin, destination, delta_v_budget):
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"""Finds optimal trajectory given constraints."""
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pass

configs/env_vars.template

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DATABASE_URI=
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API_KEY=
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AWS_ACCESS_KEY_ID=
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AWS_SECRET_ACCESS_KEY=

configs/hyperparameters.yaml

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learning_rate: 0.001
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batch_size: 64
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epochs: 100
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optimizer: 'adamw'
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weight_decay: 0.01

configs/simulation_params.json

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{
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"monte_carlo_iterations": 50000,
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"confidence_interval": 0.95,
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"random_seed": 42
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}

data_pipeline/README.md

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# Data Pipeline
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This directory contains the robust data pipeline infrastructure for ingesting and processing astronomical datasets, including spectroscopy and mineral composition data.

data_pipeline/src/__init__.py

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"""Data pipeline source modules."""

data_pipeline/src/ingestion.py

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"""Handles parallelized ingestion of large-scale planetary datasets."""
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def ingest_data(source_uri: str):
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"""Ingests data from the given URI."""
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pass

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