Add comprehensive documentation suite and automation tools

[Copilot]

The project contained valuable research content across 6 domains but lacked structure, navigation, and practical tooling for users to leverage it effectively.

Documentation Structure

• GETTING_STARTED.md: 3 role-based learning paths (engineer/researcher/expert) with 4 detailed application scenarios
• RESOURCES.md: Indexed 160+ papers by conference/topic, 100+ code repositories, 10+ datasets, pre-trained models
• ROADMAP.md: Cross-domain integration patterns, technical stack recommendations, implementation phases
• FAQ.md: 24 common questions covering setup, usage, and contribution workflows
• CONTRIBUTING.md: Standards for content submission, PR review criteria, versioning conventions
• CHANGELOG.md: Version history and planned feature roadmap

Tooling

• requirements.txt: Modular dependency specifications with optional components per research direction
• setup_env.sh: Interactive environment setup with CUDA detection, framework installation (PyTorch/JAX), and per-direction dependency management

# Automated environment setup with intelligent defaults
./setup_env.sh
# Select directions: 1 2 4
# Detects CUDA 11.8 → installs PyTorch with cu118
# Installs: differentiable physics, physics foundation models, world models

README Enhancements

• Added navigation matrix linking all 9 documents
• Technical comparison table across 6 research directions
• Application scenario quick-finder
• Maturity ratings for production readiness assessment

Total: 2,669 lines of documentation, 50+ cross-references, ~35k words.

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💡 You can make Copilot smarter by setting up custom instructions, customizing its development environment and configuring Model Context Protocol (MCP) servers. Learn more Copilot coding agent tips in the docs.