matmod: Quantum Photonic Material Modeling and Quantum Machine Learning

This repository supports teaching and research training for undergraduate and graduate students in:

• Quantum photonic material modeling
• Hydrogen storage and hydrogen production materials
• CO2 reduction materials and catalytic pathways
• Quantum chip development with strong emphasis on photonic materials

The central theme is photonic materials and how quantum simulation methods can accelerate material discovery, validation, and device integration.

Teaching Goals

1. Build strong fundamentals in quantum mechanics, materials modeling, and photonic device physics.
2. Train students to use modern quantum and atomistic toolchains for practical workflows.
3. Connect simulation outputs to clean-energy applications (H2, CO2) and photonic quantum hardware design.
4. Develop reproducible research habits: versioned datasets, documented workflows, and clear technical writing.

Program Tracks

Undergraduate Track

The undergraduate stream focuses on conceptual clarity, guided labs, and scaffolded projects. Students learn how to:

• Model basic material properties relevant to photonics
• Build intuition for quantum circuits and hybrid workflows
• Interpret simulation outputs for sustainability-focused use cases

Directory: undergrads/

Graduate Track

The graduate stream emphasizes advanced methods, critical literature analysis, and independent research execution. Students work on:

• First-principles and quantum-informed materials pipelines
• Benchmarking across classical and quantum frameworks
• Publishable project design in photonic material systems

Directory: grads/

Tooling Areas in This Repository

• pennylane-gui/: Interactive workflows for variational and hybrid quantum modeling.
• qiskit-gui/: IBM-oriented circuit and simulation interfaces for materials workflows.
• cirq-gui/: Google-style circuit experimentation and custom algorithm prototypes.
• gpaw-gui/: First-principles electronic-structure modeling (DFT/TDDFT) for photonic materials.
• papers/: Reading lists, paper notes, discussion prompts, and publication drafts.

Suggested Workflow

1. Start with the undergrads/ or grads/ curriculum path.
2. Use the GUI/tool directories for method-specific labs and demos.
3. Record literature and project evidence in papers/.
4. Integrate results into final reports, presentations, and manuscripts.

Contribution Style

• Keep notebooks and scripts well documented.
• Include references for material systems and computational methods.
• Prefer reproducible pipelines with explicit environment details.

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This repository is designed as a living teaching-and-research environment for quantum photonic material modeling across education levels and research depth.