Atomistic Simulation for Quantum and Molecular Photonics

Welcome to Atomistic Simulation for Quantum and Molecular Photonics, a practical undergraduate course in atomistic simulation methods applied to materials for quantum and molecular photonics.

Course Description

This course introduces the computational tools and concepts needed to model the structural, electronic, and defect properties of materials. We use ASE (Atomic Simulation Environment) as our primary software framework, which provides a clean Python interface to a range of pre-processing tools, electronic structure codes and analysis tools.

The course has a dual focus:

• Core simulation skills that are transferable across all areas of materials research

• Application examples drawn from quantum and molecular optics: single-photon emitters, optically active defects, photonic semiconductors, and 2D materials.

Who is this course for?

This course is aimed at undergraduate students in physics, chemistry, or materials science who have:

• Basic familiarity with Python (variables, lists, loops, functions)

• Some background in solid-state physics or physical chemistry

• An interest in computational approaches to materials

No prior experience with atomistic simulation is required.

How to use this resource

Each lecture is a self-contained Jupyter Notebook. You can:

• Read the rendered version on this website

• Run interactively via Google Colab using the rocket 🚀 button at the top of each page

• Download the notebooks and run them locally

Course Structure

Lab	Topics	Skills	Exercise
1. Introduction	Motivation and scope; brief history of atomistic simulation; expectations and assessment	Setting up a Python environment; navigating Jupyter notebooks	Scientific programming warm-up
2. Atomistic Simulation Basics	Composition-structure-property relationships; overview of simulation methods; where DFT, MLIPs, and MD fit in	Using the Materials Project database; interpreting crystal structure data	Exploring the Materials Project
3. Working with Atoms	The ASE Atoms class; accessing and modifying structural data; reading and writing structure files; visualising structures	ASE Atoms object; CIF/XYZ file I/O; structure visualisation with nglview	Lattice parameter of gold
4. Manipulating Atoms	Building molecules and bulk crystals; creating supercells; introducing point defects	ASE build module; supercell construction; vacancy and substitution creation	Building a defect supercell
5. Potential Energy and Equilibrium Structure	Effective Medium Theory; computing potential energy surfaces; fitting equations of state; finding equilibrium structures	EMT calculator; equation of state fitting with ASE	Equation of state for a metal
6. Local Optimisation	Introduction to DFT; optimising atomic positions; optimising the unit cell	GPAW setup and convergence; geometry relaxation	Relaxing a crystal structure with DFT
7. Electronic Structure	Electronic bandstructure; density of states; k-point convergence	GPAW bandstructure and DOS calculations; k-point convergence tests	Bandstructure of silicon
8. Machine-Learnt Interatomic Potentials	What are MLIPs and when should I use them?; using MACE for geometry optimisation; screening studies	MACE calculator; high-throughput structure relaxation	Screening lattice parameters across a material family
9. Point Defects	Defect supercells; geometry relaxation with MLIPs; electronic structure of defect systems; relevance to quantum emitters	Defect creation in ASE; MACE relaxation; GPAW DOS for defect systems	NV centre in diamond
10. Molecular Dynamics	MD for time evolution; tracking thermodynamic properties; generating and relaxing disordered structures	NVT/NPT MD with ASE; trajectory analysis	Thermal expansion of a crystal

Acknowledgements

Much of the core ASE content is adapted from the Open Science with ASE workshop tutorials (CC-BY 4.0) developed by Adam Jackson and Lucy Whalley.

This course is developed by Lucy Whalley and James Quirk at Northumbria University.