phy-explained

Physics explained through intuition and interactive simulations, in Jupyter notebooks.

Series

CHARA Array

How the CHARA Array on Mount Wilson combines six telescopes up to 331 m apart to measure stars at the milliarcsecond scale. Start with the overview, which needs no code:

• 00_overview.md: the whole story in eight short steps, one figure each.

Then the notebooks, one topic each:

Topic	Notebook	Real data used
T1 Diffraction and resolution	01_diffraction_and_resolution.ipynb
T2 Two-telescope interference	02_two_telescope_interference.ipynb
T3 van Cittert–Zernike theorem	03_van_cittert_zernike.ipynb
T4 Stellar diameters	04_stellar_diameters.ipynb	δ Cephei (VEGA)
T5 uv coverage	05_uv_coverage.ipynb	δ Cephei (VEGA)
T6 Delay lines	06_delay_lines.ipynb	CL Lac cart positions (MIRC-X)
T7 Atmospheric turbulence and closure phase	07_atmosphere_and_closure_phase.ipynb	CL Lac (MIRC-X)
T8 Binaries and image reconstruction	08_binaries_and_image_reconstruction.ipynb	CL Lac (MIRC-X)

Notebook 05 uses the δ Cephei data downloaded by notebook 04, so run 04 first. Notebooks 06 to 08 download their own data.

Integratron

How the Integratron, a 16.8 m wooden dome in Landers, California, focuses sound, rings, carries whispers round its wall, and what a sound bath in it sounds like. Start with the overview, which needs no code:

• 00_overview.md: the whole story in seven short steps, with pictures.

Then the notebooks, one topic each:

Topic	Notebook	Audio
T1 Dome reflections and focusing	01_dome_reflections_and_focusing.ipynb	yes
T2 Ringing and room modes	02_ringing_and_room_modes.ipynb	yes
T3 Focusing in 3D	03_3d_focusing.ipynb
T4 Whispering gallery	04_whispering_gallery.ipynb	yes
T5 The singing bowl	05_singing_bowl.ipynb	yes
T6 Listening to the dome	06_listening_to_the_dome.ipynb	yes
T7 Two crystal bowls	07_two_crystal_bowls.ipynb	yes

WAV files of the notebooks' sounds are in integratron/audio/, so they can be heard without running code. Animations of a crystal bowl vibrating and of two bowls beating are shown in the overview, with longer Manim videos in integratron/manim/videos/.

All results come from models with stated assumptions, such as wall absorption and a perfectly smooth dome. No measurements of the building are used.

Running the notebooks

Each series has its own Python environment. For the CHARA series:

cd chara-array
uv venv .venv && uv pip install -p .venv -r requirements.txt

Open a notebook in VS Code (Jupyter extension) or JupyterLab and select chara-array/.venv as the kernel. The sliders need ipywidgets, which is included.

Real data are public calibrated observations from the JMMC Optical Interferometry Database. The notebooks download them into chara-array/data/ on first run (about 10 MB in total). That folder is not committed.

To regenerate the overview figures:

cd chara-array
.venv/bin/python make_overview_figures.py

For the Integratron series, replace chara-array with integratron in the commands above. It needs no data downloads.