The point
Students learn how to turn real optical and radio data into a defensible scientific result.
The arc
Weeks 1–3: learn on known datasets. Weeks 4–6: investigate a new dataset.
The output
Best case: paper contribution. Baseline: MACRO internal technical note + reproducible notebooks.
Daily rhythm
10–11
Concept
Short lecture. What are we trying to measure and why?
11–12
Guided work
Do the analysis together in Jupyter / DS9 / CARTA.
Next AM
Independent exercise
Submit a notebook, figure, table, or short writeup.
Tools
JupyterLab: NOIRLab or SciServer
Python: Astropy, Photutils, Astroquery, Matplotlib
DS9: FITS image inspection
CARTA / CASA: radio images and VLA data
GitHub: version control and notebooks
Targets: Be stars + MCV stars
Start from zero: “What is a FITS file?”
| Date | Concept | Hands-on | Due / Output |
|---|---|---|---|
| Mon Jun 8 | What is astronomical data? | Open FITS files; inspect headers; make first images. | Data inventory notebook. |
| Tue Jun 9 | Python refresher | Arrays, plots, functions, tables. | Clean Python warm-up notebook. |
| Wed Jun 10 | Coordinates and WCS | Pixel ↔ sky coordinates; mark sources. | Find 5 sources and report positions. |
| Thu Jun 11 | Images have noise | Background, RMS, saturation, artifacts. | Image quality notes + basic statistics. |
| Fri Jun 12 | Reproducible workflow | Notebook template + GitHub basics. | Week 1 deliverable: open, inspect, plot, and describe a dataset. |
Measure stars
| Date | Concept | Hands-on | Due / Output |
|---|---|---|---|
| Mon Jun 15 | Aperture photometry | Measure source flux and background. | Photometry for 3–5 stars. |
| Tue Jun 16 | Uncertainty | Error bars, S/N, bad measurements. | Photometry table with uncertainties. |
| Wed Jun 17 | Calibration | Comparison stars; differential photometry. | Simple light curve. |
| Thu Jun 18 | Catalogs | Gaia/Simbad/VizieR-style crossmatching. | Crossmatched source list. |
| Fri Jun 19 | Be stars / MCV stars | What makes these targets interesting? | Week 2 deliverable: measured optical sources with errors. |
Add radio data
| Date | Concept | Hands-on | Due / Output |
|---|---|---|---|
| Mon Jun 22 | Radio images | Beam, Jy/beam, contours, RMS. | Radio image summary. |
| Tue Jun 23 | Radio flux | Peak flux, integrated flux, upper limits. | Radio measurement table. |
| Wed Jun 24 | Optical + radio together | Overlay contours on optical images. | One multiwavelength figure. |
| Thu Jun 25 | Known result | Reproduce a known MACRO-style measurement. | Known-result notebook. |
| Fri Jun 26 | From measurement to claim | Discuss systematics and interpretation. | Week 3 deliverable: short known-dataset report. |
New dataset: first look
| Date | Concept | Hands-on | Due / Output |
|---|---|---|---|
| Mon Jun 29 | Introduce new target | What data do we have? | Dataset inventory. |
| Tue Jun 30 | Quality control | Find usable / questionable data. | QC memo. |
| Wed Jul 1 | Source finding | Identify targets, counterparts, offsets. | Source list v1. |
| Thu Jul 2 | First measurements | Optical fluxes, radio fluxes, upper limits. | Measurement table v1. |
| Fri Jul 3 | Pick questions | What can this dataset actually answer? | Week 4 deliverable: dataset memo + possible science questions. |
New dataset: focused analysis
| Date | Concept | Hands-on | Due / Output |
|---|---|---|---|
| Mon Jul 6 | Choose subprojects | Each student/pair owns one question. | Analysis plan. |
| Tue Jul 7 | Build the pipeline | Clean notebooks; repeatable measurements. | Measurement table v2. |
| Wed Jul 8 | Systematics | Aperture choices, background choices, radio RMS. | Systematics test. |
| Thu Jul 9 | Figures | Make clean science figures. | Draft figure captions. |
| Fri Jul 10 | Peer review | Group critique of notebooks and claims. | Week 5 deliverable: analysis notebook + draft figures. |
Finish and present
| Date | Concept | Hands-on | Due / Output |
|---|---|---|---|
| Mon Jul 13 | Turn analysis into a result | Write results, limits, and next steps. | Draft talk + technical note. |
| Tue Jul 14 | Final presentations | Student talks and group discussion. | Final package: slides, notebooks, figures, tables, and short report. |
One-sentence version
Learn the tools on known optical + radio datasets, then use the same tools to make a real scientific argument about a new MACRO dataset.