This month:
- Curated notebooks from MAST, HEASARC, and IRSA are now available directly on Fornax.
- New HATS Catalogs for GALEX and Hubble, and updates for PanSTARRS.
- New notebooks for moving object searches and ZTF light curves.
- Coming soon: Manage your scratch space directly from the Fornax Dashboard!
Mission- and Archive-specific Notebooks on Fornax
Curated notebooks from all three archives (MAST, HEASARC, and IRSA) are now available on Fornax, with pre-built kernels containing all necessary software. You can find them in ~/fornax-notebooks, next to fornax-demo-notebooks. These include mission-specific tutorials, how to find and access data hosted on the cloud, and more! Open introduction.mdv to see a full list with descriptions.
New HATS Catalogs
MAST has released several HATS catalog data products. HATS is a Parquet-based format that enables scalable, cloud-based analysis of large astronomical catalogs. The datasets are available in AWS S3 cloud storage buckets, and access is free. Tutorials are available at LSDB Tutorials.
- GALEX Merged Catalog of Sources (MCAT)
- Hubble Source Catalog (v3.0) (S3 path:
s3://stpubdata/mast/public/hsc/hats/hsc_v3/) - Corrections: PanSTARRS DR2 (objects, detections, forced mean object, stack object)
New Notebooks
IRSA released two new Python notebook tutorials.
- Moving Object Searches: Run MOST queries to find images of moving objects, retrieve cutouts, and stack exposures to boost detection.
- ZTF Light Curves (HATS): Get ZTF light curves directly from the cloud-hosted HATS Catalog. This method is especially good when you need a large number of light curves or for anyone who simply prefers to work with HATS/Parquet over IRSA’s on-premises Lightcurves service.
Coming Soon: Scratch Storage Self-Management
You will soon be able to manage your own scratch space directly from the Fornax Dashboard! We’ll send an announcement with more details as soon as the feature is available. As a reminder, scratch space is a working area for large data in cases where your S3 storage isn’t performant enough, and your home directory is too small.