Frequently Asked Questions

The Open Supernova Catalog is an open-access, community-curated astrophysical repository containing comprehensive data for over 110,222 supernovae and cosmic transients from 1000 AD to 2026+. It unifies multi-band optical, ultraviolet, and infrared light curves, calibrated spectra, host galaxy associations, cosmological distance parameters, and NASA ADS literature citations into a single standardized schema.

The original Open Supernova Catalog went offline around 2021, scattering transient astronomy data across fragmented silos. We rebuilt sne.space from first principles into a high-performance, modern platform that combines deep historical records with real-time survey streams (TNS, ZTF, ATLAS), AI-native discovery tools (MCP and WebMCP), and a dual-experience architecture serving both professional astrophysicists and amateur stargazers.

The IAU Transient Name Server (TNS) is the official discovery registry, but lacks unified multi-band light curves or calibrated spectral time series. WISeREP stores spectra but does not aggregate multi-color photometry. Alert brokers (ALeRCE, Fink, Lasair) stream modern alerts but lack deep historical archives before 2018. sne.space bridges these systems by synthesizing discovery circulars, broker alert streams, space telescope observations (Hubble, JWST, Swift), and peer-reviewed literature into one living entity per event.

Supernovae are broadly categorized into two fundamental physical mechanisms: Thermonuclear Detonations (Type Ia), where a carbon-oxygen white dwarf in a tight binary system accretes mass to the Chandrasekhar limit (~1.4 solar masses) and completely obliterates itself; and Core-Collapse Supernovae (Types II, Ib, Ic), where a massive supergiant star (≥8 solar masses) exhausts its nuclear fuel, collapsing into a neutron star or black hole while rebounding its outer envelope into space.

For events with measured spectroscopic redshifts (z), cosmological distances are calculated using standard Flat Lambda-CDM cosmology (H0 = 70 km/s/Mpc, Ω_M = 0.3, Ω_Λ = 0.7). Relativistic velocity is computed as v = c * ((1+z)² - 1) / ((1+z)² + 1). Luminosity distance (d_L) is derived via numerical integration of the comoving distance, and converted to light-years via 1 Mpc = 3,261,560 light-years.

Yes, when they are at or near peak brightness! Supernovae in nearby galaxies (within ~50 million light-years) frequently reach apparent magnitudes between 10.0 and 13.5, making them visible in 4-inch to 10-inch amateur telescopes. However, optical transients fade rapidly along radioactive decay tails (typically fading 2 to 5 magnitudes over 30 to 60 days). Every event page on sne.space includes an automated transient lifecycle indicator telling you whether the object is currently active or extinguished.

Data is available in multiple machine-readable formats: Complete JSON schema at /sne/{name}.json, calibrated multi-band photometry CSV table at /{name}/photometry?format=csv, and calibrated optical spectra at /{name}/spectra?format=json. All endpoints are open-access, zero-token, and support CORS for direct client-side integration.

Yes! sne.space implements an IVOA Simple Cone Search endpoint at /api/cone?RA={deg}&DEC={deg}&SR={deg}&format=votable (or format=json). It runs against a spatial 3D Cartesian index over 110,000+ catalog objects, returning sub-millisecond coordinate cross-matches.

sne.space provides direct image endpoints: /sne/{name}/host.jpg returns a 302 redirect to the highest available optical cutout. You can also specify survey layers via /api/{name}/cutout?layer=panstarrs|desi|wise|2mass|dss2&size=500.

Yes! sne.space includes a native FastMCP server (serve/mcp_server.py) exposing tools for AI assistants (Cursor, Claude, agents): search_supernovae, get_supernova, get_lightcurve, get_spectrum, calculate_cosmology, and spatial_cone_search.

WebMCP is an emerging browser standard enabling websites to expose structured tools directly to AI browsing agents. sne.space implements declarative WebMCP on all search forms (toolname and tooldescription attributes with fully described input parameters) and imperatively registers search_supernovae, get_supernova_photometry, and cone_search via document.modelContext.

sne.space publishes official AI Catalog v1.0 and ARD discovery manifests at /.well-known/ai-catalog.json and /.well-known/ard.json, discoverable via HTML tags and HTTP Link headers.

When using sne.space in academic publications, please cite Guillochon et al. (2017), 'An Open Supernova Catalog', The Astrophysical Journal Letters, 835(1), L64 (Bibcode: 2017ApJ...835L..64G). Every event page also provides a 'Copy BibTeX' button aggregating the primary discovery and data citations specific to that object.