The Type I Superluminous Supernova Catalog I: Light Curve Properties, Models, and Catalog Description

The Big Picture

Imagine a star that explodes with the energy of 100 billion suns, so bright it briefly outshines entire galaxies. Now imagine that astronomers had been cataloging these extraordinary events for over a decade, but doing so in scattered, inconsistent ways. Different librarians each inventing their own filing system. You’d have a chaotic mess of data that makes it nearly impossible to answer the basic question: what are these things?

That’s the situation with Type I Superluminous Supernovae (SLSNe), stellar explosions so luminous they defy the usual rules. Ordinary supernovae are powered by the slow radioactive decay of nickel, a heavy element forged in the blast, like a glowing nuclear afterburn that fades over weeks. But SLSNe shine up to 100 times brighter than their common cousins, and that fuel simply can’t account for all that power. Something else is going on.

A team led by Sebastian Gomez at the Space Telescope Science Institute has now built the largest uniformly analyzed catalog of these monsters ever assembled: 262 SLSNe, more than 30,000 individual brightness measurements, and a single consistent set of physical models applied to every event.

Key Insight: By treating 262 superluminous supernovae with a unified framework, this catalog lets astronomers answer population-level questions about what powers these extreme explosions. The answer points overwhelmingly toward a spinning neutron star at the heart of each one.

How It Works

The team hunted down every confirmed Type I SLSN reported in the scientific literature through the end of 2022. “Confirmed” mattered: the researchers personally verified the spectroscopic classification (the chemical fingerprint encoded in light that identifies an explosion type) for all 262 events. No hydrogen in the spectrum, luminosity above a set threshold. Those two criteria define a SLSN.

Then came the photometry, systematic brightness measurements over time. The team aggregated data across ultraviolet, optical, and infrared wavelengths from public archives and supplemented it with their own FLEET observational program. The result: 30,000+ data points tracing how each explosion brightened and faded.

From that data, they extracted a suite of observational quantities for each event:

• Peak absolute magnitude: how intrinsically bright did it get at maximum?
• Rise and decline timescales: how quickly did it brighten, and how fast did it fade?
• Bolometric luminosity: total energy output across all wavelengths
• Temperature and photospheric radius evolution: tracking the physical size and heat of the expanding fireball

The real analytical muscle came from fitting every light curve (a graph tracking how brightness changes over time) with a hybrid physical model combining two power sources: a magnetar central engine, a rapidly spinning, highly magnetized neutron star that bleeds rotational energy into surrounding gas, and radioactive nickel-56 decay. Think of it like fitting a battery model to 262 different electronic devices. Same underlying physics, different specs for each.

The fitting returned physical parameters for every event: the magnetar’s initial spin period, its magnetic field strength, the mass of ejected material, and nickel yield. All of this was done consistently across the entire sample, with no cherry-picking and no case-by-case special treatment.

Why It Matters

The results paint a coherent picture. The team recovered a previously suspected relationship between ejected mass and magnetar spin rate: faster-spinning magnetars correspond to less ejected material, suggesting a real physical link between the spinning remnant and the explosion dynamics. The inferred progenitor stars cluster around 6.5 solar masses at the time of explosion, pointing to a specific class of massive star that had shed its outer layers before detonating.

What they didn’t find may be just as important. Despite scanning 262 events across a wide range of cosmic distances, the team found no significant variation with distance. These explosions look the same whether they happened nearby or billions of light-years ago, meaning their properties haven’t evolved across vast stretches of cosmic time.

They also found no evidence for distinct sub-types within the SLSN population, despite years of debate about whether “slow” and “fast” SLSNe represent fundamentally different phenomena. And fewer than 3% of events appear significantly powered by radioactive nickel rather than a magnetar. The magnetar model isn’t just favored; it’s nearly universal.

The catalog also delivers practical infrastructure for the next generation of sky surveys. The team built analytical functions that let anyone simulate a typical SLSN light curve at any wavelength and any phase. As Rubin Observatory’s Legacy Survey of Space and Time comes online and discovers SLSNe by the thousands, calibrated templates and a clean reference sample become essential. The entire catalog (all photometry, model fits, and derived parameters) is publicly available on GitHub.

Bottom Line: The SLSN Catalog establishes magnetar spin-down as the dominant power source for these record-breaking explosions, delivers a population-level view of their progenitor stars, and provides open-source tools that will anchor superluminous supernova science for years to come.