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Supernova Algorithm Classifies 1,000 Dying Stars Without Error

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The California Institute of Technology (Caltech) has used a machine algorithm for classifying 1,000 supernovae caused by the explosion of dying stars.

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SNIascore is the algorithm that created the catalogue using data from the Zwicky Transient Facility, a sky survey instrument attached at Caltech's Palomar Observatory.

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ZTF scans the night sky looking for transient or short-lived events. This can include anything from supernovas and feeding black holes to racing asteroids.

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It was so overwhelming that ZTF team members could not possibly go through it all on their own, which led to the creation of SNIascore as a way to help with this enormous task.

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Christoffer Fremling (Caltech staff astronomer and mastermind behind the new algorithm) said they needed help.

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Since the ZTF's first 2017 observations, thousands of supernovas have been identified. 

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These supernovas can be divided into two broad categories: Type I supernovas without hydrogen signs and Type II supernovas rich in hydrogen. This is the universe's simplest element and lightest.

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Type I supernovas are the most common. This happens when a huge star removes matter from a nearby donor star. The matter falls to its surface, triggering a thermonuclear blast.

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Type II supernovas are when huge stars run out of the fuel required for nuclear fusion, and cannot support themselves against gravitational collapse.

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SNIascore distinguishes a Type Ia cosmic explosion from one with a different origin, called a Type Ia Supernova.

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These are caused by the death of a star and produce a uniform light output, which astronomers call standard candles'.

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These standard candles can be used for measuring cosmic distances across space and time, as well as to gauge the speed at which the universe expands.

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