<p>Back in the &quot;good old days&quot; (the 1980s), a lot of discoveries were made by amateurs.  Transient phenomena such as comets or supernovae were spotted by amateurs.  This was possible because the bottleneck in making discoveries was the human eye and brain.  You needed eyes to look at the sky, or pictures of the sky.  Computers couldn't process images well enough to find new transient objects. Only humans could do that.  Professionals would be no better than amateurs at looking around the sky trying to spot new stars in galaxies or fuzzy stars that are not known nebulae.  So amateurs with eyes, brains, and time had an advantage.</p>
<p>The trouble with &quot;using machine learning&quot; is that lots of people can do that.  Are your algorithms really better than the ones that the pros have already used on the data?  As computers have gotten better at image processing, the &quot;human bottleneck&quot; has gone.  So it has become possible to have automated supernova surveys, automated searchs (using space telescopes) for comets and asteroids. Automated processing of lightcurves to detect exoplanets.</p>
<p>For finding exoplanets, a space telescope is really convenient: you really want several years of data, and it is very convenient if you can get out of the atmosphere as you are looking for very small changes in brightness. The air (and the moon) make measuring this from Earth harder. And you really want a lot of measurements in order to pull the very weak signal from the noise.  The Kepler telescope did just that.  But the Kepler data is now pretty much processed out.</p>
<p>All this does not mean it is impossible for new amateur discoveries.  Amateurs can run supernova discovery surveys. Even so, they still have to compete with the pros now. This makes the entry level very high: you need a lot of cash and a lot of sky, and a lot of luck!</p>
<p>One possible avenue for new discovery is weak meteor showers. Some of the &quot;sporadic&quot; meteors are probably part of very weak streams.  Here amateurs have an advantage as meteors are local phenomena and can't be observed by a space telescope. Meteors and meteor showers don't get named after their discoverers (so you don't get your name in the skies.  But here is an area at which amateurs can still contribute.  See the <a href="https://ukmeteornetwork.co.uk/" rel="nofollow noreferrer">UK meteor Network</a> for more details</p>

CC BY-SA 4.0
2020-12-29T16:23:57.723Z
2020-12-29T16:23:57.723Z
James K
<p>Zooniverse has a citizen science project called <a href="https://www.zooniverse.org/projects/ianc2/exoplanet-explorers" rel="noreferrer">Exoplanet Explorers</a> that used volunteers to examine data on exoplanet candidates.  It was so successful that it has now run out of data, but there are <a href="https://www.zooniverse.org/projects?discipline=astronomy&amp;page=1&amp;status=live" rel="noreferrer">other space projects</a> that are looking for contributors</p>

CC BY-SA 4.0
2020-12-29T13:57:22.437Z
For historic purposes, on might also mention the discontinued [SETI@home](https://en.wikipedia.org/wiki/SETI%40home) project. Strictly speaking, it is not about exoplanets in general, but "only" for those with inhabitants sending out signals.
B--rian
CC BY-SA 4.0
2020-12-29T13:51:40.477Z
2020-12-29T13:51:40.477Z
Dave Gremlin
<p>I recently read about <a href="https://en.wikipedia.org/wiki/Precovery" rel="nofollow noreferrer">precovery</a>, where plates or images of an object predating its discovery are used to precisely determine its orbit. It occurred to me that it might be possible that some objects have yet to be identified in open-access astronomical databases, simply as an oversight or maybe as a misidentification (say, mistaking a planet for a star). Is it possible for an amateur astronomer to go through open-access astronomical image data and perhaps use machine learning algorithms to find new celestial bodies? Has it been done? If not, how likely is it that an amateur astronomer could even do so?</p>

CC BY-SA 4.0
2020-12-28T23:24:10.053Z
https://astronomy.stackexchange.com/questions/40626/ might be helpful, I guess.
B--rian
CC BY-SA 4.0
2020-12-28T23:38:49.093Z
Does this answer your question? [Why most discovered exoplanets are heavier than Earth?](https://astronomy.stackexchange.com/questions/40626/why-most-discovered-exoplanets-are-heavier-than-earth)
WarpPrime
CC BY-SA 4.0
2020-12-28T23:44:37.803Z
Related: Before the advent of automated supernova searches (~25-30 years ago), practically all of them were discovered by amateurs. Usually only 1 or 2 dozen per year.
D. Halsey
CC BY-SA 4.0
2020-12-29T00:21:04.803Z
I don't think that is a dupe.  It doesn't address the core of the question, though may be useful background reading.
James K
CC BY-SA 4.0
2020-12-29T11:51:06.593Z
I VTC'd as "opinion based" as I do not see how to make anything but a guess as to whether there is anything to find (or how much or how likely) in the images out there.  Verifying technique would also be a tricky issue.
StephenG - Help Ukraine
CC BY-SA 4.0
2021-01-02T01:32:48.283Z
I'll vote to **leave-open** so that answering is not prematurely blocked. I think fact-based answers are certainly possible, let's give the community a chance. There is no danger of a swarm of opinion-based answers overwhelming this post, so no need to quickly close in order to shut off some firehose of bad answers.
uhoh
<observational-astronomy><telescope><amateur-observing><exoplanet>
How difficult is it for an amateur to discover a new exoplanet or astronomical object?
Vikrant Sharma
# How difficult is it for an amateur to discover a new exoplanet or astronomical object?

(Asked by: username_0 on 2020-12-28)

I recently read about [precovery](https://en.wikipedia.org/wiki/Precovery), where plates or images of an object predating its discovery are used to precisely determine its orbit. It occurred to me that it might be possible that some objects have yet to be identified in open-access astronomical databases, simply as an oversight or maybe as a misidentification (say, mistaking a planet for a star). Is it possible for an amateur astronomer to go through open-access astronomical image data and perhaps use machine learning algorithms to find new celestial bodies? Has it been done? If not, how likely is it that an amateur astronomer could even do so?

**Tags:** observational-astronomy, telescope, amateur-observing, exoplanet

> **Comments:**
> **username_1**: https://astronomy.stackexchange.com/questions/40626/ might be helpful, I guess.  
> **username_2**: Does this answer your question? [Why most discovered exoplanets are heavier than Earth?](https://astronomy.stackexchange.com/questions/40626/why-most-discovered-exoplanets-are-heavier-than-earth)  
> **username_3**: Related: Before the advent of automated supernova searches (~25-30 years ago), practically all of them were discovered by amateurs. Usually only 1 or 2 dozen per year.  
> **username_4**: I don't think that is a dupe.  It doesn't address the core of the question, though may be useful background reading.  
> **username_5**: I VTC'd as "opinion based" as I do not see how to make anything but a guess as to whether there is anything to find (or how much or how likely) in the images out there.  Verifying technique would also be a tricky issue.  
> **username_6**: I'll vote to **leave-open** so that answering is not prematurely blocked. I think fact-based answers are certainly possible, let's give the community a chance. There is no danger of a swarm of opinion-based answers overwhelming this post, so no need to quickly close in order to shut off some firehose of bad answers.  

---

## 2 answers

### Answer by username_4 on 2020-12-29. Score: 2 | Accepted answer

Back in the "good old days" (the 1980s), a lot of discoveries were made by amateurs. Transient phenomena such as comets or supernovae were spotted by amateurs. This was possible because the bottleneck in making discoveries was the human eye and brain. You needed eyes to look at the sky, or pictures of the sky. Computers couldn't process images well enough to find new transient objects. Only humans could do that. Professionals would be no better than amateurs at looking around the sky trying to spot new stars in galaxies or fuzzy stars that are not known nebulae. So amateurs with eyes, brains, and time had an advantage.

The trouble with "using machine learning" is that lots of people can do that. Are your algorithms really better than the ones that the pros have already used on the data? As computers have gotten better at image processing, the "human bottleneck" has gone. So it has become possible to have automated supernova surveys, automated searchs (using space telescopes) for comets and asteroids. Automated processing of lightcurves to detect exoplanets.

For finding exoplanets, a space telescope is really convenient: you really want several years of data, and it is very convenient if you can get out of the atmosphere as you are looking for very small changes in brightness. The air (and the moon) make measuring this from Earth harder. And you really want a lot of measurements in order to pull the very weak signal from the noise. The Kepler telescope did just that. But the Kepler data is now pretty much processed out.

All this does not mean it is impossible for new amateur discoveries. Amateurs can run supernova discovery surveys. Even so, they still have to compete with the pros now. This makes the entry level very high: you need a lot of cash and a lot of sky, and a lot of luck!

One possible avenue for new discovery is weak meteor showers. Some of the "sporadic" meteors are probably part of very weak streams. Here amateurs have an advantage as meteors are local phenomena and can't be observed by a space telescope. Meteors and meteor showers don't get named after their discoverers (so you don't get your name in the skies. But here is an area at which amateurs can still contribute. See the [UK meteor Network](https://ukmeteornetwork.co.uk/) for more details


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### Answer by username_7 on 2020-12-29. Score: 5

Zooniverse has a citizen science project called [Exoplanet Explorers](https://www.zooniverse.org/projects/ianc2/exoplanet-explorers) that used volunteers to examine data on exoplanet candidates. It was so successful that it has now run out of data, but there are [other space projects](https://www.zooniverse.org/projects?discipline=astronomy&page=1&status=live) that are looking for contributors

> **Comments:**
> **username_1**: For historic purposes, on might also mention the discontinued [SETI@home](https://en.wikipedia.org/wiki/SETI%40home) project. Strictly speaking, it is not about exoplanets in general, but "only" for those with inhabitants sending out signals.  

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