<p>It's possible that two completely different sources might be located almost on top of each other, which could lead to mistakes in our analysis.
One way to help avoid this is by using the redshift of the sources, which is a measure of how far away they are from us. By only considering sources that have similar redshifts, we can be more confident that we're not getting false matches.</p>
<p>Additionally, there are other methods like using physical parameters or statistical tests that can also help us identify and eliminate false coincidences.</p>

CC BY-SA 4.0
2022-12-22T10:29:21.167Z
"statistical tests" is rather vague -- do you have a specific, relevant test in mind. (And in fact part 3 of the question is specifically asking this.)
Peter Erwin
CC BY-SA 4.0
2022-12-22T03:50:48.060Z
2022-12-22T03:50:48.060Z
Pip Lark
<p>When we go through multiple astronomy catalogs, we often do <a href="https://en.wikipedia.org/wiki/Cross-matching" rel="nofollow noreferrer">Cross-matching</a>. We compare the position parameters <span class="math-container">$(\alpha, \delta)$</span> of different sources (galaxies, quasars, etc.) in the equatorial coordinate, where <span class="math-container">$\alpha$</span> is the right ascension and <span class="math-container">$\delta$</span> is the declination.</p>
<p>However, it is possible that two completely different sources are on almost the same position. We might make make mistakes if:
<span class="math-container">$$
\alpha_1 \approx \alpha_2,\ \delta_1 \approx \delta_2
$$</span>
The question here <a href="https://astronomy.stackexchange.com/questions/932/how-can-we-be-sure-that-we-have-identified-very-distant-stars-correctly">How can we be sure that we have identified very distant stars correctly?</a> pointed out the redshift features could be very important in this problem.</p>
<p>My question is:</p>
<ol>
<li>Does the phenomenon often occur when we are doing cross matching?</li>
<li>In specific, how can we use the redshift features in cross matching programs?</li>
<li>Do we have any other way (some special statistics techniques, for example) to solve the problem?</li>
</ol>
<p>Thanks!</p>

CC BY-SA 4.0
2022-12-21T09:30:29.633Z
I think you should narrow your question down. Of course if you cross-match using only coordinates then there can be spurious correlations, since all positions have uncertainties or correspond to sources where the flux has been gathered from a finite positional area. How you resolve (if you can) this problem just depends on exactly what science you are trying to do. Q2 isn't going to be relevant in many (most) cases unless you have a specific application you want to ask about?
ProfRob
<observational-astronomy><data-analysis><positional-astronomy><star-catalogues>
How can we make sure that it is physically the same source when we do cross matching?
Chang
# How can we make sure that it is physically the same source when we do cross matching?

(Asked by: username_0 on 2022-12-21)

When we go through multiple astronomy catalogs, we often do [Cross-matching](https://en.wikipedia.org/wiki/Cross-matching). We compare the position parameters $(\alpha, \delta)$ of different sources (galaxies, quasars, etc.) in the equatorial coordinate, where $\alpha$ is the right ascension and $\delta$ is the declination.

However, it is possible that two completely different sources are on almost the same position. We might make make mistakes if:
$$
\alpha\_1 \approx \alpha\_2,\ \delta\_1 \approx \delta\_2
$$
The question here [How can we be sure that we have identified very distant stars correctly?](https://astronomy.stackexchange.com/questions/932/how-can-we-be-sure-that-we-have-identified-very-distant-stars-correctly) pointed out the redshift features could be very important in this problem.

My question is:

1. Does the phenomenon often occur when we are doing cross matching?
2. In specific, how can we use the redshift features in cross matching programs?
3. Do we have any other way (some special statistics techniques, for example) to solve the problem?

Thanks!

**Tags:** observational-astronomy, data-analysis, positional-astronomy, star-catalogues
> **Comments:**
> **username_1**: I think you should narrow your question down. Of course if you cross-match using only coordinates then there can be spurious correlations, since all positions have uncertainties or correspond to sources where the flux has been gathered from a finite positional area. How you resolve (if you can) this problem just depends on exactly what science you are trying to do. Q2 isn't going to be relevant in many (most) cases unless you have a specific application you want to ask about?  

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## 1 answers

### Answer by username_2 on 2022-12-22. Score: 1

It's possible that two completely different sources might be located almost on top of each other, which could lead to mistakes in our analysis.
One way to help avoid this is by using the redshift of the sources, which is a measure of how far away they are from us. By only considering sources that have similar redshifts, we can be more confident that we're not getting false matches.

Additionally, there are other methods like using physical parameters or statistical tests that can also help us identify and eliminate false coincidences.

> **Comments:**
> **username_3**: "statistical tests" is rather vague -- do you have a specific, relevant test in mind. (And in fact part 3 of the question is specifically asking this.)  

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