Filed to: Zero-G ·

Twin galaxies, what are the statistical odds? Consider the current estimate of galaxies, roughly two trillion, which will surely change over the coming years as the new James Webb telescope is launched in 2018. How big is two trillion?

2 trillion is 2,000,000,000,000

That’s a pretty big number . Is it statistically possible, even if perhaps not probable, that our Milky Way could have a twin? What does the math say?

What are the statistical chances of having human twins? The research indicates it really depends on where you live, but just for fun, let’s average things out and be conservative and say 1 percent. There is absolutely NO reason to make this comparison, other than there are infinite variables in each case.

It turns out that galaxies come in all sorts of sizes and shapes, and the Milky Way represents just one type, a barred spiral. Spiral galaxies make up roughly 60% of the galaxies in the local universe. Bars are found in approximately two thirds of spiral galaxies.

So, walking through the math:
0.6 x 2,000,000,000,000 = 1,200,000,000,000

and, bar galaxies occur 2/3 of those, so:
0.66 x 1,200,000,000,000 = 792,000,000,000

So one percent of 792,000,000,000 looks something like, 0.01 x 792,000,000,000 = 7,920,000,000

Okay, let’s do the math for one in a million:
One millionth of 792,000,000,000 looks something like, 0.000001 x 792,000,000,000 = 792,000.

Really? I have a chance.

“One in a million — you mean I have a chance?”

Insane!

Maybe. But before you quickly discount this line of thought, consider what is actually happening to light as it travels across the cosmos and near black holes. Consider that black holes have so much gravity that as light approaches a black hole event horizon, it bends. Other cosmic entities also bend light. How much of an effect might this be on the light that reaches us, for example, how many of these black holes are there? Consider for just a moment that our Milky Way, alone, may have 100 million stellar-mass black holes. Multiply that by the number of galaxies and you begin to see the potential impact on the light we see in the night sky. It gets better. Additionally, “light is bent and magnified by gravity of intervening clusters of galaxies” resulting in multiple images of the source of the light.

Have we ever observed this? Oh yah!

“In the 1993 Bill Murray movie, a weatherman finds himself reliving the same day over and over again. Now astronomers using the Hubble Space Telescope say they have been watching the same star blow itself to smithereens in a supernova explosion over and over again, thanks to a trick of Einsteinian optics.”

- New York Times (Astronomers Watch a Supernova and See Reruns)

The point — what we think we see when we look out into the cosmos is not the true picture, rather something warped by a ton of gravity which we have no real map of. We only see the light after it’s traveled its cosmic path, which we can guarantee was not a straight line — meaning that star, that galaxy, that cosmic event, isn’t where we think it is. We will be very surprised as we learn more, just as we have been so far.

Okay, so as we study the 90% or so unstudied galaxies, perhaps we might want to look for evidence of the possibility of an image of something that looks like our neighborhood, the Milky Way, at some very early state. With the ton of imagery we have, that we continue to generate, and will be obtaining, let’s apply some computer resources , modeling and pattern matching to the investigation. Let’s use a computer model of the Milky Way and it’s changing state to run the model of the Milky Way in reverse — to see how a series of early state Milky Way’s might have looked. Then, let’s apply pattern matching AI to the plethora of galaxy imagery being produced to see if there is a close match.

Why?

Let’s say we found a match, a close match. That light would be very, very old. It would be, in effect, looking back in time, perhaps at us. And that is what makes this exercise interesting. Remember, a photon, light, does not experience spacetime.

This article was provided by Hank M. Greene. He is a storyteller currently living in the Pacific Northwest, writing “time, a trilogy”. His passion is writing from the crossroads of physics, artificial intelligence, neuroscience, and business. He can be found on Twitter, Flipboard, and Medium.

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