Daniel and Kelly’s Extraordinary Universe - Did aliens put satellites into Earth's orbit pre-Sputnik?

Episode Date: July 7, 2026

Daniel and Kelly dissect the evidence presented in recent peer-reviewed science papers for pre-Sputnik artificial satellites in Earth orbit.See omnystudio.com/listener for privacy information.

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Listen, Inside American Soccer with Tom Bogart and Tab Ramos on the iHeart Radio app, Apple Podcasts, wherever you get your podcast. Everyone wants the aliens to arrive, right? Not just me? Honestly, I can't even tell anymore. Personally, I wake up every morning, hoping that today is the day that the aliens come, that they appear in orbit or send us a message or otherwise make themselves known to us

because either that's never going to happen, a possibility too depressing to really consider, or it will happen, which means there will be a day when that is real. And, hey, why can't that be, Today. In this episode, we'll flip that script and we're going to ask, hmm, why not yesterday? What if aliens have already visited and we could find evidence of their arrival in historical data? I don't mean seeing an alien on the grassy knoll taking out JFK, I mean historical, astronomical, scientific data, things we could analyze and make real conclusions about.

Well, one scientist thinks she's found some very compelling evidence that suggests that there were artificial satellites orbiting the Earth pre-Sputnik, which, if true, of course, would suggest aliens. We'll dig in the evidence, think about it skeptically, and hear about a competing analysis of the same data. Today is the day we think about aliens. Welcome to Daniel and Kelly's extraordinarily alien universe. Smith, I study parasites and space, and I love stories about weird stuff that's been sent to space. Hi, I'm Daniel. I'm a particle physicist who's fascinated by aliens, and I really, really, really want to find proof of aliens here or in outer space or around some distant planet. You absolutely do. I am not surprised to hear that. But my question for you today is, what is the weirdest thing you know of that has been sent to space? Ooh, good question. I think maybe the weirdest thing to send to space was like Elon sending his car to space.

That was weird. Which I think he thought was cool in some nerdy way. I don't know. Maybe the weirdest thing I know about outside of Earth is the astronauts leaving their poop bags on the moon. That's pretty weird. I told you that. Yes, you did. Awesome story. Best source of carbon on the moon, right? Probably. That's what I think. But NASA want you to leave it alone. Historical artifacts. Yep, no growing your tomatoes in the long-lost bowel movements of Neil Armstrong. How about you, Kelly, what is it the real answer since you know about everything that's in all of space? I don't know about everything that's in all of space. But Sallute 3, which was a space station sent up by the Soviet Union, had a cannon. Did you know that there had been a cannon in space that actually shot a cannon ball out?

But it waited until everybody was off board in case shooting the cannonball, like, shook something loose and everyone died. Because unfortunately, the crew of Solut One had died. Were they preparing for a sort of cannon-based naval battle in space? I mean, I think that at that point they were preparing for just about anything. I think, you know, one argument could be that if, you know, space stations start going to war, you'll want a cannon or if maybe you just want to shoot an enemy satellite out of the space sky, then you would like to have a cannon. We also brought machetes to space, but that was more for if you ended up landing in a dangerous area,

like an area where there were wolves or something, and you weren't rescued yet. you wanted to make sure you were safe. This is all just perfectly setting up the space pirates movie that we're writing. Oh, yeah. Yep, yep. Coming soon to a theater near you. There are also stories about bottles of liquor that were found stowed in the arms of space suits. But, you know, you got to have some fun in space, too.

All right, but today we're not talking about humans having fun in space. No, no. We're talking about potential aliens leaving artifacts in near-Earth orbit. because while one scenario is for aliens to arrive and announce themselves and land in Central Park and say, hello, we are the aliens. Another is that they have already visited Earth and we just hadn't noticed yet. But that made me through careful sleuthing, we could uncover some clues that they had been here. And today on the pod, we're going to dig through some pretty big claims about evidence folks found in archival plates that might suggest the existence of alien artifacts or.

orbiting Earth. And just in case this is your first time enjoying Daniel and Kelly's extraordinary universe, I would like to make clear that we are going to be addressing a lot of science here. And even though Daniel started off by saying, I love aliens, and let's talk about alien artifacts. This is a science-based show. Stick with us. Exactly. And today we're covering a controversy that's played out in scientific journals. We're talking about peer-reviewed articles and papers, which is the way that these questions should be asked and answered. We should be exploring these things with data and reproducible studies before

anybody convinces themselves that these are aliens or alien artifacts. And so thank you, Kelly, for reminding us. We are focusing on the science today, not on the drama, not on the grift. Well, we've got a little bit of drama that you know, you got to enjoy yourself when you're talking about science. But okay, so in particular today, we're addressing a question about whether or not artificial satellites have been observed orbiting Earth before Sputnik, which, you know, which was, of course, the first artificial satellite, the first satellite made by a human that went to space. Exactly.

So I reached out to the Extraordinaries, and I asked them to comment on this question. And the exact question I asked them was, were artificial satellites orbiting the Earth before Sputnik, which I thought pretty strongly hinted at the alien question. But here's what the extraordinaire's had to say. There was a manhole cover that was probably shut into space earlier. My grandmother's temper was definitely in orbit before Sputnik.

No, I think Sputnik was the first. For proof of concept, I'm sure that there were things sent into orbit before sending up an expensive pinging ball. Unless there were aliens or maybe a super secret CIA mission. So by artificial, I'm going to assume that means human made. Aliens were putting artificial satellites in orbit before. Or Sputnik. This artificianianian made?

Or does it mean not from this planet? I would say no, but maybe Daniel found some alien ones. No. Spotnik was first. Yeah, I got to say from that question, I didn't think you were trying to get at aliens. And actually, it wasn't until about halfway through the outline that I was like, this is about aliens? I guess I was trying to be fair-handed and not tip the answer or anything. and I assumed that everybody had already heard about this study.

But people mostly were like, oh, is there something that was launched before Sputnik, which technically counts? You know, they was sort of a well-actually kind of a question. But no, we're not talking about that at all. We're talking about whether there were satellites around the Earth before humans could put satellites in Earth, which would mean not human-made satellites, but artificial. But alien. If, of course, they're not.

are real. And that's going to be the whole question we're addressing today, whether or not these things are real. All right. So this is, because I don't know anything about it yet, I'm going to go ahead and call it a conspiracy theory, but we'll see what I think by the end. This is a conspiracy theory I've never heard of before. This is totally new. It's not a conspiracy theory. It's a scientific analysis and people disagree about what it means and we're exploring the various hypotheses. It's not like fact denying conspiracy theory. Okay, well, I've never heard of this argument before. So where do we start?

Yeah, so let's start with the origin of the data itself, the source of these claims, because everything is going to hinge on that. So it's important that we understand that in some great detail. And it comes from this great historical survey called the POS One Survey. It was done in 1949 to 1958, and it was just a campaign where they took pictures of the whole sky. This is the Palomar optical sky survey. POS. And you said POS 1, or is there like 50 pauses coming next?

Or was there only one? And do people who aren't fond of this call it the piece of survey one? Because I feel like that was the acronym that first came to mind. Yeah, so this is the first POS survey. There was another one later on. But this is the one that took place before Sputnik was there. And so it's the one of interest. Okay, got it.

And when did Sputnik go up? Sputnik launched in 1957, and this survey, again, was 49 to 58. Okay. And so this is the Palomar Observatory, and they just took pictures of the whole sky, which is super awesome because they just, like, wanted a map. You know, like, you stand out there under the night sky, and you're like, look at all these stars. But it's so much information. It's hard to absorb.

And then to remember, like, did I see that star last night? Has this moved? So it's really valuable to just create, like, a reference. Just take a picture of the whole sky so we know what's there. Baseline data is critical and we don't collect enough of it. Yes, exactly. And so what they did is they scanned the whole sky and this is well before digital cameras. So these are photographic plates.

Each one is 14 inches by 14 inches. So it's photographic emulsion using the same chemical technology that's in like normal old-fashioned photographs. You know, light hits it and causes a chemical reaction. Then you develop it. And so they scanned almost the whole. sky, and they had two filters, one in blue and one in red, and each exposure took like 45 to 50 minutes, because what they wanted was a really deep picture of the sky. They wanted to see really, really faint stuff as well, which requires collecting light over more than just like a second

or a millisecond, like when your phone takes a picture of something moving really, really fast, it's a short exposure. But if it takes a picture at night, it gathers light for a few seconds until it can resolve things. Here, the exposures are like 50 minutes long when the telescope is tracking the sky as it's moving so that things don't get smeared out. Wow, that sounds complicated, especially using technology from 70 years ago.

Yeah, it is complicated. And, you know, these days we have computers that can control this stuff, but astronomers have been doing this for a long, long time. And it's an awesome data set because it can see really, really faint stuff. And the way astronomers define this stuff is in terms of a very counterintuitive

metric called magnitude. And so the bigger, the number, the fainter it is. So stuff that you can see easily in the sky, like navigational stars, or magnitude like one to three. Things that you can see with the naked eye is a limit of like magnitude of six. Pluto, for example, is magnitude of 14. Every five steps is a hundred times fainter. So this survey could see up to the 22nd magnitude. So really, really faint stars across the whole sky, really, really valuable data for understanding, like, what's there. Certainly no awards for naming are going to astronomers today. And so at the time, this was the most advanced sky survey ever. There's no similar combination of the depth of sensitivity and the breadth of coverage.

And so this became like the baseline data for so much science over the decades. If you wanted to know if something was there, you would look at the POS-1 survey. Huge amounts of science came out of this survey. And the reason they did it was they had another telescope, which was good at looking at individual things, but you had to know where to point it. So this telescope was really good for broad images. They had another one, a companion telescope,

which could really focus in on one object, but they had to know what to look for. So they did this big survey looking for interesting stuff, and then they would focus the other telescope on it. Oh, awesome. That's a good system. Yeah. And this was such a powerful survey, that it really wasn't surpassed for like 50 years

until we had the Sloan Digital Sky Survey in the early 2000s. But even that was a smaller fraction of the sky. So it's still a useful data set. Okay. And so I am going to guess that we were going with this as we found aliens in those photos. There is some interesting stuff in this data set.

But one more wrinkle we need to keep in our minds as we talk about the dataset is that most people who analyze these images are not looking at the original plates. because these are like, you know, literal photographs or emulsions that are like sitting in storage at the Palomar Observatory or a copy that was made that's sitting in Edinburgh. Most people are looking at the digitized version. So in 1986, they did a scan of these plates and then there were subsequent scans later. Okay.

And that's what most people are looking at. And the scan adds a wrinkle because you're essentially taking a digital picture of the plate plus whatever is sitting on the plate, you know, dust or debris. or scratches or all sorts of stuff. The originals are very, very fragile, and so you can't just let anybody in. They're essentially like almost a historical artifact. But if you did feel like you were onto something, you could check against the original and see if it was a smudge of dust and then, like, blow it off and take another picture, right? You could, in principle, inspect those plates microscopically. And we're going to talk in a minute about the limits of what you can learn from that kind of inspection. But there's already here an opportunity. Like, we have a

picture of the sky from the 1940s, 1950s, right? So you can look at that picture and you can compare it to a picture you take today and you can look for differences. Like what if there was something that wasn't in the original survey and you can see now? That means like the sky has changed and change is always fascinating. Or what if there was something in those original pictures which isn't there now, which we don't see anymore, something has disappeared. And so this is, you know, for normal astrophysics, this is a fascinating piece of data. You can look for like, Variable stars or stars that went supernova or anything new that's out there in the universe that we didn't anticipate. Remember, so many discoveries in astronomy just came from asking basic questions about

what we're seeing in the sky, discovering something we can't explain and then having to invent a new astrophysical object like pulsars to explain some new weird thing we're seeing. So you've got to be open-minded when you're looking at this stuff. I'm wondering if you're going to tell us that billionaires from other galaxies are also shooting their cars with fake bodies into space. And maybe we could look at the fake body they put in the driver's seat to get a handle on what alien bodies look like. Yeah, maybe. Or we'd be even luckier if they left their alien poop out for us to gather. Yes.

I mean, Katrina would be excited if there were alien microbes in there. Like, the opportunities are endless. Oh, yes. And I hope those aliens are eating their fiber. So this is called looking for transients, things that change in the sky. Totally solid science, but hard science. So before we hear about today's investigation of these plates, I want to tell you a little bit about how difficult this kind of science is

and how easy it is to mistake artifacts for real stuff in the sky. Because scientists have done this before. They went out looking specifically for transients when they were trying to find more gamma ray bursts. Gamma ray bursts are these weird flashes of very, very high energy light in the sky that we can't fully explain. There are short bursts, there are long bursts. There are some theories about what might cause them, but they're incredibly energetic events that defy many explanations. So scientists would like to see more of them and to track them. So they thought, well, let's look

in plates to see if there are things that appear and then disappear. So transience would be a great way to discover gamma ray bursts. The original mission was something different, I think, but like many times in astronomy, it has many purposes. And they worked on this for decades. They co-werected. They a bunch of archival plates, not just from POS-1, but also from other surveys. You don't need the whole sky for this. And they were using similar emulsion technology. And what they found, essentially, is that it's really, really hard to tell the difference between an actual thing in the sky and a defect on the plate.

Oh. Right? So you can have, like, scanning issues, like there's dust on the plate when you scan it. You can have manufacturing defects, like air bubbles in the emulsion. You can have cosmic rays that. hit the emulsion just at the same moment when you're taking the picture and like some muon deposits energy, which leaves a little burst. You can have spontaneous clustering of the silver grains inside the emulsion, the chemistry that's like making the photograph work.

Chemistry! And these can produce things that look like stars. Even if you take those emulsions and then like do microscopic analysis of it, you like look at the individual thing that you're wondering about, like, is this a star or is this a defect, you still can't always tell whether it's real or not. That sounds really frustrating. Just to clarify, transience is a word for something that you see sometimes, and then when you look again, it's not there. Yeah, exactly.

So, you know, the lesson here from 20 years of looking for gamma-ray bursts in these surveys is that they could not find a single one that they were convinced was real. Oh, wow. Right? Not a single one that could be definitively proved to be a gamma-ray burst or even a transient, right? And so world experts, people who like spend their careers on this stuff, say that when you look closely in the microscope, you find all kinds of junk. And there's lots of different defects there, which can't easily be distinguished from stars or from real

astronomical objects. That must have been frustrating. So did they find a bunch of these defects? Or was it just like they found one defect and they were like, oh, nope, nope, nothing. No, you said a decade. They found a bunch of defects that they were like, okay, this is clearly a defect. But they also found a bunch of stuff. They're like, I don't know, it looks like a star. It could also be a defect. You can't really tell. And so the whole field of gamma ray bursts via archival plates sort of hit a dead end. And they ended up building a satellite to go out in space and to look specifically for gamma ray bursts. Basically, they had to give up on the archival data because it was not useful for this. There's too many defects. It's too hard to tell whether anything is real on these plates or not.

And they only made progress once they built a dedicated instrument for this thing. And now they've done all sorts of great science with that. So gamma ray bursts astronomy, totally legit, but not based on these archival plates. So that's the lesson is that this kind of technology is kind of poorly suited to the task of asking, are there transients in the sky? But I'm going to guess that that's not stopping everyone, and that's where we're going to go after the break. for heart-wrenching knockouts. The world's biggest stage. And breathtaking triumph.

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Listen to Hey Jonas on the IHeartRadio app, Apple Podcast, or wherever you get your podcasts. And we're back at Daniel and Kelly's Extraordinary Universe. So you just finished telling us that these pictures of the sky taken by the Palomar Optical Sky Survey, these are great, amazing photos. But if you're trying to compare those photos to some more recent photos, it's really hard because there's a lot of defects, lots of reasons why these photos aren't, you know, could lead you astray. And you indicated it's not a great source of data for these sorts of comparisons, but does someone disagree? Well, you know, it's the data that we have. And if you're interested in

transients in the sky 50 years ago, you can't go back and say, let's use better technology. We didn't have it. So always and often in science, you go to war with the data you have, right? Not the data you want. And so you try your best to extract whatever information you can from the data you have. And so we're going to talk today about a series of papers led by Beatrice Billerreal. She's an astrophysicist at Nordita in Stockholm. She's a PhD in astronomy from Uppsala, where she studied active galactic nuclei. So totally mainstream, legit scientist, excellent credentials, doing real science. And she was looking for vanishing stars. She was curious about this kind of transient. And so she went back and studied these old plates, right,

from POS 1. And she found a bunch of examples where there was something in the POS 1 plate, but then doesn't match anything else we know and it's now gone, right? Okay. And so this is already interesting. Like, what is it? What could it be? But based on what you told us before, my gut is saying dust or galactic cosmic radiation hitting

at the wrong angle or something. Yeah, exactly. And she's aware that this is an issue. So she starts with a huge data set of all possible. features on the plates. That was prepared by previous astronomer Solano, which has like 300,000 objects on it, which are candidates. And then she filtered this down to about 100,000 objects. So this is a data set she calls V. So we have the original dataset S from Solano, and now this filtered dataset V, where she's applied some filtering to remove what she hopes are artifacts. So what kind of filtering

did she use? That seems important. It does seem important. And this is going to become an issue we dig into later. How she defines her filtering seems to change a little bit from paper to paper. There are a few of these papers out there now. And the number of transients in this data set changes. So there's a little bit of fuzziness there about exactly what she did and how she arrived to this data set. She has not shared the data set with anybody outside of her publishing group. So it's not like anybody else can take this data set and analyze it and understand it. She has not provided the code to reproduce the formation of the dataset. So you see later when another astronomer tries to reproduce these claims, can't use the original data set or even reproduce it,

which is a concern. Yes. So I would say not sharing the data set or the code is a pretty massive concern. Like, at least in my field, it's becoming standard that you're expected to share those things. But on the other hand, you know, every time you write a paper, you're supposed to write your methods in a slightly different way so you're not self-plagiarizing. So I can understand that like, you know, maybe it was more clear one time or another time. And I would say 109,000 is about 100,000.

And so I don't know. I'm not quite convinced on the merits of what has been written in the paper, but it is sketchy to me that the code and the data have not been shared. It's more than just fuzzy rewording from restating the same things in different papers. The dataset B that's at the heart of these claims is described as the original S dataset with some star catalogs removed. But if you do that, if you remove those stars, Waters calculates you should have 126,000 features. But dataset V has almost 108,000. That discrepancy is not explained.

And in one paper, it's supposed to have a certain catalog removed, and then later it's indicate that that wasn't removed. So it's not totally clear what was analyzed, which is pretty important. Yeah, it's a bit of a red flag. And the reasons given for not sharing the dataset directly seem to have shifted a little over time. Originally, it was that they didn't want conflicting versions out there, so they wanted to devise a way to make sure people were talking about the same dataset. But that's not actually a big obstacle. We know how to do that, you know, all sorts of checksums and things. Since you code, you can run in the dataset that are supposed to produce specific numbers, and then you can check

that it produces the right number. So it's the kind of thing where it really should have been shared, because these are explosive claims that they're making, and this goes to the heart of the issue of whether these are real or whether these are artifacts. So she has her dataset. It's got like 100,000 candidates in it that she analyzes. And a lot of these things appear in the old data sets, but do not correspond to any like known sky objects. All right. So 100,000 things that we saw previously and didn't see anymore is a lot. Is she claiming that no more filtering needs to be done? And these are all real transients? She's not claiming that. And the original paper, she's cautious. She's not saying these are all real transients. She's not saying these are all

in real transience. She's saying, is there a signal in here for something interesting among all of the artifacts? And so she's going to look for patterns among them that are going to make statistical, suggestive arguments that these might just be more than artifacts. Okay. Let's dig into that. What are the patterns? So one of the most interesting patterns is a claimed correlation with whether these things are in the earth shadow. If it's just an artifact of the plate, then it shouldn't matter whether the object looks like it was in the earth's shadow or not. But if it's a real object out in space that's like reflecting the sun's light, then you should see it when it's out of the shadow and not see it when it's in the shadow.

Okay. So this would help you tell if there's a real signal there. Like if it varies in the way you expect real signals to, but you don't expect noise to vary, then that's an argument that there is some real signal in there, even if you can't point to an individual one and say, this one's real and this one's an artifact. It's a cool statistical analysis. Yeah. So like if a piece of dust was on the telemed,

telescope lens. That should show up in all photos whether you're in the shadow or not. Yeah, exactly. Okay. And so the Earth's shadow is actually quite small out in geosynchronous orbit, because you have to have the Earth between you and the Sun to be in the Earth's shadow, right? That's what it means. And it's interesting. What they find is that there are fewer of these features in the shadow than out of the shadow. So somewhere between 40 to 75%, depending on what level of filtering and cleaning you apply, they see fewer of these glints in the earth's shadow than they do out of the earth's shadow. What does that mean? They see fewer glints in the shadow. So if, for example, you do have a bunch of dust and artifacts, you're going to see them in the

shadow and out of the shadow. But if some population of these things are like alien satellites put up there to observe us or whatever, then you're going to see them reflecting sunlight when they're not in the shadow and you're not going to see them when they're in the shadow. Okay. So this is an argument that there's two populations there. There is some noise, some artifacts, but there's also a population which varies in this interesting physical way that it doesn't shine when it's in the shadow. Okay.

And is she arguing, and I'm jumping ahead a little bit, but she arguing that these things are gone now and that's why we don't see them anymore? Because wouldn't you expect, like, if you keep doing this over time, you should keep seeing them in, like, predictable places if they're orbiting the earth? Yeah, so that's a great question, right? If these things are out there and they're in Earth's orbit, why can't we see them in other stuff? Why don't astronauts see them when they're out there? When can you see them from the space station, right? If we're talking about a population of satellites that are out there and obvious enough to appear as a statistical signal, not just one example, then they should be pretty easy to spot in other ways, right? And so she doesn't address this in her paper, right? That's sort of beyond the scope of this one paper. But you see lots of debate online about this, like, Maybe the aliens are hiding. And now that they know we can spot them with our telescopes, they're no longer being so obvious. You have to sort of add epicycles to your theory to explain it.

But that's not what Valer-Rail is claiming. And let's make a clear distinction between what's in the paper, the scientific claims of the paper, and the speculation online about how to explain it. Okay. But you're right. That's a big question. Like, if there really were alien satellites around Earth, wouldn't we see them in other ways? And the answer is yes. Okay.

All right. Okay, so she identified some stuff that's probably dust or schmutz or whatever, and then she identified some things that seem to be real transients. Yeah, exactly. Where do we go next? So she saw other patterns which were suggestive, like she saw linear clusters. It's not just like all these things are in random locations. She would see like a cluster of these glints, like in a line.

And that suggests like maybe there's a few of these things aligned with each other. Or maybe it's one thing which is rotating and has like, facets to it. And so the light is bouncing off each of the facets, right? So it makes it seem less likely to be just random if there's structure to them. But humans are really good at looking for patterns where they don't necessarily exist. And if you've got like 60,000 objects you could make patterns with, but was this like something statistical that was able to be identified, these linear clusters? Yeah. So she did some statistical test that suggests that these alignments are unlikely to occur by chance in a randomly distributed population.

Okay. And, you know, the statistical significance of these claims is strong. Like the shadow one varies between like three and 22 sigma. 22 sigma, you know, depending on which portions of the plates you're using. So, you know, this is not something that you can just brush off as maybe random. Okay. But maybe the most dramatic and fascinating connection is the connection to atmospheric nuclear testing. Oh, okay.

So I feel like where we're going to go here. is that this created more sort of anomalies in the photos. No. I've looked at your outline, so I know that's not where you're going. No, no. What they did is they looked at the pattern of transients through time, and they compared when did we see transients to when were Earthlings blowing up nuclear bombs in their atmosphere,

and they found a correlation. They found that you're more likely to see transients within one day of a nuclear test. Like after a nuclear test, the aliens... Or before. Before. Or before. Yes. Exactly.

But how did they, do they follow our news? Are they talking to the CIA? This is not a paper about aliens. Aliens in the CIA. This is a statistical analysis of patterns in the data. And, you know, whether it's aliens or not, again, Villarreal does not make that claim in the paper. Okay. But she's doing the statistical analysis.

But you're right, it's hard to put together a theory that would explain this like, you know, maybe aliens are interested in us when we're doing nuclear tests. And they also know in advance when we're going to do a nuclear test. They have foreknowledge or something. I don't quite understand it. So just to be clear, you get objects a day before the nuclear tests and a day after the nuclear test. And then if you look two days, for example, on either side, those objects are gone. Is that right?

Yeah. Okay. Yes, but I want to leave an asterisk here because there's real questions exactly about how this statistical analysis was done and how it's normalized. But in her paper, she finds you're 45% more likely to have a transient appear within plus or minus one day of a nuclear test. So it's minus 1, 0, and plus 1. You create a little three-day window around each nuclear test. And you're much more likely to find a transit within that window than outside of that window with like very strong significance. The P factor here is less than 1%.

Wow. Huh. All right. So I found myself wondering, did they, when we do these nuclear tests, are there certain conditions that we wait for before we do these nuclear tests that could impact how the photos are taken? Does that make sense? It does make sense. And I don't think the nuclear test themselves are like appearing on the photographs. I think you're looking for like a mechanism where they create something in the atmosphere, which can then be seen by these plates. There are, I think, other much simpler explanations from what's

going on here. But let's wait until we review the critique paper, which came out. Okay. All right. All right. So how solid are these claims? I want to emphasize that this is like a real paper. in a science journal that's gone through peer review. Okay, this is not just like somebody speculating on a podcast or writing a blog post. You know, this is the way science should be done. You do your science. You submit it to a journal. Reviewers ask hard questions.

It passes or it doesn't, right? So props to Villa Rao for like putting this through peer review. That's awesome. Yeah. That's one and a very important standard. As we talked about on our science process episode, though, a more important standard is replication. Can someone else reproduce your results? because things can get through peer review and be wrong, right?

Not because there's some, like, conspiracy going on, just because, like, peer reviews limited. They're not reproducing your results. They're reading your paper. They're asking questions about it. And so there have been other folks who are analyzing this data and trying to replicate it. And a few papers came out verifying these claims, reproducing these results. Oh.

Right. But the question is exactly, like, how independent these tests are. Right. Like, some of these people were given the data. set by Villa Rao, so they start from the same V data set. So it's not clear that these things really are independent. And in some cases, they're repeating some of the same statistical processes that we're going to end up critiquing in the next section. And so until this paper came out by Waters, fairly recently, there was no follow-up study that really began from scratch and said,

let's go all the way back and try to reproduce this thing, well, from the Solano datasets, WNR, at least. If it's a physical effect, you should be able to discover it independently. Right. Yes. And I guess I'm wondering, at some point, are we going to find out that the code is released so people can independently validate this or any attempts that independent validation had to do it without the code? Yeah. As of recording today, the data set has not been released nor the code. Okay.

All right. Well, let's take a break. And when we get back, we will talk about a published critique. Listen, and you're there for heart-wrenching knockouts. The world's biggest stage! And breathtaking triumph. 2026 FIFA World Cup. The knockout stage.

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That's a rookie move. Couples massages, monogrammed bath robes, and lingerie he then owed her for. So she spent four weeks gathering evidence and taped a 10-page letter inside his luggage before flew out. In his luggage, she came to play. And the second he landed, he blocked her. So she called the hotel room directly and got the mistress on the phone. Ooh, she got the mistress live on the phone. That is a bold move. Let's see if it pays off. Then it gets worse. He took the mistress on the Bahamas honeymoon trip he had planned with his wife. And then the mistress tagged him on Facebook, outing the fair to her entire family. That's like a whole public confession. And spoiler, two years later, karma hits him so hard. He's calling his ex-wife in tears saying about the mistress, what a mistake that was. To find out what happened, listen to the OK Storytime podcast on the IHart Radio app, Apple Podcasts, or wherever you get your podcast.

Hey, everyone, it's the Jonas Brothers. If you haven't heard, our new podcast is called Hey Jonas. And this week, we're hanging out with someone we're really big fans of. Millie Bobby Brown. That's right. Eleven herself. We talk about her new movie, Anola Holmes 3, Family Life, and all the amazing things she has going on right now.

This blew my mind when I saw this, Millie Bobby Brown. You have over 60 animals. First of all, how do you even keep track of everybody? And second, do you have favorites? Who are they and why? Yeah, I need to know about this. Okay. I don't know where the number's 60.

I really got to figure that out. And I could actually have over 60. I just need to really know that number. There have been plenty of sheep in my bed. It's a big bed. In the bed. Literally sleeping in the bed. Plus, we find out what she really feels about Stranger Things ending.

Five seasons, almost 10 years of your life. life. I could have never have guessed it. I started when I was 10 years old. Our conversation with Millie Bobby Brown is out now. Go check it out. Listen to Hey Jonas on the Iheart Radio app, Apple podcast, or wherever you get your podcast. All right. So we were talking about how we have a legit actual credentialed scientist who is perhaps identifying objects that could have been aliens. And you mentioned that there is a critique of this paper. So can you tell us about the person doing the critique? So the way science is done is by papers, right? Not by debates or shouting matches, whatever, you read a paper, you can disagree with it by, like, trying to

reproduce the results yourself and writing about it in another scientific paper. And so that's what we're seeing. There was a paper put out by West Waters. He's an associate professor at Wellesley College. He's a planetary scientist. He's trained at MIT. Also another, like, legit scientist out there in the community. He originally was a member of the analysis team with Villa Real, but apparently had some sort of intellectual disagreement with her about the data processing. and withdrew. So it was not an author on this original paper. He had access to the original V-Data set because he used to be on the team,

but he asked for permission to use it and was not granted permission. So he tried to reproduce the whole analysis chain himself without access to this V-Data set. He went back upstream to start from the dataset that they began from. Wow. Good for him, but that sounds complicated and surprising that you wouldn't let a prior collaborator use data that they helped work on. But okay. Yeah, exactly.

And Villa Rao's paper says the data will be shared, but they denied it when Waters requested it. So we had to make his own data set. He went back upstream to the original dataset. And the guy who made that data set also made a cleaned version of it, where he said, let's try to remove everything from here that we know is an artifact and that we know is something we see in the sky. So like map it to the existing sky charts and take away anything we know. Like, okay, that's Beetlejuice. Obviously, it's not a transient, right?

And so they did this sort of hard filtering against known objects and artifacts. And what Solano did to clean this up was pretty clever. So there are actually two independent digital scans of the original plates. One is called DSS and another one is called Super Cosmos. It was made a few years afterwards. Both are scans of the negatives of the same original plates, but on different equipment at different institutions and years apart. So Solano compared them.

If a candidate feature showed up in one scan but not in the other, then it almost certainly isn't a real thing in the sky emitting light. It's probably an artifact of the plate, like a piece of dust on one scanner or some debris that ended up on one copy of the negative. Anything real should be in both. That's what's in dataset R, the cleanest data set that we have. So to summarize, we have the large original dataset S, where Solano removed known stars.

The original Transience paper studies set V, which starts from set S but has a bunch of stuff removed that we know are real objects in the sky, like flaring red dwarfs or other faint infrared objects, but that dataset V is not publicly shared. The cleanest set is R, which removes all known objects and removes things that don't appear in both scans. So R is the cleanest dataset. So he filtered this down to a much more restrictive dataset, the R dataset, And this has only like 5,400 objects in it. So much smaller data set.

You removed a lot of stuff, but you hope it's much more pure, right? You hope that you've removed a lot of artifacts, a lot of stuff you know are not transients. But that's kind of interesting that he removed anything that we know is an error or we know already exists and ended up with a data set that's 1 20th as big as the one that was in the other paper. Yeah, that suggests that the V data set has lots and lots of artifacts in it, right? Yeah. And if you look at some of these things, they're just obviously artifacts. Like even the ones in the R data set, the supposedly clean data set, it's very hard to algorithmically remove all these artifacts.

And some of them, even if you look at them by eye, are obviously like a piece of dust. Like there's like a little string or something. And so in Waters paper, he shows a bunch of these. Like you can tell this is not a perfectly clean data set. Okay. And so what does he conclude from the data set that he got? So number one, he finds. really interesting patterns of where the transients are relative to the plates.

Oh. Right? And what he sees is that you find many more transients near the edges of the plates than you do near the center. Okay. Right. And if these things are astrophysical or out in space, then it shouldn't matter where on the plates they appear. And this is a clear sign of some instrumental issue, something where like the telescope is not as good near the edges, or the scanning is different, or the emulsion is lower quality or something.

Anything that has an image of your detector on it suggests it's a detector byproduct, not real physics, right? So this is issue number one. Okay, yep, that sounds like a real issue. Issue number two is that there are these weird geometric patterns like rectangular voids and oval clusters where you just see nothing on the plates, right? And so there's something that happened during the cleaning up that created these new artifacts, right? So this is, again, not something in the sky, it's something relative to the plates themselves. And you see these voids, even overlapping different plates. And so those are not regions where we didn't see transients.

Those are regions where, like, we're not seeing anything. And we don't exactly know why these voids appear. But all these make you wonder about the quality of the data, right? Okay, so if there's nothing showing up in these filter areas, then why are we detecting transient? So would this be saying we detected a transient in the second set of images that wasn't in the POS one? Here's the thing to understand about these shadow deficits that's claimed. The claim is that the transients are anti-correlated with the shadows, that they appear less often in the shadows. That's the strongest claim that these are actual blips of light and not like artifacts that would show up regardless of whether the region is sunlit, like uniform artifacts on the plates or from the scanning.

To test that claim, they ask, how likely is it to see this level of anti-correlation if the transients aren't actually correlated, if they are everywhere because they're just artifacts? Is this effect they're seeing this antacorrelation? Is it statistically significant? Or is it the kind of thing you might see from random chance? And that test, that calculation of statistical significance, assumes that they are everywhere. But they aren't. These artifacts or these transients, whatever we're seeing, these features, some plates have 2,000 features, others have almost none. There are large, unexplained voids where there's

just nothing. We don't understand why. There are features that cluster near the plate edges. Once you account for that real distribution, this Bayer Everywhere assumption, overstates how significant any deficit looks, because the variant, you'd actually expect from chance is much larger than the simple their everywhere model assumes. So basically the test is using the wrong statistical yardstick. And Waters reruns it on his cleaner data set, he doesn't have access to the V data set, but the cleaner data set where some of the artifacts have been filtered out, on that data set, the statistical significance vanishes. So what Waters does is he reproduces these statistical analyses, but now on the R data set,

which we hope is cleaner, but still has a bunch of artifacts in it. And when he does this shadow analysis, this deficit disappears, right? This huge discrepancy where you see these things in the sunlight, you don't see them in the shadow. There's still an effect there, but the effect is really, really small. It's just not very significant. Definitely fails any sort of test of statistical significance. But don't you only need one of them to be real for you to actually have aliens watching us? Like, does it matter?

Yeah, that's a great question. And remember that we can't trust any individual one because even like microscopic analysis of these plates, you can't tell if it's an artifact or not. So this whole argument is, yes, there's a bunch of artifacts in there, but there's statistical evidence of an excess. It's similar to how we like discover particles. You know, I can't say this collision is a Higgs boson, but I can say there's more collisions here than you would expect from non-Higgs bosons.

And they come in a particular pattern, which we expect from Higgs. So she's making a similar argument here where the first paper is that there's a pattern of these transients, which follows a physical model. And Waters says that actually in the cleaned up version, his paper argues that evidence disappears, which suggests that it wasn't real and physical. Okay. All right. So we're not looking for one alien that came to visit us. This is a sustained effort by the aliens to observe our behavior. Yeah, exactly. He also notices that a lot of these transients appear in specific plates. So it's not like they're scattered evenly through the plates. One of them has a huge number and another has a very small number. They tend to cluster in these plates.

And he argues that the deficit, not seeing them when they're in the shadows, could just be a product of these voids, these artifacts we think may be of the filtering. So we don't even know if that's real. Yikes. Okay. What about the argument that things are lining up? So Waters tries to dig into this in the paper also. And these clusters appear not in the R data set, in the very clean one, or in the V dataset, the unshared, partially cleaned one, they appear only in the uncleaned one, the S data set, the original dataset. And so a lot of these things are obviously artifacts. And so if you look at some of these, you can see, like, there are clear asymmetries in them.

They don't look like point sources. They're like irregular blobs. They're elongated smears. So visual inspection of these clusters shows that these are clearly artifacts. Why would you look for patterns in the unclean data? set at all? Yeah, great question, right? If they're real, they need to appear in the cleanest data sets.

And there's something of a deeper problem here. The way they identify these alignments as significant in the first place, the whole statistical test, that assumes that the features are scattered randomly across the sky. It asks, what are the odds that these would line up by chance if everything was random? But the water's analysis already shows that the features are not random. They pile up at the plate edges. They form these geometric voids. So once you know the background is not random, the whole calculation that's made about how these alignments look special, it falls apart.

It's the same flaw as the shadow test. You're measuring against a yardstick that assumes randomness when the data isn't random. So you don't even have to argue about the individual blobs, what are they really. The significance was never real to begin with because the assumption undernostic. underneath it was wrong. But maybe the most dramatic claim was this correlation with nuclear weapons tests, right? Yes. And so here, your earlier question was prescient, right? Like, what happens when we're not testing? The answer is that it's hard to tell because during the period that these observations were made, this survey of the sky, we were testing almost all the time. It was like

the height of nuclear testing. And so... Let's just pause for a moment and appreciate how great it is that we are not living in an arrow where we are setting off nuclear bombs in the heavens regularly. Yeah, exactly. Yeah, so there were 380 days when they were taking pictures of the sky with this survey. That was spread out over like eight different years, but there are only 380 days that they're taking pictures. So there were only about 312 relevant observation days across those eight years. And here's the thing. Transients show up on almost all of them over 90%.

So it's not that nuclear tests brought out transients. It's that transients appear on nearly every single night they observed. And there were enough nuclear tests in this era that a test window catches almost any night you pick. The overlap is basically automatic. The real question, again, is about the correlation between nuclear tests and observations, not between nuclear tests and transients. Got it. Okay.

That's less convincing. Yeah, exactly. So there are very few days when you're taking data away from a nuclear test, right? However, in the original paper, when they claim this strong correlation between nuclear testing and finding these transients, they normalized it using the whole range of the study campaign, which is like eight years. So that's like 2,700 days. And so this effectively counts not seeing a transient during a non-observation day into your analysis, right?

And so the right way to normalize this is to say, well, let's only consider days when we were observing, is there a correlation between observing transients when we were observing and nuclear testing and not observing transients when we were observing with nuclear testing? And the answer there is if you correctly normalize it, again, the statistical significance totally disappears. Okay. So there's still some correlation there, right? It's not zero, right? There is still a correlation between observing these transients and nuclear testing, right? Right? But it's, you know, the P value is like 0.1. It's like a 10% chance that it's random. So it's still a correlation, but it's not like a really, really strong one. Okay. Still a correlation, not a slam dunk. Maybe something's going on there, but who knows?

Yeah. And remember, the correlation is not causation. It could be that there's a reason that there's a correlation there. Like maybe you like to do nuclear tests when the sky is clear. And you also like to observe the sky when the sky is clear. So there could be some sort of upstream factor, which influences when we do a new. nuclear test and when we do observations. Yes, right. Okay, so the argument is becoming a little bit less strong. Does Villarreal respond? So Villa Raal's team wrote a response. They argue that, look, you use the wrong data set.

R is not the correct data set. But again, they haven't released their data set, right? Yeah. And so it's really on them to produce it. Yes. Agreed. And is that their, that's their only argument? is that you didn't start with the right data set?

So Villarreal in their response also argues that, you know, it's possible to make these discoveries statistically, that it's okay to have artifacts in your data. And I agree with that. You know, it's true that you can have noise or background in your data and still make statistically significant discoveries, but it's crucial that your statistics are solid, that you're understanding your background

and the way that it fluctuates and the way that it can mimic your signal. Well, and it's crucial that you understand the patterns in the data points that might not be real data. You know, so like when Waters is arguing that they're all on the outside part of the pictures, that seems important to me. Yeah, exactly. These detector effects are definitely important

and need to be accounted for. And we didn't get into all the arguments in water papers, but he makes that argument strongly that if there are detector effects here that affects the statistical analysis, you can't assume like these things should be uniform across the place, which changes how you're analyzing

this background hypothesis, exactly. Yeah. And so what's tempting is to say, like, well, let's go back to the original plates. Like, if we scan these things and got a bunch of dust, why can't we go back to the original plates? And, you know, these plates are fragile. They're like in a crate somewhere in the Palomar Observatory or there's like a copy of them somewhere in Edinburgh.

And so we can scan these again. In fact, there have been multiple scans of the various copies. And you can use that to reduce some dust. But these things are fragile. They're hard to access. Scanning them is complicated and expensive. And even if you do, it's not clear that you could get definitive answers from them. Because remember, these emulsions just have like internal defects which can mimic stars even upon microscopic analysis.

Like you put it under a microscope, you look at it, you try to understand, is it a star or is it not? You still can't tell even when you're looking at the original plate under a microscope. And so some astronomers I spoke to said, look, this whole road is a dead end. The lesson from the gamma ray burst campaign was we're not going to learn something from these plates. you need a dedicated instrument. So they launch a satellite to do that job. So what we need here is like a bunch of telescopes looking at the sky and triangulating it. So if they see a glint, do we also see it over here?

Can we track this thing through the sky? It's not something I think we can resolve from archival plate analysis. We need new dedicated telescopes. And that's a bummer because the sky is now messy. Not only do we have to deal with artifacts in the data, we have to deal with the fact that there are thousands and thousands of human satellites out there glinting. So pre-Sputnik was a really nice time to look for potential alien satellites because

there weren't any of ours, but, you know, those days are gone. So was this like an absolute emotional roller coaster for you? Like you read the first paper and you were like, they care! Not only are they watching us, but they care. And then you were like, oh, well, maybe not. And yeah, what was this like? Well, when I read the first paper, I was like, wow, this is fascinating. But I also said, hmm, I'm really not an expert in how these plane analyses

work and the potential ways this can go wrong, which somebody out there in the field who is an expert would write a commentary. And so I always like to see these kind of disagreements in the scientific journals, you know, write your analysis and then somebody else comes and says, you consider this, what about this, or I didn't reproduce that and uses their expertise. So thanks to Waters for commenting, I don't know who's right, Villa Real or Waters, you know, but I appreciate that there's a conversation and that it's playing out in the journals and not just in debate clubs or blog posts. And I totally agree. But I think what's kind of frustrating is that we probably won't know who's right when this is all said and done.

Because the data will be too messy. There won't be a definitive answer when it's all said and done. And so we're just going to have to keep looking for aliens in other ways, Daniel. Don't give up. I haven't given up, exactly. But, you know, if we don't have solid evidence that we can rely on, then, you know, we can't say there aren't aliens or that there weren't alien satellites observing our nuclear testing or whatever. But we can't say that there were. All right. Well, thank you for walking us through the pros and the cons of the dataset.

It was an emotional roller coaster for me as well. And like so many other episodes of DKEU, the answer is, uh, but stay curious. That's right. Until next time, Extraordinaries. Thanks everybody for listening. Please go and do us a favor and rate the show on whatever podcast app you're using. It really helps people find us. Daniel and Kelly's Extraordinary Universe is edited by the. amazing Matt Kesselman. He really is a wizard. You can also find us online on Blue Sky, Instagram, and X, D&K Universe. Come engage with us. You can email us at Questions at Danielandkelly.org. We really do

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