Cloud9 Dark Matter Halo, Jellyfish Sleep, and String Theory Hidden in Nature (EP. 22)

Hosted by Lester Nare and Krishna Choudhary, this episode runs from the deep math of string theory to the biology of sleep—then out to a starless “ghost cloud” that may be a naked dark-matter halo. We open with a Nature paper showing that physical networks in nature (brains, blood vessels, fungal networks) appear to organize like energy-minimizing surfaces—spitting out the same branching rules you see in soap films and (surprisingly) in the mathematics behind string theory. Then we hit a neuroscience twist: even simple jellyfish need sleep—and the evidence points to sleep as a repair cycle for DNA damage. We close with Cloud9, a newly characterized, starless gas cloud that could be a rare “reionization-limited” RELHIC—potentially exposing a dark matter halo without the glare of stars. Summary String theory… in your body? Why real-world transport networks converge toward minimal-energy geometry—and what that has to do with string-theory math and 120° branching angles. Jellyfish need sleep (and it’s not optional): Evidence that sleep pressure tracks cellular stress and DNA damage repair—even in a brainless animal. Cloud9: A nearby starless cloud that may be a dark matter halo in plain sight—plus what it implies about “missing” galaxies and the post-reionization universe. The Rundown: iron asteroids, artificial metabolism (ReForm), scalable helper T-cells from stem cells, and NASA’s Pandora exoplanet mission. Show Notes Physical networks / string-theory-like math (Nature) Jellyfish sleep & DNA repair (Nature Communications) Cloud9 (Astrophysical Journal Letters)

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Lester Nare?

  Hello, Internet. This is your captain speaking, Lester Nare, joined as always by my co-host and our resident PhD, Krishna Choudhary. This is episode 22. We have a fantastic three-story episode set up, plus the rundown today. We're going to touch on string theory, biological networks, three-dimensional geometry. We have a neuroscience and sleep story, and as always, we can't forget astronomy with an interesting star formation topic. My friend.

• 0:33Krishna Choudhary?

  How's it going?

• 0:35Lester Nare?

  It's going well. It's going well. We're in January. It's 2026.

• 0:38Krishna Choudhary?

  Yes.

• 0:38Lester Nare?

  It's 80 degrees outside.

• 0:39Krishna Choudhary?

  It's pretty nice.

• 0:40Lester Nare?

  Pretty nice. There was no snow in Big Bear.

• 0:43Krishna Choudhary?

  Oh, yeah.

• 0:44Lester Nare?

  This past weekend. That was a little bit unfortunate.

• 0:46Krishna Choudhary?

  Yeah, that's kind of surprising, given like how much precipitation we've had in Southern California, so.

• 0:51Lester Nare?

  Exactly. I was like, oh, it's gonna be snow. It was all in the desert.

• 0:55Krishna Choudhary?

  Yeah.

• 0:55Lester Nare?

  A couple of housekeeping notes for this episode. If you didn't catch it on social, our new website, ffpod.com, is now available. It's great. You can get all of our past episodes. You can also see and search through all of the research papers that we cover in each episode. We have a whole variety of details, key takeaways, links out to the original paper. And we also have introduced our new submissions board.

• 1:23Krishna Choudhary?

  Yeah.

• 1:24Lester Nare?

  So many of you have commented about, hey, can you cover this paper? Can you cover that paper? So you can go to ffpod.com backslash submissions. You'll see a ranking leaderboard of the most popular papers. You can upvote the papers you want us to cover. You can submit your own. We're trying to engage the community here, so we're super excited about that. You haven't taken a look, take a look, because we will have more coming to the site soon. I don't know, maybe a leaderboard or something?

• 1:50Krishna Choudhary?

  Yeah, something like that.

• 1:52Lester Nare?

  So I think what's so fascinating about the two-way street of like the social media era.

• 2:01Krishna Choudhary?

  Right.

• 2:01Lester Nare?

  Is like, the response to our stuff is real time.

• 2:04Krishna Choudhary?

  Yeah.

• 2:04Lester Nare?

  Right? So, you know, immediately the day an episode comes out, we're getting people like, this is fantastic. Like, the econophysics feedback from the last episode was fascinating.

• 2:14Krishna Choudhary?

  Yeah, yeah, yeah. There were a lot of people who I think are probably in finance that had technical degrees that are watching. And hey, welcome, welcome.

• 2:24Lester Nare?

  We're gonna learn something today. We have some fantastic stories. And as always, this is from First Principles.

• 2:46Lester Nare?

  Okay, so for our first story, we are going to go into the world of string theory in a paper out in Nature, published on January 6th. Paper is about nature's hidden blueprint, how physical networks follow string theory mathematics. Scientists have discovered that biological networks, from brains to blood vessels, violate simple wiring rules and instead follow complex surface minimization patterns predicted by string theory.

• 3:19Krishna Choudhary?

  Yeah.

• 3:19Lester Nare?

  Really good at predictions. This one's out of Rensselaer Polytechnic, Northwestern, the University of Chicago, and Northeastern, so a nice Marvel compilation.

• 3:29Krishna Choudhary?

  Yeah.

• 3:31Lester Nare?

  And the idea is that they can now reveal how surface optimizations shape the architecture of physical networks, impacting both the brain and our vascular system. This is fascinating.

• 3:46Krishna Choudhary?

  It's really cool, because it's not just the brain and vasculature, it's all over biology. If you look at mycelia and fungal networks, this has something to say about that. If you look at how trees branch out into patterns, this has something to say about that. And we've been trying to figure out the mathematics behind how these physical networks branch out. And the unlikely savior came in the form of string theory. And it's really wild, because it's all over the news, because string theory has kind of a bad rap, given that it doesn't predict anything, at least in terms of the fundamental physics that it promised to predict. But it's kind of cool that this mathematical physics

• 4:31Krishna Choudhary?

  approach is now being used for biological problems. And one of the reasons why I really loved this story is... You know, I'm a biophysicist by training and there's so many examples of the mathematics of physics being used for something totally different being applied to biology. You know, if you look at hot field networks and associative memory in the brain, that uses the mathematics of Ising models that was being developed to describe magnetization. Or if you look at the renormalization group, which is being used for phase transitions or deep quantum field theory, that's being used to describe the starling flocks and how

• 5:15Krishna Choudhary?

  they do murmurations in the sky. So it's one of these really cool examples of how mathematical physics research for something totally different can be applied to biology. And we're just discovering how life is so clever, you know?

• 5:32Lester Nare?

  And this sort of translational nature of the frameworks of physics being applied in other spaces.

• 5:39Krishna Choudhary?

  Yeah, yeah, yeah. And I think that's just really cool. There's a neat line between the mathematics when we go really deep down, you know? I think that's really cool. So the core subject has to do with networks, okay? Networks are basically things and then those things have relationships. And usually when we talk about networks, what we use is graph theory, okay? One of the famous networks that we all use every day is the internet, right? There's links from one page to another page, that's the relationship. And the things, the nodes of these networks are webpages. And the very famous PageRank algorithm that was developed by Larry Page out of a Stanford

• 6:24Krishna Choudhary?

  PhD thesis that became the bedrock of Google, a trillion dollar company now, realized that what they could do is use the mathematics of graph theory to understand relationships on the internet and then rank pages based on their connectivity rather than, you know, some naive approach that, if you remember Ask Jeeves, you know, we're old enough to remember Ask Jeeves.

• 6:49Lester Nare?

  We are, we are old enough.

• 6:50Krishna Choudhary?

  Or like the Yahoo search. They weren't as good because they weren't realizing this underlying graph structure. Google was good because it was ranking pages. With the attitude that the graph structure of the internet is what's important.

• 7:04Lester Nare?

  And this ended up being confirmed to be true, not only by the fact that arguably the best business model ever invented in humanity with the best margins.

• 7:14Krishna Choudhary?

  Yeah.

• 7:15Lester Nare?

  Is Google. And that same concept then ultimately got applied to social graphs.

• 7:21Krishna Choudhary?

  Yeah.

• 7:21Lester Nare?

  In the rise of social media, Zuckerberg being the first to apply the same concept.

• 7:26Krishna Choudhary?

  Yeah.

• 7:27Lester Nare?

  But in the context of social networking, which then became social media.

• 7:30Krishna Choudhary?

  Yes, exactly. And all of these things, at the end of the day, they're graphs, they're vertices. In the case of social networks, there would be individual profiles. And then a connection would be like a friendship.

• 7:40Lester Nare?

  Yes.

• 7:40Krishna Choudhary?

  Between the two, right? Now, when it comes to physical networks, physical networks are embedded in 3D space. I'm talking about the brain, which has neurons connecting from one to another. But this isn't isn't some abstract link. There's a little physical connection of a synapse between a neuron A connecting to a neuron B. Right? If you look at vasculature, that's blood vessels that are physically connecting. And all of these physical networks are constrained by 3D geometry.

• 8:09Lester Nare?

  Right.

• 8:09Krishna Choudhary?

  They're constrained by thickness. How much room do I have to move in the brain, in the body? And it's not just these like 1D abstract links. So Ramon Kahl in 1899, he's one of the pioneers of neuroscience. He's the first guy to establish the neuron doctrine, which is the idea that the nervous system is made out of tiny individual cells called neurons that connect to each other. And it's not just one giant network. And he proposed a neuron morphology that's driven by minimizing wire volume. These are some

• 8:42Krishna Choudhary?

  great drawings that he drew. He was an artist, and he could literally trace out using these incredible techniques where he would stain individual neurons, and he could trace out how these neurons connected to one another. And you could recreate things like the hippocampus, things like the optic nerve.

• 8:58Lester Nare?

  That's incredible.

• 8:59Krishna Choudhary?

  And a lot of what he found even back then is true today. Like he in the hippocampus, for example, he figured out that there's this cell layer called CA1, and it gets input from the dentate, which is another part of the hippocampus, and another part of the hippocampus called CA3, and so on and so forth. It's a he was an incredible scientist. And he proposed that the way that these biological networks figure out where to go, and what connections to make. Is by minimizing wire volume, which basically turns into what's the minimum distance between two points? Like if I want to connect this point and this point, I just want to figure out what the minimum distance is.

• 9:38Lester Nare?

  So you're saying the shortest distance between two points is a straight line?

• 9:41Krishna Choudhary?

  Yes, and that's exactly what what he figured out that biology would at some point figure out like evolution would optimize for this, right? Um, he wasn't the only one in 1926. There was Murray who established Murray's law, which governs vascular branching in the blood. And he figured out that, you know, you can minimize work that the body has to do by doing this minimum distance kind of thing, right? Where using that heuristic, what you can do is say, with this network architecture, the blood can maintain the blood volume. But at the same time, it does the least amount of work to get over the friction of pushing fluid through my blood vasculature.

• 10:24Lester Nare?

  It's it's sort of like an optimism, a biological optimization.

• 10:26Krishna Choudhary?

  Yes, exactly. And he's like, he's like the the simplest optimization of finding the shortest link between two nodes. That actually works. Okay, so it was an old paradigm. And in graph theory, this is effectively what's called the Steiner tree problem. Okay, if you've got a graph of points in Euclidean space, these are the blue points in this photo, then if I want to connect them with edges such that the sum of all the edges is smallest. So it's the it's the most optimized graph that minimizes the distance between all these edges, then what I can do is introduce little points called Steiner points in between

• 11:10Krishna Choudhary?

  the vertices that I want to attach. Okay. And there's a certain rule that all of these Steiner points follow. Okay, if I basically, if I want to have an algorithm that makes a graph. Such that all of the edges are least distance, okay? Then there's two things that we notice, okay? First is that all branching points have only three nodes. They're called bifurcations, meaning one path is going to lead out to two. There's never one path leading out to three. Because one path leading out to three, you could actually decompose that into one path leading out to two, and then this branch leads out to two.

• 11:48Lester Nare?

  It's it's suboptimal to have three.

• 11:50Krishna Choudhary?

  Coming out of.

• 11:51Lester Nare?

  Out of a single node.

• 11:52Krishna Choudhary?

  Yeah, a fork is always two.

• 11:54Lester Nare?

  It's right.

• 11:55Krishna Choudhary?

  A fork in the road is always two. There's never three paths out of a out of out of an input. Okay, so that's the first thing that's just a mathematical truth. If you want to solve the Steiner tree problem.

• 12:06Lester Nare?

  Okay.

• 12:06Krishna Choudhary?

  Okay, the second point is all of these intersections happen at 120 degrees. Okay.

• 12:14Lester Nare?

  Oh.

• 12:14Krishna Choudhary?

  And that kind of makes sense, because if you've got three paths coming out, a circle is 360 degrees. 360 divided by three is 120, right?

• 12:22Lester Nare?

  Got you.

• 12:23Krishna Choudhary?

  So that it all like kind of makes sense.

• 12:25Lester Nare?

  Okay.

• 12:26Krishna Choudhary?

  The problem is, if you look at empirical data from biology, this is not true. Okay.

• 12:32Lester Nare?

  Okay.

• 12:32Krishna Choudhary?

  In recent times, we've done incredible work mapping out the 3D morphology of biological networks. This right here is a neuron from the Human Connectome Project. They've mapped out a human neuron, and what you can see is violations of that Steiner tree.

• 12:48Lester Nare?

  Yes.

• 12:48Krishna Choudhary?

  You've got trifurcations, so a single path leading out to three. And you've also got these orthogonal connections where the angle is not 120, but 90 degrees.

• 12:58Lester Nare?

  So it is structurally, it appears to be suboptimal.

• 13:02Krishna Choudhary?

  Yeah.

• 13:03Lester Nare?

  From an efficiency perspective.

• 13:04Krishna Choudhary?

  Yes, and if you were to actually calculate the minimum Steiner tree, and then add up the lengths of all of these guys, the length, the total length is about 25% more. Then what the minimum would be.

• 13:18Lester Nare?

  So it's requiring more surface area to have the output that equivalent to the optimal version.

• 13:25Krishna Choudhary?

  Yeah, yeah. Well, you're jumping the gun here a little bit because it's requiring more length.

• 13:31Lester Nare?

  Okay.

• 13:31Krishna Choudhary?

  Right?

• 13:32Lester Nare?

  I

• 13:32Krishna Choudhary?

  Like, the length is what is what is what is not optimal.

• 13:36Lester Nare?

  I understand.

• 13:37Krishna Choudhary?

  You see what I'm saying?

• 13:38Lester Nare?

  We're separating different degrees of measurement.

• 13:40Krishna Choudhary?

  Yeah.

• 13:41Lester Nare?

  They have different implications.

• 13:42Krishna Choudhary?

  Exactly. And and the older paradigm was that I want to minimize length. But you got there by saying, well, what if I want to minimize surface area instead? Now, let's think about it. Why would I want to minimize surface area? If I'm a living being, why would I want to minimize surface area rather than length? Well, the reason is surface area is the actual thing that requires material. You know, I need a cell membrane. And that cell membrane is the thing that I want the least of. Doesn't really matter what the length is.

• 14:14Lester Nare?

  Right.

• 14:14Krishna Choudhary?

  Right? Because if I can, if I can minimize surface area but have a longer length, maybe that's fine because I'm using less material. Okay? And that is the insight of this new paper.

• 14:26Lester Nare?

  Interesting.

• 14:26Krishna Choudhary?

  Okay, the new papers introduces the fact that maybe if we minimize surface area,

• 14:33Krishna Choudhary?

  then we can replicate biological networks. And what's really cool is they introduce an exact mathematical mapping between this local network design of minimizing surface area and the high dimensional Feynman diagrams that we see in string theory. Okay?

• 14:49Lester Nare?

  Yes.

• 14:49Krishna Choudhary?

  That's the key insight.

• 14:50Lester Nare?

  Okay.

• 14:50Krishna Choudhary?

  The key insight is string theorists have been worried about this problem for like 30 years. And if we can just borrow all their mathematics.

• 14:58Lester Nare?

  And apply it.

• 14:59Krishna Choudhary?

  Here.

• 15:00Lester Nare?

  Instead of in an abstract space, in a, in a measurable space.

• 15:04Krishna Choudhary?

  Then, then all of a sudden, we've got a heuristic, a mathematical heuristic that solves for why biology is doing this.

• 15:11Lester Nare?

  It's, it's a language to interpret the observations of biology where we don't necessarily have a coherent, cohesive, like.

• 15:19Lester Nare?

  Language to describe it mathematically.

• 15:20Krishna Choudhary?

  Yeah.

• 15:21Lester Nare?

  Currently.

• 15:21Krishna Choudhary?

  Yeah, currently, but now maybe we do.

• 15:23Lester Nare?

  Okay.

• 15:23Krishna Choudhary?

  Right? That's the idea.

• 15:25Lester Nare?

  Yes.

• 15:25Krishna Choudhary?

  So let's think about this a little bit more in detail. Okay, biological networks are 3D manifolds, right? There are these 2D structures embedded in 3D. So you've got tubes bounded by membranes, bounded by endothelium, things like that. And what we want to do, the optimization, is to find the minimal surface. This is what's called a plateau problem. And physical structures do this all the time. Here you see a bubble in between two rings. That bubble naturally is going to minimize the surface area of the bubble because of surface tension.

• 15:58Lester Nare?

  So we sort of see this concave-esque. Uh, because a bubble, when you said bubble, it's.

• 16:05Krishna Choudhary?

  It's a spherical thing, but imagine now two rings, like the bubble generators, right? And they're right next to each other. You get this sort of concave surface.

• 16:13Lester Nare?

  Yeah.

• 16:14Krishna Choudhary?

  Right?

• 16:14Lester Nare?

  Because it's trying to minimize.

• 16:15Krishna Choudhary?

  Yeah, the surface area.

• 16:17Lester Nare?

  And this is a natural example.

• 16:19Krishna Choudhary?

  Yeah, yeah, yeah. I mean, the reason why a bubble is spherical is because a sphere minimizes surface area. Right? So the same mathematics maybe we can use for this, right? And the other constraint is that the surface curvature has to be continuous. So you can't have like kinks, you can't have like singularities, like little points, like, you know? You want a smooth surface everywhere.

• 16:39Lester Nare?

  You want a nice, smooth bald head.

• 16:41Krishna Choudhary?

  Yeah, yeah, yeah, yeah, yeah. And so with that in mind, let's now do a little bit of string theory.

• 16:49Lester Nare?

  Okay.

• 16:49Krishna Choudhary?

  A deep dive into string theory.

• 16:50Lester Nare?

  Okay.

• 16:50Krishna Choudhary?

  Okay? The infamous physics theory that is supposed to solve everything. Okay?

• 16:56Lester Nare?

  Yes. And just to briefly, before we dive in.

• 16:59Krishna Choudhary?

  Yeah.

• 16:59Lester Nare?

  Is the, is the, is this the idea that it's meant to be a theory of everything? Or unifying classical and quantum? Or, or no, that's like a different concept?

• 17:10Krishna Choudhary?

  No, no, no, no, this is the same theory and it's, it's unifying general relativity and quantum.

• 17:15Lester Nare?

  I'm sorry, okay, yeah.

• 17:16Krishna Choudhary?

  Yeah, yeah, but it is, that is exactly what we're talking about. This is the thing of Ed Witten fame. And who's that guy who goes on Joe Rogan and talks trash all the time?

• 17:27Lester Nare?

  I know.

• 17:28Krishna Choudhary?

  Weinstein.

• 17:29Lester Nare?

  Yeah.

• 17:29Krishna Choudhary?

  Eric Weinstein.

• 17:30Lester Nare?

  Yeah.

• 17:30Krishna Choudhary?

  I believe his name is.

• 17:31Lester Nare?

  The geometric unity.

• 17:32Krishna Choudhary?

  Geometric unity. So, so string theory is purporting to do the following, which is unify quantum mechanics.

• 17:37Lester Nare?

  Yes.

• 17:38Krishna Choudhary?

  With general relativity, right?

• 17:39Lester Nare?

  Copy.

• 17:39Krishna Choudhary?

  And in quantum mechanics, the, the best picture that my favorite picture is Feynman's picture, which has to do with the particle picture, but the field picture of quantum mechanics. Okay? The way we understand the interaction between particles in quantum mechanics is that they exchange virtual particles. So here, what we see is an electron that's being deflected by an electron, you know, electrons repel each other.

• 18:03Lester Nare?

  Like.

• 18:03Krishna Choudhary?

  That's the classical picture, right? It electrons have negative charge, so they don't like to be next to each other. In the quantum picture, the reason why they don't want to be like next to each other, and the reason why they get deflected in opposite directions is because they're exchanging a virtual photon.

• 18:17Lester Nare?

  Okay.

• 18:18Krishna Choudhary?

  And that's what you're seeing in that Feynman diagram. An electron is coming from the left, an electron is coming from the right, and they're exchanging a virtual photon, and that's how the momentum gets transferred from one to another.

• 18:29Lester Nare?

  Copy.

• 18:29Krishna Choudhary?

  Okay, so that's the Feynman picture, right? In string theory, there's no longer anything called particles. Instead, all of our fundamental particles, all of our fundamental fields are made out of one dimensional strings. So you can imagine a rubber band that's one dimensional. It's a line, and that line oscillates in multiple dimensions. Okay, just like a guitar string can oscillate, you know, this way or into the guitar and out of the guitar. So that's two dimensions that it's oscillating. A string can oscillate in multiple dimensions, sometimes 10, sometimes 12, depending on what theory is your favorite. Okay?

• 19:02Lester Nare?

  And, and the idea here is that in this diagram, we see, starting from matter all the way at the top, as you break down to smaller scales, molecule, atom, neutron, strings are smaller.

• 19:14Krishna Choudhary?

  Than that.

• 19:14Lester Nare?

  Are, are the, are the most, are, are in this theory are the most fundamental atomic unit of physical.

• 19:21Krishna Choudhary?

  Exactly.

• 19:22Lester Nare?

  Reality.

• 19:22Krishna Choudhary?

  And they're the same, the, the beauty of string theory is that it's all just one string, but the way that it oscillates in all these different dimensions, make it an electron or a photon or a up quark or a down quark, things like that. So it's this nice, like, unified. Side principle, right? That actually, there's no such thing as all these different fields and all these different particles. There's only one fundamental thing, and that is the one dimensional string. And the way that it moves around in these 10 dimensions gives it the properties of an electron or up quark or a down quark and all these things. So it's a nice like mathematical unified picture.

• 19:56Lester Nare?

  That's interesting.

• 19:57Krishna Choudhary?

  It just hasn't found any like real world physics use cases. Because in order to prove whether these strings exist, you need to go down to the fundamental scale, like the Planck scale of really tiny length, really tiny time. The energy is massive, 10 to the 19 gig electron volts, which, you know, the LHC only has 10 to the 4 gig electron volts. So we're trying to do 10 to the 15 on top of what the LHC at CERN is doing.

• 20:25Lester Nare?

  The Large Hadron Collider, for those who might not know.

• 20:28Krishna Choudhary?

  That's right. Yeah. The LHC is the Large Hadron Collider. So we need a, we need a LHC the size of the galaxy in order to probe these limits.

• 20:36Lester Nare?

  And so the, the, the point being like, this is very largely theoretical, because as of yet, there's been no way to experimentally play with these theories.

• 20:47Krishna Choudhary?

  Exactly. Yeah, exactly. And it's been a really cool mathematics exercise on its own. If you were to just look at the mathematics, it's amazing. It's won fields medals. Ed Witten won the fields medal for his work in string theory. He's never going to win the Physics Nobel Prize.

• 21:03Lester Nare?

  Right.

• 21:03Krishna Choudhary?

  Okay. Because to win the Physics Nobel Prize, there has to be some experimental grounding for whatever thing you do. But the fields medal is pretty nice. So, you know, I don't think he's like too worried about it.

• 21:14Lester Nare?

  He didn't win the Oscar, but he got the Golden Globe. Oh, no.

• 21:17Krishna Choudhary?

  Yeah, yeah. Yeah, exactly. Even though, I mean, well, I think you're gonna piss off some mathematicians in the audience.

• 21:25Lester Nare?

  Bad analogy, bad, bad analogy. Do not come in my comments. Maybe like something closer is like he won finals MVP, but not league MVP.

• 21:35Krishna Choudhary?

  Yeah, yeah.

• 21:36Lester Nare?

  That's maybe a better.

• 21:37Krishna Choudhary?

  Yeah, yeah.

• 21:38Lester Nare?

  No one, please stay out of my comments.

• 21:41Krishna Choudhary?

  Yeah, but um, so in string theory, you know, we had that original Feynman diagram, which was looking at the interaction between particles. So in string theories, what you can do is you can turn a Feynman diagram into something called a world sheet. Okay, so on the left, we have that same Feynman diagram. And on the right, you have strings that are merging together, and they're interacting in this world sheet, which is like how they're going through spacetime and all these dimensions. And then they come out. And that is the key here. The world sheet. That world sheet is the key here, because it turns out that that smooth merging of those 2D world sheets, those 2D string world sheets, because when they merge,

• 22:24Krishna Choudhary?

  they have to obey smoothness. There can't be any kinks in this world sheet, because that's unphysical. And they also have to minimize the surface area in this world sheet, in this, in this, you know, space, whatever they're moving in. And that is topologically identical to the smooth merging of biological tubes in 3D space. Yes. That's the key insight. Okay, yes. Okay? Yes. Yes. That is the key insight. Yes. And the equivalence is pretty stark. They they lay it out in their paper. You know, on the right hand side, they've got that Feynman diagram and the world sheet. Yes. And on the left, what they're showing is if you've got these physical networks,

• 23:06Krishna Choudhary?

  they're going to start obeying the same physics of those world sheets. Yeah, yeah, yeah. Right? That's the, that's the key thing. The string cross section is now our biological tube cross section. The time evolution for strings, like how I go from past to future, for us, it's just, oh, I'm just like moving along the tube. Yeah, yeah, yeah. Okay, so it's another spatial dimension. My 2D world sheet is my biological membrane now. And the the tension, the string tension, which is something that is used in string theory to figure out like, you know, how tense sort of the strings are in a loose sense, that becomes the metabolic cost of surface area. Yes.

• 23:43Lester Nare?

  Oh, that's so, that's really, okay, I, I, I'm tracking because I, I think what's, what's, what's fascinating is we've basically, there's been a mathematical structure that has been very, millions and millions of dollars has been spent on

• 23:58Krishna Choudhary?

  Yes.

• 23:58Lester Nare?

  in string theory to really hone in on this mathematical framework and language to communicate a conceptual idea.

• 24:05Krishna Choudhary?

  Yes.

• 24:06Lester Nare?

  That when we look at these physical manifolds in like biology, that math that we've spent millions of dollars on almost as a perfect, and you can see from these images, almost a perfect map

• 24:16Krishna Choudhary?

  Yeah.

• 24:16Lester Nare?

  to our observed biological structures that effectively take the same shape.

• 24:22Krishna Choudhary?

  Exactly.

• 24:22Lester Nare?

  And potentially respond to a similar math framework.

• 24:24Krishna Choudhary?

  Exactly, exactly. That's the idea. And what they're doing is they're, they're trying to basically do the math of string theory, which is this Nambo-Goto action. It's an action that measures the area of the world sheet, which is the total cost, right? And the equation is insane. I think I've got a little photo of it. The, the equation is it's, it's minimizing this integral over all of your possibilities, right? And it's making sure, this mathematics is making sure that your stuff is smooth. And it's making sure that if you minimize this giant integral, that the surface area of this whole thing is going to be minimal.

• 25:03Lester Nare?

  It's going to be minimal.

• 25:04Krishna Choudhary?

  The point is, this math looks insane.

• 25:06Lester Nare?

  Looks like man.

• 25:07Krishna Choudhary?

  But we've worked on it.

• 25:09Lester Nare?

  Yeah, yeah, yeah.

• 25:10Krishna Choudhary?

  Because all of these physicists have been working on string theory.

• 25:13Lester Nare?

  Yes.

• 25:13Krishna Choudhary?

  So we've worked on it. So we don't need to start from scratch. We can just take all of these results

• 25:18Lester Nare?

  Yes.

• 25:18Krishna Choudhary?

  and apply it here.

• 25:19Lester Nare?

  Yes.

• 25:19Krishna Choudhary?

  Right? And it bakes in the smooth, it, it bakes in the smoothness. And all of these mathematical toolkits, toolkits that have been developed can now just be applied directly to the biological problem.

• 25:32Lester Nare?

  So the, the point being the biologists don't have to spend years sort of wading through the dark of discovery

• 25:39Krishna Choudhary?

  Yeah.

• 25:39Lester Nare?

  around, you know, finding the four corners of the sandbox on the mathematics. It's a Lego block that already exists. They can just be like, oh, here are these glasses. Let's look at it over here. Oh my God, I can see.

• 25:49Krishna Choudhary?

  Yeah, yeah, yeah. It's pretty cool. It's pretty cool. So now let's see how it actually works with biology.

• 25:56Lester Nare?

  Yes.

• 25:56Krishna Choudhary?

  Okay, so.

• 25:59Krishna Choudhary?

  Let's first tackle the bifurcation versus trifurcation, which is the idea of a single path going to two, according to the old paradigm of Steiner trees. But now, what we see is single paths going to three. Why would the new paradigm, now that we've borrowed this math from string theory, allow trifurcations? And make that totally chill?

• 26:19Lester Nare?

  Yes.

• 26:20Krishna Choudhary?

  Okay? The reason for that is because the surface area is what matters.

• 26:26Lester Nare?

  Right.

• 26:26Krishna Choudhary?

  Not the length.

• 26:27Lester Nare?

  Not the length.

• 26:27Krishna Choudhary?

  Right? So, the wiring economy of minimum length only matters if your width of the world sheet is really small. And basically, if the thickness of your world sheet, the string, like the radius of your string is really small, then it becomes a line.

• 26:46Lester Nare?

  Yes.

• 26:46Krishna Choudhary?

  And then you only have bifurcations.

• 26:49Lester Nare?

  There's not enough complexity to need bifurcations.

• 26:52Krishna Choudhary?

  Right. But the thicker we make the biological network, the more we might need trifurcations. And that's what you see in this paper. That's what they figured out. As we go from thinner manifolds to thicker manifolds, at some point, the two forks in the road merge to become these three forks in the road.

• 27:18Lester Nare?

  Because as you get thicker, your surface area is increasing

• 27:23Krishna Choudhary?

  Yeah.

• 27:23Lester Nare?

  over every length of distance.

• 27:25Krishna Choudhary?

  Yeah.

• 27:25Lester Nare?

  And so subsequently, it's becoming inefficient, even if you're at the same distance.

• 27:30Krishna Choudhary?

  Yes, exactly. And they actually introduced an order parameter. They call it chi. And that controls whether you're gonna go for two or three.

• 27:37Lester Nare?

  Okay.

• 27:37Krishna Choudhary?

  Okay? If it's really thick compared to the separation distance, that's the thing that matters.

• 27:43Lester Nare?

  Ah, yeah.

• 27:43Krishna Choudhary?

  You see?

• 27:44Lester Nare?

  Yeah, that makes sense.

• 27:44Krishna Choudhary?

  If it's like, if it's really far away, then I could do these Steiner tree approximations. But if my branching is really close compared to my thickness, then I'm gonna need to... Do these

• 27:54Lester Nare?

  Yes.

• 27:55Krishna Choudhary?

  Higher order.

• 27:56Lester Nare?

  Yes.

• 27:57Krishna Choudhary?

  For occasions.

• 27:58Lester Nare?

  But that that makes sense.

• 27:59Krishna Choudhary?

  You know what I mean? And that's what this is showing.

• 28:01Lester Nare?

  Right.

• 28:01Krishna Choudhary?

  And you can actually see the prevalence in the biological data. So they got data from the human connectome project.

• 28:07Lester Nare?

  Yes.

• 28:07Krishna Choudhary?

  They got data from fly neurons. They got data from tropical trees. They got data from blood vessels. They got data from coral. It's just a massive amount of data. And what you can see is 15% of the time you do have these trifurcations. And it depends on that order parameter that I was telling you about.

• 28:25Lester Nare?

  Yes.

• 28:25Krishna Choudhary?

  How thin is it versus how thick is it?

• 28:27Lester Nare?

  Yes.

• 28:28Krishna Choudhary?

  Like, how far away is the is the branching versus how thick it is?

• 28:31Lester Nare?

  Yes.

• 28:31Krishna Choudhary?

  And they can immediately map the biological data and show that the Steiner tree algorithm is wrong. But this new heuristic that they have using the string through tree, using the string three, using the string theory mathematics.

• 28:46Lester Nare?

  Yes.

• 28:46Krishna Choudhary?

  That's what's closer to the biological data.

• 28:49Lester Nare?

  So the idea is if you have two nodes at some distance apart, the old Steiner model worked if the distance between those two nodes where the branching was happening was

• 28:59Krishna Choudhary?

  Really far away.

• 28:59Lester Nare?

  Really far away. But as those nodes close in distance, the the the thickness of the the line between those two nodes or the path and branch between those two nodes, as it gets thicker and as it gets closer, again, the the optimal, the the optimization algorithm flips from

• 29:21Lester Nare?

  optimizing for two bifurcations.

• 29:24Krishna Choudhary?

  To now, we need, we need to start introducing three.

• 29:26Lester Nare?

  We need to offload more.

• 29:27Krishna Choudhary?

  Yeah.

• 29:28Lester Nare?

  And keep, it's almost like the thicker you are, the shorter you need the distances, the more bifurcations, the more outlets you need.

• 29:34Krishna Choudhary?

  Yeah.

• 29:34Lester Nare?

  For optimal, for optimizing for efficiency.

• 29:37Krishna Choudhary?

  Exactly. And what's really cool to me is that across all of these different biological networks, right? We've got neurons. We've got trees. We've got fungi. We've got corals. It's all showing the same strategy.

• 29:51Lester Nare?

  There, there is an under, again, going back to what we always talk about, there's a, there is something that is true across all these different types. That they all are speaking the same mathematical language that the string theorists have been trying to get everyone else to think about for so long.

• 30:06Krishna Choudhary?

  And it and it kind of makes sense because like, even though these guys are so evolutionarily distinct, right? You've got plants, fungi, coral, and and the human brain. Even though evolutionarily, we're divided by millions, hundreds of millions of years.

• 30:23Krishna Choudhary?

  The fundamental resource is surface area, right? The fundamental resource is how can I build this? And so I still want to optimize minimum surface area because I don't want the building costs to go up.

• 30:35Lester Nare?

  Yes.

• 30:35Krishna Choudhary?

  Right? The second thing that I was telling you about the Steiner tree is all of the nodes happen at 120 degrees. But in normal biological networks, it should happen. Sometimes it happens at 90 degrees. Why is that happening? Well, if the thing that's coming out of my tube is really thin, again, it's that same order parameter. If the thing that's coming out of my tube is really thin, then it's actually preferable for me to be 90 degrees away from the tube. On the other hand, if the branching is like thick, thick, thick, then I get to the 120 degrees. And that's what they're showing. They're showing that with these neurons, what you can see is if you've got these like tiny little synapses

• 31:19Krishna Choudhary?

  that come out of, let's say, an axon or a dendrite spine, right? Those tiny little synapses are really thin compared to the thickness of the dendrite. And so what I really want to do in that situation is come out at 90 degrees. I don't want to go at 120 because that's the thing that minimizes surface area.

• 31:38Lester Nare?

  It's funny if you think about suburban neighborhoods and the design of the road networks.

• 31:47Krishna Choudhary?

  Yeah.

• 31:48Lester Nare?

  You know, this looks like a cul-de-sac in a subdivision.

• 31:50Krishna Choudhary?

  It kind of does.

• 31:51Lester Nare?

  You know, because you have your main

• 31:53Krishna Choudhary?

  Yeah.

• 31:53Lester Nare?

  two-lane road. Then you have these offshoots that are narrower, right, off the main road at 90-degree angles.

• 32:00Krishna Choudhary?

  Yeah.

• 32:02Lester Nare?

  So we've also mimicked that, obviously. And for, you know,

• 32:04Krishna Choudhary?

  Yeah.

• 32:05Lester Nare?

  It's the whole image of you see people with traffic going really fast in cities. And then people like map the blood vessels. And there's the similarities in these structures.

• 32:13Krishna Choudhary?

  Yeah, I mean, their structure all the way down, you know? All the way down. And so I just thought this was really cool. In terms of the computational methodology, I thought the way that they did it was very cool. This is the MinSurf Netwa. It was implemented in Mathematica. This is the new code that they use with finite element methods to solve for surface variation problems. They actually have it available on GitHub, so you can use it.

• 32:39Lester Nare?

  Yes.

• 32:39Krishna Choudhary?

  And what they really did was They inputted the connectivity of real maps. And then they said, okay, what is, they asked the algorithm to generate the optimal surface geometry. So it makes up a bunch of meshes, of polygonal meshes, and then tries to figure out what the optimal surface geometry is such that it minimizes surface area. And they could reproduce what the biological networks were doing.

• 33:03Lester Nare?

  So there's sort of this generative model that's based on mathematics.

• 33:08Krishna Choudhary?

  Yeah.

• 33:08Lester Nare?

  But it is, it is not, it is generating net new.

• 33:11Krishna Choudhary?

  Yeah.

• 33:12Lester Nare?

  Structures.

• 33:12Krishna Choudhary?

  Mm hmm.

• 33:13Lester Nare?

  And those net new structures that were generated based on this underlying mathematical framework, when then held up next to our observed biological comparison.

• 33:23Krishna Choudhary?

  Yeah, the statistics match.

• 33:25Lester Nare?

  It's just, it's, it's like.

• 33:26Krishna Choudhary?

  And it's very nice.

• 33:27Lester Nare?

  It's very nice.

• 33:28Krishna Choudhary?

  So I just thought this was a very cool paper, right? And it's, it's kind of a unification of biological physics across so many different types of organisms, fungi, plants, vessels, brains, coral. All of them have the same principle, right? The structure is shaped by a universal physical constraint of minimizing the amount of membrane that I need to use to create a network.

• 33:52Lester Nare?

  Because it kind of makes sense too, because we think, you know, the larger your surface area, the more energy you need.

• 33:58Krishna Choudhary?

  To make it.

• 33:58Lester Nare?

  To make the things and sustain the thing. So it's like, again, if you're trying to minimize that.

• 34:02Krishna Choudhary?

  Yeah, yeah. And it's not, not just the energy in making the thing, it's the material cost. You're using more carbon atoms, right? You're using more hydrogen atoms, which you could use for something else.

• 34:12Lester Nare?

  Right.

• 34:12Krishna Choudhary?

  Right? So you want to optimize at all times. There are a bunch of really cool applications that I just want to go over. One of them is the 3D bioprinting. So what you can do is design scaffolds using this algorithm to create physically correct microvasculature. If you want to create an artificial tissue and you want to improve blood flow in medicine, right?

• 34:35Lester Nare?

  So now, we now basically have a pathway to 3D print things that can be integrated into our system.

• 34:40Krishna Choudhary?

  Exactly.

• 34:41Lester Nare?

  That would map structurally.

• 34:44Lester Nare?

  More on to the way our biological system is

• 34:46Krishna Choudhary?

  Exactly.

• 34:46Lester Nare?

  Is exists to optimize for the potential of the body rejecting it and all these

• 34:51Krishna Choudhary?

  Exactly, and the body not having to work harder than it should to push blood through this artificial system.

• 34:59Lester Nare?

  Yes.

• 34:59Krishna Choudhary?

  Right?

• 34:59Lester Nare?

  Yes.

• 35:00Krishna Choudhary?

  Another one could be hardware design, like if you want to use these surface optimization principles to make 3D chip architectures.

• 35:08Lester Nare?

  Yes.

• 35:08Krishna Choudhary?

  Right?

• 35:08Lester Nare?

  Yes.

• 35:09Krishna Choudhary?

  Like neuromorphic chips, you can now use these principles to do that.

• 35:13Lester Nare?

  Yes.

• 35:14Krishna Choudhary?

  Right? And finally, what I want to touch on is like kind of the philosophy of science, right? There's string theory has gotten a lot of heat and it shows in this XKCD comic, string theory summarized. The string theorist said, I just had an awesome idea. Suppose all matter and energy is made of tiny vibrating strings. And his friend says, okay, what would that imply? And the string theorist says, I don't know. It's a string theory has been the butt of so many jokes in physics and mathematics, in the idea of funding fundamental science. And I think that's like quite dangerous. Now, there's stuff to be said about perhaps the scale at which we funded string theory versus something else.

• 35:56Krishna Choudhary?

  But the idea of funding something like string theory should not be totally looked down upon just because, oh, it doesn't have any real world applications. Because at the end of the day, if we go into fundamental research.

• 36:10Lester Nare?

  Yes.

• 36:11Krishna Choudhary?

  Just being curious about how stuff works, maybe it works this way. What would the mathematics look like? You don't know where it's going to end up.

• 36:19Lester Nare?

  Hundred percent.

• 36:20Krishna Choudhary?

  You know?

• 36:20Lester Nare?

  And this is a perfect example of the importance of curiosity.

• 36:23Krishna Choudhary?

  Just curiosity driven research.

• 36:25Lester Nare?

  In frontier research, again, this is the difference between research that's being done in the corporate environment and you know, in business architectures, which are well funded, but do not have the incentive to explore areas of research that don't immediately have a profit motive.

• 36:44Krishna Choudhary?

  Exactly.

• 36:45Lester Nare?

  And there are so many things that are beneficial to mankind and all of us in our health, in our socialization, all these things that don't inherently have the profit motive, but are still valuable. Again, if you're starting to create artificial hearts and heart transplant stuff, or skin grafting and replacement therapies, based on the fact that string theorists spent all this time and money figuring out the structure.

• 37:09Krishna Choudhary?

  Yeah.

• 37:10Lester Nare?

  And now it's going to save people and extend your life. That's pretty cool. That's pretty good. That's, that's, that's pretty good. Yeah. And this is, this is again, why we always like to talk about the methods and the concepts behind things, even if it's not an immediately applicable, like, finding, because this is what we're gonna end up utilizing as we get older, as our children get older, in the world around us. It's not going away, it's only accelerating. Yeah. And it's a great way to start episode 22 with, with a little bit of balanced views on string theory. Yeah. You know, we have our, not we. It's still funny. It's the. The, the comic is still funny. I'm gonna laugh, you know?

• 37:54Lester Nare?

  Uh, this is, this is so good, and I could, there's so many things about that I could dive, dive into, but we are moving on to the rundown for the week after our first deep dive. Yeah. On string theory. Again, we are sort of looking to see what else will come from that, but he, he, he, here's the thing that's interesting. You have four universities. Mm-hmm. Involved in this story. Mm-hmm. Um, it takes a village. Yeah. To do these things. This is not some one person in a lab by themselves. No. It really requires cross-institutional and cross-functional work to do so. Yep.

• 38:38Lester Nare?

  But that being said, we will move into the rundown. Uh, it seems like the audience likes a little quick, rapid fire, so again, the concept of the rundown, we can't cover all frontier science research in the level of detail we do, we would be here until the end of time, but it is still important to know briefly what's going on in the world around us, and we're gonna start with our first ra- rundown story from January 8th, The Hidden Strength of Iron Asteroids. This is a planetary defense story. The oblique of space, why iron asteroids are harder to deflect. The byline on the story is a groundbreaking simulation reveals that iron-rich asteroids possess a hidden strength, strength that makes them more resilient to impacts.

• 39:22Lester Nare?

  Than previously theorized. This is out of the University of Oxford and CERN. And the implications here are using CERN's HIRAD map facility. Physicists irradiated meteorite samples with high-energy proton beams to see how they would deform under stress.

• 39:39Krishna Choudhary?

  Yeah.

• 39:40Lester Nare?

  They discovered that there was this dampening, meaning that the faster the asteroid is hit, the better its internal structure dissipates energy, which is a little counterintuitive. So this just suggests that kinetic impactors, like the idea of NASA's DART mission, which I believe was to like intercept, shoot something, intercept an asteroid on its way in.

• 40:00Krishna Choudhary?

  Yeah, so intercept an asteroid and change its trajectory.

• 40:03Lester Nare?

  Yes, yes. The idea is that it would remain intact because it would be able to dissipate the energy. The asteroid would be able to dissipate the energy on impact.

• 40:14Krishna Choudhary?

  Exactly. We wouldn't have like an Armageddon situation where the asteroid would break up into a bunch of chunks. And then now, instead of worrying about one thing, we're worrying about nine things that are coming in. Basically, the idea is like, as you hit the asteroid, if it's full of iron, it's gonna like ring, you know?

• 40:33Lester Nare?

  Yes.

• 40:34Krishna Choudhary?

  And and sort of dissipate its energy internally.

• 40:36Lester Nare?

  Yes.

• 40:36Krishna Choudhary?

  Maybe heat up a little bit, but it's not gonna totally break apart.

• 40:40Lester Nare?

  Yes.

• 40:41Krishna Choudhary?

  Very cool.

• 40:42Lester Nare?

  The context analogy for this one is it's similar to hitting a pool of oblech, which is cornstarch and water. If you poke it slowly,

• 40:50Krishna Choudhary?

  Yeah.

• 40:50Lester Nare?

  It's soft. But if you punch it hard, turns into a solid wall.

• 40:54Krishna Choudhary?

  Yeah.

• 40:55Lester Nare?

  And these asteroids essentially have this hardening response to an impact, making them tougher to move. So if you're in planetary defense, you can't just bomb and shoot our problems away.

• 41:05Krishna Choudhary?

  Yeah. You gotta get a little bit clever, but the asteroid could do some of the work for you.

• 41:11Lester Nare?

  Armageddon was a great movie.

• 41:13Krishna Choudhary?

  It was a good movie. I liked that movie.

• 41:15Lester Nare?

  There was a, one of Ben Affleck's greatest works was the DVD commentary on.

• 41:21Krishna Choudhary?

  I have not watched this.

• 41:23Lester Nare?

  Armageddon, because if you remember, it was like a bunch of guys who work on an oil rig.

• 41:27Krishna Choudhary?

  Yeah.

• 41:27Lester Nare?

  Came into NASA and they were like, we have no one else on the planet who can do this job. Other than a bunch of guys from the oil rig, which Ben Affleck was making fun of in his DVD commentary. He's like, why would NASA not know how to drill?

• 41:39Krishna Choudhary?

  Right. Oh, yeah. It's like, why couldn't we just train astronauts to do oil rigs? Maybe that's easier than training oil riggers to be astronauts.

• 41:49Lester Nare?

  Yeah, and he was having, having, having a fun time taking the piss. Our story number two, reform and artificial metabolism for carbon. Uh, this is a synthetic biology story. Uh, January 5th, 2026 headline, synthetic biologists transform waste CO2 into the building blocks of life. Scientists have created an entirely new artificial metabolism that bypasses natural evolution to turn waste carbon dioxide into valuable chemicals. And this is out of Stanford University and Northwestern University led by Michael Jewitt.

• 42:30Krishna Choudhary?

  Yeah, this one's a pretty interesting one. It's using like the cell free system. So they remove all of the enzymes from a cell. They put it inside a test tube. And then what you can do is screen thousands, I think 3,000 enzyme variants to create what they call the reform pathway. And what it's doing is it's a synthetic system. So it's outside of a living cell and it's taking formate, which is a chemical compound that's derived from CO2 and converting that into acetyl coenzyme A, which is a universal molecule found in all living cells. It's part of our metabolism, mitochondria, love it, so on and so forth. And it provides a path for sustainable carbon neutral manufacturing. Because if we want to take CO2 out of the atmosphere, we got to get clever. Maybe this is one of the ways that we do it.

• 43:14Lester Nare?

  Mm hmm, mm hmm. The, for those who are lost in the explanation, the analogy is imagine opening the hood of a car. And using the engine to power a factory instead of just driving the car, researchers are using the machinery of life in a test tube to build sustainable products out of thin air. Again, that's out of Stanford University and Northwestern University. Story number three is a stem cell research story, "Culturing the Immune System's Conductors." This is January 8th, 2026. Headline, "UBC Scientist Solve the Mystery of Growing Helper T Cells." Now, if you've watched this show in the past,

• 43:57Lester Nare?

  you know, we've talked about the immune system.

• 44:00Krishna Choudhary?

  Yes.

• 44:00Lester Nare?

  A lot. So in our past episodes, we do cover this. But the log line is for the first time, researchers have reliably produced helper T cells from stem cells, a major hurdle in creating off the shelf living drugs. And this is out of the University of British Columbia, led by Peter Zanstra and Megan Levings.

• 44:22Krishna Choudhary?

  Yeah, this one's interesting because, you know, we've been able to grow killer T cells, which are, you know, the soldiers of our immune system. But the helper T cells, which are kind of like the generals or like the kernels of the immune system, they're the ones that conduct all of the responses. They activate B cells to make antibodies. They trigger the macrophages, which are the eating immune cells that'll like eat up bacteria and bad things. They conduct all of this stuff by releasing cytokines and all of these other important factors. But they're really hard to grow in a lab. And these guys precisely tuned a development signal called Notch.

• 45:06Krishna Choudhary?

  And they were able to direct stem cells to become either type.

• 45:10Lester Nare?

  Right.

• 45:10Krishna Choudhary?

  You know, either killer or helper, right? And now this allows for large scale manufacturing. Again, personalized drugs. You could take the stem cells from a patient and then make. Designed helper T cells.

• 45:23Lester Nare?

  That are specific to like that specific patient.

• 45:26Krishna Choudhary?

  Yeah, it could be much more affordable. You know, you can customize patient specific therapies. It's very cool.

• 45:33Lester Nare?

  So to the analogy that you brought up, we've already learned how to train soldiers to fight cancer, but we didn't know how to recruit the conductors who lead the orchestra on the battlefield. So this discovery finally gives us the full leadership team needed for a strong lasting Yeah. immune response. Our last rundown story of the day. As the UFO guy, you know, we always have to some point talk about exoplanet exploration, unmasking alien atmospheres. This is on January 12th. A conversation NASA's Pandora telescope will study stars in detail to learn about exoplanets

• 46:18Lester Nare?

  orbiting them. Now I'll just briefly note, this is the not the last time we're going to be talking about exoplanet exploration.

• 46:26Krishna Choudhary?

  That's right.

• 46:27Lester Nare?

  We're not going to leak any classified information at this moment in time. But for this story, log line, as the first mission of NASA's Astrophysics Pioneers Program, the Pandora small sat will provide the first ever high precision tool for disentangling stellar noise from the actual atmospheric signal of distant worlds. And we did talk about this in the episode where we covered the greatest evidence yet.

• 46:50Krishna Choudhary?

  Yeah, K 218B.

• 46:52Lester Nare?

  Of life on an exoplanet. But this story is out of the University of Arizona, led by Daniel Apai, NASA, Goddard Space Flight Center and Ames Research Center and the Lawrence Livermore National Lab and Cornell University.

• 47:06Krishna Choudhary?

  Yeah, this one's a cool one because it's quite a small satellite. The lens is only like 17 inches, which is pretty small compared to like Hubble or James Webb. But it's very specific. What it's trying to do is basically stare at the stars that have transiting planets. And what they want to do is disentangle when we see a planet going in front of the star and the sort of light coming from the star going down versus if the star has a sunspot and the sunspot has come this way and now all of a sudden I'm just seeing less light because part of the star is dark.

• 47:43Lester Nare?

  Right.

• 47:44Krishna Choudhary?

  Right? It's very hard to disentangle the two, but if you just like stare at something for a long enough time, you'll have an averaged out version of what that star should look like. And then you'll have a much better idea of what the planet looks like when it goes in front of the star.

• 48:01Lester Nare?

  Yes.

• 48:02Krishna Choudhary?

  You can disentangle those two aspects.

• 48:04Lester Nare?

  Yes.

• 48:04Krishna Choudhary?

  It's only in charge of 20 planetary systems. It's got a year's worth of

• 48:09Lester Nare?

  Oh, really?

• 48:10Krishna Choudhary?

  Yeah. It's it's it's kind of like a pilot project in some sense, but not really, because, you know, even 20, getting that understanding for just 20 at that precision is going to be vital for interpreting data from larger missions like the James Webb Space Telescope. You can use that understanding for how stars work and then now start applying it to when the James Webb looks at something, right?

• 48:32Lester Nare?

  This goes back to our point we always talk about, which is all of these discoveries and these movements are cumulative. They're not happening in a vacuum. So the immediate thing I just thought of was, you know, Vera Rubin and the massive amount of data that's going to be there in combination with JWST and some of the instruments that are looking at exoplanet atmospheres.

• 48:53Krishna Choudhary?

  Yeah.

• 48:53Lester Nare?

  Like, there are data sets that have answers that we already have in our possession.

• 48:58Krishna Choudhary?

  Yeah.

• 48:58Lester Nare?

  Some are proprietary, some are open source, whatever. But that, once we find an unlock, all of a sudden makes these data sets incredibly valuable.

• 49:07Krishna Choudhary?

  Yeah.

• 49:08Lester Nare?

  And this is sort of maybe a scout type of mission.

• 49:10Krishna Choudhary?

  Yeah.

• 49:11Lester Nare?

  To be able to create some of that better understanding, to get rid of the baseline of the planet.

• 49:15Krishna Choudhary?

  Exactly.

• 49:16Lester Nare?

  Better read. And so that's, again, the exoplanet stuff, I'm always such a huge fan of. We are going to come back into our main story, number two of three. And this one is going to be an interesting combination. It's neuroscience, sleep, and marine biology.

• 49:38Krishna Choudhary?

  Yes.

• 49:39Lester Nare?

  This is in Nature Communications, published on January 7. Why do jellyfish need sleep?

• 49:47Lester Nare?

  The ancient origins of our nightly rest. This is from Bar Ilhan University. And the hook here is imagine a creature without a brain.

• 49:55Krishna Choudhary?

  Yep.

• 49:56Lester Nare?

  That sleeps just like you. And scientists have discovered that jellyfish do exactly that.

• 50:02Krishna Choudhary?

  Do exactly that.

• 50:03Lester Nare?

  They have no brain, but they sleep like us.

• 50:05Krishna Choudhary?

  Yes. Um, it's a core paradox in biology, to be honest. It's like, why do we sleep?

• 50:11Lester Nare?

  Right.

• 50:12Krishna Choudhary?

  It's a very simple question, but if you think about it from an evolutionary point of view, it seems naively really dumb to do. Okay. Because sleep is a state, there's behavioral vulnerability. You're not, you're not like aware of stuff. Something could come and kill you. Um, you're vulnerable to predation. It ceases foraging, you're not getting food. And also you're not having sex. So you're not really procreating.

• 50:38Lester Nare?

  Yes.

• 50:38Krishna Choudhary?

  Right? So what's the point? And yet it's conserved across 600 million years of evolution. We have whales doing it, humans do it. And now we've got jellyfish do it. Right? And the traditional view was it's a neurocentric view, meaning it has to do with complicated neural mechanisms, right? This idea of the synaptic homeostasis hypothesis, which is the idea that over the day, your neurons are constantly learning and your synapses are growing. And if you just let it just keep growing and growing and growing, then you're going to get this runaway interaction, kind of like last episode, we were talking about in DeepSeek, right? If you have these matrices that just start blowing up, then you're going to get a very chaotic system.

• 51:23Krishna Choudhary?

  So you need some way to constrain them. And maybe sleep was one way to constrain our synapses such that the signals don't propagate in a chaotic way. But now we've got this new finding, which shows that sleep is actually a fundamental cellular requirement because of DNA repair. And it's happening even in these brainless basal metazoans. So in this case jellyfish, but they also did the experiments on C anemone. And they found very similar results. Okay. So let's get into some of the historical context for sleep research. Pre 1980s, there was this guy Hans Berger in 1929. He invents the EEG, which is the electroencephalogram. And what he showed was that people that are sleeping, they've got these cortical oscillations, alpha waves,

• 52:08Krishna Choudhary?

  and other types of brainwaves. And he said, okay, sleep is basically the state when we get that.

• 52:16Lester Nare?

  Right.

• 52:16Krishna Choudhary?

  All right. Now, that's fine, but that totally excludes invertebrates, because invertebrates don't, I can't do an EEG on an invertebrate, right? I need some kind of centralized brain. So I can do this on mammals, but are you saying that like, you know, lower order organisms don't sleep? So in the 1980s, there was this neuroscientist Irene Tobler at the University of Zurich. She came up with the behavioral criterion, okay? She showed that actually insects sleep, scorpions sleep, and there were three definite, three things that she wanted to classify something as sleep. She was a pioneer in her field. The three things are the following. First, reversible immobility. That makes sense, right?

• 52:59Krishna Choudhary?

  When we sleep, we're still-ish, but somebody can wake us up. So that's the reversible part.

• 53:05Lester Nare?

  Okay.

• 53:05Krishna Choudhary?

  Okay. The second one is increased arousal threshold. If I poke you when you're awake, you can sense it. But if I poke you when you're asleep, you probably can't. I need to poke you really hard in order to wake you up. Okay? Like, I need to like slap you, and then you're gonna wake up.

• 53:22Lester Nare?

  The amount of effort needed to

• 53:25Krishna Choudhary?

  elicit a behavioral response is higher. Is higher when you sleep. Okay. And the third thing is homeostatic regulation. This means that if I deprive you of this sleep, then the next time you sleep, you're gonna sleep longer. We've all had this, right?

• 53:40Lester Nare?

  Yes.

• 53:40Krishna Choudhary?

  Like, if you're, if you've had a night out, the next day, you're quote hungover, but what you're really doing is homeostatic regulation, on top of the fact that you don't have any electrolytes. But, you know, you're sleeping way longer than you should be.

• 53:53Lester Nare?

  Yes.

• 53:54Krishna Choudhary?

  So those are the three sort of behavioral definitions that I need in order to characterize sleep.

• 54:00Lester Nare?

  I don't think I've ever thought about how do you define sleep before.

• 54:02Krishna Choudhary?

  Yeah.

• 54:02Lester Nare?

  In my life, like, but that's.

• 54:04Krishna Choudhary?

  You know, it becomes obvious when you talk about humans, you can just ask them, like, did you sleep? With mammals, again, you could hook up a EEG. But now, when we're getting into something like jellyfish, it's like, how do we define sleep for an organism that's just doing this the whole time?

• 54:18Lester Nare?

  Yes.

• 54:19Krishna Choudhary?

  Right?

• 54:19Lester Nare?

  Yes.

• 54:19Krishna Choudhary?

  So, but these three criteria, actually, we can translate.

• 54:23Lester Nare?

  Mm hmm.

• 54:24Krishna Choudhary?

  Okay? So the model organisms in this paper are Nigerians, jellyfish, and sea anemone. Okay? It's a paper that came out of Nature Communications, and these organisms actually diverged from the bilaterals, which are us, the, you know, bilateral meaning to the symmetric kind of thing, instead of the round symmetry.

• 54:46Lester Nare?

  Yes.

• 54:47Krishna Choudhary?

  They diverged from us 600 million years ago.

• 54:50Lester Nare?

  Okay.

• 54:50Krishna Choudhary?

  It's even thought that maybe the nervous system of these Nigerians is completely separately evolved from us. There's a little bit of debate on that, because if you look at the neurons of these guys, the genes that they express are very similar to the neurons, the genes that our neurons express. So perhaps there's a little bit of independence, but also, at the same time, a little bit of the same genes going forward. But what's very cool is these guys don't have a brain. They have nerve nets. There's no centralized repository.

• 55:21Lester Nare?

  Mm hmm.

• 55:21Krishna Choudhary?

  Okay? It's a bunch of nerves that are just in a net together, and they're making decisions together. And it's very unclear how they're doing it.

• 55:31Lester Nare?

  Okay?

• 55:32Krishna Choudhary?

  But in any case, very different from our centralized nervous system that we have, with a central hub and it branching out to create motor functions. There's a decision-making that happens in our brain, and then the rest of the neurons carry it out. Here, we've got a very decentralized decision-making process.

• 55:47Lester Nare?

  Is this the idea of like, there's like, no executive function in these, like, because there's not?

• 55:53Krishna Choudhary?

  Yeah, it's very related.

• 55:54Lester Nare?

  There's not like, there's not an authority who decides, and then everyone else has to follow.

• 55:59Krishna Choudhary?

  That's right.

• 55:59Lester Nare?

  For lack of a better way to put it.

• 56:00Krishna Choudhary?

  Okay. Very, very much so. So, the, the challenge now becomes, okay, we've got these two organisms that we want to study. Let's try to define sleep for them, right? Using those three criteria. So what they did was just make videos of these organisms in their natural, not natural habitat, but in lab conditions. They used infrared light because if you use normal light, then you're just messing with their rhythm, right? It's like you still need a night and day cycle. So instead you use high resolution infrared light. So this is infrared light. And here you see the jellyfish that are pulsating, right? This is Cassiopeia Andromeda, the jellyfish. And what they could do is analyze these videos and figure

• 56:44Krishna Choudhary?

  out, basically classify two behavioral states based on those three rules that we had about what sleep is. They did the same thing for the starlet sea anemone. That's the nimato- nimato stella vectennis, right? These are, they're like hydro looking things. This is a 20 minute time lapse. They're much slower moving. So it's actually harder to classify immobility. But what you could do is actually classify the, even when they're awake, they have a little bit of jitter and they could, they could really hone in on that jitter and classify rest, just five minutes of rest versus actual sleep. Okay. And that's, that's,

• 57:26Krishna Choudhary?

  that's what was really cool about how they did this, right? They actually figured out a way to move beyond just these arbitrary dimensions and used threshold based optimization algorithms that were custom made for this use case, right?

• 57:40Lester Nare?

  Yes, yes.

• 57:42Krishna Choudhary?

  And it's a rigorous definition. So they came up with these rigorous definitions. And now let's go ahead and try to analyze the sleep. When you analyze the sleep, one thing that's really cool is the Cassiopeia Andromeda, which is the jellyfish. Yeah, that's the one that actually it's so in the light phase, it was highly active. So during the day, it's very active. That's the high on the Y axis. And then during dark times, it was very inactive. But what's very cool is during the day, right in the middle, it takes a siesta. It takes a midday nap.

• 58:12Lester Nare?

  They're very European, I see.

• 58:14Krishna Choudhary?

  Yeah, yeah. These jellyfish are Spanish, in fact.

• 58:17Lester Nare?

  In fact.

• 58:19Krishna Choudhary?

  Yeah. But so these jellyfish, just like us, we like taking naps. These jellyfish like taking naps. The-

• 58:27Krishna Choudhary?

  C and M on the other hand, they were actually more active during dusk and dawn. And then they slept mainly during morning and that could have something to do with the fact that like their feeding has to do with tides, right? Because the water is moving in and out. So perhaps you want to be more active during the dusk and dawn and then you can be less active. When the sun is high in the sky and when the sun is low in the sky.

• 58:47Lester Nare?

  Which kind of maps on to like nocturnal versus non nocturnal.

• 58:49Krishna Choudhary?

  Yeah, yeah. And speaking of nocturnal versus non nocturnal, they also had the melatonin. That was affecting them. So melatonin, you know, that's the very famous compound that we can take in order to induce sleep.

• 59:00Lester Nare?

  Yes.

• 59:01Krishna Choudhary?

  They tested it with 100 micromolar melatonin and the melatonin promoted both in promoted sleep. In both the diurnal jellyfish and these anemone.

• 59:12Lester Nare?

  So you're saying that someone's going to make billions of dollars selling melatonin 10 milligram, 100, 100 million, whatever packages to to see like Nemo, Nemo, tell your dad.

• 59:22Krishna Choudhary?

  Yeah.

• 59:22Lester Nare?

  We're coming with the melatonin.

• 59:24Krishna Choudhary?

  Yeah, exactly. Yeah, there's a huge market there, dude.

• 59:29Krishna Choudhary?

  Yeah. So the now we've established that they sleep and the sleep is like pretty close to how we do it.

• 59:35Lester Nare?

  And we saw it both in a natural context and by trying to induce it.

• 59:38Krishna Choudhary?

  Yes, exactly. So now the big question is, why are these guys sleeping so much? Okay, if

• 59:45Lester Nare?

  They have no brains.

• 59:46Krishna Choudhary?

  If they've got no brains.

• 59:47Lester Nare?

  The way we conceptualize.

• 59:48Krishna Choudhary?

  Yeah, the way we conceptualize brains, they don't have these like synaptic connections that they need to regulate. Up and down. So why are they sleeping so much? And this is the key significant contribution of this paper. Okay, they're tying the sleep. Not to neural activity, but to cellular activity and the idea that at the molecular level. All cells need to recover.

• 1:00:14Lester Nare?

  Oh.

• 1:00:15Krishna Choudhary?

  Because at the molecular level, what's happening with activity is activity means high entropy, right? There's high metabolic flux, the mitochondria are going crazy, they're creating ATP. Now that's going to create a lot of reactive oxygen, oxygen species. Okay. And these reactive oxygen species are going to cause damage to the DNA backbone. If you're Remember from our DNA episode, the DNA has this phosphate backbone, right? The reactive oxygen species that come as a byproduct of mitochondrial metabolism is going to start attacking this DNA backbone. And if you ever get something like a double stranded break, that's really bad. Okay, and what they could actually quantify is during wakefulness, the double stranded break was happening more often.

• 1:01:01Lester Nare?

  So literally, the, the, the, the process of living, of being awake and active, is not only impacting your body in the physical sense that we think about it today, but the reason that our body needs sleep and rest is because at the, at the DNA level.

• 1:01:23Krishna Choudhary?

  At the DNA level, it's causing damage.

• 1:01:25Lester Nare?

  It's causing damage and, and that's, that's, that's. Because again, I always thought like from my layman's perspective, like, oh, we sleep because your brain is tired.

• 1:01:34Krishna Choudhary?

  Yes.

• 1:01:34Lester Nare?

  Like that was the, that was the idea.

• 1:01:36Krishna Choudhary?

  Yeah.

• 1:01:36Lester Nare?

  Like you need to give your brain a rest, you're going to go crazy.

• 1:01:38Krishna Choudhary?

  Yeah.

• 1:01:39Lester Nare?

  But really what this is identifying is that the destructive property that happens from lack of sleep is a degradation of your, of underlying DNA.

• 1:01:47Krishna Choudhary?

  Yeah, yeah. And for higher order organisms, it could be that the brain is also tired and the synaptic homeostasis model works, right? And that could be a thing.

• 1:01:56Lester Nare?

  Yes.

• 1:01:56Krishna Choudhary?

  And it most definitely is. There's a lot of papers that do that. But this is showing that even at 600 million years back, we needed sleep. Because fundamentally, the act of living, as you said, degrades the molecular structure of our genetics, right? And what they could do is show, they could actually tag phosphorlated histone, and this phosphorylation happens at double stranded breaks. And they could track that actually the longer you're awake, the more double stranded breaks you're having, okay? And if you kept these organisms awake, the breaks would actually build up. The craziest thing to me was they could actually.

• 1:02:35Krishna Choudhary?

  They could actually use that damage to drive sleep. So you know that homeostatic regulation that I was telling you about? Like, okay, if I if I deprive these animals of sleep, then they want to sleep longer. Well, I could actually artificially make double stranded breaks happen. You know, expose them to UV radiation. Now I have a bunch of DNA damage. The animals would sleep more because of more UV radiation, because there was more double stranded breaks. So it's a direct causation now. It's not just a correlation. You've established a direct causation between DNA damage and more sleep.

• 1:03:10Lester Nare?

  That's fascinating.

• 1:03:10Krishna Choudhary?

  Very cool.

• 1:03:11Lester Nare?

  They they artificially triggered DSBs, double stranded breaks.

• 1:03:17Krishna Choudhary?

  Yeah.

• 1:03:18Lester Nare?

  After having already monitored natural behavior.

• 1:03:20Krishna Choudhary?

  Yep.

• 1:03:20Lester Nare?

  And it triggered an increase in the amount of sleep in both the jellyfish and the sea anemone. When they were exposed to an external factor that one of the primary things it did was create a larger volume of double stranded breaks.

• 1:03:37Krishna Choudhary?

  Yeah.

• 1:03:38Lester Nare?

  Or degradation of the molecular DNA stuff.

• 1:03:40Krishna Choudhary?

  And they didn't comment on this, but I've always felt that like if I'm out in the sun for really long.

• 1:03:44Lester Nare?

  Yeah.

• 1:03:45Krishna Choudhary?

  I need to, I need a nap.

• 1:03:46Lester Nare?

  I need a nap.

• 1:03:47Krishna Choudhary?

  I don't know. I'm not saying that the author's, I'm just saying it's like kinda, I don't know.

• 1:03:54Lester Nare?

  Look, it is Southern California, so we do know what it's like to be out in the sun a lot.

• 1:03:58Krishna Choudhary?

  I feel like when I get sunburned, and I do get sunburned, okay? Even though like I'm brown, I do get sunburned. And then when I do, it's like I do, like I end up napping for like two hours and it's the best nap.

• 1:04:09Lester Nare?

  It's the best, it's usually the best.

• 1:04:10Krishna Choudhary?

  Yeah.

• 1:04:11Lester Nare?

  It's usually.

• 1:04:12Krishna Choudhary?

  And you know, maybe that's like, you know, the DNA repair being like, finally, we get to like fix all this nonsense that he's been up to.

• 1:04:19Lester Nare?

  This, this, this is good. And again, this is like, again, a story at the intersection of spaces I didn't expect to sort of see, right? You have, it was like, I said, DNA damage, okay? The neuroscience story, oh, because we thought that sleep was about.

• 1:04:34Krishna Choudhary?

  Yeah.

• 1:04:34Lester Nare?

  Only, again, we we've caveated, this is not saying that, uh, sleep is not involved in neurological activity. It is just that we can see that it is not the only thing that it's involved in.

• 1:04:47Krishna Choudhary?

  Yeah. And it's like an invariant across animals that have neurons. And one of the cool things is when you think about like, why would neurons specifically need sleep?

• 1:04:55Lester Nare?

  Yeah.

• 1:04:56Krishna Choudhary?

  Right? Neurons are organisms that don't divide.

• 1:05:02Krishna Choudhary?

  Right? Neurons, not organisms, neurons are cells that are postmitotic. They don't do mitosis, they don't cell divide. So, once you have them, you have them. So, maintaining the cell state of a neuron is way more important than, let's say, skin cells. Skin cells, if you've got something that's bad, you shed it, you make new ones, because those things are going through mitosis all the time. Muscle cells as well, they're replicating all the time. Neurons, on the other hand, you got what you got. And so, you need to maintain it, right? Which is why animals with neurons might require sleep, because DNA damage in a neuron is way more important to fix than anything else.

• 1:05:37Lester Nare?

  And so, in order to protect your limited neurons, make sure you share the pod with a friend, because what better way to stretch out and exercise those neurons than listening to the From First Pringles podcast? It's for your brain health.

• 1:05:52Krishna Choudhary?

  Yes.

• 1:05:52Lester Nare?

  So, if they ask you, this podcast helps my mental health, my biological mental health.

• 1:05:59Krishna Choudhary?

  Yeah.

• 1:05:59Lester Nare?

  By stretching, pulling and keeping flexy.

• 1:06:02Krishna Choudhary?

  And then get some sleep right after, because then that'll actually, studies have shown that, you know, sleep actually consolidates that memory into long-term storage. So, you might actually remember something that we're talking about.

• 1:06:12Lester Nare?

  It's for your health. That's why you listen to the pod. Great story number two. We started with string theory.

• 1:06:18Krishna Choudhary?

  Yeah.

• 1:06:19Lester Nare?

  Then we went into this sort of biology neuroscience sleep story, understanding a little bit more about sleep having a larger scope of value.

• 1:06:31Krishna Choudhary?

  Yeah.

• 1:06:31Lester Nare?

  To other sort of animals within the animal kingdom. And we're going to end this episode with a space story.

• 1:06:42Krishna Choudhary?

  Yes.

• 1:06:44Lester Nare?

  Story number three is about dark matter.

• 1:06:48Krishna Choudhary?

  Yes.

• 1:06:50Lester Nare?

  Dark matter's first frontier and the discovery of cloud nine. Not that cloud nine. A different Cloud Nine, or is it?

• 1:06:59Krishna Choudhary?

  Or is it? I don't know. I don't know how it was named, honestly.

• 1:07:02Lester Nare?

  We will get to that question, but astronomers may have found the first example of a primordial gas cloud trapped in a dark matter halo, offering a rare glimpse into how the universe's first structures formed billions of years ago. This is coming in the Astrophysical Journal Letters on January 7th from the Space Telescope Science Institute, the Universita D'Aglia Studi di Milano Bioka, University of Victoria, and another placement, I think they might be third place in our stories, of the University of Wisconsin.

• 1:07:41Krishna Choudhary?

  Wisconsin is doing well in our stories.

• 1:07:43Lester Nare?

  They are performing very, very highly. So what makes Cloud Nine, the new celestial discovery, a cosmic game changer for star formation theories?

• 1:07:55Krishna Choudhary?

  Yeah, so they're claiming, you know, it's been all over the news. They're claiming that this is a new type of object, okay? It's a compact, gas-rich, starless object, and it's a totally different thing in our cosmic zoo. You know, we got galaxies, we got stars, we got planets, and now perhaps a totally different animal altogether.

• 1:08:20Lester Nare?

  Okay.

• 1:08:20Krishna Choudhary?

  Okay? That's very rare, because we've been staring at the night sky for a while.

• 1:08:24Lester Nare?

  Right, right.

• 1:08:25Krishna Choudhary?

  So a new type of object is quite interesting, right?

• 1:08:29Lester Nare?

  Yes.

• 1:08:30Krishna Choudhary?

  And that definitionally doesn't fit into another bucket. Yes, yes. And what's really important about this new type of object is it's confirming a lot of theories about dark matter that we have. There were some holes in that theory that this is sort of filling, and at the same time, it's raising some new questions, as almost all new stuff does.

• 1:08:48Lester Nare?

  Yes.

• 1:08:49Krishna Choudhary?

  Right? So let's start at the very beginning. We're going to start at the Big Bang, and we're going to start with something called Lambda CDM.

• 1:08:54Lester Nare?

  In the Benninging.

• 1:08:56Krishna Choudhary?

  There it is. Lambda CDM is cold dark matter. That's the prevailing cosmological model that we have for all the stuff that is in our universe, not a lot of normal matter. A lot of dark matter. So I think 85% of stuff that is gravitationally influenced is dark matter. Only 15% is normal matter. And then we don't have to talk about dark energy, which is a whole other thing. You know, that's actually even more than dark matter. Right? But let's not get into that. Let's just talk about stuff that is influenced by gravity. So in the very beginning, there was the Big Bang. The Big Bang expanded into.

• 1:09:35Krishna Choudhary?

  It didn't expand into space. Space itself expanded. Let me catch myself when I say that. Right?

• 1:09:40Lester Nare?

  The comments would have gone crazy with that one.

• 1:09:41Krishna Choudhary?

  Yeah. So 300,000 years after the Big Bang, we formed atoms. That's when we got our cosmic microwave background. And then we had our first stars, our first galaxies, our first black holes. And through all of this, dark matter was also expanding with all of the baryonic matter. That's the ordinary matter. Stuff of atoms, quarks, electrons, things like that. And at some point, the first stars began collapsing. They started blowing up the dark, the black holes started creating a mess. Right? They started creating ultraviolet radiation.

• 1:10:20Krishna Choudhary?

  And all of this time, what was happening was this ultraviolet radiation was heating up the intergalactic medium to a temperature of approximately 10 to the 4, so 10,000 Kelvin, 10,000 degrees Celsius. Okay?

• 1:10:35Lester Nare?

  It's pretty cool.

• 1:10:36Krishna Choudhary?

  Pretty cool. And this was happening around 400 million years after the Big Bang. This is called the reionization epoch. Because what's happening now is all of the hydrogen that's in our intergalactic medium is getting bathed in this UV radiation. Okay? And this whole time, dark matter is just doing its thing. Okay? So all of the hydrogen, which is the baryonic matter, is getting bathed in UV radiation. Meanwhile, the UV radiation is not at all interacting with the dark matter. That's the point of dark matter. It does not interact with light, hence it's dark. Okay? So dark matter's been collapsing this whole time. And when dark matter collapses, it forms clumps. Okay. Okay, these are called halos. And the clumps happen at all different scales.

• 1:11:20Krishna Choudhary?

  If we look out at the dark matter halo function, the mass function that we see today, that function is something that we call scale free. So instead of the size of the dark matter halos sort of collapsing as an exponential, where there's some like fundamental scale constant of that exponential, this thing is a power law, which means as we get to smaller and smaller like scales of halos, there should be more and more of these dark matter halos. So there should be a halo for the Milky Way that is as big as the Milky Way. And at the center of this dark matter halo is the our normal Milky Way. But then around this Milky Way, there should be a bunch of different tiny clumps. And around those tiny clumps, there should be even smaller clumps. And around those, so on and so forth.

• 1:12:04Krishna Choudhary?

  It's it's kind of this like self referential fractally system. It's like the Russian dolls. Yes, exactly. But the smaller the Russian doll, the more there should be. That's key. Okay. Okay. Yes. Yeah. Okay, interesting. Okay, so now let's think about what would happen with these halos, right?

• 1:12:27Krishna Choudhary?

  The bigger the halo, there should be galaxies inside, right? We don't actually see all that many halos. That's kind of a problem. Okay? Yeah. Now, there could be a solution about why we don't see a bunch of small halos. Okay, and that has to do with the nature of these halos and the normal matter that's inside of these halos. So let's talk about something called hydrostatic equilibrium. Normally, we think about hydrostatic equilibrium in the sense of why are stars stable? Like, why isn't every star a black hole? Yeah. Okay, because if gravity is just like pushing everything inside, then everything should just collapse into a black hole. Well, the reason is there's a bunch of fusion going on. And that fusion creates an external pressure outward

• 1:13:10Krishna Choudhary?

  that is counteracting the gravitational pressure, right? And that's what keeps a star. Stable. Yes. Okay, now let's think about dark matter halos. Okay. Okay, with dark matter halos, remember I told you that during reionization, this cosmic dawn is what they call it. When there was a bunch of ultraviolet radiation, that ultraviolet radiation is gonna heat up normal matter. Okay, so that normal matter is inside of a gravitational well of dark matter. So it's getting pushed in because of gravity, but it's also hot. Yes. And the hot is gonna push out. And so there itself is a kind of hydrostatic equilibrium. The hotness is not coming from fusion, it's just coming from being bathed by this early ultraviolet light. Got it, got it. Understood? Yes. Okay, so there we get into

• 1:13:56Krishna Choudhary?

  a very cool thing,

• 1:13:59Krishna Choudhary?

  which is there's actually a size limit to how big a dark matter halo can get before it starts having stars inside of it. Because imagine a very large dark matter halo, okay? It's got a bunch of matter inside. The very large dark matter halo is gonna start collapsing. The matter inside is big enough that it's gonna start collapsing and it's gonna start creating galaxies. But if it's really small, Yeah. the matter inside is just gonna sort of evaporate out. Because the hotness is too big. It's, sorry, the hotness is too hot. The, the particles are moving too fast for the gravitation of that small, tiny little dark matter halo to keep everything inside. So there, there comes this critical mass threshold.

• 1:14:41Krishna Choudhary?

  And they calculate it, the, the paper actually quotes it to be around 10 to the 9.7 times the mass of the sun. The Milky Way for context is around 10 to the 12. So there's much smaller than the Milky Way. But at that critical mass threshold, the dark matter halo is big enough where it's like keeping the stuff inside, okay? Anything bigger and the stuff that's inside is gonna coalesce to become a galaxy and become stars. Anything smaller and it's not enough and the, and the gas is just gonna leave. But right at that threshold, we've got this sweet spot where the gas is gonna retain inside of my halo. Yes. But it's not enough to create stars and galaxies.

• 1:15:26Krishna Choudhary?

  You see, there's a sweet spot.

• 1:15:29Lester Nare?

  It is, it is this, it is this like buffer line where it can just contain a lot of, this is why, like, I'm thinking about, this is why the cloud metaphor becomes interesting here, because it doesn't, it doesn't, it's at a threshold where it can't materialize ma- like this physical, large-scale matter, the way we think about it. And it's just these gas particles all

• 1:15:49Krishna Choudhary?

  Yeah, just moving around.

• 1:15:50Lester Nare?

  Hanging out.

• 1:15:51Krishna Choudhary?

  Hanging out, yeah. And, and so this, there was a term that was coined in 2017 in monthly notices. It was called a relhic, which is, I think it stands for reionization limited H1 clouds. H1 meaning neutral hydrogen, okay? It was a paper out in monthly notices, and what they said was, there should be these halos right at the critical mass, right? That should be massive enough to retain nu- neutral gas, neutral hydrogen gas, but not massive enough to cool down and condense and form stars.

• 1:16:22Lester Nare?

  Yes, okay, yes.

• 1:16:24Krishna Choudhary?

  And these are called relics. So finding one of these relics would be awesome.

• 1:16:29Lester Nare?

  I just wanna quickly pause and say back engineering, I can't remember what the name for it was. Back engineering, the acronym from what you want it to sound like. Relics, I mean, it's clever.

• 1:16:39Krishna Choudhary?

  That's a good one. Dude, scientists do this all the time. So relics is a really good one. Reionization limited H1 clouds.

• 1:16:47Lester Nare?

  That's pretty good.

• 1:16:47Krishna Choudhary?

  Okay, so finding these relics would be really awesome.

• 1:16:50Lester Nare?

  Yes.

• 1:16:51Krishna Choudhary?

  But finding it is very hard, because this thing has no stars.

• 1:16:55Lester Nare?

  Right, right, so how do you

• 1:16:56Krishna Choudhary?

  The whole point, like, how do we see something? We, we see it using light, but this thing has no stars. Which, dark matter is invisible.

• 1:17:03Lester Nare?

  Which is, yeah, right, which is what makes any kind of discovery around this subject of dark matter extremely difficult.

• 1:17:09Krishna Choudhary?

  Yes.

• 1:17:09Lester Nare?

  Because our, we are only as good as the instruments we build in order to understand the world around us, and we have not yet, maybe.

• 1:17:17Krishna Choudhary?

  Yeah.

• 1:17:17Lester Nare?

  Figured out a lot of this, but maybe.

• 1:17:19Krishna Choudhary?

  Maybe, maybe. And what comes to the rescue is the hydrogen 21 centimeter line.

• 1:17:24Lester Nare?

  Yes.

• 1:17:24Krishna Choudhary?

  Okay, this is our favorite

• 1:17:26Lester Nare?

  Yes.

• 1:17:27Krishna Choudhary?

  line.

• 1:17:27Lester Nare?

  Yes.

• 1:17:28Krishna Choudhary?

  1420 megahertz.

• 1:17:29Lester Nare?

  Yes.

• 1:17:29Krishna Choudhary?

  This is the hyperfine transition, this was used in the Pioneer plaque to tell aliens what our standard time and our standard unit of measurement is for all of the, you know, diagrams that we have on the Pioneer plaque, in case the aliens found the Pioneer plaque and they wanted to see where Earth was. All of the standard measurement on that Pioneer plaque. is made using the hyperfine transition of hydrogen, which is effectively hydrogen has a proton and an electron. If they're spinning parallel to one another versus when they're spinning opposite to one another, that difference in energy corresponds to a particle of light, a photon, that is exactly the wavelength 21 centimeters or around 14, 20 megahertz, right?

• 1:18:15Krishna Choudhary?

  Sidebar, at Princeton Physics, one of my favorite classes was the undergraduate advanced physics lab, where we actually used the hydrogen 21 centimeter line to map out the Milky Way. There was a radio telescope on the roof of the physics department that we could use to point it in different directions. And we could point it at the galactic disk of the Milky Way. And you could see the 21 centimeters. And you could actually figure out what part of the galactic disk was moving away from us versus moving towards us by pointing it in different directions. And that 14, 20 megahertz would be a little bit red shifted or a little bit blue shifted, depending on where you were looking. And what you could do, I mean, there's a lot of error, right?

• 1:18:59Krishna Choudhary?

  Because you don't know exactly where you're pointing. It's kind of a, you know, old disk that they were like, okay, let the undergrads, you know, use it for their lab. So you don't know where it's pointing and the frequency resolution is not that great. But you could actually, like, I remember calculating the rotation curve, which is depending on how far away I am from the galactic center,

• 1:19:21Krishna Choudhary?

  how fast is the stuff moving? And you could actually chart out the galactic rotation curve. And you could see that the galactic rotation curve plateaued. Now, okay, this is not as good as the data that I got. The data that I got had massive error bars and only like eight data points. But what you could see is that it would rise and then it would plateau. And this is characteristic of dark matter. Vera Rubin, the astronomer, actually used these galactic rotation curves to calculate dark matter. Because if you think about it, the farther away you get from a galaxy center, the slower Yes. you should be moving. Right. Because Newton's laws, inverse square law, but Here, the farther you get away, you're still moving at the same rate.

• 1:20:05Krishna Choudhary?

  The only way this is possible is if there's a bunch of invisible matter that's actually pulling on you. That's creating this gravitational force.

• 1:20:12Lester Nare?

  That's sustained, that creates that plateau of sustained, uh, uh, speed because otherwise, like, there's no other external factor that could be.

• 1:20:20Krishna Choudhary?

  Yeah, cuz we don't see any stars. And yet, you're telling me that there's a bunch of new mass that's pulling on you.

• 1:20:26Lester Nare?

  Because you're farther and farther away and your speed has not changed.

• 1:20:28Krishna Choudhary?

  Yeah.

• 1:20:29Lester Nare?

  Even though it should now be slower because you're farther away from the gravitational center.

• 1:20:32Krishna Choudhary?

  Exactly.

• 1:20:33Lester Nare?

  So that gravitational force.

• 1:20:35Krishna Choudhary?

  Must come from something.

• 1:20:36Lester Nare?

  Has to come from something.

• 1:20:37Krishna Choudhary?

  And that's where, sort of, okay, yeah, dark matter, it makes sense. There's a lot of other avenues of research that actually point to dark matter, but this is one of the really cool ways of showing, yeah, it's got, there's gotta be something there that we're not seeing.

• 1:20:49Lester Nare?

  And it's also, like, even for someone who's not as deep in this, it can be relatively intuitive.

• 1:20:53Krishna Choudhary?

  Yeah, yeah, and it's something that an undergrad can figure out, you know?

• 1:20:56Lester Nare?

  Right.

• 1:20:56Krishna Choudhary?

  Using, um, a shitty radio dish on the roof of Jadwin Hall. That was one of my favorite, like, two weeks was actually doing this experiment and then writing the report. Okay, so now let's get back to the story. How do we find these? Well, we look at the 121-centimeter line, right? And the FAST Radio Telescope, which is the 500-meter-aperture spherical telescope, in 2023, it found a region of space that looked kind of weird. This is the radio telescope, it's out in Guizhou, China, just north of Vietnam. It looks kind of like Aracibo, which was out in Puerto Rico. It got damaged by the hurricane and is no longer in operation. But now China has something that's even better.

• 1:21:39Lester Nare?

  That pronunciation was a pretty, pretty good. And where'd you learn that from?

• 1:21:42Krishna Choudhary?

  I, I looked it up. I, I looked it up earlier.

• 1:21:47Krishna Choudhary?

  Yeah, so, um, they've got this telescope, the FAST Radio Telescope. In 2023, it spots this object, okay?

• 1:21:53Lester Nare?

  Yes.

• 1:21:53Krishna Choudhary?

  And this, this object has a bunch of 21-centimeter, 14, 20 Hz coming through. And from all of the previous surveys, there's nothing starry there.

• 1:22:05Lester Nare?

  Right.

• 1:22:05Krishna Choudhary?

  Okay?

• 1:22:06Lester Nare?

  Right.

• 1:22:06Krishna Choudhary?

  So it's, it's a patch of sky where we're getting a bunch of. Hydrogen emission, but there's no real stars there. There's nothing. It's right next to another galaxy, the M94 group. And the recession velocity of this gas. So if you were to look at the redshift of this gas, it's very similar to the recession velocity of 304 kilometers per second of the galaxy. So it's associated to that galaxy because they're both moving away from us at the same speed and they're both right next to each other. So they've got to be sort of tied together. Yes. Right? Okay. So that's the first observational signature, right? The second observational signature comes from the VLA, the Very Large Array. Yes. This is very recent. I think it came out last year.

• 1:22:48Krishna Choudhary?

  It shows that the broadening of that H alpha, that hydrogen line is very close to what we would expect if that hydrogen was thermalized to that UV radiation that I was talking about in the reionization epoch. Because imagine, right? I've got a cloud of hydrogen. It's hot and the temperature is right about at 10 to the 4 Kelvin. Yes. Which is what we calculate the UV radiation to be back then. Yes. And if the temperature is around that, then there's going to be some gas particles that are moving away from us, some gas particle moving towards us. And the spread of that thermal radiation is going to be right around 12 kilometers per second. If you calculate what the thermal radiation should be. And that's exactly what we see.

• 1:23:30Krishna Choudhary?

  The VLA looks at that thing and sees that the spread is about 12 kilometers per second. So again, okay, this is thermalized radiation. Yes. From that reionization epoch. Yes. Okay, very good. Very good. And also, if you look at rotating dwarf galaxies, those dwarf galaxies have a thermal radiation of like 30 to 50 kilometers per second, much faster than what we see. And this is where we get to the Astrophysical Journal Letters paper that we're going to talk about. Okay. The main story is this paper that came out very recently, the first relic? Question mark? They're asking. Yes. Is this cloud nine that we've been looking at for the past two or three years? Yes. Is this finally the thing that we had hypothesized in 2017? And actually, some of the authors of this paper

• 1:24:16Krishna Choudhary?

  were the authors on that original paper that hypothesized the relic. So this guy's been chasing after

• 1:24:21Lester Nare?

  Yes.

• 1:24:22Krishna Choudhary?

  A relic for like three or four years now and he's finally trying to figure out, is this it?

• 1:24:26Lester Nare?

  Yes.

• 1:24:27Krishna Choudhary?

  And what he's done is use the Hubble Space Telescope to point it at that thing and say, there are no stars here.

• 1:24:34Lester Nare?

  Right, right, right, right.

• 1:24:35Krishna Choudhary?

  Okay?

• 1:24:35Lester Nare?

  Yes.

• 1:24:36Krishna Choudhary?

  Unequivocally, because before we have like surveys and they might have missed something. But here we've got a Hubble Space Telescope mission that is looking at this thing for a very long time. Okay, almost five hours total. So it had two 9,000 second exposures at that spot in the sky.

• 1:24:56Lester Nare?

  Yes.

• 1:24:56Krishna Choudhary?

  And it's looking at it with two different filters and those filters are optimized so that it looks for red giant branch stars. Because if there's a dwarf galaxy in there, that dwarf galaxy is probably going to be old and metal poor. So the brightest stars in there are going to be red giants. Okay? And the amount of exposure time that these guys used was enough to see stars that are much fainter than those red giants. So we're not going to miss it.

• 1:25:20Lester Nare?

  Right.

• 1:25:21Krishna Choudhary?

  That's the point. If there's any there, we're not going to miss it.

• 1:25:24Lester Nare?

  The threshold was high enough that it would have captured it.

• 1:25:26Krishna Choudhary?

  It would have captured.

• 1:25:26Lester Nare?

  And it's like, oh, well, you didn't turn.

• 1:25:28Krishna Choudhary?

  Yeah, it's like, no, no, no, we stared at this thing for long enough. If there was something there, we would have seen it. And they only observed three sources that they detected in that region. And then they said, okay, is three a lot? Maybe those three stars are, you know, what I can, can I say that is that a lot? Is that a little? Well, this, this is something that's very clever and something that people do in science all the time. Is they try to measure something and then they say, what could I see just by chance?

• 1:25:52Lester Nare?

  Okay.

• 1:25:53Krishna Choudhary?

  What is my background? Okay.

• 1:25:55Lester Nare?

  Yeah, yeah.

• 1:25:55Krishna Choudhary?

  So they looked and they measured the density of sources in blank regions of that image that are far away from cloud nine. And what they found was the average background is about 3.7 for this, for a similar region. So even just by chance.

• 1:26:08Lester Nare?

  Yes.

• 1:26:08Krishna Choudhary?

  The amount of stuff that I would see in something that's not there. Is about 3.7. So the fact that I'm seeing three is kind of just a roll of the dice.

• 1:26:16Lester Nare?

  Yes.

• 1:26:17Krishna Choudhary?

  You know?

• 1:26:17Lester Nare?

  Yes.

• 1:26:18Krishna Choudhary?

  There's it's not out of.

• 1:26:19Lester Nare?

  It it it it it doesn't it's not out of the ordinary. The fact that there's three there is what all other background space looks like.

• 1:26:27Krishna Choudhary?

  Exactly.

• 1:26:28Lester Nare?

  It's about three things.

• 1:26:28Krishna Choudhary?

  Yeah, yeah, exactly. So if I were to just like, look at a random patch in the sky, I'd see three things in that in that region. But if there's a dwarf galaxy there, I should see a hell of a lot more.

• 1:26:38Lester Nare?

  Yes.

• 1:26:38Krishna Choudhary?

  Than just three.

• 1:26:39Lester Nare?

  Yes.

• 1:26:39Krishna Choudhary?

  Right? They also simulated what it would look like if there was a galaxy there. And what they found was, you know, on the bottom, you you see, okay, what if there's like this many? What if there's a dwarf galaxy that's this big?

• 1:26:52Lester Nare?

  Okay.

• 1:26:53Krishna Choudhary?

  And they went all the way down to really small dwarf galaxy.

• 1:26:56Lester Nare?

  Yes.

• 1:26:56Krishna Choudhary?

  And they said you would still be able to see something.

• 1:26:59Lester Nare?

  Yes.

• 1:26:59Krishna Choudhary?

  Okay, if I do the simulation, I'd be able to see something.

• 1:27:02Lester Nare?

  Yes.

• 1:27:03Krishna Choudhary?

  But I'm not.

• 1:27:03Lester Nare?

  So I'm saying, we're seeing three in real life. If we simulate being very bright and very dim. We would see 25.

• 1:27:11Krishna Choudhary?

  Yeah, we'd see a lot more, but but we're seeing three.

• 1:27:16Krishna Choudhary?

  So it's like, there is nothing there, guys.

• 1:27:17Lester Nare?

  Yes, yes, yes, yes.

• 1:27:19Krishna Choudhary?

  There's nothing there.

• 1:27:20Lester Nare?

  And and a lot of this is it's trying to like, remove, it's trying to one, provide a repeatable path to say, you can look at the same patch of sky.

• 1:27:27Krishna Choudhary?

  Yeah.

• 1:27:28Lester Nare?

  And you can do the same math calculations.

• 1:27:29Krishna Choudhary?

  Yeah.

• 1:27:30Lester Nare?

  And it's not a red dwarf, this, that, and the third, because we've done it and you can repeat it and you would get to the same conclusion.

• 1:27:36Krishna Choudhary?

  Yeah, it'd be hard to get time on the Hubble Space Telescope again to look at the same patches sky. But I mean, there's ground based telescope and then things like that. So you you could do it. And actually, one of the one of the future things that you could do is maybe use the James Webb Space Telescope and look for that same spatch of sky and get into an even deeper stellar mass limit, right? Maybe maybe we're we're not seeing like brown dwarfs or like really cool stars, right?

• 1:27:59Lester Nare?

  Yes.

• 1:28:00Krishna Choudhary?

  That's something that the James Webb Telescope could do. Okay, so the next thing they did was derive the halo mass of this thing. And this is actually kind of cool, because usually when we want to derive the halo mass, the dark matter halo that's in a galaxy, what we look at is stars. We say, okay, how fast is the star moving around?

• 1:28:19Lester Nare?

  Yes.

• 1:28:19Krishna Choudhary?

  Based on that, I can calculate how much mass is inside the stellar orbit.

• 1:28:23Lester Nare?

  Yes.

• 1:28:23Krishna Choudhary?

  And then from that, then I can extrapolate and say, okay, if there's this much mesh in the inside the stellar orbit and the mass function of a of a galactic halo kind of falls off like this, then I can integrate over that entire volume. And then I could say, okay, the total mass of the of the halo is something like this. Here I've got no stars.

• 1:28:42Lester Nare?

  Yeah, so how do you?

• 1:28:43Krishna Choudhary?

  So how do I, what am I gonna do? Right? So what they did was they went back to that hydrostatic equilibrium analogy. And they said, okay, if I've got a gas temperature that's 10 to the 4, and I, and I, and I do it, I can calculate the mass. And the mass is somewhere close to 5 times 10 to the 9 solar masses, which is very close to the 10 to the 9.7 that they were showing earlier. Okay, so they calculate this critical mass and it's right at that threshold, which is again, very good, because that's the whole point of the,

• 1:29:13Lester Nare?

  Right.

• 1:29:13Krishna Choudhary?

  of that theory of like, there's this critical mass. Now we've actually found this critical mass.

• 1:29:17Lester Nare?

  Yes.

• 1:29:18Krishna Choudhary?

  And it matches up.

• 1:29:19Lester Nare?

  Yes.

• 1:29:19Krishna Choudhary?

  Is it unique?

• 1:29:20Lester Nare?

  And just, and just to clarify, the point being, it's this critical mass where it's, it is not going to end up with stars forming because things collapse inwardly. And it's not going to end up with dissipation because things are exiting because it's too hot.

• 1:29:34Krishna Choudhary?

  It's balanced.

• 1:29:34Lester Nare?

  It's just balanced and we're observationally seeing something that is at that line where there should be that balance.

• 1:29:41Krishna Choudhary?

  Exactly.

• 1:29:41Lester Nare?

  Which, and, and that's inevitably like, it kind of is all pointing to this could be the relic.

• 1:29:47Krishna Choudhary?

  It could be the relic.

• 1:29:47Lester Nare?

  Because it's in, it's in the, the Goldilocks zone.

• 1:29:50Krishna Choudhary?

  Yes.

• 1:29:51Lester Nare?

  For, for this dark matter halo concept with no matter inside, but still able to maintain structure without dissipating or expanding.

• 1:29:58Krishna Choudhary?

  Exactly.

• 1:29:58Lester Nare?

  Okay.

• 1:29:58Krishna Choudhary?

  Exactly.

• 1:29:59Lester Nare?

  Yeah.

• 1:30:00Krishna Choudhary?

  And so now the question is, how unique is this thing?

• 1:30:03Lester Nare?

  Right.

• 1:30:03Krishna Choudhary?

  Right?

• 1:30:04Lester Nare?

  Right.

• 1:30:04Krishna Choudhary?

  How unique, because you're saying this is a new celestial object.

• 1:30:07Lester Nare?

  Yes.

• 1:30:08Krishna Choudhary?

  That's a tall order.

• 1:30:09Lester Nare?

  Yes.

• 1:30:09Krishna Choudhary?

  Okay, so here what they've plotted is on the x-axis, the stellar mass of the thing.

• 1:30:14Lester Nare?

  Yes.

• 1:30:15Krishna Choudhary?

  And then on the y-axis is the hydrogen mass. How much hydrogen does it have? Most of the stuff, like the dwarf galaxies, normal galaxies are way to the right.

• 1:30:24Lester Nare?

  The top to the right.

• 1:30:25Krishna Choudhary?

  Yeah.

• 1:30:25Lester Nare?

  They're very big with a lot of hydrogen.

• 1:30:27Krishna Choudhary?

  Yeah, because the, the point is, if you've got a lot of hydrogen, then usually you're gonna have a bunch of stars.

• 1:30:33Lester Nare?

  Mm-hmm.

• 1:30:34Krishna Choudhary?

  Okay, if you've got a lot of intergalactic hydrogen, usually you got a bunch of stars. Here, you don't have a lot of stars, but you got a bunch of hydrogen. That's why it's all the way to the left. And there's nothing like it, right?

• 1:30:45Lester Nare?

  It is, it is, and for people who are listening, and I, we really do encourage you, if you have the opportunity to, to watch the show when you can, or even segments, because the visuals really illustrate it. This is like an order of magnitude.

• 1:30:58Krishna Choudhary?

  Yeah, no, it's actually two orders of magnitude because the the the axes are on a log scale.

• 1:31:02Lester Nare?

  Ah, okay.

• 1:31:03Krishna Choudhary?

  Yeah.

• 1:31:04Lester Nare?

  It is like so.

• 1:31:05Krishna Choudhary?

  It's like so far away.

• 1:31:06Lester Nare?

  Away from anything else to to the point of is it unique? And it's like, well, it doesn't look at them. Look it, look.

• 1:31:12Krishna Choudhary?

  Look, dude, it's like there's nothing around it, right? This is a new type of object and it could be this relic that they've been trying to look for.

• 1:31:20Lester Nare?

  Yes, yes, yes, yes.

• 1:31:21Krishna Choudhary?

  So future observations, what are you gonna do? James Webb Space Telescope, obviously, try to find even cooler stars and really rule out that there's no stars there.

• 1:31:28Lester Nare?

  Yes.

• 1:31:29Krishna Choudhary?

  Um, the other one that I thought was really cool, interesting was the deep H alpha imaging, right? This is the idea of really honing in on that hydrogen line because if there's a bunch of hydrogen there and it's fluorescing, right? Because it's still interacting with all of the radiation that's in the universe, then on the skin of that cloud, you should be able to see H alpha emission that's more prominent than, let's say, on the interior. So you should see like a ring around that cloud if you really stare at it for long enough.

• 1:32:01Lester Nare?

  Fair.

• 1:32:01Krishna Choudhary?

  Right? And from that, you could maybe figure out the substructure of that cloud and how that hydrogen is like moving around, let's say, or like really clumped together.

• 1:32:11Lester Nare?

  Because you would map the outside and because you then have, you know, ideas of how motion and things move in space. And then you could sort of project in in simulations.

• 1:32:20Krishna Choudhary?

  Yeah.

• 1:32:20Lester Nare?

  How would you end up with this?

• 1:32:21Krishna Choudhary?

  Yeah.

• 1:32:22Lester Nare?

  Based on some of the composition.

• 1:32:23Krishna Choudhary?

  Exactly, based on all the stuff that's around and you can you can figure out the ionization rate of that hydrogen and the gas density profile. Um, the other cool thing is there's a new array coming up, the square kilometer array.

• 1:32:36Lester Nare?

  Oh, yes.

• 1:32:37Krishna Choudhary?

  It's gonna be in Australia and it's gonna be in South Africa. It's set to come online in 2027. This is an artist's rendition. They haven't made these yet, okay? But it's gonna be massive.

• 1:32:47Lester Nare?

  This is.

• 1:32:47Krishna Choudhary?

  There's gonna be a bunch. It's gonna be VLA on steroids.

• 1:32:50Lester Nare?

  This is like way bigger than the.

• 1:32:51Krishna Choudhary?

  Yeah, yeah, it's it's gonna be the very large array, but very, very, very large array, the square kilometer array. And it's expected to detect thousands of these relics. So if we can really hone in on how to find a relic using this one that we found.

• 1:33:05Lester Nare?

  Yes.

• 1:33:05Krishna Choudhary?

  Then we could transform the study of. These into a statistical science rather than it's a one off deal.

• 1:33:13Lester Nare?

  This kind of maps conceptually onto the idea of the our previous story where the string theorists created the framework that then was very easily able to be applied to bio.

• 1:33:20Krishna Choudhary?

  Yeah.

• 1:33:21Lester Nare?

  In a new category with new data. This is same same.

• 1:33:23Krishna Choudhary?

  Yeah, this is same same.

• 1:33:24Lester Nare?

  Different, different.

• 1:33:25Krishna Choudhary?

  Yeah.

• 1:33:25Lester Nare?

  But the idea that past work is helping to lower the barrier.

• 1:33:28Krishna Choudhary?

  Yeah, and that's always something that science does, right? Past work is always good for the future.

• 1:33:34Lester Nare?

  We we we love to see compounded value. This this was this was great.

• 1:33:37Krishna Choudhary?

  I thought this was very cool.

• 1:33:39Lester Nare?

  This was very cool.

• 1:33:40Krishna Choudhary?

  Yeah.

• 1:33:40Lester Nare?

  We are going to have our call out for those who have listened to what has been one of our most tightly run pods, especially with our new season two setup. This was great for episode two. If you've listened this far and you've stayed, it's helpful for us to know. So the comment of those for those who stayed is, what do you think the reason is why this was named Cloud Nine? Or any other Cloud Nine related puns?

• 1:34:08Krishna Choudhary?

  Yeah, cuz I don't know why it was really named Cloud Nine.

• 1:34:10Lester Nare?

  You don't know.

• 1:34:10Krishna Choudhary?

  And actually, one thing I do want to shout out is a friend of the pod, Daniel Gilman.

• 1:34:15Lester Nare?

  Yes.

• 1:34:16Krishna Choudhary?

  Actually, asked him about this story.

• 1:34:17Lester Nare?

  Yeah.

• 1:34:18Krishna Choudhary?

  And he connected me with Julio, who's one of the authors of this paper. And we had a really quick email exchange where I had some questions about some of the stuff that was said on this. So, you know, thank you, guys, for actually indulging and like giving me a little bit of your time. Because I know you guys are busy trying to figure out what dark matter is and all this stuff. But very cool paper, Julio.

• 1:34:41Lester Nare?

  Yes, yes. And thank you for the work. And hopefully, if you take a listen to it, we did it justice.

• 1:34:46Krishna Choudhary?

  Yes.

• 1:34:47Lester Nare?

  And.

• 1:34:47Krishna Choudhary?

  Let us know.

• 1:34:48Lester Nare?

  If not, always send over a correction for us, which brings up our next section, which is going to be corrections from last episode.

• 1:34:57Krishna Choudhary?

  Yeah, these aren't that egregious, but you know, as always, we try to stay true to who we are. So if we do make mistakes, we do want to shout them out. Okay, first one, not a science mistake, more of a literature mistake. I said that I was quoting Julius Caesar, the famous Shakespeare play. And I said that the friends Romans countrymen lend me your ears. And also, you know, but Brutus was an honorable man and they're all honorable men. I said that was Augustus, AKA Octavius. No, that was a speech by Mark Antony. At Caesar's funeral. Yes. And it was, it's an amazing speech because that's the speech that finally convinces all of Romans that Brutus is actually a bad guy and maybe killing Caesar was not a good thing.

• 1:35:41Krishna Choudhary?

  The, the second, this is more, not really a correction. This is kind of an interesting tidbit. I was talking to my friend Alan Southworth, who works in energy in California. And he was actually telling me that energy or markets might be an exception to the square root law. Because energy markets don't really work the same way that commodities markets or stock markets or, you know, crypto markets work. Because the demand is like not elastic at all. Like the price and demand stuff is not elastic at all. Because imagine, right? Let's say that like, there's a demand for electricity at a certain rate. Like we're offering, we're offering to buy electricity at a certain rate.

• 1:36:22Krishna Choudhary?

  At that rate, it might only be feasible for certain electricity producers to meet that demand. Because it could be, you know, wind or solar or things like that. Because turning on additional wind turbines is not really that hard. Right, right, right. On the other hand, turning on like nuclear or turning on natural gas, you gotta buy a bunch of natural gas to turn something on, right? So the, it's, it's not so trivial to just be like, oh, you need this much amount of electricity? Let me just go turn on my, you know, gas burner. Yeah, yeah, yeah. So there, that square root law might not actually work. So it might not be truly universal. Universal. And, and that's something that the Tokyo Stock Exchange might not actually account for. Right? Which is, which is what that paper was.

• 1:37:06Krishna Choudhary?

  That paper was very specifically for the Tokyo Stock Exchange. Right. Perhaps it's different for these other types of markets. Great, great insight and note from friend of the pod. Yeah. And then the final one was, I did say that the, there was a Japanese satellite that took that photo of being in between the sun and the earth, taking that photo of the moon coming in between and crashing it. That's not actually true. That's from the Deep Space Climate Observatory, which is a NASA satellite. So we want to give NASA its due credit. That was NASA, not the Japanese. The Americans. Yeah, we're doing it. Whenever something good, really good or really bad is happening, reasonable responses, the Americans.

• 1:37:47Krishna Choudhary?

  Yep, so those are the three corrections.

• 1:37:49Lester Nare?

  Three corrections, and just as a quick reminder, we love comments, we love seeing the back and forth in discussion. Keep commenting, keep sharing. If you work in a lab, bring it into your next lab meeting, just play them a snippet, people will love it, you're gonna sound great and amazing. So, we appreciate the sharing, we're trying to fight the billionaire algorithms as best that we can, and we're trying to provide some mental health benefits to the people of the world by stretching out some of those neurons, getting them exercised. Your feeds are full of enough random nonsense, so those who tune in and listen to the full thing, we really appreciate you. Again, great episode today. We started off, string theory applying to biological networks.

• 1:38:34Krishna Choudhary?

  Yep.

• 1:38:35Lester Nare?

  That was a nice crossover episode, it's like when Power Rangers went on, whatever thingy, you then did Power Rangers from space hooked up with the Power Rangers from Mighty Morphin and.

• 1:38:44Krishna Choudhary?

  Yeah.

• 1:38:45Lester Nare?

  Great first story, we did our rundown, got some fascinating tidbits. Jellyfish sleep, even though they don't have a brain.

• 1:38:52Krishna Choudhary?

  Yeah, that's a cool one.

• 1:38:53Lester Nare?

  And it's because it damages your DNA. And we may have found a genuinely new celestial object in Cloud Nine. More soon, we shall see.

• 1:39:04Krishna Choudhary?

  We shall see.

• 1:39:05Lester Nare?

  A great spectrum of institutions with papers in Nature Communications, Nature and the Astrophysical Journals. I am your host, Lester Nare, joined as always by my co-host and our resident PhD, who is off-center in this broadcast, so we'll make sure that he's more centered.

• 1:39:24Krishna Choudhary?

  I'm sure, I'm sure someone's gonna say some shit.

• 1:39:25Lester Nare?

  Oh, why are you leaning into the camera? Can't we get the camera angle centered?

• 1:39:29Krishna Choudhary?

  Yeah.

• 1:39:30Lester Nare?

  You can't do anything right. We really appreciate you all so much. As always, this is from First Principles.