Daniel and Kelly’s Extraordinary Universe - Can we simulate the Universe?

Episode Date: August 27, 2026

Daniel and Kelly talk about what a recent simulation project can tell us about how the Universe got so clumpy.See omnystudio.com/listener for privacy information.

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wherever you get your podcast. How did the universe get this way? It's got all these beautiful stars and galaxies and quasars and flamingos. and bicycles, why is it this way and not some other way? Do we understand that? How could we possibly explore that question without seeing it happen in real time or making universe-size experiments? That's where the simulation comes in. Computers these days can do your homework and read your emails, but they can also answer tough science questions like, why is the universe this clumpy. Why doesn't it have more stars or more flamingos? Today, we'll dig into how to study the universe on a computer. And yes, of course, we'll talk about whether our universe is someone else's

homework problem. Welcome to Daniel and Kelly's extraordinary, maybe simulated universe. Lee Wienersmith, I study parasites and space, and I sometimes wonder if we live in a simulation, only because of the kinds of nerds I hang out with. You ever wonder if the flamingos are simulated? Whoa. I hope they are. Actually, I hope they're robots, you know, collecting data on us. Nobody would suspect it. Hi, I'm Daniel. I'm a particle physicist. I write books about aliens, and I make heavy, heavy use of simulations in my science. Oh, I have done some simulations for my work as well.

But my question for you, Daniel, is, if tomorrow you've received, in-combed, Controvertible. Oh, good word. Incontravertible. That was... Inspellable. If you found out, you definitely live in a simulation. 100%. What would you change about your life?

Wow. Am I given access to the source code so I can change? Or is it just the kind of changes one could normally make, like, eat a Sunday every day? Yes, that kind of thing. All right. So I don't get godlike powers in this question, Kelly? Nope. Nope.

Sorry. You'd kill us all. You'd bring the aliens and you'd trade us all for parts. That's true. No, if I had access to the source code, I wouldn't need the aliens. I'd have the source code. But it's a good question. You know, if I'm limited to living in this universe anyway with its rules,

then I guess I would probably make a lot of the same decisions I make. But really your question is like, yeah, but you're always saying if you understood the context of our lives, it could change how you live your life. I'm always saying that, which is true. So if I got a big update on the context of our lives, would that make me change how I lived it? I don't think so. I think I live anyway with the uncertainty of, are the people around me actually real? Do they have a first person experience?

Or are they philosophical zombies? And I don't think the answer matters to me because I feel like I love them and I feel their pain and their joy. And that matters to me, even if they're philosophical zombies or real flesh and blood creatures or simulation artists. facts. All right. How's that for an answer? Yeah, no, that's a good answer. It also revealed that you think about stuff like this often, it sounds like, I don't.

I'm just like, I'm doing what I need to do. Here's my to do list. I got to get through it. Simulation or not, I want to get this stuff done. I don't know. I think you are. You just don't realize it. Like, aren't you always thinking about like, what are my goats feeling?

Did they want to be crushed or not want to be crushed? Oh, no. Back to that. But does that, would that matter? I guess I'm not thinking, is there pain real or are we all just source code? I'm thinking this is a real universe that I live in and there are decisions I need to make that will, you know, determine whether or not I look back at the end of my life and think, did I live a good life or not? But I never think, you know, the source code is making these decisions or something. All right.

Well, if you found out that your goats were just source code, would you treat them differently? No. No, it's a really good simulation. I think I might enjoy life less if I knew that. So I think I'd be like, all right, take that information away from me if you can. I'm just going on and enjoying doing what I'm doing because I can't get out of this simulation. And so I'm just moving forward. All right. Well, today in the episode, we're not just talking about simulating Kelly's goats. And we're not talking about simulating particles of the Large Hadron Collider. We're talking about simulating the whole universe. Can we, in fact, describe the whole universe? Why would anybody ever want to? What can we learn from it? How close are we to being able to do this? And this question is not just something Daniel sits around and thinks about while not smoking banana peels, while Kelly is blissfully free of these philosophical questions.

I think we've discovered that I'm not as philosophically curious as you are. This isn't a good thing. But the good thing is that if we do live in a simulation, we live in a simulation filled with curious listeners who share their thoughts and hopes and dreams and questions with us. That's true. And in real or simulated Ann Arbor is Joe, who sent me this question about a recent universe simulation advance. Here's the question from Joe. Hi, Daniel and Kelly, but unfortunately, mostly Daniel. This is Joe from Ann Arbor, and I wanted to know more about.

the Flamingo project done by the Virgo Consortium. They apparently used some wild amount of computing power to simulate the evolution of the universe, and it includes both gravitation and hydrodynamics. Apparently, there are some results about clumpiness that it can help answer, but nothing went on to enough detail to satisfy my curiosity. Could you help?

So Joe was talking about a really exciting new result, hilariously called Flamingo, in another example of tortured science acronyms. Oh, no, it's an acronym. I didn't realize that from the outline. You're going to have to tell what the acronym stands for when we get to it. But congratulations, physicists. I know they called the flamingo.

It has nothing to do with flamingos. Oh, I thought surely the universe is pink. There was going to be something in there. And, you know, I reached out to our listeners to ask them about similarity in the universe, and I thought about including flamingo in the question, but I was, pretty sure I was just going to lead them all astray because the science actually has nothing to do with pink birds at each shrimp. And they trust us so we shouldn't lead them astray.

That's right. Yes. Instead, I asked folks the question behind the question, which is, can we simulate the whole universe? Think about it for a minute. And if you would like to add your voice to this chorus of curious contributors, we would love to have you please write to us to questions at Daniel and Kelly.org. And you'll get a bunch of weird questions in your inbox that you can either respond to or not. Up to you.

In the meantime, think about it for yourself for a minute. Do you think it's possible to simulate the whole universe? Here's what our clever listeners had to say. I guess the question is, how good do you want the simulation to be? I strongly doubt that we can actually simulate the entire universe with any medium smaller than a universe. Jess, I think it would be possible with a supercomputer. Could any advanced civilization simulate a universe, then maybe yes. Maybe we do live in a simulated universe.

One, we don't even know what the whole universe is. Two, starting conditions. We've got to jump in at some point to get the simulation right. And three, this is just too much. Too much. We would need to simulate the simulation that we are running. So it will be an end of the recursion. things have to be less complicated in the simulation than they are in reality?

It would be something like Space Engine, the game. No, we can't simulate the whole universe because we don't know anything about most of the universe. Probably not with the technology humans have right now. Well, the listener's gut reaction pretty much agrees. I was going to say pretty much agrees with mine, but then someone said yes on a supercomputer. And I am not convinced that we have the computing power

to simulate the entire universe. But maybe, maybe the question is like, on what level? Like, are you just simulating the movement of some planets? Is that what you mean? Or are we talking about, like, down to the level of atoms? Because that sounds nuts. Even on a supercomputer? What about a super duper computer?

Whoa. Whoa. I don't. I don't know. Do we have super duper computers yet? How far out is that technology, Daniel? I don't know, but now I want to write a grand proposal and use that phrase. These superdupertubers.

I would fund that grant, no doubt. Or maybe, you know, hyper computers. What other prefixes could be had? Hyper super duper. Hyper super duper fragileistic. Computers. Queen of the Latin names. I thought you were going to go with something more scientific sounding, but I like that.

No, no, I'm having fun this morning. So let's start by talking about what is a simulation. We've talked about this before, but I think. Let's do like a brief explanation of what a simulation is and then dig into like what level of detail is really being asked for in this question. Yeah, I think that's a good idea because you already raised a lot of the issues that we need to tackle. You know, how much do you need to simulate? Why do you do it? Et cetera, et cetera.

So what is the simulation? It's some kind of program run on a computer that uses usually step-by-step methods to describe the approximate, very keyword, approximate behavior of a math. mathematical model, which resembles a physical system. Okay. So let's say, for example, you want to describe a ball getting thrown across your backyard, and you want to know where it's going to land, you know, and so you can change the velocity or change the angle, and you want to know where is this ball going to go. It's going to go into my friend's hand, or am I going to miss them or something.

So the first thing you can do is say, well, I'm going to make it very, very simple. You know, there's just gravity and there's just the ball, and there's no air resistance or anything, and in which case you can just calculate it. You can use Newton's laws. You can say F equals MA. It's a very simple problem. Boom, you can do it in one step. You can do it on a computer.

You can also just do it on pencil and paper. Either way, it's still technically a simulation because you've taken your physical system, the ball and the backyard, and you described it with a mathematical model. You said there's mass, there's gravity, there's a few components. Here's how they interact.

There are rules for how things happen. And then you've used your mathematical model, model to make a prediction about the actual physical system, the thing in your backyard. So the mathematical model is the simulation of the thing in your backyard. And if everything is very, very simple, the model can be very, very simple. Good so far? We are. All right. So maybe you say, well, but it gets it wrong. It doesn't exactly drop where I predict. You think, well, that's probably because my simulation is too simple. I'm assuming there's no air resistance, that there's no wind, that this is a very simple problem. And so if I want a more accurate,

answer, then I add more to my simulation. And some people might not. They say, I'm fine with this answer. This is all I need. And already we've learned something crucial, which is how much detail you add, how much accuracy you have depends on the question you're asking. And if you are asking a question that doesn't need to be very, very precise, then you're done. You don't need to add bells and whistles and simulate everything in great detail. But if somebody really wants a super precise description for whatever reason, then they got to add more. And in physics, we're always playing this game. We're saying, what's the simplest useful model? Because adding more costs resources and brain power and everything. So let's say you needed more, right? You wanted to also include air resistance.

Well, you can add that to Newton's laws, and you can make that work, and you have a more complicated equation to solve, but you can still get it to work. But what if you want to also add, like, the pattern of wind across your backyard? And you set up a bunch of sensors to measure, like exactly what is the flow of wind across my backyard and you measure this in great detail. You want to incorporate that into your model. Well, now you don't have a simple equation anymore, but you can still solve something. You can say, well, I'm going to move the ball one centimeter at a time and I'm going to count for the wind at that location. I'm going to let it push.

And so I don't have a single equation that's going to describe what happens to the ball across the whole backyard, but I can slice it in time and solve an approximate version of it each step. and I can measure where the ball goes and I can correct it. And I have a very elaborate, very complicated simulation of something pretty simple, just throwing a ball across your backyard. And so all of those are simulations, but they're at varying levels of fidelity. The model becomes more and more accurate, becomes closer and closer to the physical system. And so its answers are more precise.

Got it. And is every mathematical model a simulation? I think a simulation is using the mathematical model to make a prediction. and that can be on a computer, but it can also be a physical system itself, right? Like you can build a little model, like a physical model of like how water flows in a river. You can make a miniature version of it,

and you can pour water into it and see what happens, right? That's a simulation. Like you can simulate the Hoover Dam, you know, with a small version of it before you build it to see like, hmm, have I misunderstood anything? Is there anything I'm missing? Right? and so you can use the universe to simulate other parts of the universe.

Or you can do it on a computer or you can do it on pencil and paper, which is how they used to do it. Like in the beginning, when they were trying to predict the weather, it was like a whole bunch of calculations, pencil and paper. And to predict the weather six hours in advance took like six weeks. Which is not helpful anymore. And folks should check out the amazing weather episode that you did to see how we ended up getting a lot better at that.

Yeah. And there's other examples like sometimes we want to understand what happens in black holes. There's certain relationships between what happens around a black hole and what happens in certain fluids that are spinning really, really fast. And so, for example, people have made, like, sonic black holes as an analog of black holes in order to try to understand black holes. They're not actual black holes you've built in the laboratory, not yet, unfortunately. Unfortunately. Oh, my gosh, Daniel. You are looking for ways to kill us.

No, I just want to learn about the universe, you know. Humans be darned. I will learn about the universe. consequences irrelevant, but you can build something which has a mathematical relationship. Like if the mathematics of your fluids and sound waves are similar to the mathematics of general relativity, then by building this system, you can learn something about black holes as described by general relativity. So you're always making this analogy. You're saying, I want to learn about X. I'm going to build system Y, which is similar to it in the ways that's important

to me. But you're never going to get all the details right. Even if you describe the air molecules in your backyard, there's still something. You don't know. There's uncertainty in the measurements of those things. You're making assumptions about how you move your simulation forward in time. There's always going to be some imprecision. You can never get everything exactly right. But often you don't have to because you're asking a science question. You're not just like, I must describe the universe at the most granular level. People don't simulate just to simulate. People simulate to answer questions like how much dark matter do we need in the universe or how important is air resistance to throwing a ball or can I build this dam or will it collapse? Or what happens if I throw a goat into a black hole,

right? People have a science question. They want an answer to and they use simulation to answer that question. No, no spigetifying my goats. Goats like spaghetti, Kelly. That's what I hear. Do they? Who are you talking to? Because my goats are very picky eaters. What? I thought goats would eat anything. Don't they eat like cans and carb bumpers and stuff? This is why stereotypes are harmful, Daniel. Oh my gosh. Wow. You can't just drop them in a junkyard and watch them thrive and flourish. No, they don't eat cans. I've just been slandering goats.

Oh, my gosh. I mean, that's what I've been saying. But so, okay, so what you're saying is we can specify narrow questions. We can answer them accurately. We decide what we want to have in the model and what we leave out. And sometimes we even leave out important stuff just because we're like, well, you know what? We don't have enough computing power. Yes.

What would you say is like the biggest simulation or biggest thing we've ever tried to simulate? Bigger than the universe? I don't know. Or most detailed. You know, in particle physics, we simulate all sorts of stuff down to the particle level. You know, what happens when a muon slams into our detector and it's made of copper and there's layers of uranium there? We model all of those details down to the atom. The muon emits a photon, which then slams into a nucleus. which then emits this particle, which then emits that particle.

And that's why our simulations are so computationally expensive and so slow. It can take like tens of minutes to simulate an individual collision at the Large Hadron Collider because we've got to track all those details because we're interested in like, well, how many photons ended up on this one part of this one detector? Because that's what we measure. And we want to compare the simulations to reality. And we can't skip any details. So for my point of view, those are some of the most involved simulations.

But I'm also really in love with these physical simulation models. Like there's this working hydraulic scale model of the San Francisco Bay and the San Joaquin River Delta System that the Army Corps of Engineers built in the 50s to study engineering interventions in the bay like what to build and how to change the currents and stuff like that. It's super awesome. Oh, I worked on the Sacramento-San-Wrudeau-Delta Systems Pod Problem. Oh my gosh, what's the problem? The pod problem is pelagic organismal decline. There are all of these...

Oh, there's nothing to do with podcasts? No, I know. Like we don't have enough podcasts about the river system? I mean, probably we could use a podcast about the river system. But no, the fish that lived in like the big open water area that used to dominate this ecosystem. But over time, they started disappearing and people were trying to figure out what was the cause of the loss of all of these native fish. And I was trying to figure out if the problem was that a bunch of... of invasive species had been added to the system.

And so now you've got these invasive plants and largemouth bass and all these other fish in the system that didn't use to belong there. And so I spent a significant amount of my Ph.D. on boats riding around the River Delta system. And I kind of on some of those days would have preferred if I could have just been moving a boat around a little hydraulic model. And being like, this is the same thing. Yeah. And a simulation could really help you in that kind of situation. You have a hypothesis like, I think this is because of this endangered system. How would you test that hypothesis? Well, if you had access to a simulation of the system and you could, in simulation,

inject your invasive species and see what happens and see if it lines up with reality, then you could confirm or reject that hypothesis without doing any actual physical experiments. These are like virtual experiments that help us understand what might be happening in the real world. Well, and ecologists do this kind of thing all the time. And just like you were saying, you know, the goal is to try to figure out what are the important features of the system that we need to understand better? What can we ignore? How can we sort of tinker with the system to get it in a better state? Yeah, these are all things ecologists do as well. And those are great examples of the kind of questions you can ask of a simulation. The reason a simulation is useful is that you have higher level questions, emergent questions, right? Like, why did this species die off? Or where do they? this ball go, and you don't know how to model that directly, you can't, like, write down equations to tell you exactly what's going to happen. It's too complicated. Instead, what you can do is model the lower-level stuff. This fish will eat that fish. This air molecule will bounce off the

ball. That lower-level stuff we can model. And then if we can describe enough of it, we hope that the higher-level questions emerge from that system, right? So, simulation is very useful when you have a handle on the lower-level details, and you have questions about the bigger picture. but you don't have equations that describe it. In the same way that like on the weather episode, we talked about we're interested in, is that hurricane going to hit Alabama? Yes or no. And we don't have an equation that can tell us that.

Instead, we have equations that tell us what water droplets do in certain velocities of wind. So we can model a bunch of water droplets in simulation and get answers to the bigger questions that we have. But in order to do that, simulation only works when you have two things. One, you understand the lower level details like you can. describe the physics of water droplets or air molecules or, you know, fish eating fish or whatever. And this is probably what Kelly was involved in, the data, right? This only works. You can only describe what's happening in your backyard if you know the wind patterns.

You can only describe what's happening in your river delta if you know the crucial information, the shapes of it, the current flows, where the fish are, for example. So you need the initial conditions and you need to know how things evolve. Those are two crucial ingredients in making a simulation. Well, I managed to get fish into this conversation, so I know that no one is simulating being interested in what we're talking about. And so let's take a break. And when we get back, we will talk more about simulations. Bill. Connection is everything.

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Okay, so we are talking about simulations. And Daniel, I have heard that quantum computers are going to help us. simulate things in better ways. Quantum computers, I think when you listen to pop articles about quantum computers, they're able to do all kinds of amazing things, and I'm not actually sure that they're able to do

all of the things that they are said to be able to do. And so... You don't think they can quantum balance your checkbook? I do a fine job at quite... You know what? Actually, I don't have a checkbook. I just every once in a while open up my bank account, and I'm like, that's what's happening there. You're like, oh, I hope the number's not negative. Yay, it's not negative.

It's not negative. We don't buy a lot of stuff. But anyway, so, okay, so would quantum computing make it easier for us to simulate the universe, or is it essentially no different than a classical computer in this regard? I mean, yes and no. The no is because anything a quantum computer can do, a classical computer can also do, right? So there's no problems that quantum computers can solve, that classical computers can't. Can they do it faster? And so not in general. It's not like quantum computers are faster at everything than classical computers. You know, there are a few cases where we think quantum computers could be faster than classical computers,

but so far those are like really, really specialized cases, you know, like one factoring algorithm here or another mathematical algorithm there. So so far it's still like at the, ooh, this would be cool and maybe it's the harbinger of things to come and eventually everybody will have a quantum computer on their wrist. That would be cool. And it's exciting because it's like another way to do computing, which is, fascinating from a philosophical point of view, but practically it's not going to speed up our simulations of the Large Hadron Collider. It's not going to help us predict the weather. It's not going to balance your checkbook. There is one way in which it's cool. And this is one of the initial, I think, impetus is for quantum computing, which is, look, a lot of the physics we do is quantum,

right? And so doesn't it make more sense to have a quantum computer to model quantum processes rather than a classical computer? You know, in some sense, the universe is quantum. So why are we building classical computers onto it to then model quantum processes? And so, you know, there are ideas about building mini quantum systems to describe those quantum systems, the same way like you build a mini river delta with real water to describe the real water in the actual river delta. You could build a little mini quantum system that has quantum properties and help you model a bigger or more complicated quantum system you're interested in. But it's not a general overall simulation. it's now going to be instantaneous or anything like that.

Okay. And just to sort of bottom line, the problem that we're trying to solve here, when someone says we're going to simulate the universe, do they mean, like, at the quantum level? Like everything at the quantum level and up? Is that what you would need to create a simulated universe? Or could you create a simulation at, like, a higher level, but just let the quantum stuff happen to produce the higher level stuff without modeling it?

Does that make sense? Yeah. Well, the answer is. always you're doing a simulation to answer a specific question. Nobody's out there being like, let's simulate the whole universe, man, just because somebody would be massively complicated and inexpensive. But isn't that what we're talking about today? We're not talking about trying to simulate the whole universe? I mean it. No, well, we are because we ask questions about the universe, like we ask, how old is the universe, or how did galaxies form, and will they continue to form?

And why are galaxies distributed this way and that way? Those are questions about the universe. And so to answer those questions, we need a simulation of the universe. That simulation doesn't have to include everything in the universe because some details about the universe don't change the answers to that. Like, if you bought your kid a red bicycle or a blue bicycle for their ninth birthday, doesn't change the answer to, is Andromeda going to smash into the Milky Way? Or why is this galaxy bigger than the other galaxy? Your kid's bike is awesome, but really it's kind of irrelevant on the cosmic scale. And in the same way, lots of stuff is irrelevant. And so we don't include it in the simulation because we don't need it to answer that question.

So there's no general purpose simulations. It's just like simulate everything just because we're always building simulations to answer science questions. And often it's the only way we can answer a question. Like you want to know what's going on inside the sun or at the heart of neutron stars? We can't yet observe that stuff. And so the only way to think about it is using simulations. Also, because we don't have equations that describe it, there's no like F-equals M-A emergent physics that describes the turbulence inside the sun. And so we can simulate it and build models of it, but we don't have any exact solutions.

Right, but that's the human limitation. If we were living in a simulation created by aliens much smarter than us, would their simulation have to include everything from the quantum scale to your son's bike? If we're living in a simulation run by super intelligent or just hilarious aliens, then whatever their simulation includes is our reality. And so really then you're asking me, like, are they modeling everything down to the quantum level? Well, like, if that exists, then they're modeling it, assuming our universe is a simulation, right? Okay. Yeah, I think so. So the answer to that is yes. But we can dig into that question at the very end after we talk about the flammuzzi. What? All right, we're back to animals. No, I know. You told me it's a tortured acronym. What is the tortured acronym here?

So the Flamingo Project stands for full hydro, large scale structure simulations with all sky mapping for the interpretation of next generation observations. Holy cow. Wait, but I thought you said full hydros. Was it the Flamingo project? And I lost track of the rest of it after that. No, no, you can just pick a letter. from your name to make an acronym in physics, apparently. F from full hydro, L from large scale structure simulations, with A from all sky, M from mapping, for the I from interpretation of G from generation, O from observations. Flamingo, I told you, has nothing to do with birds.

Wow, okay, nothing to do with birds. And I think that actually wins the most tortured acronym that I have come across award. But anyway, I'm glad that they had animals on the brain. I love an acronym that's tortured, but then also manages to actually be related to the topic at hand. You know, like, if it's just totally irrelevant, then I don't think it's very impressive. But, too, Flamingo doesn't have anything to do with the topic at hand, right? No.

Absolutely nothing. Other than there are flamingos in the universe and they are simulating the universe, but that's a stretch. Okay, fair enough. And they're probably one of the better parts of this universe because who doesn't love a flamingo? All right. So what is this project working on? This project wants to understand how do the universe get the way that it is? Like, we look out in the universe and we see there's structure there, right?

There are stars, there are galaxies, there are clusters of galaxies, and there's dark matter laying behind all of it, right? Everywhere there's a galaxy almost, there's a big halo of dark matter surrounding it. There's dark matter between the galaxies. There's streams of matter and dark matter between clusters of galaxies. How did everything get into this configuration? Well, we have an idea about that. We have these theories that 14 billion years ago-ish, the universe was filled with a hot, dense plasma with small fluctuations in density, and we say,

well, gravity. Gravity clumped those things together, a little bit of density here, and a little bit of density there, had more gravity, which pulled on more things. Dot, dot, dot, dot, you get galaxies. Well, what we really want to do is flesh out the dot, dot, dot, dot, dot part, and understand, does our physics predict that when you go from a universe filled with plasma with slight over densities and under densities, that you get the large-scale structure that we see? And if we run the simulation and it disagrees, that tells you that either something is wrong with our picture of the initial conditions of the universe or something is wrong with our understanding of how things evolve in time.

Super duper useful, right? Because it gives you a handle on something that's going on in the universe. Yeah, but just to root, what does agreement look like? Like, would agreement mean like every star, for example, needs to be in exactly a predictable place? Or just like sort of it generally has the same shape? Like what would we consider to be a model that had simulated the universe? Great question. And I think a lot of people imagine that when you simulate in the universe, you're predicting the outcome for our exact universe, that you should like be able to predict exactly the stars in the sky and this galaxy and that galaxy.

And in principle, you might be able to do that if you knew the exact initial conditions of our exact universe, like where every particle was 14 billion years ago and where all the densities were, et cetera. You might be able to do that. We don't know that specifically. We only know it statistically. Like we know, on average, what was the density of stuff? How big were the fluctuations, right? We can't see the whole early universe. We can look out in the sky and we can see light from the very early universe. But we're just getting one slice of that light. You know, the universe is 14 billion years old, and so we're getting the light that has just now arrived to us from that plasma in every direction. Imagine like a huge but very thin shell of plasma really far away, 14 billion years ago, all emitting light towards where we are now. We're here, it arrives here.

So we see that little slice of the universe. And as time goes on, we see a different slice. That shell grows as the time goes on. but we never see the whole initial slice of the universe. So we don't know enough to predict our specific universe. Instead, what agreement looks like is, well, here's what we think the distribution of stuff looked like statistically. So do we get galaxies of the same size?

Do we get galaxies in the same kind of arrangements? Not specifically this galaxy and that galaxy, but like, what's the distribution of galaxy sizes? What's the typical distance between galaxies? This kind of stuff. So it's more a statistical comparison than a specific one. which is kind of unfortunate. It would be awesome to simulate our exact universe and be like, look, that's where Kelly appears. Yeah, but, you know, it would not make it more useful to know where Kelly appears, even if it would make it more awesome to know where Kelly appears.

But it does allow you to ask really cool questions, like, what would happen if you had a universe without dark matter? Like, take the universe as we know it, fill it with the photons and the protons and the neutrons that we think we're there. but don't put in the dark matter. What happens? Well, we can answer that question. You do that simulation and you don't get galaxies. Like 14 billion years is not enough time for gravity to pull protons and neutrons together to make stars and galaxies without the help of the gravity from dark matter.

So that's already like a really interesting result. It says that the structure we see, the fact that we have galaxies and stars, is itself evidence for dark matter or evidence for something out there helping pull stuff together because the visible matter doesn't have enough gravity to do it on its own. Okay. And so I think that's really cool because it shows you the power of simulations. It says if your initial conditions and the rules to evolve it are inconsistent with what we see, right, then something is wrong with one of those two. And so if you put in no dark matter and you run the rules, you get something which looks very much not like our universe, so that's probably wrong. But if you put dark matter in, then you do see formation of

galaxies. Dark matter itself clumps. Remember, there's a lot more dark matter than anything else, and it pulls those stars together, and it pulls those galaxies together. And so if you put in the dark matter we think was there, and it's measured independently in like nine other ways, then you get the formation of structure just like the structure that we see. And I assume this is something we've simulated before the Flamingo Project. Is that right? Okay. That's right. And people have played with it. They're like, well, what if we put in more dark matter? Let's double the amount of dark matter.

What happens? Well, the universe collapses. There's too much gravity and things get squished, and it doesn't look like our universe. So you can use this to measure the amount of dark matter in our universe by tuning the simulation, the initial conditions, until you get an outcome that matches what we're seeing today. Right? It's like if you didn't know how much salt Zach put in dinner, but you ate the dinner. And you were like, okay, let me try it. I'm going to try it without salt.

No, it comes out bland. I'm going to try it with a pound of salt. No, that comes out too salty. And you refine it, comparing your experiments to your memory of dinner that Zach made until you figure out how much salt Zach put in his dinner. It's just like that with dark matter in the universe. Got it. Okay.

Let's take a break. And when we get back, we will find out what the Flamingo project did in particular to create a newsworthy simulation. Get Bell Pure Fiber Internet with Crave Netflix and Disney Plus from $94 a month. Price guaranteed for two years on internet with a two-year term and auto pay credit. Visit bell.ca for details and to check availability. Bell, connection is everything. Hey, this is Hayes Davenport. And Sean Clements.

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What is the surprise woman? Actually, you think is the straight man is actually the one who's acting weird. Adam Scott. this entire time you've been expecting Adam Sandler to come to visit the show I would never

let go of that I have I would never set expectations for something like that to happen if the universe allows for something like that to happen I'm open to it I'm always going to accept you know Danny McBride

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All right, Ann, we're back. And Daniel, in closing, I said that this was a newsworthy simulation. But maybe it only appears newsworthy to me because it's got the word flamingo in it. And so I feel like it should be in the news because that's awesome. Did this simulation tend to make the news? Well, I mean, the news that I read, of course. And the emails I get from listeners, I definitely heard a lot about it. It was in sky and telescope and a bunch of other Popside places.

Okay, cool. It was a step forward. I don't always understand why a particular piece of science gets a bunch of attention. And another piece of science, I think it's really cool, doesn't. But, you know, that's just the way the popsai cookie crumbles. But this is legitimately a really cool piece of science, one because it's huge. Like, they took on a really big task. They wanted to simulate a big chunk of the universe.

So not the whole universe, but they described a cube of universe with sides 10 billion light years on a side. Wow. So, like, that's a lot of stuff. And in that are a lot of particles. They couldn't model all of them with their computing budget. What they could do is describe particles with masses like 130 million times the mass of our sun. So basically, like, they could zoom into, like, mini galaxies. They couldn't describe individual stars or individual planets or flamingos or podcasts.

They can only have granularity down to like mini galaxies. But in a cube of universe that big, there's like 300 billion of those. So that's what they described, like 300 billion clumps of matter, each about as massive as a mini galaxy. And for reference, do you have like a sense for how much of an advance in like specificity this is relative to prior models? This is a big chunk of compute. but the real step forward is not that they zoomed in more or they had a bigger slice of the universe. The specificity is that they made the rules much more realistic. So previous simulations were like, let's model the dark matter and we'll also put the protons in,

but we won't let the protons interact with each other because, ooh, that's really complicated. Like dark matter is very simple. It doesn't really interact with itself. It's just gravity and it flows around and it clumps and we can handle that. Protons are hard because they have the strong interaction. and they have the weak interaction, and they generate other kinds of particles, which are really complicated,

and we know because we eat them every day, and that's why they're delicious, because of all their complexity. And so most simulations have the atoms, the barons in them, but don't let them interact, because that's too complicated. And so what the Flamingo Project did

was they included the barons and their physics. So they have things like gas flows and hydrodynamics, and how do winds get generated? All these things are, really important for the structure of galaxies. You know, like when there's massive radiation from the central black hole that blows out stars in the centers of galaxies, and it changes how stars form in galaxies. And you have like active galactic nuclei that can shape the structure of nearby clusters. So they included all of those details in the simulation, and they included neutrinos.

So previous simulations at this scale hadn't included this barionic physics, like, you know, all the interactions between protons or the neutrinos. Okay. Awesome. That seems like quite a big step forward. Did they have access to a hyper, super duper computer that we didn't have access to before? They got time on a very fragilistic computer at Durham University. They ran it on 30,000 CPUs using 50 million compute hours.

So this is a computer that existed. It wasn't built specifically for them, but they got a bunch of time on it. So, you know, people always want time on these computers. it's very valuable. And you're competing with folks who like want to simulate hurricanes or want to simulate nuclear weapons or want to simulate other stuff. Okay. So it was awesome that they got all this compute time to answer this question because there are really interesting open puzzles. Like we talked about modeling how dark matter changes the structure of the universe and we described it as if it sort of works.

And it does mostly work and it's cool. But the more we study it, the more we see discrepancies. just like when we were talking about throwing a ball and you use your first model and it mostly works, but then you notice, it's not exactly right. What are we missing? As we get more and more specific, we can look more and more carefully at the discrepancies and wonder, what are we missing? And you've probably heard of the Hubble tension, you know, this discrepancy between how rapidly the universe was expanding at early times, like 14 billion years ago, as measured in the cosmic microwave background radiation, and how rapidly it seems to be expanding today as measured by like supernipers,

Nova and other things, there are other tensions in cosmology, places where our models of the universe don't quite agree with our observations. And one of them is called the S-8 tension. It's not as sexy or doesn't get as much pressed as the Hubble tension, but it's really important. This S-8 is a measurement of like how clumpy is the universe? Has stuff pulled together into big clumps or is it still mostly spread out? And just like with the Hubble tension, we have two measurements from the C&B and from late times, and those disagree. So the C&B says the universe was clumpier. And the late time says, no, the universe was less clumpy.

And we want to understand which of these measurements is wrong. Can you build a model of the universe that's compatible with both of them? So far we haven't been able to. And so this simulation thought, well, let's study this question. Let's include all the physics that we can because we know that protons and neutrinos affect clumpiness. And they ran 28 slightly different simulations, tweaking cosmic parameters, like the dark matter fraction or how massive is the neutrino or how important are these active galactic nuclei, this hydrodynamics of the barions we were talking about, how big are stars when

they're formed typically, you know, which percentages of stars fall in which mass ranges. They ran 28 different versions to see if they could understand this problem. I bet they agonized over the 28 different simulations. I remember when I used to do simulations, the hardest part was figuring out what part of the parameter space am I going to explore? And, yeah, trying to figure out, like, the, you know, values of the variables for those different simulations was probably painstakingly done. Oh, you know, they argued.

They had meetings. They had disagreements. More meetings. Yeah, people suggested stuff. Other people asked their suggestions, you know, there was grumbling and teet gnashing. And, you know, these are important decisions because later when you get the results, you're like, ooh, that's interesting. I wish we had another point with this other tweaked value.

But, you know, you used up all your time. Sorry. Yep. Or one answer comes out really boring. You're like, well, that was a big waste of a zillion hours of computing. Thanks, Joe. Great idea, Joe. So, yeah, exactly.

It's definitely very painful when that happens. But they ran these simulations. And what they found is that the barionic effects, including all these protons, does change the clumpiness, but not enough to explain this S-8 tension. And so the question they went in with was, does adding the protons making the simulation more realistic, does this solve the problem? It's the problem just an artifact of our simulation being too simplistic and not including all the physics we love and no. And the answer to the question is no. It's not an artifact of the simulation being too simplistic in this one way. So that would have been very cool if it had solved that problem.

Like, oh, look, the universe now makes sense. But now it's very cool because it means, oh, the universe doesn't fully. makes sense, which means there's something to learn, right? Either maybe there's some kind of dark matter that has self-interaction that's not being included in these models, right? We describe usually dark matter just as having gravity and no other kind of interaction, but maybe dark matter is complicated and there's lots of different kinds of it and some of it has interesting interactions with other kinds and that's not being included in the model and that's why the models don't agree with reality. That's just like one hypothesis. So there's a lot still to learn here. It's such a

a roller coaster doing science? Because, like, you know, obviously you set out to do an experiment. You kind of think you know what the result's going to be, or at least that's what you say in your grant. And if you get the result, you're like, what? Yay! But then if you don't get the result, you're like, but this could be equally as interesting or maybe even more interesting, especially if it sets you on, like, gives you a little bit

of a hint for what you were maybe missing that you should think more about. But like, yeah, so this sounds like something where the result would have been fascinating no matter what. Yeah, exactly. I think it made news because it's a big, awesome piece of computing, like, wow, what a cool project. But unfortunately, it didn't get the answer they were hoping for. But, you know, we learned something. We crossed something off of our list of hypotheses, and we're still on the hunt to understand the universe and figure out why it is exactly as clumpy as it is today. I think it's wonderful. I don't think it's too clumpy. I don't think it's overly clumped. I don't think it's underclumped. I think it's just right.

What do you think, Kelly? I think you are a very accepting universe partner. And, you know, I haven't thought too much about the universe's clumpiness. I like it for its personality. And so I'm totally okay with the universe as its clumpy self, you know? You're making me sound superficial here. I'm only into the universe because of its clumpiness. I mean, you were the one who was focusing on the clumpiness.

I'm just saying. I didn't say it's the only thing I like about the universe, Kelly. The universe is multifaceted. Yes, it is. So I think that answers Joe's question, and we'll send this to him and hear if he has any follow-ups. But, you know, the episode as posed sort of asks a bigger question. Like, all right, this simulates a bunch of stuff in the universe, but it glosses over a lot of details. If the smallest thing in your simulation is a particle with a 130 million solar masses, then you're not describing Little Timmy's bicycle.

Is it red or is it blue? And I think it's an interesting question that the listeners were responding to and that you were asking about earlier, like, is it possible to describe the whole universe? And I think that the answer to the question has to be no, because a simulation

containing the complete quantum state of the universe would require at least as much information as the universe itself contains, right? And so like, a smaller computer cannot contain a lossless description of a larger physical system. And if that computer is in the universe,

universe, then it has to be smaller than the universe. You can't use the whole universe to simulate the universe. And even if you did, right, there are parts of your computer which are not being described in the simulation. And so I think there's this cool recursive issue. Your simulation would have to conclude a description of the simulation. And so I don't think it's possible to describe the whole universe within the universe, right? The simulation hypothesis is another question. It's like, is our universe a simulation? That implies that our universe is running on a computer in some larger universe. The same way that like, you know, we describe Super Mario Brothers in a simulation. We create a universe and it has its own rules. And that exists within our universe.

And in our universe is a little piece of the universe we call a Nintendo system, which is complicated enough to describe the Super Mario universe. Right. And so if our universe is a simulation, then that implies that there's a computer out there capable of describing all of these details that must be within another universe that's at least as big. Yeah, so I was going to ask, why would anybody want to simulate our universe? But now that you've used Super Mario Brothers as an example, our universe is clearly better with it in it. And so now I, maybe we are the fun part of some other creatures universe. I dig.

Yeah, but I want to point out some fun loopholes here. like, you know, people talk about looking at the way our universe operates and looking for evidence that it is a simulation. I think that's really dangerous and misleading because what you're looking for is evidence that the universe operates the way our simulations operate. But if our universe is a simulation in some other universe, we have no idea what the physics is of that universe, the same way that Mario has no idea what the rules of physics as Newton and Einstein have developed our, his universe has different physics. And so if he's looking for

hints in the Mario universe as to how our universe operates, he's not going to mind anything. And so if we're looking in our universe for evidence that operates like our computers, we're on the wrong track. We need to look in our universe for evidence that operates like the meta-universe's computers about which we have no information because they follow other laws of physics we don't know anything about. And so I have. I think that's a little bit hopeless. Okay, so just to be clear, Daniel is being the wet blanket today and is essentially saying there's nothing in this universe that can answer the question, are we living in a sim or not? I think that's true, yeah.

Oh, man. But there are some other fun loopholes like, you know, can you simulate a whole universe? I don't think you can, but you can simulate large parts of the universe, right? Like, you could a big chunk of the universe, really high fidelity, and that can answer a lot of physics questions. often you don't need to simulate the whole universe. Like to answer this question about dark matter, you don't need to add Timmy's bicycle on whether it's red or blue. It doesn't change the answer.

And so the fact that the universe breaks into these levels of emergence where you don't need to know all the lower level details to make chicken soup, for example, like you can make chicken soup without knowing quantum gravity or string theory. That's great. Chicken soup is delicious, but it also means we can do science at various scales without knowing all the details. that's a blessing. So it's good, actually, that our simulations don't have to include everything in the universe.

And then the other thing is that sometimes you can get away with not describing the universe in all of its gory detail because there are patterns. So we have laws of physics. We have symmetries that tell us constrain what can happen. So, for example, say you're simulating a particle and it decays into two other particles. Well, conservation of momentum tells you that if the first particle was at rest, the next particles have to be back to back. They have to have momentum that's exactly opposite each other, so that the total momentum is still zero. What does that mean? Has it help you? It means you only have

to store in your simulation one of the momentum. You don't have to store both because the other one you can derive instantly from your rule. So symmetries and rules mean you don't have to store the full state of the simulation in your computer. You only have to store enough information to derive it when you need it. And so these symmetries, these constraints, essentially are like a way to compress your knowledge of the universe more compactly and losslessly. So there are some loopholes here too. You have to have a computer the size of the universe in order to describe the universe. Yeah. So what if we are one run out of 10,000 of a simulation that's testing five rules? And we are the result of testing some of those rules. Would that work?

Yeah, that could work. And I wonder if our universe is one that somebody fought for in inclusion. You know, like, thank you, Cosmic Joe for including our universe. Our Joe totally messed up. Yeah, but Cosmic Joe. Thank you, Cosmic Joe. All right. So we'll send this episode to Joe from Ann Arbor to hear if we've answered his question about the flamingo simulation and about simulating the universe in general.

here's Joe's answer. I totally forgot that the listener's name was Joe when I picked Joe as the maybe that was in the back of my brain subconsciously the whole episode. Sorry, Joe, we didn't mean to blame you for the bad run of the simulation. It just goes to Joe you.

Uh-huh. Thank you so much. I really love that episode. Daniel, I know that you would especially like to contact the being running the simulation, but I can neither confirm nor deny whether I am Cosmic Joe. I can confirm, however, that the universe is overly clumpy in the vicinity of my desk.

But seriously, thank you both for the thorough explanation of simulations and the Flamingo Project. Emergent properties at different scales seem to be a major theme on the podcast lately. And I am fascinated of the idea of simulations being a way to probe from one layer of abstraction to the next. I don't have a follow-up question, but I do want to urge everyone to ask their own questions. Listening to the raw audio was a treat, especially right after listening to the episode with Matt Kesselman. Daniel and Kelly are somehow even more charming in real time. My only complaint is that I didn't hear a single goat. Thanks for answering my question.

I love getting smarter with you. Thanks very much, everybody, for taking this trip down the simulated universe to understand how we think about the universe, how we understand it, and how simulation is an absolutely vital part of modern science. May your simulation be a good one. Thanks everybody for listening. Please go and do us a favor and rate the show on whatever podcast app you're using. It really helps people find us. Daniel and Kelly's Extraordinary Universe is edited by the amazing Matt Kesselman.

He really is a wizard. You can also find us online on Blue Sky, Instagram, and X, D&K Universe. Come engage with us. You can email us at questions at Daniel and Kelly.org. We really do want to hear from you. And you can find our website, www. www. danielandkelly.org, where you'll also find an invitation to join our Discord where everybody comes and talks about the amazing universe. And we also have the most amazing moderators.

This is an I-Heart podcast. Thanks for joining us. Hey, this is Hayes, Davenport. And Sean Clements. We host the podcast, Hollywood Handbook. Each week, we talk to someone in show business and try to help them with their careers and see what they have to offer us. Everyone has a good time and no one gets mad at their publicists for letting them do our show. We've had a lot of great guests like Sarah Sherman, Adam Scott, Danny McBride, Ben Stillard,

and a lot of other big shots that wouldn't be where they are without us. Listen to Hollywood Handbook on the IHeartRadio app, Apple Podcasts, or wherever you get your podcasts. On the new podcast Solita, we share the messy reality of traveling alone as a woman. I can wait four hours for the next bus or this random dude is offering me a ride on his motorcycle. I chose option B. I'm Julie Pinero, and I travel by myself because it's a rare space where I can say yes without asking anyone else first.

I'm on a mission to reclaim the word Solita, trading the pity for possibility. Listen to Solita on the IHeart Radio app, Apple Podcasts, or wherever you get your podcasts. I'm Mangish Chitigula, and I'm back with a new season of my podcast, Skyline Drive. This time I talked to scientists, biopunks, curmudgins, blues owners, super seniors,

and Goa's top cryotherapy lab to try to understand this obsession with living forever and what it means for all of us. And I get into a bit of trouble along the way. I'd say probably start bone smashing. That doesn't work. To make it look more defined. They say it works. I don't know.

Listen to Skyline Drive, How to Live Forever on the IHeart Radio app, Apple Podcasts, or wherever you get your podcast. If your bookshelf and your for-you page are equally important to your personality, welcome home. Pro Society is a weekly podcast, that's part book club, part group chat for anyone who thinks pride and prejudice and love island deserve the same level of discourse. Each week, we're connecting the dots between books,

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