Into the Impossible With Brian Keating - Chris Hayward: Lerner and Gupta Are WRONG About the Big Bang (#403)

Episode Date: March 31, 2024

Join my mailing list https://briankeating.com/list to win a real 4 billion year old meteorite! All .edu emails in the USA 🇺🇸 will WIN! When the JWST captured the first images of the earliest galaxies in our universe, scientists were shocked.  The galaxies appeared to be way too bright, way too big, and way too mature to have formed so soon after the Big Bang. This discovery has, rightfully so, sparked a massive debate among astrophysicists. Some even started to question the standard model of cosmology.  However, using new simulations, some astrophysicists decided to investigate this controversy. Among these extraordinarily talented and bright minds is today’s guest, Chris Hayward, founding member of the FIRE project.  Tune in to discover the truth about the mysterious brightness at cosmic dawn! Key Takeaways: 00:00:00 Intro 00:01:02 What is a FIRE simulation? 00:03:11 The mysterious brightness at cosmic dawn 00:12:36 How FIRE provides information on the maturity of a galaxy 00:16:18 Galaxy dynamics and black holes 00:18:50 How FIRE simulations can help resolve tensions in cosmology 00:27:32 “I was made for science.”  00:34:09 The experimental minimum  00:39:54 What if the universe is actually 26 billion years old?  00:43:35 What's next for this type of research? 00:47:25 Outro — Additional resources: 📝 Get one month of Snipd Premium for free with this link: https://get.snipd.com/Cx7S/brianSnipd Snipd lets you take Smart Notes 🧠 with AI 💡 — it’s my favorite podcast player 😀 ! ➡️ Read more about the Mysterious Brightness at Cosmic Dawn https://www.simonsfoundation.org/2023/10/05/bursts-of-star-formation-explain-mysterious-brightness-at-cosmic-dawn/ ➡️ Follow me on your fav platforms: ✖️ Twitter: https://twitter.com/DrBrianKeating  🔔 YouTube: https://www.youtube.com/DrBrianKeating?sub_confirmation=1  📝 Join my mailing list: https://briankeating.com/list  ✍️ Check out my blog: https://briankeating.com/cosmic-musings/  🎙️ Follow my podcast: https://briankeating.com/podcast Into the Impossible with Brian Keating is a podcast dedicated to all those who want to explore the universe within and beyond the known. Make sure to subscribe so you never miss an episode! Learn more about your ad choices. Visit megaphone.fm/adchoices

When astrophysicists saw the first images of the earliest galaxies in the universe from the James Webb Space Telescope, they were shocked. The galaxy seemed way too bright, way too big, and way to matured to form so soon after the Big Bang. This discovery has, rightfully so, sparked a massive debate amongst astrophysicist. Is our universe really much, much older than we used to believe it was? Why do these galaxies appear so bright? In what have we learned about the early universe now that we have such advanced tools? Here today, I'm into the impossible to shine some light on these controversial subjects is none other than Dr. Chris Hayward. Chris works at the Flatiron Institute, New York City, and is part of the founding core group

of the fire project. So buckle up and get ready for a fire episode into The Impossible. Any sufficiently advanced technology is indistinguishable from magic. Open the pod bay doors, Hal. How are you doing today, Chris? I'm doing great. How about yourself, Brian? Wonderful.

Yeah. It's really a pleasure. I thank you for your patience. This paper was accepted on my birthday last September. I've been meaning to get you on since then. And thanks to our mutual friend, Professor Dushan Karras, shout out to UCSD Astro and Physics, who is a collaborator in the Fire Collaboration. And you're going to talk about that.

We had a few people on talking about simulations and the work of simulations, and we'll have more on it and simulations in cosmology. But the first thing I want to do with you, Chris, is to explain what is the fire simulation? What is it used for? What is its core strength? Tell us, what is the fire simulation? So fire stands for feedback in realistic environments. And that first word feedback is really the key aspect of the fire simulations. So galaxy formation, the first kind of most important thing is gravity pulls things together

and gas cools, and that collapses, and it forms stars. And if that was all that was going on, it would be relatively easy to solve the problem of galaxy formation. But the issue is that there's various feedback processes, feedback loops, where when we have stars form, what happens is those stars can then interact with and have effects on the gas out of which they are born. And so that's something that we call stellar feedback. And so what we do in the fire simulations is we try to really, really, you know, do the best job that we can treating the physics of these, this stellar feedback processes in

order to have simulations that are that are more predictive and more physically robust than simulations with with lower resolution. They don't resolve the fine details of the interstellar medium of galaxies. They don't have as physical a treatment of the stellar feedback processes. So fire stands out and this is something that Douchon Karras, who you mentioned, our mutual friend, He's one of the leaders of this collaboration, Phil Hopkins at Caltech, Claude André Foshae-Jeggerat Northwestern, and many other people involved in this. It's really a big global effort involving over 100 scientists at this point doing these simulations. So one of the articles that will link in the show notes was this article from Simon's Foundation, which is the proprietor, if you will, the Flatiron Institute. It was called Burst of Star Formation Explains Mysterious Brightness of Cosmic Dawn, which is the title of the Sun at All Paper that you're,

one of the major participants and collaborators in. But they put out an article, and I just want to read the first couple sentences from their article October of 2023, said scientists were shocked when they viewed the James Webb Space Telescope's first images of the universe's earliest galaxies. The young galaxies appear to be too bright, too massive, and too mature to have formed so soon after the big back. It would be like an incident growing to an adult than just a couple of years. The Starling discovery even caused some physicists.

to question the standard model of cosmology. And then that's linked to an article by past guest on the podcast, Adam Frank, and upcoming guest tomorrow, actually, Marcello Gleiser of Dartmouth College. So if you have any comments from Marcello about his article, that article is called The Story of Our Universe may be starting to unravel. Can you walk us through what you've heard, how you came to be interested in it? Were you working on this topic before the claims of, either a 26 billion-year-old universe or an infinitely old universe by a friend of the show,

Eric Lerner or Regendez Gupta. Can you talk about that for a little bit, Chris? How did this come to be your interest in this? Was it to confirm Lambda CDM or was it predating that to understand the dynamics of feedback and stellar formation alone? And then it led to this serendipitous finding that compatibility could be maintained. One of the things in astronomy were very much an observational-driven field where a lot of times theorists are playing catch-up when a new major telescope comes online and first starts taking data, then there's a lot of things that we can't explain and we try to figure out what's going on, what can explain those observations. So a couple of years ago, we had the James Webb Space Telescope sending back

the first data that it was taking. And this, this telescope, is really groundbreaking. It's amazing the amount of detail that it's provided and it's just been it's been beautiful to see. It's a very exciting time. And one of the most exciting discoveries was early on people were discovering a lot of these extremely bright. So looking at the rest frame ultraviolet light, they were discovering a lot of very ultraviolet luminous galaxies in the early universe. So I think that a lot of your listeners are familiar with the concept of redshift. You look at high redshift galaxies. Those are galaxies that are from the early times of the universe, the first few hundred million years of the universe's evolution since the

Big Bang. And so there was a number of papers that came out that were presenting basically the counts, the number of these very bright galaxies. And I was looking at one of these papers, quite carefully, a paper by Steve Finkelstein and collaborators from the Sears program. And And they presented what's called the luminosity function. So that's just saying the number above a certain brightness. So it's a measure of how many bright things there are. And they had a comparison with different galaxy formation models with different simulations, not including the fire simulations, but including a lot of cosmological simulations.

And one of the points of that paper is that the number of bright galaxies was much higher than was predicted by not only individual models, but essentially any of the previous galaxy formation models. And so this is, I have to credit the authors that they were quite careful with their language. They didn't say that our knowledge of cosmology is wrong. They didn't try to throw away Lambda CDM because there are other possible explanations, as we'll discuss. But they did highlight that this is a very surprising, exciting result coming out of from this new telescope. And there is some scientists like to always talk about tension. There is some quote unquote tension with theory here based on the existing models.

So I was super excited to see this. And when I looked at these results, I said, well, you know, I'd be interested to see how our predictions from fire would compare. Because to me, a possible explanation of this tension is bursty star formation. And the reason that I say this, there's a famous bias called Eddington bias, which again, we'll probably talk about the details later on. But essentially, this is something where if you have some scatter, like from noise, in your data or some intrinsic variation, it could cause the shape of your luminosity function to go from very steep to be flattened out a little bit at the bright end, the bright rare things. And so to me, this kind of just popped in my head as like, well, we have this scatter in our

simulations that isn't in these other simulations they're looking at. Maybe we would agree with these data. And so we had written a paper about this exact topic about the ultraviolet luminosity function in 2018. And I looked back at that paper and I said, oh, shoot, we stopped at Redshift 8. We didn't go high enough into, you know, we didn't have the foresight to go up to Redshift 14 or something where people are observing with JWST. And so I emailed the original author of that paper,

and I said, hey, I just want to check with the existing data how we compare to these new observational results from JWST. And I didn't get any response to my email for a long time. I said, oh, you know, well, it would be really cool if we could do this, but didn't get a response. You know, I have a lot of things going on. Then I found out that this guy had left the field and he's making, I think, self-driving cars. He's doing some working for a self-driving car company at this point, right?

But long story short, we ended up then having a different postdoc, Jason's son in Northwestern. He ended up looking into this question, just taking our existing simulations, doing the calculation to compare the ultraviolet luminosity function. And we found very good agreement with the JDBST data. So that's kind of the overall arc of it. As I saw the surprising result, I thought, well, other. models are having problems, but I think that our simulations might agree, and it turned out to agree. So it really was beautiful in that regard that we didn't have to change our theories at all, that we already naturally had agreement with these new data. One of the takeaways I got from reading

the paper, and by the way, we should play the game that I told you we always play with authors on the Into the Possible podcast, and that's what you're not supposed to do, which is to judge a book by its cover. So if you would, there's not really much of cover. I explained the title of the paper and sort of summarize the main takeaways, if you would, for my audience, as if we're judging a book by its cover. The title is, Bursty Star Formation naturally explains the abundance of bright galaxies at cosmic dawn. So we can start from the end of the sentence there. The abundance of bright galaxies at cosmic dawn, that refers to this ultraviolet luminosity function from the James Webb Space Telescope. So observers went out and just said, I'm going to look at the highest redshift galaxies.

So galaxies from very soon, only a few hundred million years after the Big Bang, I'm going to measure how many they are, how many there are, what's the abundance of these ultraviolet bright galaxies? The first part of the title is that bursty star formation naturally explains the abundance. So what that means is in the fire simulations where we have this very bursty star formation, which means that stars are being formed not in a smooth fashion where they're forming at a constant rate with time, but instead there's periods where you form a whole bunch of stars,

and then there's relatively quiet periods when you're not forming stars. And then you'll have another period where you have a burst of star formation. So if you look at the rate at which you're forming stars versus time, it's going to be a very spiky graph, as opposed to just a steady one, something like that. So in our simulations, this, process of star formation happens in this very bursty fashion because of the treatment of the physics. As I mentioned, the fire simulations, we really focus on trying to capture what we call the small

scale physics of how stars form and how they impact the gas from which they form. And as a result of these feedback processes, you have this bursty star formation. And you don't see this in simulations that don't resolve this kind of small scales and have to use what we call sub-resolution or sub-grid models for star formation and stellar feedback. The title essentially says what I said previously. Disbursty star formation naturally explains the abundance because we didn't mess with the models at all. We didn't do any changes.

We didn't have to run new simulations. We just looked at our existing simulations. We compared the prediction with the data from JWST, and there was good agreement. And then we go on to show in the paper that if we artificially, make the star formation happen in a smooth fashion, so we make it not bursty, but we form the same amount of stars, that the ultraviolet luminosity function that we get out is no longer in agreement with the JWST UV luminosity function. It's peak pollination season, and my business is scaling fast.

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So when we look at the kind of controversy that people have discussed, you know, one of the, you know, big topics, at least in the paper by accident, Adam Frank and Marcel Gleiser was that, you know, the early maturity in these galaxies is also an issue. So would you say that the feedback can explain the, you know, the burstiness and the intensity, but how, if any, impact or how, you know, if at all, does fire provide information on the maturity of a galaxy? And maybe for the audience, could you explain what people typically mean when they say a galaxy is mature? This is a fundamental aspect at the heart of comparing observations and theory in astrophysics is we have an epistemological challenge that for the most part in astrophysics, we're just counting photons.

We just get light from these distant objects. We can't go out and manipulate them. We can't put a galaxy on a scale to measure its mass. We can't use a ruler to measure its size. So we have to infer a lot of physical properties just from, the light that we get, right? So with these high red shift galaxies, that's something that we're comparing our simulations with. We compute how bright they would be if they were real galaxies, and this depends on the rate at which you're forming stars and other properties. And we can make an

apples-to-apples comparison with the observations of the ultraviolet brightness. So what our paper shows is that when we compare this directly measurable quantity with the simulations, we get good agreement. But that's not the end of the story. So this question of maturity, people could be referring to a number of things. I mean, scientists don't really refer to the maturity of galaxies. That's something that's more for press releases and popular media and things. But one thing we could think about is the mass. So mature, galaxies grow in size and mass over time as they get more gas comes from the larger scales,

the intergalactic medium. and they form more stars. So the amount of mass in the form of stars in a galaxy is at some level an indicator of the amount of maturity that people are referring to. And there's also other things we could measure the ages of the stellar population, the chemical composition. There's other ways to quantify maturity. In this particular discussion, I would say when people say maturity, they're thinking about the stellar mass. So that's where there's another possible tension with the theory that observers have gone out with these galaxies observed by JWST, and they've tried to, based on the available information from the light, they've tried to infer the amount of stellar mass,

so how much these galaxies weigh. And you can also compare the mass function, so the number of galaxies with mass of a certain value, you can compare that with simulations. And if we trust the mass is the observers give us, there still seems to be some disagreement with theory in that regard. And this is something that if we take those masses at face value, it could even threaten our theory of cosmology, Lambda CDM. Hey there, it's me, Brian Keating, your fearless host. I hope you're enjoying this episode about these groundbreaking astronomical observations. I've done some observing myself and peered into the data, finding, only about 50% of you

are subscribed or following the podcast and audio. So please, while you're here, subscribe on YouTube or follow on your current podcasting platform, It's your way of letting me know that you're enjoying the content and helps the show grow immensely. So subscribe now before you forget. Thanks. Now, back to the episode. So in terms of the dynamics of the galaxies, their momentum, their spin, et cetera, like is that to a professional, to an amateur cosmologist like Eric Lerner, something like that,

it seems to be a big deal. How much to you as a pro, does that really trouble you, if I'll? Yeah. So the dynamics is, uh, is, even more complicated, so things like the spiral structure or how much order there is in general of galaxies. This is something that really depends on the nitty-gritty details of these star formation and stellar feedback processes, and we haven't even talked about black holes, which one of the big surprises from JDBST is there seems to be a lot more black holes in the early universe,

which incidentally that relates to this mass measurement question that I was alluding to. But in any case, the amount of structure and order and dynamics of galaxies is very sensitive to these feedback processes. And no one makes any claim that we have the final answer about stellar feedback and star formation, and especially about how black holes grow and how black holes feedback on the galaxies that are hosting them. So if there's some discrepancy, say we see more spiral galaxies than fire or other simulations predict in the very early. the universe, that could just mean that we don't have a fully accurate treatment of what we call baryonic physics, of how gas and stars and black holes interact, how the gas is moved around

and heated. There's a lot of detail there, and it's just something given the huge range of spatial scales involved, we can't just brute force it. We can't say, well, we know physics, we know the proper equations, we're just going to solve them because we can't resolve the relevant scales there. So really the devil is in the details of feedback. And if we see any discrepancy there, my bet would be that it's not a fundamental problem with Lambda CDM, with our theory of cosmology, because there's many independent lines of evidence that provide a lot of support for Lambda CDM on large scales where these so-called barionic processes don't actually matter on those very large scales very much.

They only matter on what we call small scales of individual galaxies. So personally, I feel that Lambda CDM is still on, quite solid footing, and any of these tensions that are based on properties of individual high redshift galaxies probably have to do with the messy details of galaxy formation rather than cosmology. And speaking of, you know, cosmology, some of the standard attack vectors have to do with the so-called tensions in cosmology. And I often, you know, I've said that perhaps the number one thing that we could do besides

building, you know, bigger telescopes is to hire a therapist for that community. We've got so many tensions and crises and so forth. I've had a quote from Stephen Weinberg back in the 80s. He said, you know, physics thrives on crisis, but unfortunately, we don't have many crises right now. That was perhaps premature. When you look at the spectrum, you know, obviously one of the number one crises is the so-called Huppel tension. I know that's not exactly what you studied, but there is bearing them, the underlying cosmological model in terms of what the impact on the fire simulations can provide.

Can you take us through a grand step? And maybe we'll cover one or two other tensions, crises, anxieties, you know, phobias, whatever we can do in half an hour. But how does the global cosmological background, the amount of dark energy, dark matter, ordinary matter, et cetera, how does that come into play in fire? Or put it another way. could you invert, you know, kind of simulations of are using fire to actually predict or measure what these fundamental constants are? The way that the overall cosmology comes into these simulations is it essentially provides a background.

So I like to think of space time as kind of a grid that you have your rulers that are showing the structure of space time. And what cosmology tells you is how those rulers are changing as, as the rules. the clock of the universe is progressing. You know, early on during inflation, they're just blowing up super rapidly, right? And then once inflation is done, they're expanding more slowly. There's the famous balloon concept. You imagine the universe, your galaxies are on the surface of a balloon, and the universe is being blown up, which is a little bit of a, it's a little misleading

because we're not expanding to anything, right? It's the metric of space time itself that's expanding, but that's something as humans, it's a little hard to get our heads around without just thinking in terms of abstract math. So that is a useful analogy. So I think of that metric expanding. The rulers are growing over time. And then we're doing our calculations of galaxy dynamics and feedback and everything in the context of that metric. So essentially, cosmology is just telling us how our background space time is changing.

and that definitely affects how things like dark matter and gas flow from the larger scales onto galaxies, right? So this is important. And if you had really gross inaccuracies, so for example, if we think that dark energy is the dominant component of the energy density of the universe, say that we are wrong and there's no dark energy, and it just totally changes the dynamics of the universe. That would certainly affect the properties of galaxies. That would affect our predictions from the simulations a lot. The tension with the Hubble constant is relatively subtle. So it would certainly make some differences in the quantitative predictions coming from the simulations. But the problem is, again, is that treating these feedback processes, treating the barionic physics,

as we call it, that's something that's still quite uncertain. And there's a lot of people are doing their best to treat these processes accurately. Different groups have different models. Those models don't agree 100%. And so if you compare the predictions from different groups that use different feedback models, those differences could be greater than the differences from cosmology from, say, using a different value

for the Hubble constant. It would be difficult to constrain cosmology at the moment with galaxy properties, just because we're not there yet in terms of predicting, in terms of treating the barionic physics. But we are getting at the point where the two fields of so-called precision cosmology and galaxy formation are converging, where really our understanding of,

or our incomplete understanding of galaxy formation is hampering the inferences we can make about cosmology because of those small scales where this barionic physics matters. But the approach that we're taking in learning the universe collaborative, for example, which is funded by the Simon's Foundation, and Brian, you're probably well aware. You might even be involved, I'm not sure. But this is a very large collaboration that's trying to bring together cosmologists and galaxy formation physicists and people doing machine learning

and various others. And we're not trying to have the right answer for galaxy formation, but what we're trying to do is bracket the range of possible effects given our uncertain understanding of galaxy formation physics. And we're trying to do what we call marginalizing over our ignorance essentially to kind of tell us, you know, how much does that matter for these cosmological measurements? And another tension in cosmology, although, you know, it's probably the logarithm of, you know, on the important scale or the anxiety scale, certainly doesn't make the New York Times is the so-called Sigma-8 tension. And I would imagine, as a naive experimentalist, that perhaps Byer could have a lot to say about Sigma-8. Am I wrong? And if you would

be so kind as to define what Sigma 8 is, why it's so important to cosmology. And if I'm correct, that fire, you know, with accurate feedback on these really intimately high resolution scales, can tell us anything at all about Sigma 8. Sigma 8 refers to when we, in the early universe, that we know from the cosmic microwave background that the universe is almost constant density everywhere. There's very small fluctuations, but there's still fluctuation. But there's still fluctuation. in the density of matter throughout the universe. And these fluctuations are the areas that had slightly higher than average density. Those are the things that end up collapsing and forming galaxies at later times.

And the areas that have slightly lower than average density, those are kind of emptied out as the universe expands and gravity pulls the dense regions together and makes those collapse. So Sigma 8 tells us information about those fluctuations in the density field. of the universe. And so if we run a simulation with different Sigma-8 values, what that can do is that it can affect, for example, the number of very massive, very extreme galaxies or galaxy clusters. So we could have more or less galaxy clusters at the present day, depending on the value of Sigma-8. So what we do in Fire for the most part is doing what are called Zoom simulations, where we're really drilling down on an individual galaxy and tracing back its history over cosmic time.

And this is to be contrasted with what we call large volume simulations, where that we're just saying, you know, we have a chunk, we have a piece of the universe, and we are modeling the evolution of all of the galaxies within that volume. And Sigma 8, trying to constrain Sigma 8, it would be more appropriate to look at these large volume simulations, because you need to have statistics. You need to be looking at things like the mass function that I refer to before see how that responds to changes in Sigma 8. And that's something that some of my colleagues at Simon's Foundation at the Flatiron Institute

that they do, there's a project called Camels where what they do is they run thousands of simulations of large volume simulations, where they vary the cosmological parameters, and they also vary the parameters that describe their feedback models. And they try to say is, how much can we learn based on properties of the galaxy population, how much can that tell us about the underlying cosmology like Sigma 8?

So this is the sort of thing that you can definitely try to do with simulations, but using large volume simulations rather than zoom in simulations, if that makes sense. Hey there, it's me again. So sorry to interrupt this amazing interview with Chris, who's truly a remarkable scholar, but I have a very special offer for you. Would you like to get your very own piece of space schmutz?

A real-life meteorite? A real tangible piece of the early universe? Well, go to bryankeating.com slash list and join my Monday Magic mailing list. You'll automatically win if you have a .edu email address at briancating.com slash list to enter. Thanks so much. Now, let's get back to the episode. I may have this wrong, but I get the sense you have a lot of like systems and tools and and kind of life hacks that most of my audience are young men.

I have, you know, 20% females and they're all interested in STEM and nerding out. Can you take us through your kind of career arc? And then I want to nerd out on the tools that you actually use, the supercomputting tools, the potential AI tools, and if you have any hacks and systems like the calendar asynchronicity that you seem to exhibit. So I'm always trying to optimize my life. So please indulge me if you don't mind. I haven't actually read it, but I know that Max Weber wrote something called

Science as a Vocation, and that's how I felt that I was just drawn to it. It was what I was made for, essentially. And I love science, and I would just nerd out all the time. that back in grad school, I would be at a concert with my friend and colleague who I'd collaborate with and we'd have our partners with us. And he and I would be talking about sub-millimeter galaxies, you know, in between sets or something. And we're just kind of always consumed by science. And I'm used to answering emails whenever and just not having, I guess, good work-life balance. I do plenty of fun things, vacation, et cetera. But for me, at some level, I'm kind of always on.

And I recently learned that especially the sort of younger people, junior researchers, they might not like getting an email on like Saturday morning or something because then they might feel pressure to respond to it. When I never intend that, I just write whenever, but that's become fashionable to have like an explicit disclaimer in one's email. Just because I email you at 4 a.m. on a Tuesday doesn't mean that I expect you to respond, you know, by six or something like that, right? But that's the backstory for that particular little disclaimer was just kind of trying to keep up with the times now that I'm no longer even an early career researcher apparently. And I try to stay aware of the mindset of the youth because I don't want to be making anyone feel stressed out or anything like that. But to answer the more general question, as a young child, I was super interested in NASA. I thought, you know, I wanted to go to space.

Unfortunately, when I applied during my second postdoc, they rejected me. They don't want me as an astronaut, so that dream is dead for now unless I can save up a lot and buy a Blue Origins flight or whatever. But as a kid, I loved space program. I loved learning about all that. I dreamed of going to space, to the moon. I was thinking, well, slightly more realistically, maybe I won't be an astronaut, but I could at least be an engineer for NASA. And that was kind of my provisional career goal at that time.

But then when I got to high school and I took physics, and I'd been super interested in math as far as I can remember. I thought math was beautiful. I just love it, that it's this clean place where things make sense and are logical. And it was very different from the rest of reality, essentially. I think math is so elegant. It's something I still love. And I learned about physics when I took physics in 11th grade.

And I was like, whoa, I love this. This is amazing. It just blew my mind, again, how beautiful. how we can understand reality using this elegant system that is fundamentally based on math. And then I learned about astrophysics. And I was like, whoa, I can do this technique I love, physics and math, and I can apply it to space, which I still think is super cool, and like get paid to do this. And so at that point in 11th grade was when I said, like, this seems like an excellent career path, and this is what I want to do with my life. And since that time, I basically been on that track.

I did still consider other things. I considered going to Asian studies because I have a strong interest in Buddhism. I considered philosophy, literature, human rights law. There are other things, other possibilities in undergrad, but I still, once I got to Michigan as undergrad, I got into research right away and I explored other areas, but I still kept on that track and haven't deviated since then. So I did my undergrad at the University of Michigan. Had a great experience there.

I love the place. I went to Cambridge in England for a year before grad school because, again, as a young nerdy kid, I idolized Stephen Hawking. I read a brief history of time and the universe in a nutshell. And I just dreamed of going to Cambridge and doing part three mathematics and applied mathematics and theoretical physics. And I achieved that dream and I did it. And it was awesome. But it was also extremely humbling because that was the first time where I felt like I was one of the stupidest people in the room.

It was like, wow, these people are genius. geniuses, this theoretical physics is really pure math. And, you know, my brain is, I need to do something more concrete. So I was glad I was going. I already had my spot at Harvard for grad school lined up where I was going to do theoretical astrophysics, but to me more concrete compared to like string theory. So when I tell a layperson, you know, I want to do something concrete. So I did galaxy formation theory. They're like, look at me like, you're crazy, right? But I'm sure you understand, you know, it's much more concrete in real world than something like string theory is. I did. my PhD at Harvard after that. And then as I'm sure many of your listeners know, the kind of normal path for an academic is you get your PhD and then you have to join the academic rat race trying to get a faculty position hopefully. So I did a postdoc in Germany and then I went to Caltech after and then I got my position at the Simon's Foundation. Well, it's really delightful to meet somebody. You know, a lot of times, like you, a lot of times I find with my students that they know how to do what they're doing, but to use the Simon Sinek, they don't know why they're doing.

They haven't sound their why. The passion. They're good at, you know, soldering and designing superconducting, you know, quantum interference to buy circuits and building, you know, the most sensitive and largest cosmology telescope in the world, the Simon's Observatory, which is about to get first light in the coming months, maybe even right after this airs. But so few people have this kind of real bare bones. you know, base level, just passionate curiosity about the universe.

It's obvious that you do. I wonder, you know, you're not, you're not a faculty member yet. I hope that someday you will be. If that's your goal, I should ask you what your goals are. Yeah, but I assume anyone who's willing to do, you know, at least one or two postdocs like I had to do and you're doing now, has at least, you know, passing interest if the opportunity is offered to him or her. But I wonder if you were, let's say you were a faculty and you do advise graduate since. I think Jason was a graduate student when he was doing.

this work, right? So he's a postdoc, actually. Oh, he's a postdoc. Okay. So, so nevertheless, we advise a lot of students unofficially as postdocs ourselves. What would you say to use past guest, Lenny Suskin's terminology? He talks about the theoretical minimum in one of his books, which is kind of like what you need to know to become a world-class physicist. This is the minimum you need to know. I want to know from your perspective as a phenomenologist, as a, you know, theorist, as a a model builder, what would you say is the experimental minimum, Chris? What would you say you would want your students or your protegees, of which there are many? What would you want them to know about the base level of an experiment or an observatory like the Simon's Observatory or JWST?

In your opinion, if you're devising a theoretical or phenomenologist or computational astrophysicist, what do you want him or her to know about the nuts and bolts of the instruments that make the data possible? Yeah, that's a great question. I love that framing. I haven't thought about it that but it's certainly something that I do think about subconsciously when mentoring students and postdocs. And I would say not even necessarily at the level of taking the data because with astronomical observations, there's a lot of steps. I kind of glossed over, I said, well, we can measure the ultraviolet fluxes. That's hard. It's not something you can go and easily do. There's a lot of work there. But at some level, there's a lot of nitty-gritty details that it's not something that we necessarily

need to worry about. I feel like there's not necessarily a lot of value there. It is good. I've done observations myself. I have learned about it that way. But I would say that it's maybe okay to trust the observers at the level of they can measure fluxes. But then where I would really want people to understand is the subtleties in interpreting those

data and going from the measurable quantities to something like a mass. function because often what people will do, what theorists will do is they'll say, well, I have my model that I predict. Again, let's just stick with the mass function as one of the most fundamental things. And I want to compare with observations. So they'll go and they'll say, they'll do one of a number of things. They'll pick like some random recent paper that someone might have told them, oh, you should go compare with Smith at L's mass function. Okay, they'll do that. Maybe they'll grab a sample of random recent papers. They might grab some outdated one just because they've seen that. in various other papers that are theory papers,

or they might look at a bunch of different ones, and they're like, well, this one agrees, so I like this one, I'm gonna show this one, right? And none of these are good ways to compare with observations. And one has to understand what are the subtleties, what are the things I need to worry about, and essentially what should I trust and what should I be more skeptical about?

And at what level? So how accurately can we measure mass? Do I need to worry if my mass function disagrees with someone's observed function at the 10% level, definitely not. Factor of two level, we're getting into the regime where we can measure masses maybe to that level, at least in some regimes.

If I disagree at the factor of 100 level, oh, that's definitely a problem, because we can measure galaxy masses to well within a factor of 100. So that's something that as a theorist, you really need to know, have an idea of like, what can I measure from observations, what are the important things, and also when I want to compare, my model, you want to make sure you're comparing apples to apples. So to me, it's a matter of that

epistemological challenge that I mentioned, that you need to really think about what are the, what are the things that we can know, what are the things that we can't fundamentally know, and what are the things where I just need to use a lot of caution and be very careful. Very good. And then, you know, as we close out, you had mentioned, you know, kind of this potential branch of the wave function where you became a philosopher. Thank God he didn't become a lawyer. You know what Hubble said about lawyers, by the way, Chris? I don't know. So he also did the same voyage that you did. He left the Midwest and he moved to, he went to Cambridge, I believe Cambridge or Oxford, because his father wanted him to become a lawyer.

And I believe that he actually completed a course in law. And then he quit. And he came back to America and he told his father in a British accent. He said to his father, father, I'd rather be a second-rate astronomer than a first-rate lawyer. Apologies to all my friends. George Osteadyo has agreed to come on the podcast, and I think now he's going to cancel the chapter. And sorry, in my defense, I said a human rights lawyer. So this is quite different than my friend who's a corporate lawyer, for example. And he's probably not going to listen to this. By the worst, the family lawyers, I've had experience with that as a.

unfortunately of divorced parents in the 70. But I want to ask you, you know, you mentioned philosophy as another branch of the way of function. And I'd ask you about, you know, kind of the epistemological humility that you mentioned earlier, just as the search and limitations therein. Let's say you were trying to steel man the claims of Eric Lerner, Rajendish Gupta. What would you say are some of the things that we as card carrying cosmologists, members of big Lambda CDM? You know that there's a conspiracy theory that, you know, you and I are controlled by big cosmology because our paychecks depend upon it, Chris.

You know, if we don't tow the party line that the universe is 13.8 billion years old, we get, our paychecks get taken, our health insurance gets canceled. Tell me, what are some of the more persuasive? If you had a steelman, learner, Gupta, whatever, what were you to mention as some of the arguments in their favor? And then we can start to dig into that in the final few minutes. As some of their arguments in their... Your summer starts now with Memorial Day deals at the Home Depot. It's time to fire up summer cookouts with the next grill, four-burner gas grill on special buy for only $199.

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their perspective that the universe is either you know, infinitely old or 26 billion years old, you know, or that there's, that the big bang never happened

in the context of learners claimed, or even the paper by Glycher and Frank, who are really legitimate, excellent outstanding scientists. So talk about what if you were, you know, kind of tried to bolster their,

their arguments about either the, the much old, older age than commonly accepted and or the fact that the Big Bang is in crisis and may not have even happened. Some of these issues we've been talking about, we have a theory where there is potential disagreement with observations, whether it be with these galaxies that if we trust the masses, they're too massive at early times. Any of those disagreements, that could be a reason to abandon a theory.

And I think, you know, again, I'm not sure we can trust those masses. which we would have time to get into kind of technical details of that, but let's just say, if the observers are right with the masses they measure for galaxies, then I would say that's very strong evidence that our understanding of cosmology is not correct. Because even if I assume that all of the available gas goes into stars within a dark matter halos, I wouldn't get enough of those very massive galaxies in the early universe. So to me, that would be a very significant disagreement between Lambda CDM and observations. So the thing as a scientist, and this ties into the philosophical point of view,

we're interested in the most parsimonious theory. So we have a theory that can ideally explain all available observations, and there's infinitely many theories that could be in that class. We could just add arbitrary complexity to the theory that doesn't have any observable consequences. That would be a separate theory. but we want to go for the simplest, the most parsimonious theory. We don't want to throw that theory away until we have strong enough evidence that kind of weighs on the other side of all the evidence that the theory can explain.

And so that's the issue with trying to find reason to get rid of Lambda CDM is there's just so much that it explains and so much accumulated evidence that any challenger theory, any competing theory, it needs to be able to explain all of the evidence that Lambda CDM does, plus some new evidence without introducing a ton of unneeded complexity, essentially. So this is something like modified Newtonian dynamics as an alternative to dark matter. As far as I know, there's not a theory of Mond that can explain everything that CDM explains, you know, sort of as elegantly. I can look at those tensions, and if someone came up with a theory that could explain those tensions away and explain everything that Lambda CDM does, then I would switch over to that.

that, I would believe it. But absent that, I'm just going to stick with the default, the sort of of null hypothesis that our current theory is our best. We never know what the truth is. The truth is a fundamentally inaccessible concept, philosophically speaking. But we can have a theory that can explain all available data potentially. We don't have that. We've talked about these potential tensions, and Lambda CDM doesn't explain the origin of consciousness, for example. But it's a pretty good theory and it explains a lot. So I need to be convinced to throw it away. And I don't think there's anything that I could point to that says this is enough to throw Lambda CDM away at the moment. So I'm not sure I'd be able to give a very convincing defense of their stances, unfortunately.

Yeah. I mean, I think a lot of it is, you know, kind of the blurring of, you know, science and philosophy in terms of what is, you know, possible to be, to be discovered using epistemological tools and the role of observation of things that either, you know, happened once in the history of the universe are, you know, according to others, not at all. And I guess, you know, as we, as we wrap up, I'm curious about the future trajectory of both you personally and where this, where this research might go. And if it could, in fact, address some of the, claimed epicycle-like adjustments that the detractors and the assailants against Lambda CDM are proposing. So where are you going with fire personally, professionally? What's next for this type of

research? I'm excited, as you said, Weinberg said, that science thrives on crises. I'm super excited that there's so much interest in these JWST results in early galaxy formation. We had the NASA Decatal Survey, Astro 2020, that said Galaxy Formation is one of the key open problems in astrophysics. And so that's good for me because I have, so I'm actually the equivalent of faculty here with one important difference that we have no tenure. So I have an at-will position. It's like a normal job. So I could be fired. I could leave this room and my director, Julianne Delcanton, could say, hey, I don't like your haircut. You know, you're fired. And that would be fine, right? But hopefully that won't happen.

And as long as I have problems that I need to work on, open questions, then I should be able to remain employed. So that's kind of my personal trajectory. So these tensions, these possible challenges to learn the CDM, they're good for me at a personal level and that I still have work to do, basically, without having to switch over to a new subfield or even a new field, go talk to my colleagues, working on neuroscience, for example. So in terms of specifics, as I keep referring to this idea of the masses, so the UV luminosities, we can explain.

That's no problem. But if we trust the masses the observers tell us, then there's real tension with Lambda CDM. But there's a lot of subtleties there in the actual measurement of the masses. And one of the things that I do a lot of work on is predicting observables from simulations. So predicting what they would look like, what the spectrum of a system. simulated galaxy would be. And one of the cool things you can do with that are what we call ground truth experiments, where you can take these methods for inferring physical quantities like stellar mass, they rely on simplifying assumptions. You can apply these to the data that we predict

from the simulations and see how well can I get the true answer out. And this is a way to kind of check these inferential models that observers are using. You can say, well, how accurate are these? how well can we actually know the masses? And so that's something that I and others are working on to try to drill down into these uncertainties and check should we be trusting the masses that the observers give us. And this is something that is clearly a very critical question that we need to know how robust these numbers are

because if they're overestimates, then Lambda CDM isn't actually being challenged, basically. But if these masses are accurate to within a factor of two level, let's say, then we really have to wonder, well, where could we be going wrong? Because as I said, this is really bumping up into the limits of Lambda CDM when you look at the masses, not just like Lambda CDM plus galaxy formation. It's really talking about the fundamental distribution of dark matter halo masses. And so to me, one of the most pressing questions is how well can we actually infer masses of galaxies

in the early universe? And so I'm working on that along with various other related questions. Well, I very much appreciate that, and I do hope that you will be present when I come to New York again. I'll be there in summer and maybe again in the fall. And I would very much like to do a part two and follow up on this research and the studies that you're doing. And also just keep in touch with you. I think you've got a career of brightness only matched by the galaxies which you study. So lovingly. Chris Hayward, thank you so much.

This has been a real delight. you're a fascinating individual. I know my audience will appreciate it. I took copious notes, including that paper by Max Weber, who was one of my wife's favorite authors. The guy was amazing. I mean, I haven't read the paper. I just made a bookmark to it,

so I'll put that in the show notes down below. But he wrote, you know, capitalism and the Protestant work ethic, which, you know, as a Jew, I'm very interested in, even though. I'm not Protestant. I don't protest in that, at least. But he's an amazing intellect, so I really appreciate that.

I believe he also wrote about Buddhism, as I mentioned, it's one of my big interests. And I think I won't put any money on that, but I believe so. Yeah, definitely a very interesting. Would not surprise me. Do you have any comments or questions for Marcelo Gleiser who wrote this paper after this article in the New York Times? He has a new book out about the Dawn of the Mindful Universe, I think it's called. I'm talking with him tomorrow. So if you have any questions for him, please send him my way.

Otherwise, Chris, it's been a delight. Thank you so much. Thank you, Brian. It's been a really enjoyable time. Much appreciated. Me too. Own it all. Pay off your home, travel for life, drive a Ferrari.

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