Hypersonic Physics, Deep Sea Life & Princeton's Millisecond Qubits

Intro — LA rain, UK weather, and gutters

0:00GOG internet this is your captain speaking Lester Nar joined as always by my co-host and our resident PhD Krishna Chowdery my friend how are you today >> doing well you know not as well as I could be because it's like raining and cold >> it's uh in Los Angeles miserable it's a little Seattle right now in LA >> dude oh my gosh >> if this is what it's like in the UK I understand why everyone's miserable >> yeah it also reminds me of why I moved out of the east coast after college and back to my beautiful home of LA. And I'm not one of those guys who's like, we need this, >> you know? Maybe maybe like California needs this, but like in LA, the water is just going into the ocean. >> Yes.

0:40>> Like the the stuff that's coming outside of the studio is just going like like the rain needs to to happen where the reservoirs are. >> Yes. >> To fill the reservoirs, not here. >> Yes. Right. >> I don't We don't need We don't There is a a 6 to 12 in of water flood on the road. >> Yeah. I had to jump over that I was like >> in the driveway. >> Yeah. Yeah. Yeah. Yeah. And there was a, you know, there was a timing battle there because the longer I stood to figure out how to get over that puddle, the wetter I got. So I'm like, what? You know, there's a calculation I was making of like where where am I okay getting wet? >> I I want people to understand like houses don't have gutters here. >> Yeah. Yeah. Yeah. >> Like like literally there's no gutters.

1:21So everything just falls off the side of buildings. It's >> Yeah. It's that's so funny. It's just it's a >> as I was I was mentioning earlier, rain has done more chaos and damage than any other culture war issue you want to bring up about Los Angeles. That's true. >> Rain is our number one enemy. Um >> but I think so we have a couple of good stories this week. >> Yeah, >> we're on episode 17. We're about to wrap up season 1, which I'm arbitrarily saying is every year is a season. >> Yeah, that's good. >> So we're getting close to the end of season one. >> This is the pilot season. >> Pilot season. Uh, it's kind of like Breaking Bad. It's going to be a cult classic. People thought the first season was slow and then all of a sudden it was

2:03the greatest.

Season 1 framing & “pilot season” banter

2:04>> Yeah. Yeah, that's going to be us. This week, we're going to touch on three stories. Our first story is about hypersonic aerodynamics. So, there's a breakthrough that might enable planes to fly 10 times faster than the speed of sound. >> Yeah, >> we're going to talk about some modeling stuff there. Uh it's it was in Nature Communications out of Stevens Institute, Jersey. Jerseyy's in two of our stories today. >> Jersey. Yeah, >> I know Jersey gets a lot of flack. Uh Union County, born and raised. Not born and raised. Raised. >> Raised. Yeah. >> Not born. Uh but uh no Jersey slander will be tolerated. Story number two.

2:44We're going to go deep in the oceans for a deep sea life story. We found some life in these sort of very extreme areas of the deep sea that we did not think was possible. >> Yes. And there's potentially some implications for exoplanet research and the search for astrobiology and the search for extraterrestrial life outside of University of Bremen. And our third story is out of our favorite.

Story lineup — hypersonics, deep sea life, quantum qubits

3:07>> It is our favorite institution. >> Can you blame us? >> You can't. It's the best. So like we just have good taste. Yeah. >> Uh, a Princeton team, uh, has built a millisecond transmitt breakthrough, which is going to allow us to actually do stuff with the quantum. I'm using the quantum as a term of art. >> The quantum should trademark that >> better than we have before. So again, this is uh in uh out of Princeton in nature, >> right? So our first story was uh nature communications. Our second story was nature and earth environment, but nature. Nature. >> Yeah. Yeah. Now it's nature. Nature. >> Nature. The real one, Princeton. >> Uh, this is from first principles.

Story 1 starts — hypersonic aerodynamics setup

4:03>> So, let's dive into our first story on hypersonics. >> So, for me as the UAP guy, >> Yeah. >> Mr. the UFO guy. >> I I thought you would like this one actually. >> The the hypersonics is an interesting uh so the idea of these things that travel very very fast. >> Very fast. Yeah. >> Uh obviously the number one arena that this operates in is military. >> Uh because hypersonics as a delivery vehicle for >> nukes especially is kind of like the thing Yeah. >> that is sought after by any sovereign nation that wants global dominance and power. >> Yeah. >> This breakthrough. So the headline on the story is uh hypersonic's breakthrough could enable planes that

4:45fly 10 times the speed of sound. >> This is in nature communications from the Stevens Institute of Technology. But what specifically about this? What is the breakthrough that they are alleging is happening here? Yeah. So you know we

Mach number basics & the sound barrier

5:00want to travel faster. Yes. Right. This is something that'll give us access to faster air travel. It would be really nice if we just, you know, got to go to, if I could go to India in an hour and visit my grandmother, that would be really awesome, right? Pretty chill. >> But the age of the Concord is gone and now it's sort of coming back. Supersonic travel is sort of coming back. Um, hypersonic travel is something that is on the docket, >> but it's a little more non-trivial compared to supersonic. Okay, so in order to get into that, there's some fundamental physics involved that I think is very, very cool. Let's talk about the mock number. You know about the mock number, right? It's the ratio of the speed of your object divided by

5:40the speed of sound. The speed of sound is about 750 mph. Planes usually operate at around like what 200 300ish. Yeah. >> Right. Um and at the altitude that planes are at, you're a little bit lower. The speed of sound is around 600 650, right? Because the density is lower. But at the end of the day, the the air behaves differently when you are traveling at close to or above the speed of sound. Okay? And one of my favorite movies of all time is The Right Stuff. It was a movie about the early US Army tests out in um Edwards Air Force Base. And there's a great scene where Chuck Joerger is trying to conquer the demon

6:23in the sky. And the demon in the sky is the sound barrier. Okay? Because back then no one had gone faster than the speed of sound and it seemed non-trivial whether you could. Now engineers were like of course you can because a bullet goes faster than the speed of sound and uh you know Erns Mock had >> that famous photograph of the bullet going through the speed of sound that we had covered in some earlier episodes. So >> it's it's obvious that stuff can go faster than the speed of sound and the atmosphere permits it. Okay. It's less obvious whether something as big as a airplane that's carrying a human being can go that fast. >> It there's a scaling issue, a potential scaling issue.

7:03>> There's a potential scaling issue because what ends up happening is when you go faster than the speed towards the speed of sound, the disturbance, the pressure waves that the the disturbances that you're creating with your object are going to move away from your object at the speed of sound. That's what sound is. Sound is the speed at which some disturbance moves through air. >> But if you're piercing through that barrier, right? Then the disturbance is sort of catching up with you. You're or you're catching up with that disturbance, right? And you're piling up air in front of you. >> And air goes from something called incompressible an incompressible fluid,

7:45which is >> a way a way of saying that basically air doesn't change its density as we change its pressure and temperature to something where it does. Now you can squish air. Okay? And what ends up happening is at the speed of sound, you get these things called the mock cone where the wavefront of all of that disturbance becomes a nice little conical wavefront >> in your >> device like right around the device that's going through. >> Right. This picture here is of >> a model airplane in a wind tunnel. Yes. Where the wind is moving faster than the speed of sound. Right. So then relative the the the object is moving faster than the speed of sound and you're getting

8:25that really nice mock cone. Right. Right. And the angle of that cone tells you how fast you're going.

Shock cones, boat wakes & compressibility

8:30>> Uh so like it'll it'll like like it'll be wider or more narrow based on >> based on how fast you're going. It's kind of like the wake on a boat, right? It's the same same principle is like the the waves in the water are moving at a certain speed, but your boat is piercing through that disturbance faster than the waves can proliferate. Yes. Right. And what ends up in in water, you're not getting this compressibility thing because it's it's just water. It's in it's in it's a two-dimensional sort of surface in three dimensions. So, it can dissipate its energy in this like Z direction, right? But but in sound, the energy has nowhere to go. And so, you're just piling up these air particles one on top of the other, right? >> So, that's the pressure wave that you

9:11get when you go supersonic. >> Okay. >> Okay. We figured that out. Obviously, we have the we have the F-16s and all of these like really nice military jets. We have the Concord that used to be a >> the only commercial supersonic jet. >> Yeah. >> That has not been replicated at scale yet. >> Since Yeah. I think there's there's recent things coming out of Boeing and NASA that are trying to resurface that and they're trying to make a version of the Concord without the sonic boom >> without sonic boom >> which is going to be very cool. There is I do know and I because they're abusing me with advertising on X. There is a uh startup >> uh that is doing supersonic

9:53jet uh they're building their own supersonic jet platform outside of the primes. >> I'm not saying they're accomplishing it, >> but that's what the advertising is putting forth. I mean nowadays with like the the access to computation and AI and all that stuff, I wouldn't be surprised if a if a small rag tag team of engineers like cracks Yeah. >> you know certain problems, >> which is fair. >> So, so that would be very interesting. So, okay, we've gotten to supersonic, right? >> Yes. >> Then there's something called hypersonic. The definition of hypersonic is greater than Mach 5. So, five times the speed of sound. >> Five times the speed of sound. Got it. And there the air behaves even more differently. >> Okay. The physics turns into a different

10:35animal altogether. >> It's kind of like levels in a video game. And like when you get to level two, it's it's harder than level one. >> It is harder than level one. And now we're here in level two, right? What ends up happening is the physics of the air starts mattering. Before you could just treat it as an ideal gas. Ideal gas meaning a bunch of point particles that are bumping around. Sure. Like even even the speed of sound you can derive that actually um you know in in physics at Princeton physics um one of the problems on the final for statistical mechanics was to derive the speed of sound from

11:16first principles. And I remember being like, "Thank goodness." Because like half an hour before the test, I saw this derivation and I was like, "I'm just going to memorize it." And and then and then it came up on the test. I was like, "Dude, I got this." And I just like and just like wrote it down >> and and then some of my classmates afterwards was like, "What the hell was that?" And I was like, uh, you know, I just randomly happened up on that page and I was like, this is something that I should probably just know how to do. >> Yeah. >> In case. And it it was the exact problem. Oh my gosh, I love that. >> That's so >> it's it's a really cool problem where you basically treat the particles like billiard balls, like an ideal gas. And

11:57you start asking like how how the the dissipation, how these billiard balls will >> bump into each other to create the effect of sound. Yep. And then and then how fast that sound is going to go in terms of temperature, density, and things like that of the air, right? And the mass of the particles even Yeah. Yeah. There's like there's there's terms that go into that derivation. >> So, >> Yep. >> Um, all that is fine before hypersonic, >> right? >> Okay. When you get to hypersonic, then you start caring about what is the air made out of. >> Yes. >> It's not pointlike particles. Most of it is nitrogen and oxygen. Okay. >> And those are diatomic particles. Okay. Right. Diatomic molecu molecules.

12:38>> Yes. >> So diatomic molecules means you've got two atoms. Nitrogen is an N2. >> Oxygen is an O2. >> Yep. >> And those guys have other degrees of freedom. They don't just move. >> They also vibrate >> and they also rotate. >> Okay. So there's other ways in which energy can affect them. So, and so the

From ideal gas to diatomic molecules with vibration/rotation

12:59ways in which they interact themselves and with each other >> and with the object >> and with the object start mattering >> because there's there's there's more complexity now at when we're starting to get into above Mach 5 >> above Mach 5 because the energy scales correspond now the kinetic energy that you're putting into the air is now at the same regime as the energy of this and the energy of this. Yes. Yes. You see that's physics is always about energy scales. It's like what energy scale am I operating in? Right now >> the energy in the room is at what maybe 20° C, right? So 270° Kelvin

13:42>> at that scale the vibrational modes aren't doing much. So you can you can you can just use PV equals NRT and be like this is an ideal gas. It's fine. >> When you get to higher temperatures, higher kinetic energies, that's when that's when the molecules start doing this. Yep. >> Right. And then you got to start caring >> because there's emergent properties of the particles doing this. >> Yeah. >> That matter in the overall equation of what is happening on >> exactly at a low at a low velocity when I'm just like moving my hand around the molecules are just getting out of the way. >> But if I start moving my hand around at hypersonic speeds the the speed at which the the the energy that I'm imparting on these molecules is now making them go like this. I mean this is the whole idea

14:24of the point that you can't just go infinitely fast because at some point you start the surface of your materials starts >> yeah it'll start melting melting because yeah like if I go infinite if I go really really fast I'm going to start imparting energy on these materials those materials will start imparting the energy back into the surface the metal that I have right and then maybe that energy is enough to start melting the metallic stuff volume of that energy. >> Exactly. >> Is getting so high that it is not just and there's reasons why this makes a lot of sense, but >> Yeah. Yeah. I mean, you you you might have read about this with like, you

15:04know, a lot of your UAP research. >> I mean, it's it's this idea. It's why it's why these all of these like advanced aerospace platforms when you talk about, you know, the the M22, the M35s, sorry, F F-32, F22, F25,35s, like all the the B-52s, like all these super advanced platforms. Material science is actually one of the most important aspects of these platforms because we're trying to have them operate both at altitudes and at speeds and with levels of maneuverability that are pushing these limits >> like physical limits of like the stuff that it's in even >> and and the understanding of

15:44hypersonics. The reason why hypersonics is still the realm of massive global power nation states is because it's very

Energy scales & when air chemistry starts to matter

15:53complex. Yeah, it's very Yeah, it's very complex. All of a sudden, you you can't just rely on the Navier Stokes equation to like tell you everything, right? And now now it's it's no longer just viscosity and density and pressure. There's like molecular effects. You got to get down to the molecular level. And that's why it's hard, right? So, when it comes when it comes to like making something that wants to move at a hypersonic scale, there's two tyrants that you have to deal with. Okay? There's two types of drag. There's a pressure drag, which is basically my my plane is going through the air. There's higher pressure in the front because I'm piling up all the air and then I'm creating an effective vacuum behind me.

16:34>> Yes. >> Right. So, that's going to create a force >> because there's high pressure here, low pressure here. Just like a piston. >> Yes. >> There's going to be a force that's going to be like, "No, I don't want you to move that fast." >> That's the That's the pressure drag. >> Yes. Then there's also skin friction drag, which is the air is moving over my body. Yes. Right. And I'm I'm like tearing the air apart in some sense because the part that's stuck to my my vehicle, my flight >> is going to be moving with me, but the air away from me is stationary, right? So there's going to be that like velocity difference, right? And then there's another thing which is the heat. All of that energy that I'm imparting,

17:15if I'm going hypersonic, that heat is now changing the chemical structure of the air in front of me. >> Yes. >> And that heat load, that aerothermal load from the viscous dissipation is going to be something that I need to care about. Right. >> Right. So, there's all of these like little things. >> Yes. >> And the source of most of my problems comes from some something called the boundary layer. >> Okay. So, imagine you've got an air foil. It's like a wing. >> Yes. What I was saying earlier is there's a thin there's a thin layer where the velocity shears from zero relative to me. So I'm moving through the air. I'm moving through the air. >> All of the molecules that are near my

17:56that are stuck to my wing are moving with me. >> Yeah. >> But all of the molecules that are even a few millimeters away from me >> are far gone. Yes. >> Right. There's got to be some continuous way that I go from zero to my speed. >> Yes. >> Right. >> Yes. >> And that's that boundary layer. Okay. That boundary layer turns from laminer to turbulent. >> Okay. >> Okay. When it when it fully attacks when it fully attacks the air, it's laminer, meaning it's quite smooth. >> It's very smooth and it's very nice. Yes. >> Okay. There's a continuous sort of transformation from zero to whatever my velocity is. >> Yes. Later on that laminer flow is going

18:37to turn into turbulence. Yes. And the turbulence is going to be there's going to be these eddy currents. There's going to be like weird like like circulations happening in the back of my wing. And that transition from laminer to turbulent is a very poorly understood event. >> Gotcha. Okay. >> Okay. >> Yes. >> Like like like seeing where that happens in my wing, how that happens when I change the deflection of my wing. Yes. you know all of these things are are you know we've got models for it and we've got ways of understanding it but at the end of the day this is a extremely nonlinear phenomenon which means that you know there's not a simple nice >> like differential equation that I can

19:18just like solve and like and like I have like a solution that is like enclosed form okay th this makes sense and is it

Boundary layers, drag (pressure vs skin friction) & heat loads

19:26also the case that because of the lack of to be able to do hypersonics is extremely expensive Yeah. >> And it's also classified. >> Yeah. >> And so the amount of actual source for data >> to inform the models >> is not really accessible. >> Yeah. >> In terms of having a feedback loop for how you iterate on your model's predictions. >> Yeah. >> And so you're kind of extrapolating from what you can get. But it's an environment because of this laminer flow to turbulent flow and these new problem sets that happen when you start going hypersonic. >> Yeah. the ability to have a feedback loop from real world real world data sets is kind of a cha it's a little bit

20:06of a challenge. >> It is a little bit of a challenge and you know I will I will go out on a limb and say that even the classified programs haven't really crap cracked like greater than five mock. >> Okay. >> Okay. Because because >> some of this fundamental physics is just like so foreign. >> Yeah. that like there hasn't been fundamental research that's happened to figure that out. Maybe they've cracked it for small things, right? Missiles. Okay. Right. But like you're putting a human in something that's going hypersonic. >> Yeah. Yeah. >> No, that's a different No, that's that's actually No, you could you could be going at Mach 10. You could be going at Mach 10 in the

20:47upper upper upper Earth's atmosphere. Yeah. Right. >> Yeah. >> There's not that many particles. The density of air is low. >> I mean, okay. Is the International Space Station going at Mach 90 or whatever the hell? Right. It's not really a thing. >> Yeah, that's fair. >> Right. That's fair. >> But but when when densities are high, >> right, >> then it >> it's a different it's a different >> it matters. >> It's a different like animal altogether, right? And even I mean one of the things that I I would suggest is the space shuttle for example, right? The orbiters, they had these overdesigned tiles, the heat absorbing tiles on the on the very end. They were overdesigned because predictive models of that turbulence of the laminer from turbulent

21:29background. >> Yes. >> Were so bad that they were just like, "Okay, I'm just going to make this like 10 times >> what I need." >> Right. >> Right. Because I don't know where that transition is and I don't know the physics of that. >> So I'm just going to I'm just going to overdesign for safety reasons. Right. >> So So it shows you that I mean I mean I'm sure like the top echelons of NASA have access to some of the hypersonic stuff, >> but but I don't know. But a key point is as far as we know at this point in time in the public data realm, hypersonics are exclusively for >> payloads like missiles, not for human travel. >> Exactly. Which is they're very different. >> Those are very different things like like like a human life is worth way more

22:11than some nuclear thing that I just like made as I'm I'm testing. Yes. You know. >> Yes. No. No. But that that that is the that is the key thing. >> That's the key thing and that's where this paper comes in. Okay. >> Okay. Okay. The central challenge of hypersonic design is predicting and modeling that turbulent boundary layer. Right? And this paper is doing an experimental >> addressing >> of that >> of that problem. Okay. And that's why I think it's very it's very exciting. Okay. What it's doing is basically testing a 60-year-old hypothesis. Okay. It's a it's called a Morov hypothesis. And what it says is the essential dynamics of this like very high-speed

22:52high mock turbulence is not fundamentally different from low mock turbulence. >> Okay. >> Okay. Morov came up with this in 1962. He was looking at some preliminary data and he said that this seems to be true. Okay. It's essentially the same. What he's saying is at high moach air is going to become compressible and there's going to be all of these density fluctuations and temperature fluctuations. But what I can do is I can take the physics that I know from low mock and I can do a transformation.

The Morkovin hypothesis (1962) explained

23:31Basically, I just adjust the parameters for density and I adjust the parameters for turbulence or sorry for temperature >> and I'm going to get the turbulent effects that I get at high moach. Okay, this is a non-trivial statement. Okay, because what it's assuming is the essential physics at the at the high scale at the at the vehicle level is going to be very similar, >> right? It's saying all I have to do is adjust some parameters and I'll get the right physics. There's nothing like weird that's happen in between. I if it's raining outside, I can just put on a raincoat and I'm fine. Like I there are no other derivative thing like the addition of a single item that is

24:13trivial. >> Yeah. Yeah. Yeah. That is that Yeah. Yeah. I can just adjust some parameters, right? It's not the rain is like acid rain that's going to melt my rain coat and kill me and all this other stuff, right? Right. You know which which is which is like it is it is it is filling in in it's not in it is saying that the this maps in both domains in a way that what we're saying is that is a big deal that we're saying that it >> we're saying that yeah we're saying that there's some there's some trivial transformation >> that can scale the compre the really complex yes >> compressible stuff >> into just a couple knobs. >> Yeah. Into just a couple of knobs. Right. And and why that matters is

24:54because like right now we have simulations, >> okay, >> that deal with this kind of stuff, okay? They're called computational fluid dynamics. They basically churn physics equations in a computer and tell you how the air is going to flow around an object going at a certain speed, given the air density, given the temperature, and things like that. Formula 1 people do it all the time. >> This is what video games use for like water. >> Yes. >> You know, like water animations in your Uncharted 4 or whatever. >> Yeah. Exactly. >> They need to use models like this. >> They they use models like this and like people at aerospace companies use probably more sophisticated models, but at the end of the day, at the end of the day, it's just like it's it's resting on this hypothesis, right? Because there's

25:34two ways to do it. There's a direct nu numerical simulation called DNS. That's the gold standard. Okay. >> You're basically solving Navier Stokes for like tiny tiny little packets of of space. >> Okay. >> And you're and you're getting really granular with it. >> Yep. doing a direct numerical simulation for something like an airplane. We don't have the computation. >> I was going to say like we barely have the computation for me to get an image of me making eggs in the morning out of Chachi BT let alone this multi-point. >> Yeah. This is like imagine every single little part of air that's interacting with every other little part of air, right? How many how many supercomputers are there that you're going to like rent time on? >> Correct. to like deal with every single

26:17iteration of your design. It's not going to work. >> The the point is classical computing does not really have the horsepower to do like physicsbased or physics level models without getting to supercomputer scale. >> Exactly. Yeah. Yeah. And there's not that many supercomputers in the world, right? Like there's not one like just here. >> Right. Right. >> Right. And then and then the other so what what we usually do is we use something called a computationally cheap RANs. It's called Reynolds average Navier Stokes. It's basically a way to like blur out >> a lot of the physics. So on the left you've got direct numerical simulation. Yes. >> And on the right you've got the Reynolds

26:57average simulation. You can see that it's kind of a blurred out version >> Yes. >> of the direct numerical simulation. So it's giving you a good enough answer. >> Yes. >> Okay. >> Yes. But here's the thing. Every single one of those simulations, especially when you're trying to go into this Mach 5 and beyond level, it's assuming explicitly Marovven's hypothesis. >> Okay. >> Which is that the physics up there is basically equivalent to the physics down here >> up to a certain scale factor that we can calculate. >> Mhm. >> Okay. >> Mhm. >> The key thing is this. No one's actually like done the work.

CFD vs DNS — why hypersonics “should” need supercomputers

27:37>> I love it. to show that that this is equivalent. >> Yes. >> Right. Right. >> That like we can assume these things. >> We've just sort of been like ah >> yeah probably >> probably. >> Right. >> We got other things to do. >> And then and and then came some experimental data that suggested not. >> Okay. >> Okay. So there was a conflict. Experimental data came out of something called PIV which I'm going to go into. But there on the bottom you're seeing the red is the experimental data. >> Yeah. Yeah. >> And the green is the DNS, which is the direct numerical simulation, the really high thing. >> And there's a discrepancy. >> You see that discrepancy? >> And it's it is it is sign statistically significant. >> It is it is statistically significant.

28:18You're going from something like 0.4 to to like 1.1 on the y- ais, right? That's that's a 2x almost. >> So, >> okay. >> Right. >> Yeah. So, now we're in a conundrum. >> There's a problem. >> There's a problem. Right. If we want to trust this thing, if we want to trust Marovven's hypothesis to beyond Mach 5, yes, in this hypersonic regime, >> yes, >> we have to answer the question one, >> is Marovven's hypothesis correct or >> Mhm. >> is >> is is the experimental data correct? Right. Right. One of those two >> is the thing is the thing >> is the is true. Right. Right. So that was the question that these guys at

29:00Stevens Institute were trying to handle. >> Shout out Jersey. >> Shout out to Jersey because here's what they did. They said, "Okay, direct numerical simulation is like kind of the gold standard." >> Sure. Understandably. >> How did they get the experimental data? >> Mhm. >> They use something called PIV, which is particle image velocymmetry. Okay. It's a state-of-the-art optical experiment. And here's what's happening. You got some fluid. You put in some particles can be dust particles, oil particles, aluminum dust. And those dust are going to track where the fluid is moving. >> Moving, right? Got it. >> That's the idea.

Particle image velocimetry (PIV) and tracer lag problem

29:37>> It's kind of like when you put the the dye in animal testing to make the things show up when you look at it different areas. >> Exly. Yeah. Yeah. Because the fluid is just moving around on its own. >> But you need to be able to visualize it somehow. >> But you need to visualize it somehow. So, you're going to put some tracer thingy that's going to track where the fluid is moving. Okay? >> And it's going to be seated with these microscopic tracer particles. >> But here's here's the problem. Those tracer particles are quite big compared to the air itself. >> Okay? >> Right? The air is made out of nitrogen and oxygen. These are single molecules. The particles are made out of let's say

30:1810 the 5 10 the 10 something like that number of these. So there's going to be a particle lag. >> There's going to be the air is going to be pushing this particle and then the particle is going to move and then I'm going to image it and create this velocity field. Right? >> So there's a delta between the thing we're tracking and the thing we actually care about. >> Yes. >> Because of this scale difference. >> Yes. That's not going to matter at low low speeds. >> Matters a lot. But at Mach 5, Mach 6 now all of a sudden maybe it matters. >> That's the question. Does it matter? Right? Does at high speeds the fact that my tracer, my dust particle or whatever

30:58>> is so much larger than the fluid particles themselves, does that matter? >> Yes. >> And here's what they did. They they said "Okay >> instead of having tracer particles, I'm going to use something called krypton tagging velocytry. >> They're going to use krypton gas." Okay? and the krypton atom which is a monatomic gas because it's a noble gas it doesn't make molecules that's going

Krypton-tagging velocimetry — ionizing atoms as tracers

31:22to be my tracer >> because it's it is closer in size to the thing we are trying to trace >> track yeah >> than the other aluminina dust and other things and so the we can the point is if we do it this way we can start to rule out the lag problem as the source of the issue >> because the crypton is just going to be going with it >> yes it's going to be moving at the same level and paste and all these things as the actual >> and this is the part that was like a little bit non-trivial to me right it's like with dust it's really easy to set up a 2D laser field and like image the dust because the laser remember from first principles how do we image something we got to capture light

32:02>> yes so what do we do for the dust for the um particle image velocry we set up a 2D laser field the dust is moving moving around the laser bounces. The light from the laser bounces off the particle and then it goes to our detector and we take an image. >> Mhm. >> With a single krypton atom. What? How are you going to do that? Here's what they did. And it's I I thought this was very cool. So, they got a laser and they use the laser to ionize krypton. Okay, they have this two photon procedure where they focus all the laser beam into a tiny spot where the where the krypton is getting seated.

32:43>> Okay, and if two photons interact with a single krypton atom, it's going to bump up in energy level and ionize itself. >> And then you're going to be able to >> and now this krypton is an ionized thing. And when it goes back to its normal state, it's going to release a photon. the the krypton itself is going to create the photon that we're going to use to track it with. So there's like a read. So there's a write mechanism, right? We're writing the krypton. We're tagging it. >> We're tagging it. Yeah. Yeah. >> And then and then we're reading it later when the photon's released. >> Yeah. >> And it's we're basically created readwrite level permissions on >> on like on an atom. >> On an atom >> and we're tracking it as it goes through

33:25this Mach Mach 5 Mach 6. I hope people who are watching and listening to this understand how outrageous what he said. >> That's so like and it took him 10 years to like figure this out obviously like like >> credit to them dude that that's so that's such a cool idea. That is a really that's actually really right cuz you got to think like that's really that's clever. Yeah, it is clever because because I want to trace how the gas is moving around, but I want to image the gas itself. >> Right. >> Right. How do I image the gas? I can't image atoms. >> Right. >> Right. I can image dust particles cuz they'll scatter light. >> Yes.

34:05>> But if I make the atoms themselves like this like weird like light bulb. >> Yes. This this reminds me of the story we talked about in episode 16 last week about how we were use the the the camouflage story about how we're manipulating biology in order to generate an outcome based on its existing evolutionary processes and building into that infrastructure >> uh in order to get the outcome we're looking for. Just conceptually it's like using the fundamentals of physics. It's like we're eliciting >> the reaction >> that then enables us to do the thing we want to do based on the fundamental principles. >> Uh we're not just like we can't just

34:45force the answer. We kind of have to like work with the universe a little

Stevens shock tunnel at Mach 5–6

34:48bit. >> Yeah. Yeah. Yeah. Yeah. Yeah. And so and so and Krypton was the way to do it. >> Krypton was the way to do it. That's >> I think I think that was really cool. And so what they did was in the experiment they have something called the Stevens Shock Tunnel which is at Stevens University. was funded by the office of naval research. It's an impulse facility and what it does is it creates these shock waves that move through that tunnel at like Mach 5 Mach 6. Right? So you've got you've got some apparatus that like where the krypton moves through the tunnel at Mach 5 Mach 6. You can now measure you can ionize the krypton in one part. You can track it and then you can get that level of fidelity that was never possible with

35:30the older method. Yes. >> Right. And the the results speak for themselves. You get the mean velocity curve and the cryptonaging KTV data perfectly aligns with the DNS,

Krypton data vs DNS — resolving the PIV discrepancy

35:41>> right? As opposed to what we looked at earlier where there was that delta that discrepancy. Um, meaning we're now actually tracking in a modeling context close to the direct uh actual like this the the the direct value we see in that really high fidelity gold standard. We're now able to kind of replicate that with like less

Validating Morkovin at Mach 6

36:05>> with Yeah. Yeah. And now it's in the real world and we can say okay experimentally the model is actually tracking >> the model. Okay, that's that's got it. Yes. It's like it's like the the particle stuff that we were doing earlier with the dust particles that wasn't good enough at these >> at these velocity regimes. >> Above Mach 5, we now have a regime a velocity regime that can work with lower without needing a supercomput. Exactly. We can we can now we we can rest easy that the simulation framework that we've been using >> is is >> is valid is more accurate. >> Yeah. Yeah. It's like it's it's

36:47definitely less fidelity, but we don't have to we don't need a supercomput to let's say test a bunch of designs before we like go into production. This hugely reduces the scale of engineering, right? because >> I can I can now I can now try a bunch of different things on my computer. It can be a big computer, let's say, but it doesn't have to be a super computer. >> It could be an M5 Mac. >> Yeah. Yeah. Exactly. Like it can it Marovven's hypothesis is now experimentally validated at Mach 6. >> At Mach 6, right? Yes. Got it. And that's kind of like the the the key point is like this 19 was it 62? >> 62. Yeah. uh uh sort of hypothesis

37:30has now been validated a scale of fidelity of high fidelity measurement. >> Yeah. >> Above Mach 5. >> Yeah. And and it we hadn't gotten that far before experimentally. >> Experimentally we hadn't really known is the hypersonics regime as opposed to the supersonics regime have something where Marovven's hypothesis is no longer >> valid. Yeah. >> Above this limit. >> Yeah. And we've now said, "No, no, no. We're good. >> We're good. >> We're good." So now it can, you know, we we can start like actually pushing these measurements. >> Yes. >> Right. To to to greater fidelity. And we can also start engineers can be a bit more confident,

38:11>> right, >> about the designs that they produce in silica in the computer. Yes. And they and they try to validate it, right? You can now be a bit more confident about, okay, this thing works in the computer. Let's try to actually make it, right? >> This is This is >> I'm looking forward to it, dude. Hypersonic travel before I'm before I'm out of here. >> That would be great. >> That would be dope. >> That would be fantastic.

What this unlocks for hypersonic aircraft and missiles

38:34>> That would be dope. >> That would be fantastic. >> I mean, it's probably going to be like $10,000 a flight, but >> as we know, they got they always got to monetize. >> Yeah. >> I I Before we move on to our story number two, I just want It's funny the timing of this because literally earlier today, I saw or I think it was today. Yeah. Sam Alman um made this post about uh anyway, long story short, there's a company that has reached criticality on uh a a a nuclear reactor infrastructure that is venture capital funded. It is the first BC funded entity that has been able to show

39:14the ability to reach uh the splitting of the atom in a new reactor architecture and they did it in computer >> and then this was the first nonhe no heat no power but like I guess physical test of that simulation and they were able to theoretically reach that point. It is just another if all these real world examples of simulations moving to real world and like I don't think like the everyday person understands how much we depend on modeling >> oh yeah >> and simulations >> it's insane >> to be able to like validate ideas before we even start putting >> no cuz that stuff is expensive so

39:56>> making stuff in the real world is super expensive so whenever people are building new chips the first thing you do is validate it in silica right you have CAD designs and you have all of the software whenever Nvidia makes It's the next H4000 or whatever the hell, right? It's going to it's going to >> create so much testing within the computer because we just know physics >> at this level so well, right? We're not we're not going into CERN >> trying to find the Hig Bzon. We're like we need to I don't know what the mass is. I know what the mass of the electron is. I know what temperature like so we know physics so well that it's just way cheaper to do stuff

40:37in a computer before we rig up a whole factory to actually make stuff. Yeah, you're right.

Modeling, simulations & nuclear reactor analogy

40:44>> Which makes total sense and it's an important >> I got to I got to check this out. That's pretty cool. No, it's it was it was it kind of took took off on X earlier today and you know I'm not uh I did try to do some very brief validation. It does appear to be the first time that a private venturebacked like investor back like private capital has been able to do so which is >> that's that's something I always look at the comments on >> it was part of a DOE program to get three three uh private uh versions of of uh reaching criticality by 2026. So it's a part of a a sort of an ongoing DOE

41:24program. >> Yeah. Um, which made it a little bit more >> Yeah. Yeah. Definitely a little bit more legit for sure. >> Legit. Um, >> I mean, this was funded by the Office of Naval Research. >> Same same idea. >> A lot of federal government funding. >> It's all >> another reason why we need more federal funding. >> All the beautiful things we love, >> you know, it requires >> Yeah.

Story 2 starts — “life found in a place scientists thought impossible”

41:47>> Yeah. >> We're going to move on to our second story, which is about microbes >> and and and a new biosphere. uh where we thought life was impossible on Earth. >> Yes. >> And it has some implications potentially for astrobiology. So the the headline on the story, life found in place scientists thought impossible. >> Yep. >> This is a paper out of Nature Communications Earth and Environment. A biomarker evidence for a serpentite chemosynthetic biosphere. >> Nice. >> At the Mariana for arc. This is out of the University of Bremen, German University.

42:28>> Uh many people are familiar with the Mariana Trench. People sort of through a variety of sources might be, oh yeah, like there's like these hot vents and there's these things that live in these hot vents and that's the most extreme place. But but there is something really interesting here about life defying the limits that exist in the deep sea uh in

Subduction zones vs mid-ocean ridge vents

42:48this paper. >> Yes. Yeah. I think I think it's very cool. the the core concept of is is life is constantly like evolving in places that we never thought was possible. >> This one is happening near the Mariana's trench and it's very different from the deep sea thermal vents that you were just alluding to actually. Okay, perfect. Okay. Because the deep sea thermal vents usually happen at places where the oceanic crust is diverging >> like in the middle mid-Atlantic ridge where there's a there's the crusts are like splitting apart. So there's a lot of volcanic activity happening. Right. Right there. >> Yep. >> Um and so there's a lot of like sulfur

43:28gas and all sorts of stuff coming out and then all of the bacteria are are capitalizing on that. This one is a subduction zone. >> Okay. Okay. The Mariana's Trench is something where where one plate is going under another rather than two splates splitting. Two plates splitting. >> Right. In the Mid-Atlantic Ridge, they're splitting. Here, one is going under another, right? >> Mhm. >> So, so it's a little bit different. And I think that's what's really cool. So, life is constantly trying to redefine boundaries, right? We've got extreopiles everywhere. Yellowstone, the the life in the hot springs. That's something that's in every single biology textbook. You've

44:09got hypers saline ponds in the Atakama desert that somehow managed to have bacteria. You've even got like nuclear reactor cores of power plants. >> They've got weird bacteria. >> That's interesting. >> And I want to cover that in another future episode because those things are very cool. this new paper, it's a landmark 2025 paper and it provides biomarker evidence for serpentine chemosynthetic biosphere. Okay, in the Mariana's Trench. So the setting is something called the Mariana for arc right under Japan east of the Philippines is the Mariana's

Serpentinization — rock–water reactions, H₂ and abiotic methane

44:48Trench. And you see that like the sort of crescent of the Mariana's Trench, >> the Captain Hook. Yeah, that hook is the Mariana's trench, right? That is one plate subducting under another. Okay. >> And right, not in the trench itself. The trench is like the bottom of that subduction zone, right? Where the the ocean is like a few Mount Everests deep or whatever. It's very very deep. Here, this is a part of the of the subduction zone that's at the top. M. >> Okay. It's only about 3,000 m below the surface, but it's still impossible conditions. Okay, hyper alkaline pH, so you've got 12.6

45:30pH. >> Jesus Christ. >> Okay, water is at 7. And we're going to get into that a little bit. >> Um, it's really cold. 3.5° C, >> right? So that's about maybe what uh 40 30 37° F. Very cold. Very cold still. I mean, I might have surfed in that kind of temperature, but I didn't have a good time. >> Yeah, exactly. But somehow these bacteria are living there. And there's also a nutrient scarcity. There's profound limitation, especially when it comes to phosphate, right? There's not a lot of phosphate there. >> And what's what's really cool is this paper finds life there and then tries to characterize how that life is doing

46:11living right >> down there, which I thought was very very cool. Yes. The geochemical engine is something called serpentinization. Okay. It's a reaction between water and whatever mantle rocks are down there because this is like very close to the earth's earth's crust, right? So, you've got water, you've got some rocks, and what what is output is a mineral called serpentine. >> You've got a lot of molecular hydrogen, >> okay? >> H2. >> Okay. And H2 is a very energetic molecule, right? You can burn H2 and create energy in water and CO2.

46:52So, um, that's what's very interesting here. Okay. And the analogy is like, you know, when when when you've got iron and minerals, that iron splits and reacts with the oxygen and creates creates hydrogen because the water, it's going to strip the the oxygen out of the water and create H2. >> Yep. Something similar is happening down there, right? The minerals are reacting with the oxygen. Yes. In the water and liberating the hydrogen. Yep. >> Okay. And then that hydrogen then goes and then creates methane because there's going to be carbon there too >> cuz there's a free It's free hydrogen floating around. >> Yeah. Free hydrogen floating around. And that fuel is then going to create

47:33abiotic methane. So this is not methane coming from life. This is methane just coming from the chemistry down there. >> Got it. Okay. You know what I mean? >> Yeah. Yeah. No, that makes sense. Yes, that makes sense. >> And and so that's that's what's really interesting. We got to understand sort of the the the tectonic setting here >> in in the Mariana's Trench. So I told you, right? It's a subduction zone. >> Yes. >> Um you've got you've got one plate going under and another plate going over. >> And the fluids in that subduction zone in the mantle itself are what create the serpentinization. You've got like a sort of chemical process that like rejuvenates the ocean floor with with with new chemicals and things like that,

48:15but that resulting chemical is like the the the the water there is like really really messed up. Okay, >> which which makes sense. >> Which makes sense. It's like way deep. >> It's it's near a subduction zone, but the pH is 12.6. Okay. That's like bleach and oven

Bleach-level pH 12.6, 3.5°C, and nutrient scarcity

48:32cleaner. >> Yeah, it might it might cure COVID. I I heard that. >> Oh, yeah. Yeah. Yeah. Yeah. So, so we just got to go to the Mariana's Trench, >> right? Get it and then drink it. Yeah. Yeah. Yeah. Yeah. But somehow, so these bacteria don't have CO for sure because they live there in that bleach and oven cleaner of 12.6. And just to tell you just how bad that is, right? So the pH of water is 7. Water is at a pH of 7. And what that means is pH means percent hydronone hydrogen ion. >> Okay. Um it's a log scale meaning that water has a concentration of H+ which is 10 the -7 moles per liter. Moles is a is a unit of the amount of stuff. It it has

49:14to do with Avagadro's number. It's about 10 the 23 thingies. Like a dozen is 12. A mole is 10 the 23 * 6. >> So I'm not I'm not going to order a mole of cupcakes from >> But you would order a mole of water. >> Oh, actually no. A mole of water is like I think 55 L. So maybe not but something like that. Like a mole of carbon 12 would be 12 g. >> Got it. >> Right. >> So um that means that there's about 10 the 15 hydrogen ions per liter. >> Mhm. >> In just normal water that we drink. >> Okay. >> Something with a pH of 12.6 Six means that there's 10,000 fewer hydrogen ions and 10,000 more O

49:58minus ions because the oxygen the the H2O can split into an H+ and O minus. Yep. Right. >> 10,000 more O minus ions and 10,000 fewer H+ ions. That is an incredibly basic environment. There's all these O molecules with a minus, right? They're an ion. They're it's extremely reactive. And the fact that anything can just like stay stable down there is incredible. >> Got it. Okay. Yeah. So what we're trying to identify is the base environment in which we are trying to even operate >> is not ridiculous is not conducive to

Gravity corer, blue serpentine mud and mineralogy

50:35operation. >> Yeah. Yeah. Yeah. It's ridiculous to like to like stuff that we know >> stuff that Right. Right. Right. Right. Right. >> So here's how they uh they um they got the sample. They have something called a gravity corer. >> Okay. It's a It's a It's a core. So, what they do is they they get like a 1.4 ton weighted steel pipe and they just shoot that down into the into the ocean floor and they grab like 2 m worth of >> soil. Yeah. >> In there, right? They bring it back up into the surface. Then they take the mud out. The mud h has this blue hue which is serpentine. Blue serpentine. Okay. There you can see. And the you can do

51:16minology on it. You can do X-ray defraction and thermal gravity and you can identify minerals like serpentine >> okay >> and brusite and things like that >> the pro and what you want to do is you want to find life there right >> the immediate thing that anyone would do it's like okay I want to find life what do I do I look for DNA >> easy yeah >> I look for DNA >> this thing has about 10 cells per cubic cm that's really low >> right low usually usually You got something like 10 to the 5 cells per cubic centimeter in soil. >> Okay. >> Okay. Soil has a ridiculous amount of cells, a ridiculous amount of DNA. >> This thing has only 10.

51:58>> So what's going to end up happening if you try doing something like PCA, which is polymerase chain reaction, it's basically a way to amplify DNA in your sample. So whatever little bit of DNA you have, you multiply it and then you try to, >> you know, put it through your measurements >> sticks and you try to figure out what the thing is. Um, if you try to do that, you only got 10 living cells. Most of the DNA that you're going to have is just going to be dead stuff that's conglomerated on the ocean floor. >> Right. >> Right. Because the the ocean has just raining dead material >> all the time. Yeah. >> All the time. Phytolanton, maybe a whale died somewhere. So, you're going to have

52:38all of this random DNA and not the actual DNA of the stuff living in there.

Why DNA fails here — too few living cells, too much dead rain

52:46>> Not a perfect analogy, but if you try to take a photo that is really low resolution and blow it up to really high resolution, you're trying to take pixels that didn't exist and make them larger and this just going to be a larger version of not a lot of information. >> Yeah, exactly. Like if if you did one of those like AI um depixelizers of a really bad photo, it's just going to start making up stuff because you don't have actual in it's this is dead information from potentially a lot of dead stuff. >> A lot of dead stuff that's just been raining down on the ocean floor, right? So you can't really do that. >> Okay, that makes sense. >> So instead, what you do is you go for trying to detect lipids, which are fat molecules. Okay, lipids are the stuff that make up the cell membranes of your

53:30cell. Every single thing has this. Okay, a lipid membrane. You need a lipid membrane because how do you how do you define life? Well, you need an inside and outside, >> right? >> It's the border. How do you define a country? You need a border. >> Yeah. Yeah. Exactly. Yeah. But how do you define life? You need a border. You need a a 2D border for a 3D object, right? And that is always a lipid, a bi- lipid membrane, right? So, so every single thing of life is going to have these lipids. Now, there's going to be two types of lipids. There's going to be the living lipid, >> okay, >> from whatever is living in there. And then there's going to be the dead stuff that's raining down. How do we actually discern between the two, right? And so,

54:11here we're going to have two different types of lipids. There's the core lipid, which is lipids that look like this. They've got a um they've got a part that likes water >> on the top, the purple one, and then a part that doesn't like water. >> And what you do is you make two membranes out of this. So there's a part that likes water that is facing the outside, that is facing both the inside and the outside. And then the inner part is the part that doesn't like water. So now you've got a way to separate water from water, >> right? So you've got a way to separate the cytoplasm of your cell based on a wall that really doesn't like to cross.

54:53>> Those lipids have two parts. There's the part that likes water, the hydrophilic part, and then the hydrophobic part, which is like part that doesn't like water. >> If you see those intact, >> that means it's pretty recent. M >> on the other hand, if it's died for a while, >> those two will have clipped off >> and you're not going to see the two >> together >> together. Right. So, you've got these intact polar lipids. >> Okay. >> Right. And that's what these guys were

Core vs degraded lipids — distinguishing living vs dead biomass

55:18looking for. >> Make that makes sense. The point being that the by finding these uh what you say uh bipolar lipids. >> Yeah. Polar lipids. >> Polar lipids. um both sections still being >> in close proximity, meaning that they were preserving something inside that was a bi like a living process. >> That means it was as close to living as we can get because they're still in close proximity. As an organism dies, >> those things naturally because they no longer need to maintain the life inside. They will uh part away from each other. >> Yes. Exactly. And so this is like a tangible way for us to be like this is

55:59>> recently living or currently living versus this is for sure dead. >> Exactly. Exactly. Right. So that's one way of doing this. >> The other way to do this is to actually look at the carbon isotopes in your life. >> Right. There's uh there's two stable isotopes. There's carbon 13 and carbon 12. Carbon 12 is way more abundant than carbon 13 but both are sort of mixed in together. Um, there's a baseline like there's a baseline abundance of them, but life is going to have way more carbon 12 than carbon 13 because it's lighter. And so whatever enzyatic action is happening, the enzymes are lazy and

56:39they're going to use the carbon 12 more than the carbon 13 because the carbon 13 is harder to move around, right? Takes more energy. >> It takes more energy, right? And so for whatever little bit of energy you have, you're going to usually just by probability fix the carbon 12 into your organic chemistry more than your carbon tw carbon 13. So by looking at this abundance, we can also tell whether what we're looking at is alive now >> or has died and is just sort of, >> you know, part of the thing. >> Yes. >> Right. And from this they they found that there's there's one thing that was really cool is when they look at the mudline, right? They have this 2 meters, two or three meters of the ocean floor. Yes.

57:19>> At the very top that's close to the ocean floor, >> they don't see a lot of these biomarkers. Okay. >> So, a lot of the stuff is dead, >> but underneath they're seeing living organisms, >> right? So, there's a living tissue that's happening underneath. There's a layer of dead stuff. >> Yeah. And then there's active biology >> underneath it. >> Underneath it. Right. And by doing a bunch of different oxidation measurements and like HLC's and all this other kind of stuff, they came up with a really complicated ecosystem where you could actually like find like what were the things that are making this happen. And they have an hypothesis where the

58:00methane comes from the bottom and the CO2 comes from the top and the water comes from the top. And they have all of these different mechanisms that they've actually traced through. >> Yep. >> To create a a a magnificent ecosystem, >> right? >> This is it's there's a circle of life just for this >> just in there.

Carbon-13 fractionation as a metabolic fingerprint

58:19>> Just in this area, >> isolated from the sun. There's no sun. >> Right. Right. Which is important. >> This is important. It's isolated from the sun. It's completely driven by chemical processes that are happening because of the interaction between water and the Earth's crust. Right. >> Mhm. >> And it's completely in isolation from the rest of life on Earth. >> Mhm. >> Mhm. I think that's that's that's a foundational claim >> because because and again I think that just to kind of parse the implications a little bit here part of the point is for a layman like myself a lot of times

58:59we'll think of uh sunlight solar energy as being a required prerequisite for all life >> and when the sun goes away you can't have the light life because that's the only source is why uh uh photosynthesis is so foundational and all this other stuff. >> What this is saying is independent of sunlight and this goes back to your point earlier about why it's different than the the heat vents or heat >> or Yeah. Yeah. Yeah. or heat or the sulfur the the active stuff moving out. This is just like slow chemistry

59:39happening in the crust and it and it and out of that slow chemistry in the crust, you still get life. >> You still get life. They still find a way, >> right? As uh Jeff Goldblum was saying, life finds a way no matter where. And there there it's it's incredible how they find a way, right? There's all these adaptations that they've come up with. For example, >> in there in that high pH, those lipid molecules are just going to become like soap. >> Mhm. Right. So, how do you prevent the soapification of my cell membrane? Well, instead of the estrobonds, they're using ether bonds. So, instead of a carbonil bond where the carbon is attached to an oxygen and then two groups, you've got an oxygen that's mediating that. And

1:00:21that oxygen becomes the anchor for your phosphoipids. Not not phosphoippids, sorry, glyolippids because you don't have a lot of phosphate. >> Right. You're using actually like sugar and a bunch of lipids to actually create your cell membrane. The other thing that's kind of crazy is that, you know, at that temperature, fat freezes, right? Butter, butter is a solid in the fridge, >> but that's because it's a saturated lipid. If you use unsaturated lipids like oil, that's not going to freeze. And the reason why it's unsaturated is because you've got these kinks in your carbon skeleton. You've got a double bond instead of all single bonds. And a double bond means you're going to have a kink in your carbon skeleton, which

1:01:02means it's not going to stack up >> as nicely as saturated lipids will, right? And if you're saturated, then everything's going to stack up and you're going to become solid. >> Yes. >> But without the saturation, then you're going to remain liquid and you can you can have that malleability that you need for life. >> Yeah. Yeah. >> That's And it's so funny that it's literally that double bond kink of Let me actually pull that back up. That was photo 12. That double bond kink carbon >> in the middle. >> Yeah. >> Literally just that. >> Just that >> totally uh changes the entirety of the the the expanded structure that you scale up to.

1:01:42>> It's kind of crazy, right? >> Like life figures out ways to >> it's crazy >> to make it work. >> Yeah. >> You know, using fund it's just fundamental physics. The double bond creates a kind of weird quantum mechanical effect here where like now my bond can't be linear, >> right? And which means it at at this temperature it can't just then solidify into a block. It has to remain in that. Look at that. >> It's so cool. >> Yeah, I like that. >> It's so cool that like life can find this out. And this has huge astrobiological implications >> obviously >> and for me that's the coolest part. Um >> the cool biosphere analog, right? Like the Mariana's Trench is this first highfidelity analog of cool

1:02:24serpentinization >> in the cold. >> In the cold. >> Okay. Not in the hot, right? >> Not in these um zones where the plates are drifting apart and the heat's coming

A cold, chemosynthetic biosphere under a dead sediment layer

1:02:34out and sulfur and all the >> This is cold. >> That's actually really important. So like it all of the ice moons >> Mhm. >> become much more interesting. Yes. Because of the existence of proving that cold serpent, cool serpentization can have a biosphere. >> Exactly. Exactly. And Enceladus is a big one. Cassini actually sampled plumes. This is a moon of Saturn. >> And Encelatus is something where we know there's an ocean oceanic >> um ocean. There's an ocean there. There's a crust on top. And there's so much geological activity that there's actually geysers that shoot out plumes of stuff into the into the into the

1:03:15cosmos. And Cassini, we were lucky enough the Cassini got close enough that it actually sampled those plumes. >> Mhm. Mhm. As it was flying by. >> As it was flying by. And what we measured was hydrogen gas and methane. >> Uh which is which is exactly what we have here. meaning and so like just I know I'm extrapolating this is an extrapolation however given what we just walked through about what we've seen at these two plates >> in the Marian's trench on Earth where we were able to send down our little torpedo pull up meters worth the

1:03:56top layer was dead but below that the same chemistry yeah >> that exists in that region here on Earth mimics the chemistry that Cassini pulled up. >> Yeah. >> And there's a direct match. >> There's a direct match. >> That's not to say that there is life on Enceladus. >> Yeah. >> However, the chemistry >> the chemistry is very same. Same. >> It's very similar. >> Yeah. >> A pizza in New York is not the same thing as a pizza in California. >> Yeah. >> I get it. >> Yeah. >> But it's still a pizza. But there there's possibility there which is so

1:04:36exciting. >> Which is so exciting. The other thing with Europa, right, models predict that serpentinization is actually more probable than let's say deep sea vents on Europa, which makes sense. And now we've got Europa Clipper going there, it's going to do a bunch of things. >> If we're going to send, you know, if we get our funding back >> and JPL gets its funding back, we >> need our funding back. >> Yeah. But if we do, then we're going to send, you know, let's say something that drills into the Europa Y ocean and then tries to look for it. Well, those things should probably have a mass spectrometer, >> right? Because the mass spectrometer is what was used to actually characterize these lipids and these lipid biomarkers. So maybe let's not look for DNA. Maybe

1:05:18let's look for lipids. Right? This introduces a whole new paradigm for what to even look for when we go to these distant worlds looking for extraterrestrial life. That's a brilliant insight in that what we look for determines the results and it's the so it's the push back that people have given about steady looking for radio signals and it's like any sufficient technological da da like would they be still using it yada yada I mean in a in an analog in an in an analogy what we're saying is historically maybe we'd always be looking for DNA as the sign of life uh looking for lipids the presence of lipids is another signature >> yes >> that is equally relevant and viable

1:06:00search and might be more fruitful >> because even on earth we can see in regions that we previously believe to be uninhabitable life is there but the way we found it was not through the DNA was through the discovery of the lipid presence. >> Yeah. Exactly. And like who knows maybe they have a different form of genetic material right DNA is like this arbitrary thing that perhaps our ancestor 4 billion years ago came up with right to to encode data >> but there there's there's got to be other ways right it's just whoever came up with it first was like this is dope >> and then just like ran with it

Astrobiology implications — Enceladus & Europa analogs

1:06:36>> right >> uh we are living with the uh choices that the internet pioneers of the early9s decided how a browser was going to work and how graphical user interface was going to work and that's just >> what it is and now we have to deal with that. That is a very interesting story >> with huge implications not only for again expanding our idea of what does life mean just here on earth >> but then informing how we ask questions about the universe around us in that same journey. Uh fascinating fascinating paper. Um we have that one again from University of Bremen. That was a nature

1:07:16communications earth and environment. >> This this week of stories is fantastic. We're going to move on to our third story. Our last story of the day, our Princeton story. >> Yes, >> we've we've we've kept a couple weeks of not shilling Princeton, >> but like when you're the best, things happen. >> I don't I don't know what to tell you. >> Like it's just it's it's a breakthrough. And so we cover breakthroughs. The millisecond transmon cubit breakthrough out of Princeton. This was in nature. No subjournal. >> Yeah. >> Nature mainline. >> Princeton's new quantum chip makes a major step toward quantum advantage. Now in a previous episode, you explained to me the distinction between quantum

1:07:58advantage and quantum supremacy. >> Yes. in the context of Google's paper claiming that they've achieved quantum supremacy which received a significant amount of push back >> but this is about Princeton's quantum computing >> uh for a new cubit the cubit being like the fundamental unit bit in a classical computer cubit and a quantum computer so what is it that we literally we as in you and I personally >> Yeah yeah yeah I I donate I donate I donate my money They called me up like

Story 3 starts — Princeton’s millisecond transmon qubit

1:08:30uh last month being like, "Hey, are you the class of 2014?" I was like, "Yeah, fine, fine, fine, fine, fine." Here. >> As long as I get the claim that I was the one who came up with this quantum breakthrough. So, so talk to help me understand like what >> cuz we talk about quantum quite a bit actually. So, we do. So, this is it has to be actually a big deal. Yes. >> For you to put it in. >> It is. It is. It is a big deal. Yeah. So, quantum computers, right? The promise is to break encryption, simulate materials, you get a better portfolio for your financial stocks because it's going to like figure out the best way to do things. And all of that relies on actually making a quantum computer, right? And making a quantum computer as of now, it's still a hardware problem.

1:09:13>> Okay. >> Okay. Okay. >> It is still a hardware problem. A quantum computer, let me just go through briefly what a quantum computer is. Okay. It uses a cubit instead of a classical bit. So a classical bit is your transistor that is in a state of either I'm going to let current through or I'm going to block current. So that's my zero and one. A cubit can be in a superp position of two states. It can be in a zero and a one. And it can be in a linear combination of something in between. The other thing that's different about a cubit versus a classical bit is a classical bit, one transistor doesn't really talk to another until it's like really told to, right? It's like maybe

1:09:54one one transistor flips its sign based on the state of another transistor. And that's an explicit sort of thing that we're doing within the algorithm of whatever we're implementing. But in a cubit, the power of the cubits is that they can be entangled to one another. They are not independent, right? So one cubit can be in a superp position of zeros and ones. Another cubit right next to it can be in in a superp position of zeros and ones and so on and so forth. And I can get access to an exponentially large number of states in my memory without actually having to explicitly encode each one of them. Right? As a

Cassini plume chemistry and the Earth match

1:10:33terrible analogy because I'm always trying to figure out ways to think about it in my head. If you have a relay race, a 4x400, classical computers, you have to wait to hand the baton to the next runner. >> Yeah. >> But in a quantum computer, my first lap, the first runner can have like multiple >> runs >> and like whichever one happens to get there first is like and so it's like your parent >> all four just basically cheat, right? Go through the whole thing. Yeah. But just as trying to like contextualize like what the difference is when you say that a cubit can be in a superp position of both zero and one. There's not you're not waiting for the handoff in order for the next thing to do its next process.

1:11:15>> Yeah. Yeah. You can do a lot of things in parallel and and you can access a lot of computational stuff in parallel. Yeah. Yeah. It's a weak analogy but it'll work actually. Um and and at the end of the day, how a quantum algorithm works is the following. There's something that's very um famous called the shores algorithm. Okay, this is the one that all the NSA and everyone is excited about because this is the algorithm that lets you break RSA encryption. >> Okay, >> but it works like any other quantum algorithm in that here's what happens. You've got a bunch of cubits that you're going to prepare in some kind of state. Let's just say for for um argument sake, I'm going to prepare them in the zero

1:11:56state. So they're all zero. >> And then what I'm going to do is that I'm going to apply quantum gates to these guys. Okay? And what that means is I'm going to poke this cubit a one way. So it's going to maybe flip from a zero to a one or it's going to flip into halfway between 0 and a one. And then this guy's going to talk to its neighbor who's going to talk to his neighbor. And all of these quantum gates are basically pokes in some way >> of each of the bits that I have. >> The the key bottleneck is the following. Okay, my gates and my poking have to be faster than how long it takes for my cubit to forget itself. Here's what I

1:12:38mean by that. Okay. >> In a transistor, if I turn it off, it's going to stay off. >> Unless like a cosmic ray comes in and like like you know the the the some proton comes in and knocks exactly that transistor from a zero to a one. It's going to remain off and I can reliably come back and it'll remain off. This is how data works, right? Why why is my data >> or how do I store stuff, right? This this is the transistor is in the in or like whatever thing is in the zero and the one is going to be in the zero and one forever. It's not a transistor. It's solid state or whatever. But at the end of the day, I have some time horizon that is way longer than my computation.

1:13:18>> Yes. >> That I know can reliably remember if it's a zero or a one. In quantum mechanics, that's no longer the case because these cubits are made out of incredibly small technologies. Okay? And so there's a lot of forgetting that happens. I I I prepare my cubit in a zero state. For example, let's take the extreme case of an electron that's spinning in one direction and that's my zero. If it spins in the other direction, that's my one. >> Well, I need this thing to remember that it's spinning in that direction. Yep. >> But if there's a bunch of stuff around it, it's going to start poking it, right? There's a bunch of atoms and a bunch of little magnetic fields that the

1:13:58atoms create that are going to try to change the way that my electron is spinning. So if my electron is this cubit where spinning down is zero and spinning up is one and I prepare it in the down, it's not going to take very long for that electron to just get influenced by all of the stuff around it and forget that it was a zero in the first place. This is called the decoherence time. >> Okay. And one of the central challenges is one one of the central challenges in creating a workable quantum computer is to make the decoherence time way way longer than the

1:14:39algorithm time. So so this this actually

Decoherence time — why qubits “forget” so quickly

1:14:42makes total sense. The the point is you don't actually have like a workspace that is active for long enough for you to do like yeah >> like valuable computation to get an output because the decoherence time is so short. similar to our first story because we're at a scale now where the little stuff >> changes in very very very small things >> that might not have mattered in a classical system matter a lot in this uh quantum system in the same way that like under five mock you don't have to worry about the little stuff but above five mock you have to worry about stuff in a in a different way or the details matter and so >> if you can increase the decoherence time

1:15:24that means I can run a longunning algorithm. It's like a context window in AI. Yeah. Like exactly like like you you have more time to do the thing you want to do before >> forgets. Yeah. Before before it forgets, right? And Yeah. Yeah. And there and there's ways to do this to get around it. There's stuff called error correction where what you do is you like replicate the cubit multiple times and then you have like a bunch of cubits retain that information. So if one of them forgets, you can have like the other guys. But like at the end of the day, a hardware solution is >> is king. >> It's not it's not clean. It's not >> clean. >> It's not clean. Right. Right. You have to do all of these contingencies. If you have a hardware solution, well then you can implement that software solution

1:16:05with the hardware solution and even multiply. Correct. Beyond >> beyond like what you were. So the hardware is always king. >> The king. The biggest fundamental limit is still at the hardware level. >> It's still at the hardware level. Exactly. And so there's different kinds of cubits. I just gave an illusion of the electron being a single cubit, right? Where it's like spinning one way or the other way. The one that we're talking about is actually pioneered by the 2025 Nobel Prize in physics by these three gentlemen's um John Clark, Michelle Devay, and John Martinez back in UC Berkeley. They came up with this idea of macroscopic quantum tunneling. Right. The idea was to make a quantum circuit, a tiny little circuit that had

1:16:45something called um a Josephson junction. Yes. And then you have on the order of billions of electrons that behave like a single quantum unit that are tunneling from one to the other from one to the other. Right? We had a great deep dive on this during the Nobel Prizes. So it it is a phenomenally well done deep dive. Yeah. So, please go check out our our Nobel Prize episode on this because if you're curious about this concept of the superconducting circuits with Joseph and junctions and macroscopic quantum tunneling, it is really fascinating and we have I think one of the best explainer videos out that's available.

1:17:25>> We won an award from Tik Tok. >> We we did Tik Tok did give us second place for our science content because it was so good. Um, and I just was so fascinated by please watch that video. >> Exactly. So, so these guys sort of, >> you know, went and created that thing, >> right? >> And IBM and Google now use something called a transmon design, which is a charge cubit. It's basically their design, but they've attached a large capacitor on on the side, and they've made it insensitive to charge noise. But this is this is basically the cubit that they're using to make the um the quantum computers that they talk about. So

Segue — three big stories & Princeton hype

1:18:02currently there's not a lot of quantum computers that are being built. There's very few amount of entities that are doing so. The ones that are like you're saying with with IBM and they're using this particular structure >> uh for the in order to be able to like do the the process that we're talking about how which has existed prior to the paper. >> Yes. Exactly. Like like there there's a platform that everyone's using saying this is kind of the way we got to go everybody. This is the current state of the art and that's what it is.

Materials, defects & tiny-scale imperfections as the enemy

1:18:34>> Yeah. Yeah. Exactly. But those guys had this problem of decoherence time. This new paper that's come out um in nature. >> Yes. >> Millisecond time scales. They're they're getting they're getting their stuff all the way to milliseconds. And this is a victory against the materials that we're using to actually create that transmon cubit. And this millisecond time scale is about three times the time scale that was there before the record. And it's 15 times what is the industry standard. >> Okay. Got it. >> Okay. It's very long. >> It is an order of magnitude. >> Order of magnitude >> um better improvement uh upscale. Got

1:19:15it. Okay. >> Exactly. Yeah. And what they're doing is they've the problem is, as I was saying, right, there's these tiny defects that happen everywhere else that sort of make my cubit forget what I am. If it's a zero, it'll just go halfway. If it's a one, it'll go halfway. Um, there's all these like glassy materials. There's oxides, there's substrates that happen when I construct my chip that is gonna that is going to make the decoherence happen. And so and just just to kind of zoom in on that point, the point is >> in the process of generating these chips, >> we have to make things at these incredibly small scales. >> Our engineering capabilities are quite

1:19:56good, but there are still levels of imperfection or just that the scales are so small that things tens of atoms, hundreds of atoms. So the slightest little thing um is going to again take our gate of our decoherence time and shrink it with any amount of >> 10 to the negative >> big number imperfection which is like barely anything. Yeah. >> Am I understand the quantum world >> it matters everything it's everything. Okay. >> You know. >> Yes. Yes. So that that's that is the one of the core sources of the decoherence time problem. >> Yeah. is all of these little

1:20:37imperfections that are coming in. And so there's been a history of trying to make things better, >> right? >> Okay. When it comes to getting longer and longer decoherence times, the first platform was to try and use nobbium and aluminum. Okay. >> The sapphire actually sapphire is just aluminum oxide >> and that was being used instead of nobbium in 2021 there was a breakthrough. The same group actually instead of nobbium they used tantelum. Okay. >> On the sapphire aluminum oxide. >> And there they got up to about 300 milliseconds. >> Okay. >> Okay. Sorry. 300 uh.3 milliseconds. So 300 microconds. Right.

1:21:19>> And then finally now they've challenged this bottleneck and instead of using sapphire they're using highresistance silicon. >> Okay. >> So extremely pure silicon that is high resistance. And what's happening is you're superconducting stuff that's happening in the cubit. It's no longer dissipating energy into the substrate itself because the substrate has such high resistance. One way to think about it is the energy just doesn't want to go there. Right. And so it's staying within the the cubit the the part of the circuit that actually matters. >> They they've locked down their border. >> Yes. Yes. In some sense. Exactly. That's

1:22:01exactly right. They've eliminated this bulk loss and using tantelum which is something that >> not a lot of people use but these guys were using it. Tantelum turns out to be much better than nobbium and aluminum. >> Okay. >> So it's this combination of tantelum and silicon and that was super non-trivial for them to actually grow because you've got silicon and you got tantelum on top. There's all this like chemistry that's happening that's like kind of weird. They had to use a really ultra high vacuum. Before they were using just high vacuum >> and it wasn't enough. >> It wasn't enough. Yeah. Yeah. So they had to use ultra high vacuum so that when they were depositing this stuff, no

1:22:42weird oil was getting in. Nothing like that. When it interacts with the air, nothing weird is happening. It it's it's it's been a process that's been happening for quite some time. But at the end of the day, they beat that millisecond barrier and they got to the key. The point is like they had to cook up like like Breaking Bad like like Heisen they had to cook up the the material that actually went into the the the thing itself the chip itself that is being now used to do this process. >> Yeah. Exactly. It's like completely novel. >> It's not like you can just go like hey Nvidia like hey you know TSMC and then let's just they were doing it. >> They had to which like I I want to like make that just >> like that's a big

From niobium/sapphire to tantalum — history of longer coherence

1:23:24>> Yeah. challenge. It's it's it's multiple groups in the university. The chemistry department was involved. The electrical engineering department was involved. Like like there's all these different players that were like, "Oh, actually I'm really good at tentelum." >> Yeah. Right. >> And I'm pretty sure you need tentelum, right? And then somebody else was like, "Put this on the silicon and you're going to need a higher vacuum. >> You're going to need a higher vacuum." Yeah. Someone was like, "You're going to need more cowbell." >> Yeah. Yeah. Yeah. And there's all of these different different factors that are coming in in this ecosystem at Princeton to create this cubit. And this cubit is amazing. It's got >> the best one. >> The best one had 1.7 milliseconds. >> That's crazy. >> And to tell you just how how big this

1:24:05is, you know, before you were getting to.3. >> Yes. >> The best one is now five times. >> Right. Right. >> And that.3 was in a lab setting. It's not at the industrial setting. Okay. M so you're getting you're getting almost 20 times to 25 times the industrial setting of stuff right and you you might be thinking you know a millisecond that's a thousandth of a second thousandth of a second is not very long well the gates right the the the stuff that we're using for quantum stuff is on the order of tens of nanconds >> right so you can fit in a lot more stuff >> in one millisecond now a nancond is >> um a 100 thousandth of a millisecond.

Ultra-high-vacuum fabrication & campus-wide collaboration

1:24:47>> A millionth. Sorry. Yeah. >> The this is actually really significant because um it's also because it's like qu like when you're doing it's parallelized, right? So it's it's the volume of what you're actually doing. It's not like it's not like every millisecond that goes by because you're now parallelized in what you're actually doing like the actual amount of work the way we think about it in a classical sense >> it I don't know if I'm explaining that correctly you're exactly right like the the >> the >> how do we say it the the the amount of stuff you can do with this

1:25:28>> the amount of tokenacy the token output >> is is is not just like the same as you would get in a millisecond on a classical system. >> No, no, not at all. >> The token output is like running chatbt parallelized n number of times and all of those token outputs get you to your derive like your ideal whatever up. I'm just trying to talk about how that millisecond difference is extremely meaningful. Exactly. And the other thing is you know getting let's say 20 times longer >> Yes. >> in this decoherence time >> Yes. adds up exponentially because because here this is a physical error, right? This is this is something that's happening at the hardware level, right?

1:26:09So all of your error correction algorithms >> can now take advantage of the fact that the thing that they are doing the error correction on is itself not that bad. >> Yeah. Yeah. It's less errorprone. Yeah. Right. Right. It's it's more it has higher >> efficacy. So so so you're adding on exponential on exponential, right? and and it's going to it's going to be a really big thing. I think the the other the other huge thing about this is this chip um which is it's it's just an upgrade on the industry dominant transmon architecture >> okay >> which is the same thing that IBM and Google have been using in their current architecture right the recent paper that came out of the willow quantum chip in

1:26:51Google >> it's using the same architecture >> so the thing is this is something like a I can take that out >> and I can put this thing Yeah. Yeah. All of the outside of the chip itself, there's all of the other the cooling system, like all the other infrastructure. >> Yeah. The way I talk to the chip, >> all of that. >> They could hot swap the chip. >> It's not a new It's not a totally new uh chip design that requires a refactoring of the rest of the infrastructure. That's really >> That's huge actually. Right. Because because now this is scalable. It's industry compatible. >> Yeah. >> Right. And and so and so if Willow just gets this design, it's going to be a thousand times better. And Willow

1:27:33already is like making headlines. >> So imagine what it can do with this, right? It's really bringing us closer to that >> future possibly of where >> something scientifically standard could be happening with quantum computers, you know, within the next decade, >> you know.

Millisecond coherence — ~3× the lab record, ~15–20× industry

1:27:53>> Mhm. And I I mean there's again everyone always talks about all the implications of quantum computers. The one that still gets me most excited is like the ability to create simulations and models with higher fidelity. Coming back to our first story, >> new materials. >> Yeah. Right. Right. And like the things you can then >> Yeah. Instead of trying a thousand different materials to see which one is the room temperature superconductor, I can just like simulate a bunch and then be like, "Oh, these are 10 good candidates. Let me try making those." And you know >> because like like alpha fold was a lower complexity problem to like do all the folds that proteins can do. >> Yeah. I mean it's still an incredible >> not minimizing. >> Yeah. >> Not minimizing but we've already crossed

1:28:33that bridge. So you know what I'm saying? Like >> you already got the Nobel that's in the past. We trying to go orders of magnitude. Yeah. Yeah. Yeah. Now we doing quantum mechanics mother which is like it's a big that's a big these the all of these stories are actually pretty crazy. >> Yeah. Like so so I think this is this is huge. The other thing is um they're using silicon, right? Instead of sapphire. So instead of aluminum oxide, they're using silicon. Well, we're as humans incredible at making silicon. >> We have the whole the whole industrial

Why milliseconds matter for gate depth & error correction

1:29:01infrastructure for that is actually like prime. >> Yeah. So scalability in terms of that is going to be huge. >> That makes sense. That makes sense. >> Um yeah, we can piggyback on this trillion dollar semiconductor fabrication process. >> This is crazy, >> right? Yeah. And that's that's a photo of one of the grad students probably posing with it. >> Yeah. They're like, "We don't need your face. We just need your beautiful hands." >> Yeah. Yeah. Yeah. You're a hand model. >> Yeah. Put the gloves on, though. >> This is expensive. >> Yeah. Exactly. Um, so yeah, very very very cool. I think I think it primes the new chips for industrial scaling. We could be we could be getting we could be getting ever closer to that dream. this.

1:29:41So now I can read the title the millisecond >> 5x 3 to 5x longer amount of time you can actually run and keep things in memory for lack of a better term. >> Um transmon the platform >> that is already industry standard that's used and so it's not like net new and everyone has to change everything. >> Yeah. >> Cubit breakthrough that the type of thing we do a tantelum silicon cubit out of Princeton >> in nature. >> Yeah. We're still number one. I don't care what nobody says. >> Yeah. >> Actually, there we we are though because there was a there was a thing that um it took the US News rankings and all these other rankings and then averaged it out.

1:30:23>> Oh, yeah. >> And we were number one. >> Yeah. Look, I'm just We talked about our leaderboard that's coming in our last episode. That leaderboard, we're going to create our own metric. >> Yeah. >> And make sure, >> you know, it it'll be the the methodology will be public. >> Yeah. It won't be a black box like all these other AI >> models as cool as always >> and it will just rank based on the facts, you know, as we like them. >> Yeah. >> Um

Human scientific resilience & modeling everything

1:30:53>> uh three super super sick stories this week. We talked about hypersonic aerodynamics above Mach 5. >> Uh very interesting. Had a Stevens uh Stevens Institute of Technology in New Jersey. That was in Nature Communications. We followed it up with uh some microbial life in the deep sea. Not near hypothermal vents or anything. This is in a different This is cold. This is cold. Uh scientist The title was life found in place scientists thought impossible out of University of Bremen. There were biomarker evidence for serpentine serpentine chemo synthesis. >> Yes. >> Yeah. >> In the Mariana for arc communications uh nature communications earth and

1:31:33environment. And we ended with an incredible quantum breakthrough. Millisecond transmon cubits out of Princeton in nature. I I just I mean the stories we've covered this year have just been and again it's it's tough because we weren't doing this in previous years. So it's like >> Yeah. We don't know. >> We have no baseline. >> Yeah. I mean I'm learning a lot doing this show. It's it's pretty it's pretty

Season-1 energy, future leaderboard idea & rankings banter

1:31:55cool. >> It's incredible. I just hope people recognize and understand how incredible some of the stuff we're doing all the time is. I mean, as humans, we're we're so sick. We're Dude, we're so sick. >> We have problems. Okay, we get it. >> Yeah. Yeah, we get it. >> That's those are like individuals and like groups that identify with problematic stuff. >> But when we when it comes to like science and like resilience and like just like our ability to >> like chipping away at that cave of the unknown, you know, it's just amazing.

Outro — “we’re so sick” as a species & closing credits

1:32:27>> It's incredible. Uh I'm Lester Nar as always joined by my co-host and our resident PhD Krishna Chowy with another incredible episode. We will see you all next week. This is from first principles.