Speaker 1: So imagine for a second that you possess a button,
just a literal, physical, heavy red button, sitting right there
on your desk. Okay, I'm picturing it, And every time
you press this button, you can compress time. And I
don't mean, you know, skipping a boring meeting or fast
forwarding through a commercial break. I mean compressing twenty years
of grueling, sweat equity laboratory research. Oh wow, Yeah, the
failed hypotheses, the broken test tubes, the funding dry spells.
Shrinking all of that down into a single week.
Speaker 2: I mean it sounds like the premise of a sci
fi novel or maybe some kind of superhero origin story,
honestly exactly.
Speaker 1: But let's actually play this out for a minute. If
you could take the trial and error of two decades,
that slow, incremental creeping of progress that usually defines how
science works, and shrink it down to seven days, what
would the world actually look like? Like? How fast would
we cure diseases or how quickly would we solve the
global energy crisis?
Speaker 2: Well, if innovation actually moved at that kind of speed,
the world wouldn't just look different, it would be entirely unrecognizable.
Within a calendar year, you'd essentially be compressing centuries of
human progress into a single decade.
Speaker 1: Welcome to thrilling Threads. I'm your host, And today we
really aren't talking about science fiction. We aren't talking about
some distant you know, maybe in fifty years promise of technology.
We are talking about right now. We are talking about
a list, a massive, verified list of fifteen revolutionary discoveries
that have already.
Speaker 2: Happened, right And that's the key distinction for today's deep dive.
Usually when people talk about this topic, quantum computing, it's
all theoretical. It's all one day or potentially, which, I'll
be honest drives me a little crazy.
Speaker 1: H The hype cycle is real, it is.
Speaker 2: But the source stack we are looking at today proves
that the era of potentially is over. These are fifteen specific,
quantified breakthroughs. We're talking everything from creating entirely new states
of matter to legitimately fixing the global battery shortage.
Speaker 1: It is a massive list too. We've got sorts from
the field referencing everything from Microsoft and Google to national laboratories,
and our mission today is pretty straightforward. We are going
to connect the dots between subatomic physics, which let's be fair,
can be a little intimidating to dive into very intimidating. Yeah,
we're connecting that to your daily life. We're talking about
the battery in your pocket, the medicine sitting in your cabinet,
and literally the security of your bank account.
Speaker 2: Because it's really about that transition from scientific curiosity to
engineering reality. We're finally moving from the chalkboard to the
factory floor.
Speaker 1: So let's start with that time compression idea I mentioned
at the top, because discovery number fifteen on our list
is literally about buying back time. It's the battery revolution. Now.
I think we all generally know the problem.
Speaker 2: Here, right, the lithium bottleneck exactly. We all want electric vehicles,
we want grid storage for our solar panels and wind turbines.
But current lithium ion batteries are incredibly resource heavy, they
can be all and mining the lithium itself is a
geopolitical and environmental nightmare. We desperately need a new recipe.
Speaker 1: Enter Microsoft as your quantum and the Pacific Northwest National
Laboratory or PNNL. They teamed up to find a new
material for a battery electrolyte, but they didn't do it
the old fashioned way.
Speaker 2: No, they didn't. Historically, material science is a lot of
well it's shaken bake. You have an idea, you mix
the chemicals, you test it, it fails, you wash the beaker,
and you try again. It's incredibly inefficient.
Speaker 1: So how did they bypass all that? How did they
cheat the system?
Speaker 2: Well, they didn't cheat, They just vastly optimized it. They
used Azure Quantum Elements, which is a platform that combines
high performance computing with artificial intelligence. They started with the
database of thirty two point six million possible inorganic materials.
Speaker 1: Thirty two point six million. Just let that number sink in.
If a human team had to screen those using traditional
density functional theory, which is correct me if I'm wrong.
Basically the math we used to simular electron behavior.
Speaker 2: Yeah, that's a good way to put it. It models
the electronic structure of many body systems.
Speaker 1: Right, So how long would that have taken humans.
Speaker 2: To do If you were doing the high fidelities simulations
for all of them, you're looking at about twenty years.
Speaker 1: And there's the twenty year's number, right.
Speaker 2: But they used AI models trained on quantum data to
filter this massive list They didn't just pick random ones, obviously,
They filtered for specific things like stability, connectivity, and cost.
They narrowed those thirty two million down to five hundred thousand,
then to eight hundred, and finally down to eighteen top candidates.
Speaker 1: And they did all this in how long roughly one week? Okay,
I have to play Devil's advocate here for a second,
because speed is great, but AI can hallucinate. We've all
seen AI write terrible poetry or makeup facts. We definitely
don't want it designing a battery that explodes in your driveway.
Do they just blindly trust the computer or is there
some kind of check in place?
Speaker 2: That is the crucial question. No, you can't just trust
the AI. Once the AI identified those top eighteen candidates,
the researchers switched back to hard physics. They used density
functional theory DFT to verify the AI's homework. DFT is
computationally expensive. It takes a ton of processing power, but
it's incredibly accurate. Because they only had to run it
on eighteen materials instead of thirty two million, they could
easily afford the computational costs.
Speaker 1: Got it, So the AI acts as the scout running
ahead and finding the path, and the physics engine acts
as the surveyor, coming in behind to make sure the
ground is actually solid.
Speaker 2: Precisely, and the result wasn't just some theoretical PDF file
P and and L scientists actually synthesized one of the
candidates in the real world. It's a solid state electrolyte
that uses roughly seventy percent less lithium than current standards.
It replaces all that lithium with sodium, which is dirt
cheap and available literally everywhere.
Speaker 1: Seventy percent less lissium, I mean that changes the economics
of an EV completely. But let's zoom out a bit.
You mentioned scouting materials. This brings us right into discovery
number ten, which is like the industrial scale version of
what Microsoft just did. We're talking about Google DeepMind and
their genomesisty.
Speaker 2: Oh yes, GENOIME graph networks for materials exploration graph networks.
Speaker 1: That honestly sounds more like social media analysis than quantum physics.
Speaker 2: It's actually a very similar concept mathematically. In a social network,
you map how people are connected to predict who knows
who or who might buy a certain product. In a
crystal structure, GENOIME maps how atoms bond and interact to
predict which structures will hold together.
Speaker 1: And the scale here is just absurd. The reports say
Genome generated two point two million crystal structure predictions. But again,
my skeptical brain has to ask, are these just pretty
computer pictures of molecules or they real things.
Speaker 2: That's exactly the skepticism we need, and it's what the
scientific community demanded. DeepMind claimed they found three hundred and
eighty thousand materials that are thermodynamically stable, and stability is
the hard part. You can force atoms together for a
split second in a simulation, but will they stay that
way sitting on a shelf?
Speaker 1: Right, I don't want to build a bridge out of
a material that disintegrates if the wind blows on it.
Speaker 2: Exactly so, to prove these predictions were valid, independent researchers
and autonomous labs have already physically synthesized seven hundred and
thirty six of these materials.
Speaker 1: Wait, back up, autonomous labs, you mean robots? Yes.
Speaker 2: The source specifically highlights a robotic laboratory at Berkeley Lab.
It's called the A Lab. There are no humans in
white coats pouring beakers there. It's all robotic arms. They
mix the powders, bake them in furnaces, and analyze the
results with X rays.
Speaker 1: That seriously sounds like science fiction. Again, the robots are
doing the actual science.
Speaker 2: They are doing the synthesis. Yeah, the A lab synthesized
forty one out of fifty eight targeted materials in just
seventeen days. That's seventy one percent success rate.
Speaker 1: Forty one brand new materials in two weeks.
Speaker 2: To put that in perspective for you, autonomous labs are
now producing more than two new materials per day. Think
about the history of humanity for a second. We had
the Bronze Age, the Iron Age, the Silicon Age. We
usually discover one major material clause every few centuries or
maybe decades if we're lucky. Now we are discovering two specific,
stable new compounds every twenty four hours.
Speaker 1: That is staggering. It completely shifts the bottleneck of human progress.
It used to be well, we can't find the right material.
Now it's we have too many materials, which one do
we even bother.
Speaker 2: To build exactly. We were entering the era of computational design.
We decide what properties we want, super hard, superconductive, heat, resistant,
and the computer tells us exactly how to build it.
Atom by Adam.
Speaker 1: Speaking, is super hard. Let's talk about discovery number eleven,
because this one challenges a rule I'm pretty sure I
learned in elementary school, the rule that diamond is the
hardest material on Earth.
Speaker 2: It was the rule, but rules are meant to be
broken by quantum supercomputers. This discovery focuses on a specific
phase of carbon called BC eight.
Speaker 1: BC eight what does that actually stand for?
Speaker 2: Body centered cubic carbon. So, in a normal diamond, and
each carbon atom is bonded to fur neighbors in this
tetrahedral shape, it's an incredibly strong structure. But BC eight
is a slightly different arrangement that allows for even tighter
atomic packing under immense pressure, and.
Speaker 1: The simulation says this stuff is harder than a.
Speaker 2: Diamond, significantly harder. Large scale simulations on the Frontier supercomputer,
which used machine learning models trained to absolute quantum accuracy,
predicted is thirty percent more resistant to compression than diamond.
Speaker 1: Thirty percent harder. That implies a good cut of diamond
the same way a diamond cuts glass.
Speaker 2: Theoretically, yes, and it's stable. The simulation suggests it remains
stable above ten million atmospheres of pressure.
Speaker 1: Ten million atmospheres. That's I can't even fathom that that's
deep planet pressure. It is.
Speaker 2: In fact, astronomers think this BCE eight super diamond might
naturally exist right now in the centers of carbon ridge exoplanets.
Speaker 1: So we basically found a material that exists on alien planets,
but we found it inside our computer. Can we actually
make it here on Earth?
Speaker 2: That is the ultimate challenge. The recipe, according to the
quantum simulation, involves taking a regular diamond melting it, which,
by the way, is incredibly difficult because diamond usually just
turns into graphite.
Speaker 1: Before it melts, right pencil lead.
Speaker 2: Yeah, So you have to melt it and then shot
compress it to twelve million atmospheres while simultaneously heating it
to five thousand kelvin.
Speaker 1: Oh with that all, So, just melt a diamond, scratch
it with the weight of an entire planet, and heat
it to the temperature of the surface of the Sun. Easy.
Speaker 2: Not easy at all. But the point is, now we
have the map, we know it's physically possible. That's the
real insight here. Quantum modeling allows us to see these
islands of stability that nature hides under extreme conditions. We
aren't blindly smashing things together hoping for the best anymore.
We have a distinct target.
Speaker 1: Okay, so we've got better batteries, infinite robotic materials, and
super diamonds. That covers the stuff we can hold in
our hands. But I want to pivot to part two
of our deep dive quantum healing, because this is where
the whole time compression thing gets deeply personal. If we
can fast forward drug discovery, we literally save lives absolutely.
Speaker 2: And to understand how this works, we have to stop
thinking of biology as just cells and organs and tissue.
At the fundamental rock bottom level, biology is just chemistry,
and chemistry is just quantum mechanics.
Speaker 1: Right, It's all just electrons dancing around nuclei when.
Speaker 2: You zoom in far enough exactly. And that brings us
to discovery number thirteen Foundations for simulating human drug metabolism.
Speaker 1: Enzymes drug metabolism. That basically just means how my body
breaks down a pill after I swallow it.
Speaker 2: Yes, when you take a drug, say a painkiller or
a new heart medication, your body has to process it,
and the heavy lifting for that process is done by
enzymes in your liver, specifically a family called cytochrome P
four fifty.
Speaker 1: Cytochrome P four fifty. Why is that specific family so crucial.
Speaker 2: Because they metabolize about seventy to eighty percent of all
drugs in clinical use today. If you want to know
if a drug is going to be toxic or if
it will actually work the way you want it to,
you have to know exactly how it interacts with cytochrome
P four fifty.
Speaker 1: And I assume simulating that interaction is notoriously hard.
Speaker 2: It's incredibly difficult. These enzymes contain a heme group with
an iron atom right at the center. The electrons in
that iron atom are what we call strongly correlated.
Speaker 1: Strongly correlated. Unpack that for us. What does that mean?
Speaker 2: It basically means the electrons interact with each other so
intensely and intimately that you can't just calculate the position
of one without knowing the position of all the other simultaneously.
Classical computers absolutely hate this. They have to use rough
approximations to get through the math, which naturally leads to errors.
Speaker 1: So we guess how the drug works, and sometimes we
guess wrong, and then the drug fails in late stage.
Speaker 2: Clinical trials exactly, and failures in late stage trials cost
pharmaceutical companies billions of dollars and waste years of time.
But in this discovery, researchers used quantum algorithms on photonic hardware,
which are computers that actually use light instead of electricity
to calculate these electronic structures. They reported speed ups of
two high hundred and thirty four times and two hundred
and seventy eight times compared to classical.
Speaker 1: Methods, nearly three hundred times faster. That's massive, and.
Speaker 2: That's just for the specific calculation piece. Separate quantum informed
AI tools simulated systems with up to a million atoms
over nanosecond time scales. Some of those tasks ran a
thousand times.
Speaker 1: Faster, a thousand times faster. This means we can actually
watch the movie of the drug interacting with the enzyme
in real time rather than looking at a blurry polaroid
photo from a classical computer.
Speaker 2: That is a perfect analogy. And speaking of watching the movie,
let's talk about discovery number twelve, because this one targets
something that has been an absolute villain in oncology for decades.
The Kris protein KRS.
Speaker 1: I've heard this described in the medical community as undruggable.
Why is that? Is it just bulletproof?
Speaker 2: Not bulletproof, No, it's just smooth. It's a protein that
when it mutates, signals cells to divide uncontrollably. It drives
a huge percentage of lung, colon and pancreatic cancers. But
structurally it's essentially a smooth sphere. Traditional drugs work by
sticking to a pocket on a protein, sort of like
a key fitting into a lock. KRIS didn't seem to
have a lock.
Speaker 1: So how did the quantum approach manage to find a
lock on a completely smooth sphere.
Speaker 2: They used a hybrid quantum classical pipeline. They started with
this massive funnel generating over one million candidate molecules that
theoretically might stick to KRIS a million candidates, and through
high speed quantum filtering simulating the atomic interactions, they narrowed
that million down to just fifteen.
Speaker 1: From a million down to fifteen.
Speaker 2: And critically, some of those fifteen were then experimentally validated
in the lab to bind to KRIS. They actually found
the pocket. They found a way to stick a wedge
into the gears of the cancer cell.
Speaker 1: That is profound. It really moves medicine from discovery, where
we basically wander around the jungle looking for a healing plan. Yeah,
to pure engineering. We are custom building the key to
fit the exact low we need.
Speaker 2: It shrinks the search space. That's the recurring theme you'll
see across all these discoveries, whether it's batteries or cancer drugs.
Quantum computing allows us to ignore the billion wrong answers instantly,
so we can focus all our energy on the ten
right ones.
Speaker 1: Okay, let's scale up again. We went from the microscopic
cancer cells. Now let's go to the power of the
sun itself. Part three of our deep dive is about
solving the simulation crisis in physics. Infusion fusion energy.
Speaker 2: It's the holy grail, right, clean infinite energy, effectively bottling
a star here on Earth, and.
Speaker 1: We've been hearing fusion is thirty years away for the
last fifty years. It's the running joke of the physics community.
Speaker 2: At this point, the joke is getting a bit stale. Thankfully.
Discovery number fourteen suggests that the timeline is drastically compressing
the problem with fusion isn't just building the massive superconducting
magnets to hold it. It's predicting what the plasma will
actually do once you turn it on.
Speaker 1: Plasma being the super high gas inside the reactor.
Speaker 2: Right, Yes, it is millions of degrees, incredibly turbulent and
wildly chaotic. Simulating it is a nightmare. Classical three D
inertial confinement fusion models can take millions of CPU hours
to process. A single run can take thirty days to complete.
Speaker 1: Thirty days, so if I have an idea for a
slightly better reactor design, I tweak the code, I hit enter,
and I literally have to wait a month to see
if my reactor just blew up.
Speaker 2: Pretty much, imagine trying to learn how to play the piano,
but every time you hit a key you don't hear
the note until a month later. You'd never learn. Innovation
completely stalls.
Speaker 1: So what's the fix? How did quantum change this?
Speaker 2: Researchers developed a quantum partial differential equation algorithm. Now I
know that's a mouthful.
Speaker 1: Yeah, quantum partial differential equation there definitely sounds like a
class I would fail on the first day of college.
Speaker 2: Basically, differential equations are just the math we use to
describe how things change over time, fluid flow, heat transfer,
plasma turbulence. The new algorithm provides what they call a
quadratic speed up.
Speaker 1: Translate quadratic speed up for me. In practical terms, it.
Speaker 2: Means that as the problem gets harder and the system
gets bigger, the quantum computer gets exponentially more efficient at
solving it compared to a classical computer. It scales beautifully.
National lab collaborations have shown that key plasma interactions can
now be modeled efficiently. We aren't just guessing in the
dark anymore, so.
Speaker 1: We can fail faster. We can run one hundred fusion
simulations in the time it used to take to run
just one.
Speaker 2: Exactly, and simulation speed directly determines research speed.
Speaker 1: This connects directly to discovery number five, doesn't it? Simulating
magnetic materials. This brings up a name that everyone in
physics essentially worships, Richard Feynman.
Speaker 2: Oh the legend. Feinemann famously said in the early eighties,
and I love this quote. Nature isn't classical, damn it.
And if you want to make a simulation of nature,
you'd better make it quantum mechanical.
Speaker 1: He's basically saying, stop trying to use an abacus to
model a galaxy. Use the tools that match the reality, right.
Speaker 2: And discovery number five is the definitive proof that he
was right all along. Quantinuum, which is a major player
in this space, digitally simulated a fifty two quibit system.
They created a seven x eight lattice to study something
called pre thermalization in a two D spin system.
Speaker 1: Okay, pre thermalization. My eyes are starting to glaze over
just a bit. Why does this matter to the average person?
Speaker 2: Stick with me, I promise it matters. Pre Thermalization is
a weird state where a quantum system doesn't settle down
into equilibrium immediately, it holds a specific pattern for a while.
Quantinuum extracted a very specific number from this simulation, a
diffusion constant of zero point three to.
Speaker 1: Eight zero point three eight.
Speaker 2: The number itself isn't the headline here. The headline is
that they got this highly specific number directly from the
quantum data, and it matched theoretical predictions perfectly. This wasn't
some abstract math problem. This was a controlled simulation of
magnetic dynamics that classical supercomputers physically cannot scale. To handle.
Speaker 1: So it's the ultimate proof of concept. The tool actually
works the way Finemen dreamed it would.
Speaker 2: It proves we can simulate complex magnetic materials with perfect fidelity,
and that impacts everything from how we build hard drives
to the magnet spinning inside electric motors.
Speaker 1: But here's the elephant in the room. With all of this,
all these amazing simulations, the batteries, the cancer drugs, the
fusion reactors, they all rely on the computer being right.
And for a long long time, quantum computers were well flaky.
They were noisy, They made a ton of.
Speaker 2: Mistakes, they were incredibly fragile. A stray photon, a microscopic
change in room temperature, literally a vibration from a delivery
truck driving by outside the lab, poof the calculation is ruined.
Speaker 1: This brings us to part four, the backbone of the future,
security and reliability. Discovery number nine is all about error correction.
I've heard this called the gatekeeper, because if we can't
fix the errors, these machines are just very expensive, very
cold paper weights.
Speaker 2: That's the brutal truth of the industry. But Discovery number
nine is a massive leap forward. It involves the critical
difference between physical quibets and logical quibits.
Speaker 1: Explain that distinction for us. What is the difference.
Speaker 2: Think of a physical quibit like a noisy, easily distracted toddler.
It tries to hold on to the information you give it,
but it gets distracted or bumps into something and drops it.
A logical quibbit is like a team of toddlers, but
they are closely monitored by a teacher. If one toddler
drops the ball, the others catch it. The group holds
the information securely, even if the individual parts are unreliable.
Speaker 1: Safety in numbers basically redundancy exactly.
Speaker 2: Quantinuum used thirty physical quibits to create four completely stable
logical quibits, and the result of that experiment was stunning.
The error rate was about eight hundred times lower than
the physical quibits.
Speaker 1: Alone, eight hundred times better. That's a staggering improvement.
Speaker 2: It went from roughly one error in every hundred operations
to just one error in one hundred thousand. They successfully
ran fourteen thousand individual experiments without a single uncorrected.
Speaker 1: That feels like the turning point. That feels like the
moment we cross the line from a finicky prototype to
an actual deployable product.
Speaker 2: It absolutely is, And interestingly enough, what they found was
that simpler logical encodings actually outperformed the incredibly complex theoretical
ones people had been working on for years. We are
finally learning how to build these machines by actually getting
our hands dirty and building them, not just theorizing on whiteboards.
Speaker 1: Now, let's talk about the flip side of that security,
because it's a double edged sword. If these computers are
so unbelievably powerful, can't they just crack all our codes,
bank passwords, government secrets, all of it?
Speaker 2: Eventually? Yes, Shor's algorithm proved that theoretically a long time ago.
That's exactly why we need quantum encryption right now, which
leads to discovery number eight true quantum randomness.
Speaker 1: Randomness sounds a bit boring at first glance. Pick a
number between one and ten. Who cares?
Speaker 2: Your bank cares deeply. Every single time you send a
credit card number over the internet or log into your email,
it is ENCRYPTID using a key generated by random numbers.
But here's the secret. Classical computers aren't truly random. They're
what we call pseudorandom. They use an algorithm, So if
a hacker knows the algorithm and the starting seed number,
they can predict the next number.
Speaker 1: So it's like a really really complex pattern, but at
the end of the day, it's still a pattern that
can be unraveled correct.
Speaker 2: Quantum randomness is entirely different. It relies on intrinsic quantum noise,
the fundamental mathematical uncertainty of the universe itself. It is
physically fundamentally impossible to predict.
Speaker 1: So what's the breakthrough here? Haven't we known about quantum
noise for a while now?
Speaker 2: The breakthrough is the speed. They built a photonic chip
that produced more than twenty gigabits per second of completely
secure random numbers.
Speaker 1: Twenty gigabits per second, just spitting out pure chaos exactly.
Speaker 2: The previous best was around two point nine gigabits, so
this is a massive leap. It means we can generate
unbreakable encryption keys at the speed of the global Internet backbone.
Speaker 1: So we are basically building an unbreakable shield before someone
else can build the quantum sword that can break our
current encryption.
Speaker 2: Hopefully. Yes, it's an arms race, but this is a
huge defensive victory let's.
Speaker 1: Talk about discovery number seven. This is the verified quantum advantage.
This is the moment the student finally surpassed the master.
Speaker 2: This is Google's quantum echoes experiment. They measured something called
out of time order correlators or otocs.
Speaker 1: Out of time order correlators. Okay, that sounds like a
piece of equipment from doctor? Who break that down for me?
Speaker 2: Think of the butterfly effect. A butterfly flaps its wings
in Brazil and a week later there's a tornado in Texas.
Chaos in a classical system, if you scramble information is
just gone. It's like scrambling an egg. You can't unscramble it, right,
an egg is an egg. But in quantum mechanics, information
is never truly lost. Otocs are a mathematical way of
measuring how information spreads or scrambles through a system and
effectively checking if you can reverse the butterfly effect to
see exactly where the initial flap happened.
Speaker 1: That is just mind bending. But why was this specific
experiment considered an advantage?
Speaker 2: Because calculating this scrambling is computationally devastating for a classical computer.
Google ran this on one hundred and five quibits to
measure a specific property of this scrambling the Frontier supercomputer,
which remember is one of the fastest classical machines on Earth,
would have taken three point two years per data point.
Speaker 1: Three point two years for one single dot on a graph.
Speaker 2: Yes, and on the quantum hardware it took about two.
Speaker 1: Hours three point two years versus two hours. That's a
speed up of roughly thirteen thousand times.
Speaker 2: And this wasn't just a toy benchmark designed to make
the quantum computer look good. It involved measuring real magnetization properties.
It is definitive, undeniable proof that quantum has overtaken classical
computing in specific meaningful physics problems.
Speaker 1: We've crossed the rubicon. There's really no going back now,
and now that we actually have these working machines seeing
things we never even expect it, which leads us perfectly
into Part five, The Weird Physics New phases and States
of matter.
Speaker 2: This is where things genuinely get trippy.
Speaker 1: Discovery number six dynamical phase transitions. Now, I think I
know what a normal phase transition is. Ice melts into water,
water boils into steam.
Speaker 2: Right, those are thermal phase transitions driven by temperature, but
inside a quantum processor, researchers observed noise driven phase transitions.
Speaker 1: Noise driven. How does noise change the state of matter?
Speaker 2: Well, imagine a room full of people trying to have
a perfectly synchronized conversation. That's entanglement. Now imagine the background
noise in the room gets a little louder and a
little louder. At a certain point, the conversation doesn't just
get difficult, it breaks down completely all at once. The
system snaps from one state highly entangled, to another state
completely disordered.
Speaker 1: So the computer itself, the information inside it goes through
a phase change like freezing or boiling, but based purely
on interference and noise.
Speaker 2: Exactly we are learning the weather patterns of quantum information.
It completely reframes how we understand stability in these complex systems.
Speaker 1: That is wild. And speaking of wild discovery, number four
forbidden material states. I'd to say forbidden sounds very ominous,
like we opened a door we shouldn't have.
Speaker 2: In physics, forbidden usually just means we were absolutely certain
this was impossible until yesterday.
Speaker 1: Fair enough? What did they find?
Speaker 2: They were looking at a material called rhombus stacked five
layer graphene.
Speaker 1: Graphene, that' said, super material, just a single flat layer
of carbon atoms, right, yes.
Speaker 2: But if you take five of them and stack them
in a very specific rhombus pattern, things get incredibly weird.
They observed what are called fractional quantum anomalous Hall states.
Speaker 1: Okay, I'm going to need you to translate that into English.
Speaker 2: Two impossible things happened. First, electrons float along the edges
of the device with absolute zero resistance.
Speaker 1: Zero like perfect perpetual flow, no heat loss.
Speaker 2: Perfect flow. Usually you need a massive, super cooled external
magnetic field to force electrons to do that, but here,
no magnetic field whatsoever.
Speaker 1: Look, ma, no magnets exactly.
Speaker 2: And the second thing was even weirder. The conductance values
they measured were fractions of an electron charge five ninths
and five elevenths.
Speaker 1: Wait, fractions of a charge. I thought an electron was
an electron. It's a fundamental particle, one unit. You can't
just slice an electron in a half with a tiny knight.
Speaker 2: You can't cut it now. But in these incredibly complex
quantum states, the electrons dance together in such a highly
coordinated way that the collective behaves as if it split.
They form what we call quasi particles that actually carry
a fractional charge. It challenges everything we fundamentally know about
how matter organizes itself.
Speaker 1: It's like discovering a new primary color. You thought you
had the whole box of crayons, and suddenly there's a
new one.
Speaker 2: That's a great way to look at it. And Discovery
number three adds to this new visual palette high res
mapping of quantumizing magnetism.
Speaker 1: This honestly sounds like a photography project.
Speaker 2: It kind of is. At the atomic level. They used
a two hundred and fifty six atom programmable quantum simulator
and they used it to track how magnetic domains for
how they evolve and how they collapse in real time.
Speaker 1: So instead of guessing how magnets work down at the
atomic level, we're looking at a static before and after photo.
We're actually watching the movie play out.
Speaker 2: Frame by frame. We are seeing non equilibrium quantum magnetism
at scales that classical computers simply cannot resolve. We're looking
directly through the experimental.
Speaker 1: Window, which brings us to Discovery number two. New topological phases.
Speaker 2: This one used programmable atom arrays, specifically Rideberg atom systems.
They demonstrated exotic phases with names like stripe and plaquette orders.
Speaker 1: Stripe and plaquette sounds like we're discussing interior design trends
for a living room.
Speaker 2: They are designs, but they're designs of nature. These are
topologically ordered phases. They break traditional symmetry descriptions. It's about
discovering entirely new organizational principles of matter.
Speaker 1: So we aren't just taking old materials and tweaking them
slightly to make them better. We are finding the hidden
underlying rules of the universe.
Speaker 2: Which brings us perfectly to the grand finale discovery number one,
the fifty year mystery that was finally solved.
Speaker 1: This is the big one, the quantum spin liquid.
Speaker 2: This story actually starts all the way back in the
nineteen seventies. A physicist named Philip Anderson, an absolute giant
in the field, predicted a profoundly weird state of matter.
He called it a quantum spin liquid.
Speaker 1: Liquid like water. Again, are we melting something.
Speaker 2: Not quite in a normal magnetic material? All the spins.
Think of them as tiny little compass needles on the
atom's line up as it gets cold north south, north south,
they get perfectly ordered, like soldiers standing in a row.
Speaker 1: Okay, I could picture that they freeze in place.
Speaker 2: But in a spin liquid, the magnetic moments remain entirely disoldered.
They are constantly fluctuating, shifting around. Even if you take
them all the way down to absolute zones zero. They
are in physics terms, frustrated.
Speaker 1: Frustrated that's the actual technical term.
Speaker 2: That is the technical term geometric frustration. Imagine a triangle
of three atoms. If the first two want to point
in opposite directions because of their magnetic forces, the third
one doesn't know which way to point. It wants to
oppose both, but it can't. It's frustrated. So in a
spin liquid, this macroscopic frustration prevents the atoms from ever
freezing into a solid pattern. They remain liquid like because
of intense long range quantum entanglement.
Speaker 1: So they are intimately linked to each other but remaining
totally chaotic.
Speaker 2: Yes, and for fifty years this was just a theory,
a really elegant math problem on a chalkboard. But recently
researchers reported in the journal Science that they used a
two hundred and nineteen atom cogome array, which is a
very specific star like lattice shape to directly measure this
topological order.
Speaker 1: They actually found it.
Speaker 2: They didn't just find it, they created it. They confirmed
the phase definitively exists. This is a fundamentally new state
of matter.
Speaker 1: So why is this number one? I mean, why does
finding a new weird magnet state beat curing cancer or
solving the battery cressis.
Speaker 2: Because it proves that we can engineer matter into states
that previously only existed on paper. It confirms that our
theoretical understanding of quantum mechanics isn't just a nice model
we use to do math. It's the literal instruction manual
for reality. And practically speaking, quantum spin liquids might be
the ultimate key to building topological quippets, which is the
absolute holy grail of totally error free quantum computing.
Speaker 1: It's the ultimate validation of everything we've been doing. It is,
so let's take a collective breath here, because that was
a lot. We've gone from batteries that use seventy percent
les lithium, to autonomous robots making materials, to plaquette orders
and spin liquids.
Speaker 2: It really is a journey from the immediately practical to
the deeply profound.
Speaker 1: And that's exactly what I love about this source deck.
It's not just hey, here's a slightly faster can copewter
chip for your phone. It's here's a potential cure for cancer.
Here's a massive step toward fusion energy. And here's the
completely new way electrons behave that we didn't think was possible.
Speaker 2: We are standing right on a precipice. Biology, physics, computer science.
They are all merging into one unified discipline. The computational
tools of one are suddenly solving the fifty year mysteries
of the other.
Speaker 1: So if we distill all of this down, what does
this actually mean for you the listener right now today?
Speaker 2: It means the fundamental bottlenecks of human progress are breaking.
The bottleneck for the last century used to be discovery.
We don't know what material to use, we don't know
how the molecule folds. But now with systems like Genome
and Azure quantum elements, the discovery part is becoming almost instantaneous,
compressing twenty years into a week.
Speaker 1: So the bottleneck is shifting entirely to implementation.
Speaker 2: Exactly can we physically build the factories fast enough? Can
we run the FDA clinical trials fast enough? Can we
mine the sodium and integrate the new batteries into cars?
The signus is suddenly moving exponentially faster than our physical
infrastructure can handle.
Speaker 1: That is the thrilling and honestly slightly terrifying thought.
Speaker 2: It is a bit daunting, but mostly it's thrilling. Faster cures, cleaner,
limitless energy, unbreakable digital security. These aren't sci fi dreams anymore.
They are literally engineering tickets sitting in a queue waiting
to be built.
Speaker 1: I want to leave you with a provocative thought to
mull over. If we can truly simulate twenty years of
grueling research in a single week, what happens to the
very concept of human progress. We are so used to
progress being a slow generational thing. My kids will have
better tech than me, But now progress might be weekly.
Are we as a society actually ready for a world
where a limit isn't what we can discover, but how
fast our brains can adapt to handling the truth?
Speaker 2: That is the defining question of the century.
Speaker 1: We really want to hear from you on this. Which
of these fifteen discoveries do you think will impact your
daily life. First, is it going to be the battery
in your pocket, the targeted cancer medicine in your cabinet,
or maybe the quantum encryption protecting your life savings.
Speaker 2: I'm personally betting on the materials. The batteries will hit
the market first.
Speaker 1: I'm holding out hope for the medicine. We'd love to
know what you think. Leave a comment down below and
let us know your stance. And thank you so much
for unraveling these thrilling threads with us today.
Speaker 2: Until next time, keep questioning everything see on the
Speaker 1: Next deep dive.