Latest / The Quark Side - Quantum Physics Podcast / Why Quantum Computers Keep Forgetting—and How Scientists Fixed It

Transcript

Why Quantum Computers Keep Forgetting—and How Scientists Fixed It · The Quark Side - Quantum Physics Podcast

• 0:01
  Speaker 1: Welcome to the quarre Side. Quantum Physics podcast, an exploration
• 0:05
  Speaker 1: of the fundamental structure of reality where quantum laws govern matter, energy,
• 0:11
  Speaker 1: and information. Here, uncertainty is a feature, not a flaw,
• 0:16
  Speaker 1: and understanding begins of the smallest scales.
• 0:28
  Speaker 2: Imagine you're holding like the single most powerful piece of technology.
• 0:32
  Speaker 3: In human history, always a fun thought experiment, right, Like.
• 0:35
  Speaker 2: A machine that's capable of simulating the molecular structure of
• 0:40
  Speaker 2: complex life saving drugs, or cracking cryptographic codes that would
• 0:46
  Speaker 2: take classical computer's millennia to break.
• 0:49
  Speaker 3: Basically modeling the very fabric of the universe exactly.
• 0:52
  Speaker 2: So you power it up, you input the variables, you
• 0:54
  Speaker 2: get ready to change the world, and then you discover
• 0:57
  Speaker 2: your multimillion dollar machine has the memory of a old fish.
• 1:00
  Speaker 3: Yeah, that is a That's the great paradox of modern
• 1:03
  Speaker 3: physics right there. I mean, we spend billions developing machines
• 1:08
  Speaker 3: with almost unimaginable computational promise, but their current hardware instability
• 1:13
  Speaker 3: is just it's the absolute bottleneck.
• 1:14
  Speaker 2: Because they literally forget what they're doing.
• 1:16
  Speaker 3: Right If the processor literally forgets the math problem halfway
• 1:19
  Speaker 3: through solving it, the theoretical power just doesn't matter.
• 1:23
  Speaker 2: So today we're going to explore this Achilles heel of
• 1:26
  Speaker 2: quantum computers. We're getting into the unpredictable fluctuation of quantum memory, and.
• 1:30
  Speaker 3: More importantly, unpacking a massive new breakthrough that has accelerated
• 1:38
  Speaker 3: our ability to measure this information loss by more than
• 1:41
  Speaker 3: one hundred times.
• 1:43
  Speaker 2: Which is just a staggering leap. I mean, the conversation
• 1:45
  Speaker 2: around quantum computing usually gets bogged down in theory.
• 1:48
  Speaker 3: Right, oh, constantly right, But the reality of engineering these
• 1:52
  Speaker 3: devices requires confronting some incredibly harsh microscopic physics. To build
• 1:58
  Speaker 3: a reliable machine, you have to measure its unreliability first.
• 2:02
  Speaker 3: Makes sense, and for a long time our measurement tools
• 2:04
  Speaker 3: were just well, they were simply too slow to see
• 2:06
  Speaker 3: the actual problems.
• 2:07
  Speaker 2: So let's get right into the hardware of that unreliability.
• 2:10
  Speaker 2: For the audience listening, we all know what equib it is,
• 2:12
  Speaker 2: and we know they operate in delicate stakes of superposition.
• 2:15
  Speaker 2: But let's look at the physical architecture.
• 2:17
  Speaker 3: Yeah, specifically, we're talking about superconducting quibits.
• 2:19
  Speaker 2: Here, right. These are microscopic electrical circuits, usually made of
• 2:23
  Speaker 2: metals like aluminium or niobium, printed on a silicon or
• 2:27
  Speaker 2: sapphire chip, and they are cooled down to fractions of
• 2:30
  Speaker 2: a degree above absolute zero, Yes.
• 2:33
  Speaker 3: Around fifteen millik Elvin's to be exact, which is colder
• 2:36
  Speaker 3: than the vacuum of deep space. That's crazy, it is, Yeah,
• 2:39
  Speaker 3: And we do that so the electrons can pair up
• 2:41
  Speaker 3: into what are called Cooper pairs. They flow without any
• 2:44
  Speaker 3: electrical resistance.
• 2:45
  Speaker 2: And that frictionless flow is what allows the quantum state
• 2:49
  Speaker 2: to survive exactly. But clearly it doesn't survive for very long.
• 2:52
  Speaker 2: There's this constant thread of relaxation or decoherence.
• 2:57
  Speaker 3: Right, decoherence to the enemy.
• 2:59
  Speaker 2: Let me flow an analogy here. If maintaining a classical
• 3:03
  Speaker 2: bit is like laying a heavy coin flat on the table, Okay,
• 3:06
  Speaker 2: like it takes a lot of force to flip it over,
• 3:09
  Speaker 2: But a quibit in superposition is more like a spinning coin.
• 3:13
  Speaker 3: I like that.
• 3:14
  Speaker 2: Yeah, it holds both heads and tails dynamically, but eventually
• 3:18
  Speaker 2: microscopic friction from the air or the table, you know,
• 3:21
  Speaker 2: it SAPs its momentum and it clatters flat. It completely
• 3:25
  Speaker 2: loses its quantum state.
• 3:26
  Speaker 3: That captures the physics beautifully actually, and that friction causing
• 3:31
  Speaker 3: the coin to clatter flat is what we call environmental noise.
• 3:34
  Speaker 2: Even in a freezer that's colder than space.
• 3:37
  Speaker 3: Even there inside a dilution refrigerator at fifteen milik Ellen's
• 3:41
  Speaker 3: the environment is not perfectly silent. You've got stray photons
• 3:44
  Speaker 3: wandering through the chamber, you have cosmic rays striking the
• 3:47
  Speaker 3: outer casing. But mostly you have microscopic defects within the
• 3:52
  Speaker 3: silicon or sapphire substrate itself. Wait really, yeah, tiny atomic
• 3:56
  Speaker 3: imperfections called two level system defects.
• 4:00
  Speaker 2: So the noise isn't just coming from the outside. The
• 4:02
  Speaker 2: ship itself is inherently flawed at the atomic level.
• 4:05
  Speaker 3: That is the insidious part of the problem. As the
• 4:07
  Speaker 3: temperature shift slightly or electric fields fluctuate, these atomic defects
• 4:14
  Speaker 3: within the chip actually absorb energy from the quibit. Oh wow,
• 4:17
  Speaker 3: they act like microscopic sponges. They just suck the quantum
• 4:20
  Speaker 3: information right out of the circuit. That's brutal, it really is.
• 4:23
  Speaker 3: When that happens, the quibit drops out of its excited
• 4:26
  Speaker 3: state back to its ground state. The information is gone,
• 4:29
  Speaker 3: and in physics we measure the life stan of that
• 4:32
  Speaker 3: memory using a metric called T one. The relaxation time,
• 4:35
  Speaker 3: right the relaxation time.
• 4:36
  Speaker 2: And according to Jiro and Danen, who's a professor at
• 4:40
  Speaker 2: NTNU involved in this research, the problem isn't just that
• 4:44
  Speaker 2: T one is short. It's that T one is wildly unpredictable.
• 4:49
  Speaker 3: And that is the core engineering nightmare right there. I mean,
• 4:52
  Speaker 3: if the relaxation time was uniformly short, say every quibit
• 4:57
  Speaker 3: perfectly held its memory for exactly fifty micros, you could
• 5:00
  Speaker 3: just work around it exactly. You could meticulously schedule your
• 5:04
  Speaker 3: calculations to execute and finish in forty nine microseconds.
• 5:08
  Speaker 2: But it's not a static timer, not at all. Like
• 5:10
  Speaker 2: the life span of the memory fluctuates randomly over time.
• 5:13
  Speaker 2: One minute, the quibbit might hold information for one hundred microseconds,
• 5:17
  Speaker 2: and the next minute it forgets everything after like ten microseconds.
• 5:20
  Speaker 3: Because those microscopic atomic defects in the chip, they're constantly shifting,
• 5:24
  Speaker 3: they're coupling and decoupling with equibit. It's just a highly
• 5:27
  Speaker 3: dynamic environment.
• 5:28
  Speaker 2: It sounds chaotic, it is.
• 5:30
  Speaker 3: You're basically trying to build a perplectly synchronized orchestra out
• 5:32
  Speaker 3: of instruments that randomly change their tuning every few seconds.
• 5:36
  Speaker 2: Okay, So if I'm an engineer trying to fix this,
• 5:38
  Speaker 2: my very first instinct is, well, I need to observe
• 5:40
  Speaker 2: the machine while it's running. I need to find out
• 5:43
  Speaker 2: exactly when and why the tuning changes and fix that
• 5:46
  Speaker 2: specific defect naturally. But this brings us to the massive
• 5:51
  Speaker 2: roadblock that this new research published in Physical Review X
• 5:54
  Speaker 2: finally solved, because historically scientists were essentially flying blind.
• 5:59
  Speaker 3: They were because you know, measuring a quantum system is
• 6:03
  Speaker 3: fundamentally different from measuring a classical system. It used to
• 6:06
  Speaker 3: take researchers roughly a full second to measure that T
• 6:10
  Speaker 3: one relaxation time.
• 6:11
  Speaker 2: Now, let me push back on that a bit, because
• 6:13
  Speaker 2: I think a lot of people might hear one second
• 6:15
  Speaker 2: and think, well, a second is incredibly fast. Like if
• 6:18
  Speaker 2: my laptop diagnosed a hardware error in one second, I'd
• 6:21
  Speaker 2: be thrilled. Why is a one second measurement lag such
• 6:25
  Speaker 2: a catastrophic bottleneck When we're measuring quantum computers, you really have.
• 6:28
  Speaker 3: To scale your perception of time down to the microscopic
• 6:31
  Speaker 3: round here. A single second in a quantum processor isn't
• 6:35
  Speaker 3: a quick diagnostic check. It is an absolute eternity, and
• 6:39
  Speaker 3: eternity Yeah, the environment around that superconducting circuit is shifting,
• 6:43
  Speaker 3: it's vibrating, and it's changing state millions of times per second.
• 6:47
  Speaker 2: So a one second measurement means you are just entirely
• 6:51
  Speaker 2: missing millions of microscopic events.
• 6:53
  Speaker 3: Yes, you're just completely missing them. But to understand why
• 6:56
  Speaker 3: it took a full second, we have to look at
• 6:58
  Speaker 3: the mechanics of quantum op Okay, you can't just point
• 7:02
  Speaker 3: a continuous sensor at equibit and watch its energy fade
• 7:06
  Speaker 3: over time. It's not like watching a battery icon drain
• 7:10
  Speaker 3: on your phone.
• 7:11
  Speaker 2: Right because of the observer effect. Exactly, if you look
• 7:13
  Speaker 2: at the spinning coin, you force it to clatter flat immediately.
• 7:17
  Speaker 2: You force it to choose a definitive state of zero
• 7:19
  Speaker 2: or one, which destroys that delicate superposition you were trying
• 7:23
  Speaker 2: to measure in the first place.
• 7:24
  Speaker 3: Spot On the act of measuring the quibbot destroys the memory.
• 7:28
  Speaker 3: So how do you find out how long the memory
• 7:31
  Speaker 3: lasts if looking at it actually kills it.
• 7:34
  Speaker 2: That sounds impossible.
• 7:35
  Speaker 3: It's tricky. You have to use a statistical approach called
• 7:37
  Speaker 3: inversion recovery.
• 7:38
  Speaker 2: Okay, walk me through that. How does inversion recovery actually work.
• 7:42
  Speaker 3: So you send a microwave pulse to excite the quibbit.
• 7:46
  Speaker 3: Basically you spin the.
• 7:47
  Speaker 2: Coin okay, coin of spinning.
• 7:49
  Speaker 3: Then you purposefully wait for a specific duration, let's say
• 7:53
  Speaker 3: ten microseconds. Right after exactly ten microseconds, you hit it
• 7:57
  Speaker 3: with a measurement pulse to see if it is still
• 8:00
  Speaker 3: spinning or if it fell flat.
• 8:02
  Speaker 2: But that only tells you the result for that single trial.
• 8:05
  Speaker 2: It doesn't give you the average lifespan.
• 8:07
  Speaker 3: Correct. So you have to reset the quibit and do
• 8:09
  Speaker 3: that exact same ten microsecond waight time thousands of times
• 8:13
  Speaker 3: just to build a reliable probability thousands of times thousands
• 8:16
  Speaker 3: And then you have to increase the weight time to
• 8:19
  Speaker 3: say fifteen microseconds, and run another thousand trials. Oh my god,
• 8:23
  Speaker 3: then twenty microseconds, another thousand trials. You painstakingly sweep through
• 8:28
  Speaker 3: all these different weight times, plotting the probabilities until you
• 8:31
  Speaker 3: build this beautiful, smooth, exponential decay curve, and.
• 8:35
  Speaker 2: The slope of that curve tells you the t one
• 8:37
  Speaker 2: relaxation time. Wow, Okay, I see the problem.
• 8:40
  Speaker 3: Now.
• 8:40
  Speaker 2: It's not that a single measurement takes a second. It's
• 8:43
  Speaker 2: that you have to run tens of thousands of individual
• 8:47
  Speaker 2: excite weight measure reset cycles just to plot a single curve.
• 8:51
  Speaker 2: And that entire ensemble process is what takes a full second.
• 8:54
  Speaker 3: And here is where the physics really bite you. During
• 8:57
  Speaker 3: that one second you spent gathering all those thousands of
• 9:00
  Speaker 3: data points, the atomic defects in the chip were actively shifting.
• 9:04
  Speaker 2: The environment was fluctuating, right, which means the curve you
• 9:07
  Speaker 2: just claweded is basically a.
• 9:09
  Speaker 3: Lie, or at least a massive blur.
• 9:12
  Speaker 1: Yeah.
• 9:12
  Speaker 2: It's like trying to take a photograph of a chaotic
• 9:14
  Speaker 2: mosh pit, but you leave the camera shutter open for
• 9:16
  Speaker 2: a full minute.
• 9:17
  Speaker 3: Oh, that's a great way to put it.
• 9:18
  Speaker 2: You wouldn't see any of the individual collisions or the
• 9:21
  Speaker 2: dynamic movement. You just get the smeared, useless blob of
• 9:25
  Speaker 2: average motion.
• 9:26
  Speaker 3: That is a phenomenal conceptualization. Over that one second integration time,
• 9:31
  Speaker 3: the quibot's actual relaxation rate might have spiked and plummeted
• 9:35
  Speaker 3: one hundred times. Wow, But your one second ensemble measurement
• 9:39
  Speaker 3: just spits out a single smeared average. You know the
• 9:43
  Speaker 3: memory fluctuates, but you have no idea what specific microscopic
• 9:47
  Speaker 3: event triggered the loss in that exact fraction of a millisecond, And.
• 9:51
  Speaker 2: If you can't see the details of the noise, you
• 9:53
  Speaker 2: obviously can't engineer a defense against it. You just can't,
• 9:56
  Speaker 2: which brings us to the breakthrough the t at the
• 10:00
  Speaker 2: niels Bore Institute in Copenhagen, led by Fabrizio Barita, alongside
• 10:05
  Speaker 2: Jero and Dan and the NTNU researchers, they basically decided
• 10:09
  Speaker 2: that staring at a smeared mosh pit wasn't going to
• 10:12
  Speaker 2: scale quantum computing.
• 10:13
  Speaker 3: No, it certainly wasn't.
• 10:14
  Speaker 2: They needed a high speed camera and they achieved something
• 10:17
  Speaker 2: called real time adaptive tracking. They took that agonizing one
• 10:21
  Speaker 2: second measurement window and slashed it down to roughly ten milliseconds.
• 10:25
  Speaker 3: Which is a speed increase of more than one hundred times.
• 10:27
  Speaker 2: That's insane. So how do you actually do that If
• 10:30
  Speaker 2: the rules of quantum mechanics dictate that looking at the
• 10:33
  Speaker 2: quivot destroys the state and you're forced to run thousands
• 10:37
  Speaker 2: of trials to build that decay curve, how do you
• 10:40
  Speaker 2: suddenly do it one hundred times faster? Do they just
• 10:44
  Speaker 2: like buy a faster microwave pulse generator to cycle, the
• 10:47
  Speaker 2: resets quicker.
• 10:48
  Speaker 3: No. No, the hardware pulsing speed is already pretty much
• 10:51
  Speaker 3: near its physical limit. The breakthrough wasn't about pulsing faster,
• 10:56
  Speaker 3: It was about measuring smarter. Okay. They completely threw out
• 11:00
  Speaker 3: the traditional brute force method of sweeping through all the
• 11:03
  Speaker 3: wait times from scratch every single time. Instead, they integrated
• 11:08
  Speaker 3: an active machine learning inspired feedback loop.
• 11:11
  Speaker 2: Okay, break that down for me. What does the algorithm
• 11:13
  Speaker 2: actually do differently?
• 11:14
  Speaker 3: Think about the traditional method. You're blindly testing weight times
• 11:17
  Speaker 3: of one microsecond, two microseconds, three microseconds, all the way
• 11:20
  Speaker 3: up right. But if you already know from the last
• 11:23
  Speaker 3: measurement that the Quivitt generally survives for fifty microseconds, testing
• 11:27
  Speaker 3: a one microsecond wait time is a complete waste of
• 11:30
  Speaker 3: physical time.
• 11:30
  Speaker 2: Because you already know it's going to survive that long.
• 11:32
  Speaker 3: You already know the probability is going to be near
• 11:33
  Speaker 3: one hundred percent.
• 11:35
  Speaker 2: Ah, So the algorithm stopped searching the entire haystack. It
• 11:39
  Speaker 2: remembers where the needle was a millisecond ago, and only
• 11:42
  Speaker 2: searches in that immediate vicinity.
• 11:43
  Speaker 3: Precisely, they optimize the tracking by using what we can
• 11:47
  Speaker 3: call a hot and cold approach. The software dynamically calculates
• 11:52
  Speaker 3: this deepest part of the exponential decay curve, the absolute
• 11:56
  Speaker 3: most sensitive weight time, where the probability is roughly fifty
• 11:59
  Speaker 3: to fifty okay, and it focuses its measurement pulses almost
• 12:03
  Speaker 3: entirely right there on that sensitive edge.
• 12:06
  Speaker 2: I love that. It's like trying to monitor the edge
• 12:08
  Speaker 2: of a cliff in the dark. Yes, instead of mapping
• 12:11
  Speaker 2: the entire mountain from the base to the peak over
• 12:14
  Speaker 2: and over again, you find the cliff edge once. Then
• 12:17
  Speaker 2: you just take tiny steps back and forth exactly. If
• 12:19
  Speaker 2: your foot hits air, you know the edge eroded inward.
• 12:22
  Speaker 2: If you hit rock, you know it shifted outward. You're
• 12:25
  Speaker 2: only probing the exact boundary of the change.
• 12:27
  Speaker 3: And because they're only probing the boundary, they don't need
• 12:30
  Speaker 3: thousands of data points to find the new curve. They
• 12:32
  Speaker 3: only need a handful.
• 12:33
  Speaker 2: That is so smart.
• 12:34
  Speaker 3: They programmed a field programmable gate array, an ultra fast
• 12:38
  Speaker 3: FPGA processor to capture the readout data, run a Bayesian
• 12:43
  Speaker 3: estimation algorithm to calculate the new t one time, and
• 12:46
  Speaker 3: instantly adjust the weight time for the very next pulse. Wow,
• 12:49
  Speaker 3: all of that computation and physical adjustment happens entirely on
• 12:53
  Speaker 3: the fly.
• 12:54
  Speaker 2: Real time adaptive tracking. So instead of a one second
• 12:57
  Speaker 2: long exposure photograph, you're taking razor sharp snapshots every ten milliseconds. Yep,
• 13:02
  Speaker 2: you're watching the quantum system live in high definition as
• 13:06
  Speaker 2: it breeds and fluctuates.
• 13:07
  Speaker 3: It really represents a fundamental paradigm shift in quantum observation.
• 13:11
  Speaker 3: For the first time, researchers can watch the relaxation rate dynamically.
• 13:16
  Speaker 3: They can observe the peaks and valleys of the quibbet
• 13:18
  Speaker 3: stability almost perfectly syncd with the actual environmental changes happening
• 13:23
  Speaker 3: inside the chip, and that leads.
• 13:24
  Speaker 2: To the ultimate So what of this whole conversation, Now
• 13:27
  Speaker 2: that we have this ten millisecond high speed camera, how
• 13:30
  Speaker 2: does this actually help us build a better quantum computer. No,
• 13:33
  Speaker 2: because observing a problem is great, but it doesn't automatically
• 13:36
  Speaker 2: fix the fact that the house of cards is falling.
• 13:39
  Speaker 3: No, it doesn't fix it automatically, but it makes fixing
• 13:42
  Speaker 3: it physically possible. Observation in physics is the absolute prerequisite
• 13:46
  Speaker 3: for diagnosis. When your measurement took a full second, all
• 13:50
  Speaker 3: the different microscopic causes of decoherence blended together. But at
• 13:54
  Speaker 3: ten milliseconds, you can finally start correlating the rapid drops
• 13:58
  Speaker 3: in memory stability with SPECIFCI simultaneous physical events.
• 14:02
  Speaker 2: Oh, I see, it's about matching the time stamp of
• 14:04
  Speaker 2: the crime to.
• 14:05
  Speaker 3: The suspect exactly. If the T one relaxation rate suddenly
• 14:09
  Speaker 3: plummets at exactly millisecond forty, and your other sensors detect
• 14:13
  Speaker 3: a tiny burst of background radiation hitting the substrate at
• 14:17
  Speaker 3: exactly millisecond forty, you have a direct correlation.
• 14:19
  Speaker 2: Have caught them red handed?
• 14:21
  Speaker 3: You have? You can say definitively, this specific type of
• 14:24
  Speaker 3: cosmic ray interaction creates a phone on vibration that breaks
• 14:28
  Speaker 3: the Cooper pairs and kills our kubit memory.
• 14:30
  Speaker 2: And once you know exactly what is killing the memory,
• 14:32
  Speaker 2: you can start writing the ultimate hardware path.
• 14:34
  Speaker 3: You can engineer targeted solutions. You can design novel shielding
• 14:38
  Speaker 3: materials that specifically absorb that exact frequency of radiation. You
• 14:43
  Speaker 3: can design microcircuit topographies that isolate the superconducting loops from
• 14:47
  Speaker 3: the atomic defects in the silicon. You can even write
• 14:51
  Speaker 3: more efficient error correcting codes.
• 14:53
  Speaker 2: Because the software will actually know the precise frequency and
• 14:56
  Speaker 2: nature of the errors it's trying to.
• 14:58
  Speaker 3: Correct precisely makes quantum engineering out of the dark ages
• 15:02
  Speaker 3: of trial and error and brings it into an era
• 15:05
  Speaker 3: of precision diagnostics.
• 15:07
  Speaker 2: It's incredible to think about the journey here. We went
• 15:09
  Speaker 2: from superconducting quibits that just randomly hemorrhage their memory while
• 15:14
  Speaker 2: scientists stared helplessly through a one second.
• 15:16
  Speaker 3: Blur, a very frustrating blur, to.
• 15:19
  Speaker 2: The teams at NTNU and the Neils Bohr Institute leveraging
• 15:22
  Speaker 2: active feedback loops and smart algorithms to slice that window
• 15:26
  Speaker 2: down to ten milliseconds. They didn't just build a better sensor,
• 15:29
  Speaker 2: they completely reimagine how to ask the quantum system a question.
• 15:33
  Speaker 3: It's a profound reminder that in deep tech, a measurement
• 15:36
  Speaker 3: breakthrough is often the match that lights the fuse for
• 15:39
  Speaker 3: an engineering revolution. Absolutely without stable memory, quantum computing just
• 15:43
  Speaker 3: remains a fascinating lab experiment. By giving engineers the ability
• 15:47
  Speaker 3: to track and diagnose instability in real time, this breakthrough
• 15:51
  Speaker 3: brings us significantly closer to reality altering computational.
• 15:55
  Speaker 2: Power, and that leaves us with a truly mind expanding
• 15:59
  Speaker 2: concept upon As we wrap up today.
• 16:01
  Speaker 3: Okay, let's hear it.
• 16:02
  Speaker 2: We've talked entirely about humans using this ten millisecond tracking
• 16:06
  Speaker 2: to engineer better hardware. But what if we integrate this
• 16:09
  Speaker 2: algorithm directly into the quantum processor's own operating system?
• 16:13
  Speaker 3: Oh wow? Right?
• 16:15
  Speaker 2: If a machine can now track its own memory de
• 16:17
  Speaker 2: ka in ten milliseconds, how long will it be before
• 16:20
  Speaker 2: it uses that real time data to predict its own
• 16:22
  Speaker 2: information loss?
• 16:24
  Speaker 3: That is fascinating.
• 16:25
  Speaker 2: Could a future quantum computer sense a microscopic disturbance coming,
• 16:29
  Speaker 2: realize its t one is plummeting, and actively course correct
• 16:32
  Speaker 2: or reroute the calculation before the memory even disappears.
• 16:35
  Speaker 3: Self correcting on the fly.
• 16:36
  Speaker 2: Exactly are we looking at the dawn of self healing
• 16:39
  Speaker 2: quantum computers?
• 16:40
  Speaker 3: That is the frontier we are racing toward. The microscopic
• 16:44
  Speaker 3: world is full of chaotic noise, but as we learn
• 16:47
  Speaker 3: to see it clearly, we can learn to master it.
• 16:50
  Speaker 3: I encourage everyone listening to keep questioning the invisible mechanisms
• 16:54
  Speaker 3: that power our reality.
• 16:55
  Speaker 2: Thank you so much for exploring the quantum realm with
• 16:58
  Speaker 2: us today. Keep wondering, keep asking those hard questions, and
• 17:02
  Speaker 2: we will see you next time.