Speaker 1: Get in touch with technology with tech Stuff from how
Speaker 1: stuff Works dot com. Hey there, and welcome to tech Stuff.
Speaker 1: I am Jonathan Strickland, the host, an executive producer with
Speaker 1: How Stuff Works and a lover of all things tech.
Speaker 1: And this is another episode in the little mini series.
Speaker 1: I'm recording while I'm attending the Think two thousand eighteen
Speaker 1: conference in Las Vegas, Nevada. It's sponsored by IBM, and
Speaker 1: IBM does this big conference. It's sort of a an amalgamation,
Speaker 1: a gloming on to several different smaller conferences that IBM
Speaker 1: has been holding for several years. They kind of pushed
Speaker 1: them all together and turned it into a giant, mega conference.
Speaker 1: And I emphasized giant. I mean there are tens of
Speaker 1: thousands of people attending this conference. It feels like more
Speaker 1: than that when you're trying to get through the Mandalay
Speaker 1: Bay Conference Center, because holy cats, lots of executives, a
Speaker 1: lot of blazers, a lot of blazers out there, folks.
Speaker 1: I gotta watch my what I say because pretty much
Speaker 1: everybody in there is a giant stakeholder in some big
Speaker 1: business or another. And chances are if I if I
Speaker 1: say something rude, I've just insulted a millionaire, and I'm
Speaker 1: not in that tax bracket. But let's talk a little
Speaker 1: bit about one of the topics that got a lot
Speaker 1: of coverage here at IBM think two thousand and eighteen,
Speaker 1: and that is quantum computing. It's a big deal, and
Speaker 1: that's because quantum computers are beginning to emerge from the
Speaker 1: realm of experimental science into practical applications. In fact, you
Speaker 1: could argue it's already there and has been for a
Speaker 1: couple of years, but it's still relatively new and I
Speaker 1: think very mysterious for a lot of people. And I've
Speaker 1: talked about a little bit in previous episodes, but I
Speaker 1: really wanted to dedicate a an entire episode kind of
Speaker 1: quantum computing one oh one and really talk about the
Speaker 1: principles behind it, the history behind it, what it might
Speaker 1: be used for, why it's such a big deal in
Speaker 1: the first place. So this is our full episode on
Speaker 1: the topic, and I'm going to reference some of the
Speaker 1: things I've learned while I've been at this conference. Let's
Speaker 1: do what I love to do. This is like a
Speaker 1: good old traditional episode of tech stuff. We're gonna dive
Speaker 1: into the history of quantum computing and quantum mechanics and
Speaker 1: quantum theory. So this all begins before the computer age.
Speaker 1: We have to discuss the history of quantum mechanics itself. Now,
Speaker 1: I'm not going to go into exhaustive detail, because to
Speaker 1: do that would require an entire podcast series, not just
Speaker 1: an episode, but a series of episodes to kind of
Speaker 1: talk about all of the developments in quantum mechanics. And
Speaker 1: not only that, but it's a messy history filled with
Speaker 1: a lot of scientific debate and our humans and uh
Speaker 1: experiments and counter experiments, thought experiments, aim calling. There was
Speaker 1: some adultery in there too. I mean, it's it reads
Speaker 1: like a soap opera at times, and and like I said,
Speaker 1: it's just it's so deep and dense that to really
Speaker 1: cover it would require multiple episodes. So this is kind
Speaker 1: of like a an introductory a bird's eye view of
Speaker 1: the history of quantum mechanics. So let's talk about the
Speaker 1: developments around the turn of the last century, the twentieth century.
Speaker 1: In nineteen hundred, it only been a couple of years
Speaker 1: and scientists had even discovered the existence of electrons at
Speaker 1: that point. No one was even sure in nineteen hundred
Speaker 1: if electrons were even part of the atom. They didn't
Speaker 1: know our electrons actually a component of atoms or are
Speaker 1: they something else? So do they coexist with atoms but
Speaker 1: they're not bound to atoms? They weren't sure. In nine hundred,
Speaker 1: there was general agreement that atoms were in fact a
Speaker 1: kind of a fundamental particle, but beyond that, there wasn't
Speaker 1: a whole lot of agreement on them. No one was
Speaker 1: really sure what made the atoms of one element different
Speaker 1: from another, and therefore they weren't sure why elements were
Speaker 1: different in the first place. They could identify elements, they
Speaker 1: could identify the qualities of elements, but they couldn't explain
Speaker 1: why they were different from each other. Well, in there
Speaker 1: was a smarty pants physicist, Max Planck, who was trying
Speaker 1: to work out some reasons behind a curious observation that
Speaker 1: people had noticed for centuries but didn't They couldn't explain it.
Speaker 1: And that was the nature of heat radiation and the
Speaker 1: light that it can produce. So let's say that you're
Speaker 1: a blacksmith and you've got some iron, and you put
Speaker 1: in the forge and you heat the forge up. Eventually
Speaker 1: that iron, as it grows hot, will begin to glow,
Speaker 1: and it first will kind of glow red, and then
Speaker 1: that red will get brighter and brighter, kind of turned
Speaker 1: into an orange. And if it gets hot enough, it'll
Speaker 1: glow white. If you could get it hot enough before
Speaker 1: it melted, you could make it even glow blue. These
Speaker 1: different colors would represent different energy states, but no one
Speaker 1: knew that at the time. No one was able to
Speaker 1: explain why iron would change color as it got hotter.
Speaker 1: So Plank was working on this problem. He was trying
Speaker 1: to figure out, well, what is what explains us, or
Speaker 1: what at least describes this, and eventually came up with
Speaker 1: a formula that fit the observations he made in experiments.
Speaker 1: He had figured out a formula that that seemed to fit,
Speaker 1: But why did it fit? Why did that formula describe
Speaker 1: what was happening? He couldn't tell. He wasn't sure, No
Speaker 1: one was sure at first. He kept working on it,
Speaker 1: so eventually Plank figured out that the atoms could apparently
Speaker 1: only take on certain quantities of energy, So it could
Speaker 1: take a certain amount of energy, and then any above
Speaker 1: that it could not accept until it got to the
Speaker 1: next specific allowable energy level. So you could think of
Speaker 1: it as steps of energy. You could accept a certain amount,
Speaker 1: and then you could step up and accept a new
Speaker 1: larger amount, but anything in between those two steps didn't
Speaker 1: fit the formula. And this was very curious. It wasn't
Speaker 1: something that was continuous, right, This idea of steps of
Speaker 1: energy levels was really perplexing at the time. You might
Speaker 1: think of it more like a continuous string, but it wasn't.
Speaker 1: It was this broken series of steps. So this really
Speaker 1: got people wondering what the heck was going on. Um,
Speaker 1: how could materials take on specific increments of energy rather
Speaker 1: than any arbitrary amount. Planck didn't know. He didn't know
Speaker 1: why it was happening. He only knew that it was
Speaker 1: happening based upon his observations, and that the explanation he
Speaker 1: had fit what he observed. He just couldn't explain why
Speaker 1: it worked. He announced his findings on December four, nineteen hundred.
Speaker 1: Now some people trace that as the origin of the
Speaker 1: study of quantum mechanics, though of course at that time
Speaker 1: it wasn't yet called quantum mechanics. It did, however, formulate
Speaker 1: the foundation of what some would refer to as old
Speaker 1: quantum theory. Now that theory stated that these acceptable energy
Speaker 1: increments were specific quantities, right quantities of energy, and that
Speaker 1: any phenomena that would only accept certain values of a
Speaker 1: physical quantity fell into this category, and it typically was
Speaker 1: stuff on the atomic scale, tiny tiny scale, not classical scale,
Speaker 1: which seemed to follow the rules of classical physics. These
Speaker 1: things didn't seem to follow the rules of classical physics.
Speaker 1: The rules were different for some reason. So scientists said
Speaker 1: that the values of this physical quantity of energy, uh,
Speaker 1: we're said to be quantized. That's the values of this
Speaker 1: energy is quantized. It was generally believed that you'd have
Speaker 1: to do lots of experiments and make lots of observations
Speaker 1: to kind of suss out the rules for that quantization
Speaker 1: or perhaps even uncover a set of universal rules that
Speaker 1: would work in all situations. So there were scientists like
Speaker 1: Albert Einstein who seized on this notion, and they began
Speaker 1: to apply this idea to other areas of study. He,
Speaker 1: for example, Einstein, that is, proposed that the total energy
Speaker 1: of a beam of light was quantized. Several other big
Speaker 1: thinkers were looking into similar fields. But then the First
Speaker 1: World War broke out and that really slowed down progress
Speaker 1: in the sciences because a lot of the leading scientists
Speaker 1: at the time we're all in Europe, so obviously Europe
Speaker 1: being heavily affected by World War One meant that a
Speaker 1: lot of that work was put on hold. However, at
Speaker 1: the war's conclusion, things picked up again at that stage
Speaker 1: after World War One, but before World War Two, you
Speaker 1: had scientists like Max Bourne and Werner Heisenberg who were
Speaker 1: extending our understanding of the quantized world. Now Born and Heisenberg,
Speaker 1: along with Pascal Jordan's, wrote an extremely complicated but consistent
Speaker 1: theory of quantum mechanics. Meanwhile, you had another smarty pants
Speaker 1: Irwin Schrodinger or Irvin if you prefer, that would be
Speaker 1: of Schrodinger's cat fame. He was working on his own
Speaker 1: theory to describe quantum mechanics, and for a while, those
Speaker 1: two theories were the focus of a pretty nasty war
Speaker 1: within physics in which both sides were kind of disparaging
Speaker 1: the ideas of the other side. And essentially one group
Speaker 1: is saying, you guys are full of it. My theory
Speaker 1: describes what's actually happening Here's is a mess, and the
Speaker 1: other side saying, nah, our theory is far more descriptive
Speaker 1: of what is actually going on your theory is nonsensical.
Speaker 1: But then in Schrodinger and Carl Eckert, who was working
Speaker 1: completely independently of Schrodinger, both proved that these two seemingly
Speaker 1: different approaches were actually describing the same thing. They were
Speaker 1: just doing it from completely different points of reference. So
Speaker 1: on the surface they superficially seemed like they were at
Speaker 1: odds with one another, but underneath that it turned out
Speaker 1: they were. They were in alignment. As one book I
Speaker 1: read on the subject said, it's like comparing how you
Speaker 1: add Arabic numerals to how you add Roman numerals. The
Speaker 1: two processes look very different from each other, but if
Speaker 1: you do them each correctly for the same two values,
Speaker 1: you'll always arrive at the same answer, no matter what
Speaker 1: method you use. Now that's not to say that everything
Speaker 1: was smooth sailing from that point forward. Many scientists had
Speaker 1: problems with aspects of quantum mechanics, such as it's probabilistic nature.
Speaker 1: That is, much of quantum mechanics concerns itself with probabilities
Speaker 1: rather than certainties. In fact, lots of things and quantum
Speaker 1: mechanics become inherently uncertain the more you try and nail
Speaker 1: it down, the more uncertain other elements will become. That's
Speaker 1: partly what Heisenberg's uncertainty principle states. Heisenberg was specifically talking
Speaker 1: about a quantum particles position versus its momentum. Heisenberg stated
Speaker 1: that the more precisely you measure one of those two values,
Speaker 1: the less you can know about the other one. So
Speaker 1: if you measure a quantum particles position with great precision,
Speaker 1: you won't know very much about its momentum, and vice versa.
Speaker 1: And that this is just a fundamental feature of our universe,
Speaker 1: so it's tough if you don't like it. The probabilistic
Speaker 1: side of a quantum mechanics is tied also to measurement.
Speaker 1: This was a central focus of a debate between two
Speaker 1: great physicists, Neil's Bore and of course Albert Einstein. Einstein
Speaker 1: was not keen on the probabilistic nature of quantum theory.
Speaker 1: Uh He has often been attributed the phrase God does
Speaker 1: not play dice with the universe, although that is a
Speaker 1: paraphrasing of what he said. And then Niel's Bore was
Speaker 1: paraphrases saying God doesn't care what you think he's doing.
Speaker 1: Um so that was kind of the back and forth.
Speaker 1: Although both of those statements were paraphrase, neither of those
Speaker 1: were actually what the scientists were saying, just kind of
Speaker 1: was a an interpretation of what they said. Quantum mechanics
Speaker 1: experiments wouldn't really produce a definite solution. So we're used
Speaker 1: to things like calculations coming up with a specific answer.
Speaker 1: Right even let's just take simple arithmetic. If you say
Speaker 1: two plus two equals for then you know you realize that,
Speaker 1: all right, well, that that makes sense to pless two
Speaker 1: equals for that's a that's a certain value. It's a
Speaker 1: definite answer. Whereas with quantum mechanics you would get results
Speaker 1: that would be listed in terms of probabilities, not in
Speaker 1: terms of here is the answer. You would get a
Speaker 1: probabilistic distribution of possible values. So that means every single
Speaker 1: value you would get would get assigned a probability, and
Speaker 1: if you were to measure a quantum state, that would
Speaker 1: actually cause it to collapse into one of those probable
Speaker 1: values that it possibly could have been. This is also
Speaker 1: related to that concept of quantum tunneling I mentioned earlier
Speaker 1: this week. The idea of an electron could potentially inhabit
Speaker 1: one of any positions that are within a certain field,
Speaker 1: and because there's that probability, it means that sometimes the
Speaker 1: electron will inhabit that position. And if that position happens
Speaker 1: to be on the other side of a barrier, just
Speaker 1: because the zone the electron could exist in happens to
Speaker 1: overlap that barrier, then that means sometimes the electron is
Speaker 1: on the other side of the barrier, even though it
Speaker 1: did not physically pass through the barrier. It's it's part
Speaker 1: of the weird nature of quantum mechanics and probabilistic distribution. Again,
Speaker 1: it's not a certainty, it's a probability. Another concept of
Speaker 1: quantum theory that ends up being very important with quantum
Speaker 1: computers is that of superposition. This is a pretty tricky concept,
Speaker 1: as it is so counterintuitive that it prompted Schrodinger to
Speaker 1: create what he thought was an absolutely bonkers example so
Speaker 1: that he could illustrate how whacka doodle this idea was
Speaker 1: on the macro scale. But today that example is widely known,
Speaker 1: or at least it's known by name. That would be
Speaker 1: Schrodinger's cat. So what is superposition and what the heck
Speaker 1: was that famous thought experiment. Well, superposition refers to quantum
Speaker 1: particles as inhabiting all sable states simultaneously. So a state
Speaker 1: is really just a feature, something that the quantum particle possesses.
Speaker 1: So let's take electron spin as an example. All right,
Speaker 1: So electrons can spin in different directions, and for this
Speaker 1: particular example, let's just talk about spinning up or spinning down.
Speaker 1: So electron can spin up or it can spin down.
Speaker 1: According to some versions of quantum theory and its quantum state,
Speaker 1: that electron can be said to be both spinning up
Speaker 1: and down simultaneously. It's both states at the same time.
Speaker 1: It inhabits them while it's in this quantum state. But
Speaker 1: when you measure the electrons spin, when you observe it,
Speaker 1: the quantum state collapses down into one of the two
Speaker 1: possible states. So you're never going to observe an electron
Speaker 1: spinning up and down simultaneously because the act of observing
Speaker 1: changes that which is observed at the quantum level. This
Speaker 1: is the argument some people make that you know, measuring
Speaker 1: doesn't matter because if you measure, you have changed the
Speaker 1: thing that you were measuring. Now, that is true on
Speaker 1: the quantum scale, but as you move up to the
Speaker 1: classical scale, it's not really something you need to concern
Speaker 1: yourself with. So, uh, you can't confuse quantum mechanics with
Speaker 1: classical mechanics. It they are rules that define two different universes,
Speaker 1: really the quantum level and then the classical level. So
Speaker 1: it's not like classical physics need to be thrown out
Speaker 1: the door. They still apply just two things that are
Speaker 1: on the classical scale. When you get to the quantum scale,
Speaker 1: that's when you have to look at quantum mechanics, and
Speaker 1: that's when you start seeing these seemingly weird and counterintuitive rules.
Speaker 1: And I say seemingly because the only reason they seem
Speaker 1: weird to us is because we cannot observe them directly.
Speaker 1: We don't exist on the quantum level um and in
Speaker 1: the way that we can perceive it. We can just
Speaker 1: work out the math and figure it out, and then
Speaker 1: we can design experiments, and through those experiments we can
Speaker 1: we can actually look for evidence that supports these theories.
Speaker 1: And in fact, that has happened over time. People have
Speaker 1: designed experiments to test these ideas and found through the
Speaker 1: results of the experiments that those ideas seemed worthy, they
Speaker 1: seemed valuable, and and real. Now, Schrodinger's cat is a
Speaker 1: way of exaggerating this superposition effect, kind of in an
Speaker 1: effort to show how crazy it sounds. So here's the
Speaker 1: thought experiment. Let's say you've got a cat, and you
Speaker 1: put the cat in a metal case. Inside that case
Speaker 1: with the cat is a device that contains a radioactive particle. Now,
Speaker 1: that radioactive particle could undergo radioactive decay within the next hour,
Speaker 1: or equally, it could not decay within an hour. So
Speaker 1: there's an equal chance that it could decay or that
Speaker 1: it could remain whole within the span of an hour.
Speaker 1: If the particle does decay, the energy it gives off
Speaker 1: will cause a glass vial containing a poison to break,
Speaker 1: and that will release the poison in the cage and
Speaker 1: kill the poor kitty cat. The whole experiment is completely
Speaker 1: sealed away. The cat is unable to interfere with the device,
Speaker 1: because if you interfere with a quantum state and then
Speaker 1: it decoheres, the whole experiment falls apart. So you have
Speaker 1: to have this is a thought experiment anyway, but you
Speaker 1: have to have it set up in a way so
Speaker 1: that the cat's not going to interfere with the quantum state.
Speaker 1: So an hour goes by with the cat inside this
Speaker 1: cage and the radioactive element in there as well. And
Speaker 1: the question you have to ask yourself before you open
Speaker 1: up the cage is is the cat dead or is
Speaker 1: it alive? Now? According to the super position theory and
Speaker 1: Schroedinger's interpretation of that theory, you would have to say
Speaker 1: that the cat is both alive and dead at the
Speaker 1: same time. That exists in this quantum state where it
Speaker 1: is alive and dead. It is only when you open
Speaker 1: the cage and you look in and you are essentially
Speaker 1: measuring the system this way, because you're making an observation
Speaker 1: that the entire system will collapse into one of the
Speaker 1: two possible outcomes, And at that point the cat makes
Speaker 1: the transition into either being perfectly fine or very much
Speaker 1: an ex kitty cat joining the choir invisible, running up
Speaker 1: the curtain, kicking the bucket, shuffling off the mortal coil.
Speaker 1: You get the idea. This is where you get all
Speaker 1: those jokes about the cat being half dead. But here's
Speaker 1: the crazy thing. While Schroedinger's thought experiment did make superposition
Speaker 1: sound really bonkers, experiments supported the notion of superposition. Now Granted,
Speaker 1: we're talking about effect on the quantum level, not something
Speaker 1: that's observable in our macro world. Schrodinger would argue that
Speaker 1: because the the whole premise of the experiment relied upon
Speaker 1: a quantum particle, whether it decayed or not, it doesn't
Speaker 1: violate this. The consequences of the at quantum event would
Speaker 1: be on the macro level, but that the actual event
Speaker 1: itself would still be in the quantum level. Uh. There's
Speaker 1: some people who dispute that, so it kind of becomes
Speaker 1: a philosophical argument. But the point is that the experiment
Speaker 1: started to support this idea of superposition, and it's one
Speaker 1: of the few, one of a couple of principles of
Speaker 1: quantum mechanics that makes quantum computing such a potentially powerful
Speaker 1: tool and a possible revolution in computing in general. The
Speaker 1: other big concept in quantum theory that is of particular
Speaker 1: importance with quantum computers is called entanglement. Now, this is
Speaker 1: the strong correlation between two quantum particles that link those
Speaker 1: two particles together, no matter how much physical distance might
Speaker 1: separate the particles. So you could take two entangled particles,
Speaker 1: and if you could do it in a way where
Speaker 1: you're not disturbing the entanglement. You could move one particle
Speaker 1: to the other side of the universe from the first
Speaker 1: particle and they would still remain entangled. Einstein would call
Speaker 1: this spooky action at a distance, and entangling particles means
Speaker 1: that these two particles are always going to complement one
Speaker 1: another in some way. So let's take electrons again. Let's
Speaker 1: say you entangle to electrons so that their spin is correlated,
Speaker 1: and if one electron is spinning up, the entangled partner
Speaker 1: is always spinning down. This is just one example of
Speaker 1: a way you could entangle particles so that means no
Speaker 1: matter how much distance separates these electrons, if electron A
Speaker 1: is spinning up, then electron B is spinning down. If
Speaker 1: electron A starts to spin down, then electron B will
Speaker 1: start to spin up, and he'll do it exactly at
Speaker 1: the same time. There's like no delay, and this will
Speaker 1: happen no matter how far apart those electrons are. It
Speaker 1: seems impossible, and yet that is in fact what seems
Speaker 1: to be happening with entanglement. However, once you observe one
Speaker 1: of those two electrons, then the entanglement is broken and
Speaker 1: you will know at the moment of observation, the moment
Speaker 1: of measurement, what that other electron was doing, But you
Speaker 1: don't know what it's doing anytime after the moment of observation.
Speaker 1: You can only say, at this precise moment, the other electron,
Speaker 1: wherever it may be, was doing this particular activity. At
Speaker 1: that point, the system decoheres, and so it gives you
Speaker 1: information but nothing. Some people have argued that this is
Speaker 1: a way that you could potentially have faster than like communication.
Speaker 1: Others argue no, because all it does is tell you
Speaker 1: information that previously existed. The information didn't travel, just your
Speaker 1: realization of what that information was occurs to you. It's
Speaker 1: another fine distinction that gets into philosophical arguments, and its
Speaker 1: outside the scope of this particular podcast, but it is
Speaker 1: a fascinating discussion. So together, super position and entanglement are
Speaker 1: two of the factors that really make quantum computers so
Speaker 1: potentially revolutionary. And it's weird to say potentially, because today
Speaker 1: they are actual working Quantum computers just have a somewhat
Speaker 1: limited scope right now, but they're getting better all the time,
Speaker 1: and in fact, some of the prototypes are really impressive
Speaker 1: already before we get to actual quantum computers. There's a
Speaker 1: little more history I need to cover. In nineteen seventy three,
Speaker 1: Alexander Hollevo argued that for any given number of cubits,
Speaker 1: which are quantum bits, you could not possibly carry more
Speaker 1: information than that same number of classical bits. So, in
Speaker 1: other words, if you have eight quantum bits, those eight
Speaker 1: quantum bits could carry only as much information as a
Speaker 1: classical bite, bite being eight bits, and of course a
Speaker 1: bit being a basic unit of information, either a zero
Speaker 1: or a one. However, the eight cubits through superposition could
Speaker 1: represent all possible states of that bite. So it's not
Speaker 1: carrying more information, it's just carrying Uh. It's hard to
Speaker 1: hard to put this in a way that makes sense.
Speaker 1: It's not carrying more information than a bite, it's just
Speaker 1: carrying every single variation of information that bite could represent. Again,
Speaker 1: anotherir fine distinction. This gets really fuzzy and wibbly wobbly
Speaker 1: timey y me to me. In the early eighties, people
Speaker 1: begin to theorize about the possibility of quantum computing and
Speaker 1: talking about how you might use quantum particles to represent bits.
Speaker 1: So again, like electrons, you could use electrons in their
Speaker 1: spin And this is a quantum quality that electrons have,
Speaker 1: and if you were able to put those into a
Speaker 1: quantum state, you could use the electron spin to represent
Speaker 1: what would normally be a bit in a classical computer.
Speaker 1: That's just one possible example, mind you, because you could
Speaker 1: use all sorts of different stuff to represent these bits.
Speaker 1: You could use photons and their polarization if you wanted to,
Speaker 1: or other quantum particles and other qualities. In Richard Fineman
Speaker 1: presented a talk in which he lamented the fact that
Speaker 1: classical computer systems would be incapable of simulating the evolution
Speaker 1: of a quant um system, because quantum systems would just
Speaker 1: be far too complicated for a classical computer to do
Speaker 1: this in any reasonable time frame. He did, however, hypothesize
Speaker 1: that if you were able to create a quantum computer,
Speaker 1: you could potentially simulate the evolution of a quantum state.
Speaker 1: Theorists began to flesh out what a quantum computer might
Speaker 1: look like, and how it might operate, and even how
Speaker 1: you might try to go about making one. This was, all, however,
Speaker 1: still within the realm of the theoretical In the mid nineties,
Speaker 1: and engineer named Peter Shore discovered an algorithm that would
Speaker 1: really put a fire under the bottoms of quantum computer researchers.
Speaker 1: His algorithm was a set of rules that a quantum
Speaker 1: computer could theoretically be able to follow and allow it
Speaker 1: to factor large integers much more quickly than a classical computer. Now,
Speaker 1: the reason this posed both an exciting opportunity and a
Speaker 1: terrifying realization was because factoring large numbers is what most
Speaker 1: modern day cryptography is based off of. Uh, you take
Speaker 1: numbers that are hundreds of digits long, prime numbers specifically,
Speaker 1: so these are numbers that are only divisible by themselves.
Speaker 1: And then you take two of those numbers that are
Speaker 1: both hundreds of digits long, like five hundred digits long,
Speaker 1: and they're both prime numbers, and you multiply those two
Speaker 1: prime numbers together, you get an even larger number that
Speaker 1: ends up being sort of your public key, your your
Speaker 1: key that you used to encrypt stuff. But the only
Speaker 1: way you can decrypt the information is if you know
Speaker 1: what those two numbers were, those two huge numbers you
Speaker 1: started off with were, which is hard to determine. It's
Speaker 1: really hard. If you're using a classical computer. It would
Speaker 1: take years or more, depending upon how long the number
Speaker 1: was to brute force the answer if you're following classical
Speaker 1: computer science. But Shore's algorithm was a short cut that
Speaker 1: a quantum computer, not a classical computer. A quantum computer
Speaker 1: could run and run that same calculation in a fraction
Speaker 1: of the time. So, in other words, a quantum computer
Speaker 1: following this algorithm that was discovered by Shore could reverse
Speaker 1: the process we use to make all of our data secret. Well,
Speaker 1: by the late nineties, the first rudimentary quantum computers were
Speaker 1: being constructed in the laboratories. They were really primitive. They
Speaker 1: could not run very many operations before they would decohere uh,
Speaker 1: and then you'd have to start all over again. They
Speaker 1: were delicate systems. They were consisting of just a couple
Speaker 1: of quantum bits of processing power. But it was the
Speaker 1: beginning of the revolution. So how can quantum computers be
Speaker 1: so powerful compared to classical computers and exactly what sort
Speaker 1: of problems would quantum computers be good at solving? Well,
Speaker 1: i'll tell you about that in just a moment, but
Speaker 1: first let's take a quick break to thank our sponsor.
Speaker 1: All right, so let's talk about bits now. As I mentioned,
Speaker 1: a bit is a basic unit of information and it
Speaker 1: is binary, meaning it can have only two states. So
Speaker 1: we express bits as a zero or a one, and
Speaker 1: you can think of that as being off or on,
Speaker 1: or down or up. Just as an electron spin has
Speaker 1: different states or a photons polarization, so too does a
Speaker 1: bit machine. Language is made up of strings of bits.
Speaker 1: A collection of eight bits makes up a bite, and
Speaker 1: a single bite can represent up to two hundred fifty
Speaker 1: six different states. I talked about this recently in the
Speaker 1: I p V six episode. I did the numbers in
Speaker 1: an ip V four address or just a regular old
Speaker 1: IP address. Those are based off octets or bites. Each
Speaker 1: number in that IP address can have a hypothetical value
Speaker 1: between zero and two hundred fifty five. I say hypothetical
Speaker 1: because some numbers are off limits due to the rules
Speaker 1: of Internet protocol. But if you didn't have those restrictions,
Speaker 1: each of those four numerals in that address could have
Speaker 1: a value between zero and two inclusive. Those would be
Speaker 1: the two six potential values of that bite. A classical
Speaker 1: computer relies on these bits. It's the form of information
Speaker 1: the processor takes in and the form it spits back
Speaker 1: out again. The information does get translated into formats where
Speaker 1: humans can find useful or initiate some action that is
Speaker 1: useful to us in some way. Humans have made a
Speaker 1: series of computer programming languages, starting with assembly code or
Speaker 1: a similar code really, which is just a step above binary,
Speaker 1: up to high level programming languages that abstract those zeros
Speaker 1: and ones so that we can structure programs in a
Speaker 1: way that's more natural for us to understand. It's still
Speaker 1: it can look like complete gibberish to you if you
Speaker 1: don't know computer languages, but in fact it is far
Speaker 1: easier to read than just zeros and ones. So it's
Speaker 1: hard to think of any kind of information just in binary.
Speaker 1: But in the classical computer, a bit has to be
Speaker 1: either a zero or a one, it cannot be both,
Speaker 1: and classical computers will run processes in sequence. So you
Speaker 1: can speed that up a little bit by using a
Speaker 1: couple of different strategies. One is just to make more
Speaker 1: powerful processors that can handle more information and smaller amounts
Speaker 1: of time. That will help. You can improve bus speeds,
Speaker 1: You can improve the speed that a CPU can draw
Speaker 1: information from memory or put information back in memory. That
Speaker 1: will help too, but eventually you run up against the
Speaker 1: upper limits of what we can accomplish with today's technology,
Speaker 1: and of course that keeps on improving, but you still
Speaker 1: will run up against those limits. You can use a
Speaker 1: multiple core processor. Multi core processors are great. You can
Speaker 1: even use an array of processors. That's useful if the
Speaker 1: computer problems you're working on can be split into smaller
Speaker 1: problems that can be solved in parallel. Not all problems
Speaker 1: fall into that category, however, and even if your processor
Speaker 1: isn't the fastest, if you're talking about a parallel problem,
Speaker 1: multiple core processors might be a better choice than a
Speaker 1: single powerful core processor. I usually use this particular analogy.
Speaker 1: Imagine you've got a math test, and the math test
Speaker 1: has ten problems on it. You also have a math
Speaker 1: class and it has eleven students in it. One of
Speaker 1: the eleven students is a super math genius, and she
Speaker 1: has an innate sense of math. It's almost spooky. It's
Speaker 1: like she can visualize mathematics all around her, and she
Speaker 1: can solve any one problem faster than anyone else in
Speaker 1: the class. Just doesn't matter. But the teacher gives the
Speaker 1: super smarty genius all ten of the math problems on
Speaker 1: the test, whereas each of the other students in the
Speaker 1: class each of them, being good at math but not
Speaker 1: at genius level, gets only one of the ten problems.
Speaker 1: So student one gets problem one, Student two gets problem too,
Speaker 1: and so forth. You have ten students working to solve
Speaker 1: one problem each, and a supermath genius working on all
Speaker 1: ten problems. Who's going to finish first? Well, the super
Speaker 1: genius is going to solve each of her ten problems
Speaker 1: faster than any of the individual students will finish their
Speaker 1: respective problems. But chances are the group of ten will
Speaker 1: finish first because they each only have one problem to
Speaker 1: work on. They're able to divide and conquer, as it were.
Speaker 1: And some computational problems are like that. But there are
Speaker 1: classes of mathematical problems that are too tough even for
Speaker 1: the fastest classical computers running scores of processors. There so
Speaker 1: difficult as to be practically unsolvable. Now I say practically
Speaker 1: on purpose. It's not that a classical machine can't solve
Speaker 1: these sorts of problems. They just can't do it in
Speaker 1: any sort of reasonable amount of time. It could take
Speaker 1: years or decades or centuries, depending upon the complexity of
Speaker 1: the problem. So what kind of problems am I talking about? Well,
Speaker 1: there's a class of problems around the concept of optimization,
Speaker 1: and that's a big part of what quantum computers could tackle.
Speaker 1: These are problems they get very hard to solve, particularly
Speaker 1: as you add more components to it. Now, I'll give
Speaker 1: you a very simple example. Let's say you're throwing a
Speaker 1: big dinner party. You've rented out a swanky joint. You've
Speaker 1: got five tables. Each table has seating for ten people,
Speaker 1: So you've got fifty people on the way to your party,
Speaker 1: and it's your job to assign seats for each of
Speaker 1: the people who are coming. However, there's a problem. Not
Speaker 1: all of your friends are crazy about each other. So
Speaker 1: let's say you've got a buddy named Sally, and she
Speaker 1: would absolutely hate to sit next to Jim. Jennifer would
Speaker 1: love to sit next to Sally, but she definitely doesn't
Speaker 1: want to sit next to Sally's cousin, Darryl. But m
Speaker 1: and Darryl are best friends, so they definitely want to
Speaker 1: at least sit at the same table, if not next
Speaker 1: to each other, and so on and so forth. You've
Speaker 1: got all these different conditions that exist, and you want
Speaker 1: to find the best possible seating solution to the problem
Speaker 1: of who sits where in order for you to have
Speaker 1: a nice, lovely dinner and not have a breakout into
Speaker 1: a three stooges pie throwing routine. Well, here's the thing.
Speaker 1: The problem of sitting just ten people around a table
Speaker 1: is factorial. There are three point six million possible configurations
Speaker 1: for ten people to sit at a table. That's just
Speaker 1: ten at one table. And remember you have five of
Speaker 1: those tables, and you have numerous rules you want to
Speaker 1: do your best to follow to ensure that it's a
Speaker 1: pleasant party and no one's gonna go home with punch
Speaker 1: and pie spilled all over their outfits. So how do
Speaker 1: you solve this problem? Well, a classical computer would choke
Speaker 1: on this kind of problem because they would have to
Speaker 1: run every single possible scenario, and then it would have
Speaker 1: to check the results of all those scenarios against the
Speaker 1: rules that you had given it, saying all right, well
Speaker 1: don't put so and so next to so and so,
Speaker 1: and then it would have to tally up all of
Speaker 1: those different scenarios, analyze the whole thing, and determine which
Speaker 1: one out of all the different scenarios that could come out.
Speaker 1: And remember there's three point six million per table, that
Speaker 1: which one is the best. By that time, half your
Speaker 1: friends have moved away, or had kids, or have become
Speaker 1: honored ancestors to generations that follow because it just took
Speaker 1: way too long for this classical computer to work out
Speaker 1: the problem, and your party was a bust because you
Speaker 1: never got the invitations out in the first place. Now,
Speaker 1: another problem in this class is called the traveling salesman problem.
Speaker 1: This is a classic problem and it goes like this.
Speaker 1: Given a list of cities that a salesperson has to
Speaker 1: visit to do his or her rounds, what is the
Speaker 1: shortest possible route that the salesperson can follow that will
Speaker 1: allow them to visit every single city and return home
Speaker 1: to their point of origin the shortest possible route among
Speaker 1: all those cities. This one's pretty easy to understand, but
Speaker 1: it's actually fiendishly difficult to solve, especially as you add
Speaker 1: more cities to the problem. So this type of problem
Speaker 1: is called an MP hard problem, and the more cities
Speaker 1: you add, the harder it gets. So how could quantum
Speaker 1: computers do a better job than classical ones with these
Speaker 1: sorts of problems? And it comes down to a basic
Speaker 1: unit of information in the world of quantum computers, The
Speaker 1: quantum bid or the cubit you know, I mentioned it
Speaker 1: a couple of times, and a cubit can be placed
Speaker 1: in superposition, meaning that in its quantum state, it is
Speaker 1: behaving as if it's both a zero and a one simultaneously.
Speaker 1: You can also entangle cubits with one another, so that
Speaker 1: the state of one cubit and it's entangled cubit are
Speaker 1: highly correlated. So you could encoded in such a way
Speaker 1: where you say, if cubit A is a zero, do
Speaker 1: nothing to cubit B. If cubit A is a one,
Speaker 1: flip cubit B to one. That would be an example
Speaker 1: of entanglement. With these properties, it's possible to solve these
Speaker 1: traditional unsolvable problems in a very short amount of time
Speaker 1: if you have a quantum computer with a sufficient number
Speaker 1: of cubits. That's because the cubits in their quantum state
Speaker 1: can essentially run all possible solutions to a problem simultaneously
Speaker 1: rather than sequentially. I'm oversimplifying here, but that's the general principle.
Speaker 1: And as you add more cubits, your ability to process
Speaker 1: information grows exponentially. Now, how does that work? Well, if
Speaker 1: you have a single cubit, but it can potentially be
Speaker 1: two states at the same time. Because of superposition, that
Speaker 1: cubit actually represents two states, not one. Remember a bit
Speaker 1: can only represent one state at a time. If you
Speaker 1: have two cubits in superposition, that can represent four states
Speaker 1: at one time. So does that mean three cubits is
Speaker 1: going to be six states? No, No, three cubits would
Speaker 1: be eight states. So one cubit can be two states,
Speaker 1: Two cubits can be four states. Three cubits can be
Speaker 1: eight states. That means there's eight possible values of the
Speaker 1: three cubits, and I'll give them to you right now
Speaker 1: so you can see that I'm right. You've got zero zero, zero, zero, zero,
Speaker 1: one zero, one zero zero, one one one zero zero,
Speaker 1: one zero, one one, one zero, and one one one,
Speaker 1: So eight potential values. Every time you had a cubit
Speaker 1: you have to you have you end up going with
Speaker 1: two to the power of number of cubits you have
Speaker 1: for potential states. So in other words, with three cubits
Speaker 1: you have two to the power of three. That's eight.
Speaker 1: That's how many potential states you could represent. Right now.
Speaker 1: I B. M has a prototype quantum computer that has
Speaker 1: fifty cubits, and that's a prototype. It's not one that's
Speaker 1: rolled out to for anyone to in general to use,
Speaker 1: but they do have it. So that means you can
Speaker 1: represent two to the fiftieth power in states. So that's
Speaker 1: in case you wanted to know. If you knock that
Speaker 1: out too, to the fiftieth power, that is one quadrillion,
Speaker 1: one hundred twenty five trillion, eight hundred ninety nine billion,
Speaker 1: nine hundred six million, eight hundred forty two thousand, six
Speaker 1: hundred twenty four states. It's a lot of potential states.
Speaker 1: And if that's not enough, if you build a sixty
Speaker 1: cubit computer, you just add ten more cubits, you'd have
Speaker 1: one capable of representing one thousand quadrillion states. It's insane.
Speaker 1: In IBM announced it would make a five cubit computer
Speaker 1: available for people to run calculations and experiments on using
Speaker 1: a cloud based interface. Uh. This is necessary because in
Speaker 1: order to create a quantum computer, you have to take
Speaker 1: a really special, extreme precautions to not just create the
Speaker 1: quantum state, but to preserve it. So how special am
Speaker 1: I talking about? Well, the quantum computers that IBM uses
Speaker 1: are cooled to ten millie kelvin in other words, or
Speaker 1: fifteen millie kelvin, depending upon which source I was looking at.
Speaker 1: Both of them came from IBM, but once at fifteen
Speaker 1: and one said ten millie kelvin is incredibly tiny. You're
Speaker 1: talking about a fraction above absolute zero. Absolute zero is
Speaker 1: the point at which there is no molecular movement, which
Speaker 1: is quote unquote colder than space itself. To achieve this,
Speaker 1: IBM has to use liquid nitrogen to get the computer
Speaker 1: down to a low temperature, and then liquid helium to
Speaker 1: get it to an even more insanely low temperature. And
Speaker 1: what did IBM used to create the cubits? Did they
Speaker 1: use electrons or photons? Nope, they created what they called
Speaker 1: artificial atoms. They used a superconducting Josephson junction. What. Well,
Speaker 1: it's a superconductor that's coupled to a second superconductor over
Speaker 1: a weak link. And I really wish I could go
Speaker 1: into more detail and explain how this works, but frankly,
Speaker 1: it goes well beyond my understanding, and I feel I
Speaker 1: would need to take a college course to get a
Speaker 1: handle on it in order to explain it properly. So
Speaker 1: I'm not going to try because I'm afraid that if
Speaker 1: I did, I would mis explain it to the point
Speaker 1: where I would just be giving completely wrong information. Suffice
Speaker 1: to say, it's a man made component on a microchip
Speaker 1: that's paired with a microwave resonator. The microwave resonator is
Speaker 1: what is used to communicate with the cubits, and it's
Speaker 1: housed in this crazy looking metal contraption that reminds me
Speaker 1: of a super fancy espresso machine, and that in turn
Speaker 1: is encased in a cylinder that is a giant refrigerator
Speaker 1: to cool it down to these insane low temperatures. Now,
Speaker 1: to make it more complicated, if you were to interfere
Speaker 1: with this computer in any way, and that could be
Speaker 1: electromagnetic interference, it could be heat, it could be motion.
Speaker 1: It's very sensitive, you would cause the quantum states to
Speaker 1: collapse and decohere, which would turn your expensive quantum computer
Speaker 1: into a pretty pathetic excuse for a classical computer until
Speaker 1: you can repair the quantum states, and typically you have
Speaker 1: a very short amount of time on the order of
Speaker 1: milliseconds to complete your operations before either the error rates
Speaker 1: get out of hand, which makes all the results look
Speaker 1: like they were truly random as opposed to probabilistic, or
Speaker 1: the system itself will collapse. The impracticalities of quantum computing
Speaker 1: mean that only a few select organizations are ever likely
Speaker 1: going to have an actual quantum computer. They're just too
Speaker 1: complicated and too sensitive for the general person to have. However,
Speaker 1: if they follow the the methodology of IBM and make
Speaker 1: it available for other people to use through cloud based
Speaker 1: systems where you know you're able to control the quantum computer,
Speaker 1: you're just doing it remotely through an interface that they've designed,
Speaker 1: then they can make quantum computing more accessible. You won't
Speaker 1: own one, but you will be able to access one.
Speaker 1: It's pretty crazy, really. Uh. The IBM methodology is called
Speaker 1: IBM Q. You can actually go and join that program.
Speaker 1: If you want to learn how to program quantum computers,
Speaker 1: you can use IBM Q to do it. They have
Speaker 1: guides on how to program. They have a very simple interface, UH,
Speaker 1: so that you can learn how to program on the
Speaker 1: five cubit machine. They also have access to a sixteen
Speaker 1: cubit machine through this system, so you can start designing
Speaker 1: uh programs to run on a quantum computer. If you
Speaker 1: want to check that out. It's frankly, it's beyond my
Speaker 1: capabilities to actually do this, at least with my current
Speaker 1: level of understanding. But then I'm not really a programmer.
Speaker 1: So the program is out there, should definitely take a
Speaker 1: look into it and see if you're interested. Well, in
Speaker 1: ten you could have access to a live cubit computer
Speaker 1: that would give you the potential to have a superposition
Speaker 1: of thirty two states simultaneously. So when you encode a
Speaker 1: problem onto a quantum machine, what is actually happening. You're
Speaker 1: applying a phase to each of those states. So you
Speaker 1: can think of the phase like a wave. Some phases
Speaker 1: will amplify others and some phases will cancel out others.
Speaker 1: This is just like a wave and how waves work
Speaker 1: when they encounter other waves. So, for example, if you
Speaker 1: have noise canceling headphones, those work by producing sound waves
Speaker 1: that are out of phase with the sounds you're surrounded by.
Speaker 1: So if you have a perfect tone of a certain frequency,
Speaker 1: the sound wave visualization will be one of those lovely
Speaker 1: curves has a regular hills and valleys that rise and
Speaker 1: fall at a perfect curve and in a particular frequency
Speaker 1: that's depended upon whatever the tone is, and it'll look gorgeous. Now,
Speaker 1: if you were to produce a second tone where the
Speaker 1: sound wave has its peak at the same point on
Speaker 1: that wave form that the first wave the first tone
Speaker 1: has its valley. So the highest point on your second
Speaker 1: tone matches with the lowest point on your first tone,
Speaker 1: and vice versa, and they are exactly the same amplitude
Speaker 1: and same frequency. They'll cancel each other out. It will
Speaker 1: be as if you can't there's no noise at all,
Speaker 1: because these two sound waves cancel each other out, and
Speaker 1: it's it's as if there's nothing there. That's how noise
Speaker 1: cancelation headphones work. They have a microphone that takes an
Speaker 1: all incoming sound and then they generate a sound in
Speaker 1: the headphones that is out of phase with the sounds
Speaker 1: that are around you. They cancel it out. It's not
Speaker 1: just muffling sound, it's canceling it by generating this out
Speaker 1: of phase sound wave. It's kind of interesting, Well, quantum
Speaker 1: computers are doing the same sort of thing with there
Speaker 1: the various represented states of the quantum state, like all
Speaker 1: those potential combinations of zeros and ones. So the problem
Speaker 1: you encode onto the cubits applies those phases, and as
Speaker 1: long as you have enough cubits to handle the problem
Speaker 1: you're trying to solve. Everything should work out pretty well.
Speaker 1: Some answers get amplified, some get canceled out, and you'll
Speaker 1: arrive it's your solution, or it's a little more accurate
Speaker 1: to say you'll arrive at a probabilistic distribution of solutions.
Speaker 1: So better solutions will occupy a higher percentage of probability
Speaker 1: than not so good answers. So you can think of
Speaker 1: it as like each answers on a pillar, and the
Speaker 1: most likely answer is on the highest pillar and the
Speaker 1: least likely answer is on the lowest pillar. Does that
Speaker 1: mean that the answer is always the right answer is
Speaker 1: always going to be the one that's on the highest pillar. No,
Speaker 1: that's not how probability works. It's likely, but it's not
Speaker 1: always going to happen. That's where you can run into errors. So,
Speaker 1: like I said, you're gonna have to look at those
Speaker 1: error rates, quantum engineers are gonna have to keep a
Speaker 1: close eye on error rates. If we are able to
Speaker 1: build more powerful quantum computers, that's great, but if error
Speaker 1: rates are high, we can't trust the results we get.
Speaker 1: And the more operations you try to run in sequence,
Speaker 1: the more opportunities you have for error rates to have
Speaker 1: an effect on your results, until again, your probabilistic results
Speaker 1: will start to look more like randomized data. Now I've
Speaker 1: talked a bit about the sorts of problems quantum computers
Speaker 1: can tackle the theoretical problems, but that's mostly in the
Speaker 1: thought experiment world. What could quantum computers do in the
Speaker 1: real world. Well, i'll tell you right after we come
Speaker 1: back from this break for our sponsor. All Right, so
Speaker 1: you got your quantum computer. What the heck are you
Speaker 1: gonna do with it? Well, one thing you could do
Speaker 1: is follow Richard Feynman's suggestion back in the early eighties
Speaker 1: and use your quantum computer to simulate the evolution of
Speaker 1: quantum states. Actually, simulations in general would be a really
Speaker 1: useful application of quantum computers, because, unlike a classical computer,
Speaker 1: a quantum computer with a sufficient number of cubits remains
Speaker 1: undaunted by the exponential difficulties those simulations pose. So take
Speaker 1: chemistry for example. If you want to simulate chemistry down
Speaker 1: to the molecular level and you want to work with
Speaker 1: long chain polymers, that gets really complicated very quickly because
Speaker 1: you've got all these interactions going on at the sub
Speaker 1: atomic level that you have to account for. So electrons,
Speaker 1: for example, are negatively charged, and they repel one another
Speaker 1: because like charge repels like, but they also will be
Speaker 1: attracted to the nuclei of the atoms because the nuclei
Speaker 1: contained protons those have a positive charge and opposite charges attract.
Speaker 1: So you've got these really complex interactions that are going
Speaker 1: on at the molecular level, and it gets even more
Speaker 1: complicated every time you add another atom to the molecule chain.
Speaker 1: And it's that complexity that makes simulating molecules such a
Speaker 1: huge challenge for classical computers. In a presentation at think,
Speaker 1: an IBM researcher named Talia Gershon, who was part of
Speaker 1: the Science slam as well, talked about iron sulfide and
Speaker 1: modeling an iron sulfide molecule, and she said that the
Speaker 1: largest iron sulfide molecule that the most powerful classical computers
Speaker 1: can simulate right now would be a molecule that had
Speaker 1: four iron atoms and four sulfur atoms. That would be
Speaker 1: a very small iron sulfide molecule. But you couldn't go
Speaker 1: bigger than that because the classical computers just couldn't handle
Speaker 1: all of those sub atomic interactions accurately. Uh, that's a
Speaker 1: severe limitation. If we could shed that limitation, we could
Speaker 1: run simulations and all sorts of chemical compounds, and we
Speaker 1: could potentially learn the properties of those compounds and think
Speaker 1: of potential uses for those compounds. This could revolutionize multiple industries,
Speaker 1: a material science, a medicine, those two. In particular chemistry
Speaker 1: in general, the chemists could simulate the properties of a
Speaker 1: theoretical drug long before ever moving to clinical trials, perhaps
Speaker 1: eliminating false leads and saving vast amounts of time and efforts. So,
Speaker 1: in other words, you could, based upon your knowledge, create
Speaker 1: simulations of various molecules to see how they would play
Speaker 1: out in various scenarios, and anything that looked promising, you
Speaker 1: could then go forth and try and synthesize and move
Speaker 1: forward with clinical trials or at least you know the
Speaker 1: earliest stages of testing. That way and narrow down the
Speaker 1: limitless possibilities much faster and uh potentially make much more
Speaker 1: effective medicine. Arvin Krishna, who's an s VP senior vice
Speaker 1: president over at IBM, also mentioned that quantum computing could
Speaker 1: be used for financial risk analysis. I imagine it would
Speaker 1: also be good for running other types of simulations, ones
Speaker 1: that classically are really difficult to manage. For example, it
Speaker 1: could be really useful for weather forecasting. That's similar to
Speaker 1: the traveling salesman problem I mentioned earlier. Quantum computers could
Speaker 1: also be used to help plot out the most ideal
Speaker 1: travel routes, not just for a single vehicle, but a
Speaker 1: fleet of them. That would be useful in multiple industries,
Speaker 1: from transportation to shipping. More efficient travel means fewer delays,
Speaker 1: which in turn means cost savings, not to mention fuel conservation.
Speaker 1: So you might first think that shaving some miles or
Speaker 1: minutes off of travel is a trivial use of so
Speaker 1: powerful a computing device, But when you start to think
Speaker 1: of the ripple effects the things that that implies, you
Speaker 1: start to see the bigger picture. Now I mentioned weather
Speaker 1: forecasting that is a really challenging science. Actually, there are
Speaker 1: a lot of factors that impact whether you may have
Speaker 1: heard my podcast about weather forecasting and how insanely difficult
Speaker 1: it is. You've got these big components of weather that
Speaker 1: we're all familiar with, things like temperature, humidity, air pressure,
Speaker 1: that kind of thing. But there are also other factors
Speaker 1: that influence weather patterns, like geography. The topography of the
Speaker 1: area you live in affects weather, how it plays out,
Speaker 1: the presence of air pollution. Other variables can all affect weather,
Speaker 1: and there's so many different variables that shape the weather,
Speaker 1: and those variables can have an effect on other variables
Speaker 1: that in turn can have an effect on other variables.
Speaker 1: In other words, there becomes the sort of domino effect
Speaker 1: that can happen in ways that are very difficult to predict.
Speaker 1: Simulating the weather with enough data points to ensure precision
Speaker 1: is really difficult. Classical computers struggle with this. We use
Speaker 1: a lot of supercomputers to crunch the numbers now, and
Speaker 1: even then we have to make tough choices. We have
Speaker 1: to make allowances for this. So, for example, you could
Speaker 1: create a weather model that has a really high resolution,
Speaker 1: but it covers a relatively small region. Or you can
Speaker 1: have a weather model that covers a much large arger
Speaker 1: region but has much lower resolution, so you have lower
Speaker 1: amounts of accuracy within that larger model. Uh you also
Speaker 1: can have models that predict weather out further into the
Speaker 1: future than others, but again with a compromise to either
Speaker 1: the size or the resolution or both, So quantum computers
Speaker 1: might allow for unprecedented scaling of these weather models, perhaps
Speaker 1: one day even leading us to the gold mine, which
Speaker 1: would be a global weather model that has high resolution
Speaker 1: for any point along the Earth, or at least any
Speaker 1: point in those regions where we have enough reliable weather
Speaker 1: sensors to provide the data points necessary to create the
Speaker 1: simulation in the first place. Now, one thing that I
Speaker 1: mentioned earlier that quantum computers would definitely change is how
Speaker 1: we protect information. Using Shore's algorithm and a quantum computer
Speaker 1: with a sufficient number of cubits, you could determine the
Speaker 1: prime number factors of any large number relatively quickly, which
Speaker 1: puts all of our encryption at risk. Well not all
Speaker 1: of it, but but but the vast majority of our
Speaker 1: of the way we encrypt things would be at risk.
Speaker 1: And I'm not just talking encryption for stuff like email
Speaker 1: or online shopping. Credit Card transactions would be at risk.
Speaker 1: They rely on large number factoring, so that would be
Speaker 1: a problem, as would numerous otherwise secure data exchanges. They
Speaker 1: would also be at risk. All the secrets would no
Speaker 1: longer be secret, so this would be like someone creating
Speaker 1: the perfect skeleton key that fits all the locks in
Speaker 1: the world, and at that point, there's not really a
Speaker 1: reason to use a lock because you already know someone's
Speaker 1: out there with a key that's going to open it.
Speaker 1: So you've got to figure out a different way to
Speaker 1: lock stuff. So rather than give up, it just means
Speaker 1: we have to come up with a post quantum encryption strategy. Now.
Speaker 1: I mentioned that in the episodes are recorded about the
Speaker 1: IBM Science Slam to Chilia, Boscuini mentioned a lattice based
Speaker 1: cryptography strategy, which would use a plotted point within a
Speaker 1: realm of dimensions multiple dimensions as many as like a
Speaker 1: hundred dimensions as an alternative to factoring large numbers. I
Speaker 1: can only sort of pretend like I understand what she's
Speaker 1: talking about, because it goes way over my head. But
Speaker 1: according to Buscini, this could pose a problem so difficult
Speaker 1: that even a quantum computer might have trouble working it
Speaker 1: out and thus end up securing our data. We would
Speaker 1: just be switching our encryption strategies. So quantum computers do
Speaker 1: have the potential to make a tremendous impact on our world.
Speaker 1: Though it is important again to note that they aren't
Speaker 1: going to replace classical computers for all tasks. Quantum computers
Speaker 1: are ideally suited for a subset of computational problems, including
Speaker 1: ones that are really hard for classical computers to tackle.
Speaker 1: But there are other tasks that classical computers will be
Speaker 1: just as good at, or even better at, than quantum computers.
Speaker 1: So I don't mean to suggest that in twenty years
Speaker 1: everyone's going to have a quantum computer sitting on their
Speaker 1: work desk, unless you have to work in a quantum
Speaker 1: computer laboratory, in which case you might because you might
Speaker 1: have to do repairs or something. Anyway, that wraps up
Speaker 1: this quantum computing one oh one episode. I hope you
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