Quantum Computing 101

IBM does this big conference. It's sort of a an amalgamation, a gloming on to several different smaller conferences that IBM has been holding for several years. They kind of pushed them all together and turned it into a giant, mega conference. And I emphasized giant. I mean there are tens of

thousands of people attending this conference. It feels like more than that when you're trying to get through the Mandalay Bay Conference Center, because holy cats, lots of executives, a lot of blazers, a lot of blazers out there, folks. I gotta watch my what I say because pretty much everybody in there is a giant stakeholder in some big business or another. And chances are if I if I say something rude, I've just insulted a millionaire, and I'm

not in that tax bracket. But let's talk a little bit about one of the topics that got a lot of coverage here at IBM think two thousand and eighteen, and that is quantum computing. It's a big deal, and that's because quantum computers are beginning to emerge from the realm of experimental science into practical applications. In fact, you could argue it's already there and has been for a couple of years, but it's still relatively new and I

think very mysterious for a lot of people. And I've talked about a little bit in previous episodes, but I really wanted to dedicate a an entire episode kind of quantum computing one oh one and really talk about the principles behind it, the history behind it, what it might be used for, why it's such a big deal in the first place. So this is our full episode on the topic, and I'm going to reference some of the things I've learned while I've been at this conference. Let's

do what I love to do. This is like a good old traditional episode of tech stuff. We're gonna dive into the history of quantum computing and quantum mechanics and quantum theory. So this all begins before the computer age. We have to discuss the history of quantum mechanics itself. Now, I'm not going to go into exhaustive detail, because to do that would require an entire podcast series, not just an episode, but a series of episodes to kind of

talk about all of the developments in quantum mechanics. And not only that, but it's a messy history filled with a lot of scientific debate and our humans and uh experiments and counter experiments, thought experiments, aim calling. There was some adultery in there too. I mean, it's it reads like a soap opera at times, and and like I said, it's just it's so deep and dense that to really cover it would require multiple episodes. So this is kind of like a an introductory a bird's eye view of

the history of quantum mechanics. So let's talk about the developments around the turn of the last century, the twentieth century. In nineteen hundred, it only been a couple of years and scientists had even discovered the existence of electrons at that point. No one was even sure in nineteen hundred if electrons were even part of the atom. They didn't know our electrons actually a component of atoms or are they something else? So do they coexist with atoms but

they're not bound to atoms? They weren't sure. In nine hundred, there was general agreement that atoms were in fact a kind of a fundamental particle, but beyond that, there wasn't a whole lot of agreement on them. No one was really sure what made the atoms of one element different from another, and therefore they weren't sure why elements were different in the first place. They could identify elements, they could identify the qualities of elements, but they couldn't explain

why they were different from each other. Well, in there was a smarty pants physicist, Max Planck, who was trying to work out some reasons behind a curious observation that people had noticed for centuries but didn't They couldn't explain it. And that was the nature of heat radiation and the light that it can produce. So let's say that you're a blacksmith and you've got some iron, and you put

in the forge and you heat the forge up. Eventually that iron, as it grows hot, will begin to glow, and it first will kind of glow red, and then that red will get brighter and brighter, kind of turned into an orange. And if it gets hot enough, it'll glow white. If you could get it hot enough before it melted, you could make it even glow blue. These different colors would represent different energy states, but no one

knew that at the time. No one was able to explain why iron would change color as it got hotter. So Plank was working on this problem. He was trying to figure out, well, what is what explains us, or what at least describes this, and eventually came up with a formula that fit the observations he made in experiments. He had figured out a formula that that seemed to fit, But why did it fit? Why did that formula describe what was happening? He couldn't tell. He wasn't sure, No

one was sure at first. He kept working on it, so eventually Plank figured out that the atoms could apparently only take on certain quantities of energy, So it could take a certain amount of energy, and then any above that it could not accept until it got to the next specific allowable energy level. So you could think of it as steps of energy. You could accept a certain amount, and then you could step up and accept a new larger amount, but anything in between those two steps didn't

fit the formula. And this was very curious. It wasn't something that was continuous, right, This idea of steps of energy levels was really perplexing at the time. You might think of it more like a continuous string, but it wasn't. It was this broken series of steps. So this really got people wondering what the heck was going on. Um, how could materials take on specific increments of energy rather than any arbitrary amount. Planck didn't know. He didn't know

why it was happening. He only knew that it was happening based upon his observations, and that the explanation he had fit what he observed. He just couldn't explain why it worked. He announced his findings on December four, nineteen hundred. Now some people trace that as the origin of the study of quantum mechanics, though of course at that time it wasn't yet called quantum mechanics. It did, however, formulate the foundation of what some would refer to as old

quantum theory. Now that theory stated that these acceptable energy increments were specific quantities, right quantities of energy, and that any phenomena that would only accept certain values of a physical quantity fell into this category, and it typically was stuff on the atomic scale, tiny tiny scale, not classical scale, which seemed to follow the rules of classical physics. These things didn't seem to follow the rules of classical physics.

The rules were different for some reason. So scientists said that the values of this physical quantity of energy, uh, we're said to be quantized. That's the values of this energy is quantized. It was generally believed that you'd have to do lots of experiments and make lots of observations to kind of suss out the rules for that quantization or perhaps even uncover a set of universal rules that

would work in all situations. So there were scientists like Albert Einstein who seized on this notion, and they began to apply this idea to other areas of study. He, for example, Einstein, that is, proposed that the total energy of a beam of light was quantized. Several other big

thinkers were looking into similar fields. But then the First World War broke out and that really slowed down progress in the sciences because a lot of the leading scientists at the time we're all in Europe, so obviously Europe being heavily affected by World War One meant that a lot of that work was put on hold. However, at the war's conclusion, things picked up again at that stage after World War One, but before World War Two, you had scientists like Max Bourne and Werner Heisenberg who were

extending our understanding of the quantized world. Now Born and Heisenberg, along with Pascal Jordan's, wrote an extremely complicated but consistent theory of quantum mechanics. Meanwhile, you had another smarty pants Irwin Schrodinger or Irvin if you prefer, that would be of Schrodinger's cat fame. He was working on his own theory to describe quantum mechanics, and for a while, those two theories were the focus of a pretty nasty war within physics in which both sides were kind of disparaging

the ideas of the other side. And essentially one group is saying, you guys are full of it. My theory describes what's actually happening Here's is a mess, and the other side saying, nah, our theory is far more descriptive of what is actually going on your theory is nonsensical. But then in Schrodinger and Carl Eckert, who was working completely independently of Schrodinger, both proved that these two seemingly different approaches were actually describing the same thing. They were

just doing it from completely different points of reference. So on the surface they superficially seemed like they were at odds with one another, but underneath that it turned out they were. They were in alignment. As one book I read on the subject said, it's like comparing how you

add Arabic numerals to how you add Roman numerals. The two processes look very different from each other, but if you do them each correctly for the same two values, you'll always arrive at the same answer, no matter what method you use. Now that's not to say that everything was smooth sailing from that point forward. Many scientists had problems with aspects of quantum mechanics, such as it's probabilistic nature. That is, much of quantum mechanics concerns itself with probabilities

rather than certainties. In fact, lots of things and quantum mechanics become inherently uncertain the more you try and nail it down, the more uncertain other elements will become. That's partly what Heisenberg's uncertainty principle states. Heisenberg was specifically talking about a quantum particles position versus its momentum. Heisenberg stated that the more precisely you measure one of those two values,

the less you can know about the other one. So if you measure a quantum particles position with great precision, you won't know very much about its momentum, and vice versa. And that this is just a fundamental feature of our universe, so it's tough if you don't like it. The probabilistic side of a quantum mechanics is tied also to measurement. This was a central focus of a debate between two

great physicists, Neil's Bore and of course Albert Einstein. Einstein was not keen on the probabilistic nature of quantum theory. Uh He has often been attributed the phrase God does not play dice with the universe, although that is a paraphrasing of what he said. And then Niel's Bore was paraphrases saying God doesn't care what you think he's doing. Um so that was kind of the back and forth.

Although both of those statements were paraphrase, neither of those were actually what the scientists were saying, just kind of was a an interpretation of what they said. Quantum mechanics experiments wouldn't really produce a definite solution. So we're used to things like calculations coming up with a specific answer. Right even let's just take simple arithmetic. If you say two plus two equals for then you know you realize that, all right, well, that that makes sense to pless two

equals for that's a that's a certain value. It's a definite answer. Whereas with quantum mechanics you would get results that would be listed in terms of probabilities, not in terms of here is the answer. You would get a probabilistic distribution of possible values. So that means every single value you would get would get assigned a probability, and if you were to measure a quantum state, that would actually cause it to collapse into one of those probable

values that it possibly could have been. This is also related to that concept of quantum tunneling I mentioned earlier this week. The idea of an electron could potentially inhabit one of any positions that are within a certain field, and because there's that probability, it means that sometimes the

electron will inhabit that position. And if that position happens to be on the other side of a barrier, just because the zone the electron could exist in happens to overlap that barrier, then that means sometimes the electron is on the other side of the barrier, even though it did not physically pass through the barrier. It's it's part of the weird nature of quantum mechanics and probabilistic distribution. Again,

it's not a certainty, it's a probability. Another concept of quantum theory that ends up being very important with quantum computers is that of superposition. This is a pretty tricky concept, as it is so counterintuitive that it prompted Schrodinger to create what he thought was an absolutely bonkers example so that he could illustrate how whacka doodle this idea was on the macro scale. But today that example is widely known, or at least it's known by name. That would be

Schrodinger's cat. So what is superposition and what the heck was that famous thought experiment. Well, superposition refers to quantum particles as inhabiting all sable states simultaneously. So a state is really just a feature, something that the quantum particle possesses. So let's take electron spin as an example. All right, So electrons can spin in different directions, and for this particular example, let's just talk about spinning up or spinning down.

So electron can spin up or it can spin down. According to some versions of quantum theory and its quantum state, that electron can be said to be both spinning up and down simultaneously. It's both states at the same time. It inhabits them while it's in this quantum state. But when you measure the electrons spin, when you observe it, the quantum state collapses down into one of the two

possible states. So you're never going to observe an electron spinning up and down simultaneously because the act of observing changes that which is observed at the quantum level. This is the argument some people make that you know, measuring doesn't matter because if you measure, you have changed the thing that you were measuring. Now, that is true on the quantum scale, but as you move up to the classical scale, it's not really something you need to concern

yourself with. So, uh, you can't confuse quantum mechanics with classical mechanics. It they are rules that define two different universes, really the quantum level and then the classical level. So it's not like classical physics need to be thrown out the door. They still apply just two things that are on the classical scale. When you get to the quantum scale, that's when you have to look at quantum mechanics, and that's when you start seeing these seemingly weird and counterintuitive rules.

And I say seemingly because the only reason they seem weird to us is because we cannot observe them directly. We don't exist on the quantum level um and in the way that we can perceive it. We can just work out the math and figure it out, and then we can design experiments, and through those experiments we can we can actually look for evidence that supports these theories.

And in fact, that has happened over time. People have designed experiments to test these ideas and found through the results of the experiments that those ideas seemed worthy, they seemed valuable, and and real. Now, Schrodinger's cat is a way of exaggerating this superposition effect, kind of in an effort to show how crazy it sounds. So here's the thought experiment. Let's say you've got a cat, and you put the cat in a metal case. Inside that case

with the cat is a device that contains a radioactive particle. Now, that radioactive particle could undergo radioactive decay within the next hour, or equally, it could not decay within an hour. So there's an equal chance that it could decay or that it could remain whole within the span of an hour. If the particle does decay, the energy it gives off will cause a glass vial containing a poison to break, and that will release the poison in the cage and

kill the poor kitty cat. The whole experiment is completely sealed away. The cat is unable to interfere with the device, because if you interfere with a quantum state and then it decoheres, the whole experiment falls apart. So you have to have this is a thought experiment anyway, but you have to have it set up in a way so that the cat's not going to interfere with the quantum state. So an hour goes by with the cat inside this

cage and the radioactive element in there as well. And the question you have to ask yourself before you open up the cage is is the cat dead or is it alive? Now? According to the super position theory and Schroedinger's interpretation of that theory, you would have to say that the cat is both alive and dead at the same time. That exists in this quantum state where it

is alive and dead. It is only when you open the cage and you look in and you are essentially measuring the system this way, because you're making an observation that the entire system will collapse into one of the two possible outcomes, And at that point the cat makes the transition into either being perfectly fine or very much an ex kitty cat joining the choir invisible, running up the curtain, kicking the bucket, shuffling off the mortal coil. You get the idea. This is where you get all

those jokes about the cat being half dead. But here's the crazy thing. While Schroedinger's thought experiment did make superposition sound really bonkers, experiments supported the notion of superposition. Now Granted, we're talking about effect on the quantum level, not something that's observable in our macro world. Schrodinger would argue that because the the whole premise of the experiment relied upon a quantum particle, whether it decayed or not, it doesn't

violate this. The consequences of the at quantum event would be on the macro level, but that the actual event itself would still be in the quantum level. Uh. There's some people who dispute that, so it kind of becomes a philosophical argument. But the point is that the experiment started to support this idea of superposition, and it's one of the few, one of a couple of principles of quantum mechanics that makes quantum computing such a potentially powerful

tool and a possible revolution in computing in general. The other big concept in quantum theory that is of particular importance with quantum computers is called entanglement. Now, this is the strong correlation between two quantum particles that link those two particles together, no matter how much physical distance might separate the particles. So you could take two entangled particles, and if you could do it in a way where

you're not disturbing the entanglement. You could move one particle to the other side of the universe from the first particle and they would still remain entangled. Einstein would call this spooky action at a distance, and entangling particles means that these two particles are always going to complement one another in some way. So let's take electrons again. Let's say you entangle to electrons so that their spin is correlated, and if one electron is spinning up, the entangled partner

is always spinning down. This is just one example of a way you could entangle particles so that means no matter how much distance separates these electrons, if electron A is spinning up, then electron B is spinning down. If electron A starts to spin down, then electron B will start to spin up, and he'll do it exactly at the same time. There's like no delay, and this will happen no matter how far apart those electrons are. It seems impossible, and yet that is in fact what seems

to be happening with entanglement. However, once you observe one of those two electrons, then the entanglement is broken and you will know at the moment of observation, the moment of measurement, what that other electron was doing, But you don't know what it's doing anytime after the moment of observation. You can only say, at this precise moment, the other electron, wherever it may be, was doing this particular activity. At that point, the system decoheres, and so it gives you

information but nothing. Some people have argued that this is a way that you could potentially have faster than like communication. Others argue no, because all it does is tell you information that previously existed. The information didn't travel, just your realization of what that information was occurs to you. It's another fine distinction that gets into philosophical arguments, and its outside the scope of this particular podcast, but it is

a fascinating discussion. So together, super position and entanglement are two of the factors that really make quantum computers so potentially revolutionary. And it's weird to say potentially, because today they are actual working Quantum computers just have a somewhat limited scope right now, but they're getting better all the time, and in fact, some of the prototypes are really impressive already before we get to actual quantum computers. There's a

little more history I need to cover. In nineteen seventy three, Alexander Hollevo argued that for any given number of cubits, which are quantum bits, you could not possibly carry more information than that same number of classical bits. So, in other words, if you have eight quantum bits, those eight quantum bits could carry only as much information as a classical bite, bite being eight bits, and of course a bit being a basic unit of information, either a zero

or a one. However, the eight cubits through superposition could represent all possible states of that bite. So it's not carrying more information, it's just carrying Uh. It's hard to hard to put this in a way that makes sense. It's not carrying more information than a bite, it's just carrying every single variation of information that bite could represent. Again, anotherir fine distinction. This gets really fuzzy and wibbly wobbly

timey y me to me. In the early eighties, people begin to theorize about the possibility of quantum computing and talking about how you might use quantum particles to represent bits. So again, like electrons, you could use electrons in their spin And this is a quantum quality that electrons have, and if you were able to put those into a quantum state, you could use the electron spin to represent what would normally be a bit in a classical computer.

That's just one possible example, mind you, because you could use all sorts of different stuff to represent these bits. You could use photons and their polarization if you wanted to, or other quantum particles and other qualities. In Richard Fineman presented a talk in which he lamented the fact that classical computer systems would be incapable of simulating the evolution of a quant um system, because quantum systems would just be far too complicated for a classical computer to do

this in any reasonable time frame. He did, however, hypothesize that if you were able to create a quantum computer, you could potentially simulate the evolution of a quantum state. Theorists began to flesh out what a quantum computer might look like, and how it might operate, and even how

you might try to go about making one. This was, all, however, still within the realm of the theoretical In the mid nineties, and engineer named Peter Shore discovered an algorithm that would really put a fire under the bottoms of quantum computer researchers. His algorithm was a set of rules that a quantum computer could theoretically be able to follow and allow it

to factor large integers much more quickly than a classical computer. Now, the reason this posed both an exciting opportunity and a terrifying realization was because factoring large numbers is what most modern day cryptography is based off of. Uh, you take numbers that are hundreds of digits long, prime numbers specifically, so these are numbers that are only divisible by themselves.

And then you take two of those numbers that are both hundreds of digits long, like five hundred digits long, and they're both prime numbers, and you multiply those two prime numbers together, you get an even larger number that ends up being sort of your public key, your your key that you used to encrypt stuff. But the only way you can decrypt the information is if you know what those two numbers were, those two huge numbers you started off with were, which is hard to determine. It's

really hard. If you're using a classical computer. It would take years or more, depending upon how long the number was to brute force the answer if you're following classical computer science. But Shore's algorithm was a short cut that a quantum computer, not a classical computer. A quantum computer could run and run that same calculation in a fraction of the time. So, in other words, a quantum computer following this algorithm that was discovered by Shore could reverse

the process we use to make all of our data secret. Well, by the late nineties, the first rudimentary quantum computers were being constructed in the laboratories. They were really primitive. They could not run very many operations before they would decohere uh, and then you'd have to start all over again. They were delicate systems. They were consisting of just a couple of quantum bits of processing power. But it was the

beginning of the revolution. So how can quantum computers be so powerful compared to classical computers and exactly what sort of problems would quantum computers be good at solving? Well, i'll tell you about that in just a moment, but first let's take a quick break to thank our sponsor. All right, so let's talk about bits now. As I mentioned, a bit is a basic unit of information and it

is binary, meaning it can have only two states. So we express bits as a zero or a one, and you can think of that as being off or on, or down or up. Just as an electron spin has different states or a photons polarization, so too does a bit machine. Language is made up of strings of bits. A collection of eight bits makes up a bite, and a single bite can represent up to two hundred fifty six different states. I talked about this recently in the

I p V six episode. I did the numbers in an ip V four address or just a regular old IP address. Those are based off octets or bites. Each number in that IP address can have a hypothetical value between zero and two hundred fifty five. I say hypothetical because some numbers are off limits due to the rules of Internet protocol. But if you didn't have those restrictions, each of those four numerals in that address could have a value between zero and two inclusive. Those would be

the two six potential values of that bite. A classical computer relies on these bits. It's the form of information the processor takes in and the form it spits back out again. The information does get translated into formats where humans can find useful or initiate some action that is

useful to us in some way. Humans have made a series of computer programming languages, starting with assembly code or a similar code really, which is just a step above binary, up to high level programming languages that abstract those zeros and ones so that we can structure programs in a way that's more natural for us to understand. It's still it can look like complete gibberish to you if you don't know computer languages, but in fact it is far

easier to read than just zeros and ones. So it's hard to think of any kind of information just in binary. But in the classical computer, a bit has to be either a zero or a one, it cannot be both, and classical computers will run processes in sequence. So you can speed that up a little bit by using a couple of different strategies. One is just to make more powerful processors that can handle more information and smaller amounts

of time. That will help. You can improve bus speeds, You can improve the speed that a CPU can draw information from memory or put information back in memory. That will help too, but eventually you run up against the upper limits of what we can accomplish with today's technology, and of course that keeps on improving, but you still will run up against those limits. You can use a multiple core processor. Multi core processors are great. You can

even use an array of processors. That's useful if the computer problems you're working on can be split into smaller problems that can be solved in parallel. Not all problems fall into that category, however, and even if your processor isn't the fastest, if you're talking about a parallel problem, multiple core processors might be a better choice than a single powerful core processor. I usually use this particular analogy. Imagine you've got a math test, and the math test

has ten problems on it. You also have a math class and it has eleven students in it. One of the eleven students is a super math genius, and she has an innate sense of math. It's almost spooky. It's like she can visualize mathematics all around her, and she can solve any one problem faster than anyone else in

the class. Just doesn't matter. But the teacher gives the super smarty genius all ten of the math problems on the test, whereas each of the other students in the class each of them, being good at math but not at genius level, gets only one of the ten problems. So student one gets problem one, Student two gets problem too, and so forth. You have ten students working to solve one problem each, and a supermath genius working on all

ten problems. Who's going to finish first? Well, the super genius is going to solve each of her ten problems faster than any of the individual students will finish their respective problems. But chances are the group of ten will finish first because they each only have one problem to work on. They're able to divide and conquer, as it were. And some computational problems are like that. But there are classes of mathematical problems that are too tough even for

the fastest classical computers running scores of processors. There so difficult as to be practically unsolvable. Now I say practically on purpose. It's not that a classical machine can't solve these sorts of problems. They just can't do it in any sort of reasonable amount of time. It could take years or decades or centuries, depending upon the complexity of

the problem. So what kind of problems am I talking about? Well, there's a class of problems around the concept of optimization, and that's a big part of what quantum computers could tackle. These are problems they get very hard to solve, particularly as you add more components to it. Now, I'll give you a very simple example. Let's say you're throwing a big dinner party. You've rented out a swanky joint. You've

got five tables. Each table has seating for ten people, So you've got fifty people on the way to your party, and it's your job to assign seats for each of the people who are coming. However, there's a problem. Not all of your friends are crazy about each other. So let's say you've got a buddy named Sally, and she would absolutely hate to sit next to Jim. Jennifer would love to sit next to Sally, but she definitely doesn't

want to sit next to Sally's cousin, Darryl. But m and Darryl are best friends, so they definitely want to at least sit at the same table, if not next to each other, and so on and so forth. You've got all these different conditions that exist, and you want to find the best possible seating solution to the problem of who sits where in order for you to have a nice, lovely dinner and not have a breakout into a three stooges pie throwing routine. Well, here's the thing.

The problem of sitting just ten people around a table is factorial. There are three point six million possible configurations for ten people to sit at a table. That's just ten at one table. And remember you have five of those tables, and you have numerous rules you want to do your best to follow to ensure that it's a pleasant party and no one's gonna go home with punch and pie spilled all over their outfits. So how do

you solve this problem? Well, a classical computer would choke on this kind of problem because they would have to run every single possible scenario, and then it would have to check the results of all those scenarios against the rules that you had given it, saying all right, well don't put so and so next to so and so, and then it would have to tally up all of those different scenarios, analyze the whole thing, and determine which one out of all the different scenarios that could come out.

And remember there's three point six million per table, that which one is the best. By that time, half your friends have moved away, or had kids, or have become honored ancestors to generations that follow because it just took way too long for this classical computer to work out the problem, and your party was a bust because you never got the invitations out in the first place. Now, another problem in this class is called the traveling salesman problem.

This is a classic problem and it goes like this. Given a list of cities that a salesperson has to visit to do his or her rounds, what is the shortest possible route that the salesperson can follow that will allow them to visit every single city and return home to their point of origin the shortest possible route among all those cities. This one's pretty easy to understand, but it's actually fiendishly difficult to solve, especially as you add

more cities to the problem. So this type of problem is called an MP hard problem, and the more cities you add, the harder it gets. So how could quantum computers do a better job than classical ones with these

sorts of problems? And it comes down to a basic unit of information in the world of quantum computers, The quantum bid or the cubit you know, I mentioned it a couple of times, and a cubit can be placed in superposition, meaning that in its quantum state, it is behaving as if it's both a zero and a one simultaneously. You can also entangle cubits with one another, so that the state of one cubit and it's entangled cubit are

highly correlated. So you could encoded in such a way where you say, if cubit A is a zero, do nothing to cubit B. If cubit A is a one, flip cubit B to one. That would be an example of entanglement. With these properties, it's possible to solve these traditional unsolvable problems in a very short amount of time if you have a quantum computer with a sufficient number of cubits. That's because the cubits in their quantum state can essentially run all possible solutions to a problem simultaneously

rather than sequentially. I'm oversimplifying here, but that's the general principle. And as you add more cubits, your ability to process information grows exponentially. Now, how does that work? Well, if you have a single cubit, but it can potentially be two states at the same time. Because of superposition, that cubit actually represents two states, not one. Remember a bit can only represent one state at a time. If you have two cubits in superposition, that can represent four states

at one time. So does that mean three cubits is going to be six states? No, No, three cubits would be eight states. So one cubit can be two states, Two cubits can be four states. Three cubits can be eight states. That means there's eight possible values of the three cubits, and I'll give them to you right now so you can see that I'm right. You've got zero zero, zero, zero, zero, one zero, one zero zero, one one one zero zero, one zero, one one, one zero, and one one one,

So eight potential values. Every time you had a cubit you have to you have you end up going with two to the power of number of cubits you have for potential states. So in other words, with three cubits you have two to the power of three. That's eight. That's how many potential states you could represent. Right now. I B. M has a prototype quantum computer that has fifty cubits, and that's a prototype. It's not one that's rolled out to for anyone to in general to use,

but they do have it. So that means you can represent two to the fiftieth power in states. So that's in case you wanted to know. If you knock that out too, to the fiftieth power, that is one quadrillion, one hundred twenty five trillion, eight hundred ninety nine billion, nine hundred six million, eight hundred forty two thousand, six hundred twenty four states. It's a lot of potential states. And if that's not enough, if you build a sixty cubit computer, you just add ten more cubits, you'd have

one capable of representing one thousand quadrillion states. It's insane. In IBM announced it would make a five cubit computer available for people to run calculations and experiments on using a cloud based interface. Uh. This is necessary because in order to create a quantum computer, you have to take a really special, extreme precautions to not just create the quantum state, but to preserve it. So how special am

I talking about? Well, the quantum computers that IBM uses are cooled to ten millie kelvin in other words, or fifteen millie kelvin, depending upon which source I was looking at. Both of them came from IBM, but once at fifteen and one said ten millie kelvin is incredibly tiny. You're talking about a fraction above absolute zero. Absolute zero is the point at which there is no molecular movement, which

is quote unquote colder than space itself. To achieve this, IBM has to use liquid nitrogen to get the computer down to a low temperature, and then liquid helium to get it to an even more insanely low temperature. And what did IBM used to create the cubits? Did they use electrons or photons? Nope, they created what they called artificial atoms. They used a superconducting Josephson junction. What. Well, it's a superconductor that's coupled to a second superconductor over

a weak link. And I really wish I could go into more detail and explain how this works, but frankly, it goes well beyond my understanding, and I feel I would need to take a college course to get a handle on it in order to explain it properly. So I'm not going to try because I'm afraid that if I did, I would mis explain it to the point where I would just be giving completely wrong information. Suffice to say, it's a man made component on a microchip

that's paired with a microwave resonator. The microwave resonator is what is used to communicate with the cubits, and it's housed in this crazy looking metal contraption that reminds me of a super fancy espresso machine, and that in turn is encased in a cylinder that is a giant refrigerator

to cool it down to these insane low temperatures. Now, to make it more complicated, if you were to interfere with this computer in any way, and that could be electromagnetic interference, it could be heat, it could be motion.

It's very sensitive, you would cause the quantum states to collapse and decohere, which would turn your expensive quantum computer into a pretty pathetic excuse for a classical computer until you can repair the quantum states, and typically you have a very short amount of time on the order of milliseconds to complete your operations before either the error rates get out of hand, which makes all the results look like they were truly random as opposed to probabilistic, or

the system itself will collapse. The impracticalities of quantum computing mean that only a few select organizations are ever likely going to have an actual quantum computer. They're just too

complicated and too sensitive for the general person to have. However, if they follow the the methodology of IBM and make it available for other people to use through cloud based systems where you know you're able to control the quantum computer, you're just doing it remotely through an interface that they've designed, then they can make quantum computing more accessible. You won't own one, but you will be able to access one.

It's pretty crazy, really. Uh. The IBM methodology is called IBM Q. You can actually go and join that program. If you want to learn how to program quantum computers, you can use IBM Q to do it. They have guides on how to program. They have a very simple interface, UH, so that you can learn how to program on the five cubit machine. They also have access to a sixteen cubit machine through this system, so you can start designing uh programs to run on a quantum computer. If you

want to check that out. It's frankly, it's beyond my capabilities to actually do this, at least with my current level of understanding. But then I'm not really a programmer. So the program is out there, should definitely take a look into it and see if you're interested. Well, in ten you could have access to a live cubit computer that would give you the potential to have a superposition of thirty two states simultaneously. So when you encode a

problem onto a quantum machine, what is actually happening. You're applying a phase to each of those states. So you can think of the phase like a wave. Some phases will amplify others and some phases will cancel out others. This is just like a wave and how waves work when they encounter other waves. So, for example, if you have noise canceling headphones, those work by producing sound waves that are out of phase with the sounds you're surrounded by.

So if you have a perfect tone of a certain frequency, the sound wave visualization will be one of those lovely curves has a regular hills and valleys that rise and fall at a perfect curve and in a particular frequency that's depended upon whatever the tone is, and it'll look gorgeous. Now, if you were to produce a second tone where the sound wave has its peak at the same point on that wave form that the first wave the first tone

has its valley. So the highest point on your second tone matches with the lowest point on your first tone, and vice versa, and they are exactly the same amplitude and same frequency. They'll cancel each other out. It will be as if you can't there's no noise at all, because these two sound waves cancel each other out, and it's it's as if there's nothing there. That's how noise

cancelation headphones work. They have a microphone that takes an all incoming sound and then they generate a sound in the headphones that is out of phase with the sounds that are around you. They cancel it out. It's not just muffling sound, it's canceling it by generating this out of phase sound wave. It's kind of interesting, Well, quantum computers are doing the same sort of thing with there the various represented states of the quantum state, like all

those potential combinations of zeros and ones. So the problem you encode onto the cubits applies those phases, and as long as you have enough cubits to handle the problem you're trying to solve. Everything should work out pretty well. Some answers get amplified, some get canceled out, and you'll arrive it's your solution, or it's a little more accurate to say you'll arrive at a probabilistic distribution of solutions. So better solutions will occupy a higher percentage of probability

than not so good answers. So you can think of it as like each answers on a pillar, and the most likely answer is on the highest pillar and the least likely answer is on the lowest pillar. Does that mean that the answer is always the right answer is always going to be the one that's on the highest pillar. No, that's not how probability works. It's likely, but it's not

always going to happen. That's where you can run into errors. So, like I said, you're gonna have to look at those error rates, quantum engineers are gonna have to keep a close eye on error rates. If we are able to build more powerful quantum computers, that's great, but if error rates are high, we can't trust the results we get.

And the more operations you try to run in sequence, the more opportunities you have for error rates to have an effect on your results, until again, your probabilistic results will start to look more like randomized data. Now I've talked a bit about the sorts of problems quantum computers can tackle the theoretical problems, but that's mostly in the thought experiment world. What could quantum computers do in the real world. Well, i'll tell you right after we come

back from this break for our sponsor. All Right, so you got your quantum computer. What the heck are you gonna do with it? Well, one thing you could do is follow Richard Feynman's suggestion back in the early eighties and use your quantum computer to simulate the evolution of quantum states. Actually, simulations in general would be a really useful application of quantum computers, because, unlike a classical computer, a quantum computer with a sufficient number of cubits remains

undaunted by the exponential difficulties those simulations pose. So take chemistry for example. If you want to simulate chemistry down to the molecular level and you want to work with long chain polymers, that gets really complicated very quickly because you've got all these interactions going on at the sub

atomic level that you have to account for. So electrons, for example, are negatively charged, and they repel one another because like charge repels like, but they also will be attracted to the nuclei of the atoms because the nuclei contained protons those have a positive charge and opposite charges attract. So you've got these really complex interactions that are going on at the molecular level, and it gets even more complicated every time you add another atom to the molecule chain.

And it's that complexity that makes simulating molecules such a huge challenge for classical computers. In a presentation at think, an IBM researcher named Talia Gershon, who was part of the Science slam as well, talked about iron sulfide and modeling an iron sulfide molecule, and she said that the largest iron sulfide molecule that the most powerful classical computers can simulate right now would be a molecule that had four iron atoms and four sulfur atoms. That would be

a very small iron sulfide molecule. But you couldn't go bigger than that because the classical computers just couldn't handle all of those sub atomic interactions accurately. Uh, that's a severe limitation. If we could shed that limitation, we could run simulations and all sorts of chemical compounds, and we could potentially learn the properties of those compounds and think of potential uses for those compounds. This could revolutionize multiple industries,

a material science, a medicine, those two. In particular chemistry in general, the chemists could simulate the properties of a theoretical drug long before ever moving to clinical trials, perhaps

eliminating false leads and saving vast amounts of time and efforts. So, in other words, you could, based upon your knowledge, create simulations of various molecules to see how they would play out in various scenarios, and anything that looked promising, you could then go forth and try and synthesize and move forward with clinical trials or at least you know the earliest stages of testing. That way and narrow down the limitless possibilities much faster and uh potentially make much more

effective medicine. Arvin Krishna, who's an s VP senior vice president over at IBM, also mentioned that quantum computing could be used for financial risk analysis. I imagine it would also be good for running other types of simulations, ones that classically are really difficult to manage. For example, it could be really useful for weather forecasting. That's similar to

the traveling salesman problem I mentioned earlier. Quantum computers could also be used to help plot out the most ideal travel routes, not just for a single vehicle, but a fleet of them. That would be useful in multiple industries, from transportation to shipping. More efficient travel means fewer delays, which in turn means cost savings, not to mention fuel conservation.

So you might first think that shaving some miles or minutes off of travel is a trivial use of so powerful a computing device, But when you start to think of the ripple effects the things that that implies, you start to see the bigger picture. Now I mentioned weather forecasting that is a really challenging science. Actually, there are a lot of factors that impact whether you may have heard my podcast about weather forecasting and how insanely difficult

it is. You've got these big components of weather that we're all familiar with, things like temperature, humidity, air pressure, that kind of thing. But there are also other factors that influence weather patterns, like geography. The topography of the area you live in affects weather, how it plays out,

the presence of air pollution. Other variables can all affect weather, and there's so many different variables that shape the weather, and those variables can have an effect on other variables that in turn can have an effect on other variables. In other words, there becomes the sort of domino effect that can happen in ways that are very difficult to predict. Simulating the weather with enough data points to ensure precision

is really difficult. Classical computers struggle with this. We use a lot of supercomputers to crunch the numbers now, and even then we have to make tough choices. We have to make allowances for this. So, for example, you could create a weather model that has a really high resolution, but it covers a relatively small region. Or you can have a weather model that covers a much large arger region but has much lower resolution, so you have lower

amounts of accuracy within that larger model. Uh you also can have models that predict weather out further into the future than others, but again with a compromise to either the size or the resolution or both, So quantum computers might allow for unprecedented scaling of these weather models, perhaps one day even leading us to the gold mine, which would be a global weather model that has high resolution for any point along the Earth, or at least any

point in those regions where we have enough reliable weather sensors to provide the data points necessary to create the simulation in the first place. Now, one thing that I mentioned earlier that quantum computers would definitely change is how we protect information. Using Shore's algorithm and a quantum computer with a sufficient number of cubits, you could determine the prime number factors of any large number relatively quickly, which

puts all of our encryption at risk. Well not all of it, but but but the vast majority of our of the way we encrypt things would be at risk. And I'm not just talking encryption for stuff like email or online shopping. Credit Card transactions would be at risk. They rely on large number factoring, so that would be a problem, as would numerous otherwise secure data exchanges. They

would also be at risk. All the secrets would no longer be secret, so this would be like someone creating the perfect skeleton key that fits all the locks in the world, and at that point, there's not really a reason to use a lock because you already know someone's out there with a key that's going to open it. So you've got to figure out a different way to lock stuff. So rather than give up, it just means we have to come up with a post quantum encryption strategy. Now.

I mentioned that in the episodes are recorded about the IBM Science Slam to Chilia, Boscuini mentioned a lattice based cryptography strategy, which would use a plotted point within a realm of dimensions multiple dimensions as many as like a hundred dimensions as an alternative to factoring large numbers. I can only sort of pretend like I understand what she's

talking about, because it goes way over my head. But according to Buscini, this could pose a problem so difficult that even a quantum computer might have trouble working it out and thus end up securing our data. We would just be switching our encryption strategies. So quantum computers do have the potential to make a tremendous impact on our world. Though it is important again to note that they aren't

going to replace classical computers for all tasks. Quantum computers are ideally suited for a subset of computational problems, including ones that are really hard for classical computers to tackle. But there are other tasks that classical computers will be just as good at, or even better at, than quantum computers.

So I don't mean to suggest that in twenty years everyone's going to have a quantum computer sitting on their work desk, unless you have to work in a quantum computer laboratory, in which case you might because you might have to do repairs or something. Anyway, that wraps up this quantum computing one oh one episode. I hope you guys enjoyed it. If you have any suggestions for future episodes of tech Stuff, make sure you write me and

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