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  • We talked a bit about the hardware, you know, people are working on the hardware of quantum computing, yep

  • What about software? where do you start thinking about that?

  • Writing software for a quantum computer

  • In my opinion is actually not very very different from how we write software for just a normal computer

  • and we think about

  • software in terms of being able to write down instructions

  • for the computer and the computer executing these instructions changing some internal state when I write instructions for

  • any type of computer whether it be like a modern MacBook Pro or an old PDP-11

  • In both cases in the end, we have an assembly code that gets executed that's changing the memory the disk

  • The registers in your CPU and so on and it's not different with a quantum computer

  • It's just like the question is what are we changing?

  • And how do we change them? We can really describe these things

  • in quite simple terms, if we were to do this in with sort of full textbook honesty, we would discuss things like

  • finite dimensional vector spaces and in Hilbert spaces and

  • Linear operators and unitary maps and all that stuff and all that stuff is very very important

  • If if you're actually sitting down writing a program but to get an understanding of it

  • I think we can do away with it. And actually just think about things in terms of simple probabilities. So the idea of a Qubit

  • So Qubit is a Bit in a quantom computer

  • Yep it is. Yeah. It's sort of the fundamental building block. It's like a it's like a bit and a regular computer

  • The way I think of it is it's a resource in the computer. It's a resource that you can use to perform a computation

  • So a qubit to me is anything it's sort of abstract. But anything that has two states of being and

  • Some possibility or probability of those states. So for instance we can think about

  • Photons and their polarization a photon can be sort of polarized left and right or it can be polarized up and down

  • But if we're not looking then maybe it's it's possibly in one or the other. Maybe it's 50%

  • moving and traversing left and right and 50%

  • Moving up and down. This is just for photons

  • Turns out there are lots and lots of different ways to construct qubits the qubits that that we work on in the so called field

  • Of superconducting quantum computation. We use a device called a superconducting charge qubit

  • It doesn't matter all the details, but it suffice to say that the two states there

  • Are is their charge or is there no charge in this circuit?

  • And then of course, we have the same thing. It could we could have a probability like maybe there's a 10% chance

  • there's a charge or maybe there's a

  • 90% chance there's a charge. These are called superconducting charge

  • Qubits again, it sounds complicated, but the essence is the same two states

  • but maybe it's in one or the other the interesting thing though is

  • When we have multiple qubits, and this is really where the power of quantum computation happens

  • We can actually think of it sort of simply

  • Diagrammatically that if qubits if I just represent them sort of as a circle here, maybe we have three the idea

  • Is that these qubits can interact this guy can interact with this guy?

  • this guy can interact with this guy and these can interact with one another and every time we add a qubit if we were to

  • Add a circle here. Let's say we added this fourth qubit right here

  • We noticed that every single one of them can now interact with it. We have to draw lots of these lines

  • It turns out that a quantum computer can deal with these additions of qubits in a very efficient fashion

  • But like I said a qubit is something where it has two states

  • So each of these guys can be in two states with a particular probability

  • let's say the two states and our just 0 and 1, our qubit can be 0 or 1 or

  • Possibly something in between. So if I write down these qubits with the probability, let's say we have three qubits here

  • I'll call it Q0

  • Q1 and Q2 what we have is

  • That qubit 0 let's say it's this one right here 1 and 2, well qubit 0 could be in 0 or 1

  • so it has some probability of being in 0

  • Qubit 1 also has some probability of being in 0 and qubit 0 also has some probability being in 0

  • maybe that's a 10% chance

  • But now we have to painstakingly go through a write every one qubit 0 has a probability of being in the 0 state

  • Qubit 1 also 0 and qubit 2 and we can write down all these possibilities

  • Etc, etc until we get to the possibility that all of them are one and each of them has a probability. Maybe this is 5%

  • Maybe this is 7%, maybe this is like 35%, maybe there's a very high percentage chance that all of them are one

  • 8% and so on

  • so every time we add a qubit the size of this table doubles the number of probability percentages doubles and it turns out that

  • these probabilities right here are ultimately what a quantum computer is computing with when we do an

  • Instruction on a quantum computer when we instruct it to do something in the end

  • it's always about changing these probabilities to favor some computation that we're trying to do

  • When we start up a quantum computer, when we flick the switch on

  • it'll start as 100% in this state and everything else will be 0%

  • We start off here, and we know that we start off here. It might be that when we apply a certain operation

  • So for example an operation as is the so called

  • superposition

  • Initialization or we call it Hadamard initialization

  • This is if we have any number of qubits, so starting off in zero, and maybe we want every probability to be equal

  • So if we want to start off here

  • We do something called Hadamard initialization where we do

  • a particular instruction called the Hadamard gate and what happens is this 100% now turns into

  • Let's say we just have one qubit

  • It would be 50% chance in the zero State and 50% chance in the one state if we had two qubits Hadamard

  • initialization would cause us to be 25% chance with both qubits being 0

  • 25% chance

  • 0 1

  • 25% chance being 1 0

  • 25% chance being 1 1 the point is is that this particular instructions one instruction on a quantum computer?

  • Allows us to change these probabilities in a way that we'd like and it might be useful for us to do something like this Hadamard

  • Initialization with all the probabilities being equal because then from here we could do some operation that affects all these qubits and affects all these

  • Probabilities sort of in the same way. But like I said, this is just one possible instruction

  • So there can be an infinite number just like a normal computer it's not that they're an infinite number of instructions

  • It's that they're an infinite of possible things you could do with the instructions

  • So one of the greatest discoveries was that we can arrange these probabilities to be in whatever way that we would like

  • Using five instructions total

  • there are sort of five different ways that we can

  • Permute these things and change them and there are this, one is called a measure instruction

  • measure instruction is pretty important because while we're talking about probabilities

  • we can't actually see these probabilities in the quantum computer

  • They're just in there

  • At some point. We do want to see are they zeros or ones? Like we need to answer that question

  • So the measure instruction will take any list of probabilities and turn it into

  • One of them will change to 100% So each of these is 25% chance. It'll pick one

  • Let's say it's this one right here and measure is gonna make this a hundred percent with the other ones being zero percent

  • That's one way of changing and then incidentally we also get to read out from the clunkier that it was a 1 0

  • That's how we get our answers. That's the only way we get an answer. In fact from the quantum computer

  • The rest of them are just purely ways of changing these probabilities. There are lots of different ways

  • You can have instruction just like norm...

  • Regular computers every single computer that's ever been built or every single CPU that's erver been built always has a different instruction set

  • One possible instruction set is the following we have this Hadamard

  • Is that named after someone?

  • Yes, it's named after I think he was a mathematician

  • He worked on a variety of mathematical subjects and there's a matrix that's actually one divided by square root of 2

  • 1 1 1 negative 1 which is a so-called Hadamard matrix

  • Incidentally this is also used to represent how these probabilities change so Hadamard is one instruction

  • There's another instruction called Phase, again It just has the effect of changing probabilities around in a particular way

  • There's another instruction called the T gate not very

  • Creatively named there's another instruction called the CNOT gate and what's special

  • about the CNOT gate is that all of these right here act on one qubit

  • We say I want to do a measure on qubit 2 or i want to do a T gate on qubit 0

  • It sort of affects only one qubit. It'll affect a lot of probabilities because even though we're operating on one qubit here

  • it accounts for this entire column so it actually changes all the probabilities

  • CNOT is special because we get to choose two qubits

  • This is how we get this

  • interaction between them so CNOT you can say I want to do this on qubit 0 and qubit 2

  • For instance and this itself is an instruction in a sort of quantum assembly code

  • Are these instructions a bit like gates?

  • Yea, so they are like gates but there's an interesting reversal and for example a NAND gate is something like this where data is coming

  • Into the gate and data comes out of the gate

  • what's interesting about these gates and quantum computation is sort of the opposite you have data that's sitting there all these probabilities and

  • You like apply the gate to the Machine and all the probabilities change. So you're not sending data into the gate

  • You're not putting this gate on the chip like a NAND gate for instance

  • Is a gate that you would actually etch into a chip

  • Here it's an instruction that you apply to the computer and it changes these probabilities, but nonetheless

  • They're both different operations that you do on data

  • And how does what you do is code get changed into these operations of instructions

  • Yeah, so like with normal computers you can write these instructions out as assembly code. In fact one example is

  • Say I want the following probabilities

  • I have 0 0 0 1 1 0 1 1 I want this I want it to be 50% chance to be 0 0 or

  • 50% chance to be 1 1 this is called a bell state with a bell state. It's interesting because

  • Theoretically let's suppose I have a qubit. Let's say close I could hold a qubit and

  • Let's say I gave you a qubit

  • it's 50% chance 0 0 or 50% chance 1 1

  • so even if we travelled halfway across the world and I decided to measure my qubit with the measure

  • Instruction and I determine that to 0

  • Then I know for certain that you must be a 0 because there's a zero percent chance that were different, but somehow we determine this

  • It's a 50% chance. It's not that it is already chosen literally is 50% chance. You don't know which one it is

  • So we can write a program to construct a bell state

  • I won't explain exactly why it works this way

  • But you do a Hadamard on my qubit, qubit 0 we do a CNOT on

  • My qubit and your qubit and we're done. This is a quantum program. You can write this out.

  • Now there are higher levels of quantum programming where we don't want to restrict ourselves these instructions

  • Maybe I want to more directly Express the probabilities and how I want them to change

  • They all have to add up to 1 of course. I mean, we have a certain percentage chance

  • It has to be 100% in the end, but maybe I want to shift the probabilities around in a particular way

  • But not in any of the ways that's in our gate set

  • I can write that down that can use something called a quantum

  • compiler a piece of software that that converts what I want into these native instructions that gives me the

  • next level of abstraction in the code

  • we can go all the way up to using a full-blown library for writing this stuff one library that

  • We've constructed is something called "PyQuil"

  • Which allows us to actually write Python code to express quantum computations in Quil is actually this instruction set here

  • Quil stands for quantum instruction language, which lets you write down this assembly code

  • But hey, who came up with this things?

  • is this a commercial thing or is this like...

  • Yeah, yeah so quil was originally this particular type of instruction set

  • Was a paper that I actually wrote a while ago

  • The idea of gates and everything was very well known for many decades previous to that

  • So this is a particular encoding of gates as instructions PyQuil is a library that's open source, it's free

  • There are no restrictions really on using it to construct these programs, but it does allow you to actually connect up to

  • Rigetti Computing's real quantum computers if you if you so pleased to actually run your programs

  • But if you don't want to connect up to the quantum computers and you just want to simulate on your own laptop this can connect

  • Up to a an open source

  • Simulation tool that we have if you just kind of want to see how these probabilities change and so on

  • Not quite you still have to express a quantum computation so a quantum computer doesn't print things out it's

  • it's manipulating these probabilities so at some point you start to express things as

  • Quantum instructions, so definitely if you wanted to make a bell state writing the bell state program you could do that

  • But could you write "Hello world?" No, and this goes back to the fact that the quantum computer is a coprocessor

  • Just like saying you don't write 'Hello World' on your GPU generally

  • You don't express any particular computation and you also don't compile Python Into code on your GPU

  • You write special code within Python that gets run on your GPU and it's the same thing with quantum computing

  • and i know you said there are certain stabilty issues do you get hard answers outta this?

  • So, yeah, so when an answer comes out when you measure you do get definite answer out, however

  • since there's noise what we have to do is write our program get an answer out and store that and actually

  • Rerun it multiple times

  • We have to gather statistics about the answer and it turns out that the more you do this the more

  • Accurate your answers become and that is to account for noise in the quantum computer currently

  • So when we're talking about setting these probabilities, what you want them to be

  • and i understand kind of running operations and gates to do

  • just sounds like you know the answer

  • Yeah, no, you don't know the answer

  • You just show that

  • If you were to do this series of operations that you'd get the right answer on, the answer might be different depending

  • ofcourse the answer will be diffrent depending on the problem that you have

  • so for instance one of the

  • Main questions the quantum computer can solve is the same question that you can get from something called the Fourier

  • Transform where you can find if you have like a sound wave and you want to find what frequencies it has

  • you know that if you run the Fourier transform

  • Proven using mathematics and so on that the answer will be the set of frequencies that make up that sound

  • Likewise here. There's actually something called a quantum Fourier transform where if you run it

  • you know that probabilities will accumulate on the

  • Answers or the frequencies. Maybe that your that your sound wave has

  • So, you know just by the construction of your program that you'll get the correct answer

  • Not that you know the correct answer itself at the front-end, and that's the same with classical computing in my opinion

  • You rarely do you know what the final answer is

  • You just know the computation or the program that you've written will produce the correct answer

  • You need more than one qubit to make this work

  • You can use a qubit

  • if you have a normal qubit your table is gonna look like this you're gonna have prob and

  • Maybe it's like 50% in your states are just 0 and 1

  • Except they're just not very many useful things you can do with a single qubit

  • the power really comes from multiple qubits because you get this nice scaling law where if you have n qubits the number of

  • Probabilities that you get to work with is 2 to the power of n so every single additional qubit you're doubling the number of probabilities that you have to work with

  • How do you know how to do that for a regular computer though

  • Well, I suppose with a regular computer if you're if you're adding numbers together

  • Yep something comes out. Mm-hmm. It's the same thing at the quantum computer

  • Your input is a bunch of probabilities which you know at the very start and all these gates change those probabilities in a controlled way

  • You know exactly how Hadamard or Phase or T or CNOT

  • you know exactly how it's gonna change those and you can write down exactly how it'll change those so you can

  • Mechanically do the computation in the same way that we can mechanically do it with adders or ale use or whatever

  • Just turns out that the most basic type of computation is actually a really it's a really large one

  • It's actually equivalent to a big matrix multiply. If you were to write this out your probabilities as a column vector

  • 50% 25%

  • Whatever 7% etc, etc

  • Every operation in a quantum computer is actually specified as a matrix. You have a big set of matrix elements

  • Maybe it's like 1 0 0 0 0 0 0 0

  • 1 1/2

  • 3/4 whatever I'm making it up as I go along of course, but you know with certainty 100% certainty that this operation

  • Maybe this is like Hadamard on qubit 0 and Hadamard on qubit 1 or something like that

  • it's not but you know that this operation is gonna change his probabilities and I could if I wanted to

  • Manually go and compute this matrix multiplication. The thing is like I said this vector right here grows

  • doubles in size every time I add a qubit so it's better for a quantum computer to do it as opposed to me

  • or even a normal computer doing it

  • Yep, this multiplication happens on the order of 50 to 250

  • nanoseconds on a computer no matter the number of qubits that you have even if you have

  • 250 qubits this vector right here would be 2 to the power of 250 which is some enormously large number

  • I don't even know an order of magnitude estimate of what that is

  • It's so bigger than any computer on earth could store bigger than any computer in the universe could store but nonetheless it will do this

  • Multiplication in 50 nanoseconds, which really starts getting into why quantum computers show promise for very fast or very powerful applications

  • How much does a quantum computer cost then?

  • Oh my gosh

  • All the components it costs a great deal for sure if you want to buy one and have it in your living room

  • Yeah, so one of the big popular ones is a very recent algorithm back in I think 2014 is when I came out

We talked a bit about the hardware, you know, people are working on the hardware of quantum computing, yep

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量子指令集 - Computerphile (Quantum Instruction Set - Computerphile)

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    林宜悉 發佈於 2021 年 01 月 14 日
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