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36C3 Preroll music
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Herald: So hello and welcome to a quantum[br]computing talk by the Andreas [Dewes], who
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gave a talk exactly five years ago and[br]it's almost exactly five years ago, it's
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like one year and two or three hours. And[br]then he gave a talk at 31C3 about quantum
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computing titled "Let's Build a Quantum[br]Computer". And I think back then we
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basically had just found out that Google[br]was planning to partner with the
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University of California at Santa Barbara[br]to try to build a quantum computer. Of
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course, now we're five years later, we've[br]had a lot of developments, I think, in the
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field. We've had some big announcements by[br]Google and other groups. And Andreas has
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now come back to give us an update. So[br]please welcome him to the stage.
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Applause
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Andreas: Okay. Hi, everyone, so I'm very[br]happy to be here again. After five years
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of giving the first version of this talk.[br]My motivation for given this talk is quite
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simple. I was often so I did my PHD on[br]exponential quantum computing from 2009 to
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2012. I left that field afterwards to work[br]in industry, but always people would come
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to me and ask, hey, Andreas, did you see[br]like this new experiment. Did you see, you
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can like use quantum computers on Amazon's[br]cloud now? Did you see, like Google has
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this new quantum thing? This is really[br]working? Can we use quantum computers yet?
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Why are you not working on this? And I[br]couldn't I couldn't really answer the
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question. So I said, OK, I want to go back[br]to this and find out what happened in the
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last five years since I finished my PhD.[br]What kind of progress was made in the
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field? And do we actually have quantum[br]computers today that are working already
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or are we not yet quite just there? So we[br]want to do it like this. I want to first
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give you a short introduction to quantum[br]computing. So just that we have a common
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understanding of how that works and why[br]it's interesting. Then I will show you a
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small example of experimental quantum[br]speed up. Notably the work I did with my
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colleagues in Saclay during my PhD[br]thesis. Then we discuss some of the
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challenges and problems, why we were not[br]able to build a real quantum computer back
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then. And I will discuss some approaches[br]that have come up since then. That would
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basically allow us to do that eventually.[br]And then we'll, of course, discuss
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Google's recent experiment in[br]collaboration with the University of Santa
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Barbara, where they showed basically a[br]very impressive quantum computing system
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with 53 Qubits. We will look exactly to[br]try to understand what they did there and
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see if that's really like a quantum[br]computer in the in the real sense already
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or if there's still something missing. And[br]in the end, of course, I will try to give
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you another small outlook to see what we[br]can expect in the coming years. So in
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order to talk about quantum computing, we[br]need to first talk about classical
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computing just a little bit. You might[br]know that classical computers, they work
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with bits, so zeros and ones. They store[br]them in so-called registers. This here for
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example of like a bit register. Of course,[br]the bits themselves are not very
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interesting. But we have to do stuff with[br]them so we can compute functions over
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those bit registers. That's what like[br]modern CPU is doing in a simplified way,
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of course. So we take some input, but[br]register values, we compute some function
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over then and then we get an output value.[br]So a very simple example would be a search
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problem. I would discuss this because[br]later we will also see in the experiment
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how we can use a quantum computer to solve[br]this. So I just want to motivate why this
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kind of problem can be interesting. And[br]it's a very silly search function. So it
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takes two bits as inputs and it returns[br]one bit as an output, indicating, whether
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the input bits are the solution to our[br]search problem or not. And you could
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imagine that we have a very, very[br]complicated function here. So, for
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example, a function that calculates the[br]answer to life, the universe and
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everything, while not a complete answer,[br]but only the first two bits. So really
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complicated to implement and very costly[br]to execute. So we might think that it
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might take like millions of years to run[br]this function once on our inputs. And so
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we want to find the right solution to that[br]function with as few function calls as
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possible, of course. Overall, there are[br]four possibilities, so for input states, 00
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01 10 and 11 that we can apply our[br]function to and only for one of these
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states. The 01 state, because the answer[br]is 42. So that's 0 times 1 plus to plan 2
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plus some other stuff. So the first two[br]bits are 0 1 for this for a value, the
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function returns a 1 for all of the other[br]values, the function returns 0. Now let's
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think about how we can implement a central[br]search function and in principle, if we
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don't know anything about the function. So[br]we can imagine it's so complicated that we
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can't do any optimizations. We don't know[br]where to look. So we have to really try
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each of these values in sequence. And for[br]this we can have a simple algorithm so we
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can start initializing out our a bit[br]register with 00 value. Then we can call
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the function on that register. We can see[br]what the result is. In this case, the
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result would be zero. If the result would[br]be 1, then we know, okay, we have found
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our solution so we can stop our algorithm.[br]But in this case, the result is zero. So
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we can just go back to the left value and[br]to the left step and increase the register
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value, go to 0 1 and try again. And in the[br]worst case, depending if you're optimistic
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or not, we have to do this three or four[br]times. So if you want to really be sure
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that we find the right answers, we have to[br]do it four times in the worst case. And
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this is sort of say the time complexity or[br]the computational complexity of the
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search. You know, if you imagine that in[br]our algorithm, the most expensive
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operation is really calling this function[br]F, then the calling time of the complexity
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of calling this function will be what[br]dominates the complexity of our algorithm.
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And in this case, the complexity is very[br]similar, simple here because it's linear
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in the number of the search space. So if[br]you have n states, for example, in our
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examples, we have four different input[br]spaced states. We also need to evaluate
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the function four times. So and please[br]keep this graph in mind because we're
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gonna revisit that later a bit to see,if[br]we can do better with a different paradigm
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of computing. And so classically. This is[br]really the best we can do for the search
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problem here because we don't know[br]anything else about the function that
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would allow us to optimize that further.[br]But now the interesting thing is that we
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might imagine that we don't use classical[br]computing for solving our problem. And in
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fact, the discipline that we call quantum[br]computing was kind of like inspired by
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lecturer or like a seminar of Richard[br]Feynman, who thought about, how it would be
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possible to similar and or if it would be[br]possible to simulate quantum systems on a
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classical computer. A Turing machine, if[br]you want. And he found that because
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quantum mechanics is so complicated for[br]classical computers that it is not
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possible to do that efficiently, but that[br]if you would use the laws of quantum
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mechanics themselves to make a computer[br]like quantum computer, then it would be
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possible to simulate this quantum systems[br]and just kind of like sparked this whole
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idea of using quantum mechanics to do[br]computation. And in the following years,
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they were not only as solutions found for[br]simulating quantum systems, which such a
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quantum computer, but also for solving[br]other not related problems to quantum
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computing. So like search problems or[br]factorization problems, for example. And
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quantum computers can do, can do[br]computation faster than classical
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computers, because they have several[br]differences in how they work. So one of
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the key differences here is superposition,[br]which means that if you use a quantum
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computer, instead of a classical computer,[br]we cannot only load a single register
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value into our bit register. So for[br]example, the first value of only zeros.
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But instead we can kind of load all of the[br]possible state values and it at once or in
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parallel. And this so-called quantum state[br]or quantum superposition state where each
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of these values here has an amplitude[br]which is shown on the left, that is
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basically a complex number that relates[br]them to the other Qubit, to other states
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and ups. If you have like for example,[br]n-Qubits, then the total number of Qubits
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states can be very large 2 to the[br]power of N. So we can imagine that if you
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have a large Qubit quantum quantum bit[br]register, then your number of quantum
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states can be really, really large and[br]this can be very powerful for computation.
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So in the rest of the talk, we gonna just[br]indicate this by like showing the register
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as like a small rectangle to indicate that[br]it's not only a single value in there, but
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that we have a superposition values of all[br]the possible input values to our function,
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for example. And there is a condition and[br]so called normalization condition that
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puts some constraints on these amplitude.[br]Because the sum of the squares of the
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absolute values of these amplitude needs[br]to sum to one, which basically means that
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the entire the probability of each of[br]these of all of these states together
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needs to be 100 percent. So. And this is[br]the first ingredient that makes quantum
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computers interesting for computation[br]because we can basically implement any
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classical function that we can also run on[br]a classical computer, on a quantum
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computer. The difference is that we cannot[br]only run it for one value at a time, but
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we can call it can run it down on a[br]superposition of all possible input
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values. So if you want, you have like this[br]massive paralellyzation where you run you
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off computation on all possible inputs at[br]once and also calculate and all of the
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possible output values. And that sounds,[br]of course, very cool and very useful.
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There's a catch that we will discuss[br]later. So it's not as easy as that. But
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this is one step off like the power that[br]makes quantum computing interesting. The
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next thing that is different is that we[br]can on a quantum computer, not only run
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classical gates or classical functions,[br]but we can also run so-called quantum
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gates. And the quantum gates, they're[br]different in respect to the classical
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functions because they cannot only like[br]classical operations like and or or on
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like two Qubits in a predictable way. But[br]they can kind of like act on the whole
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Qubit state at once and also create so-[br]called entangled states which are really
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weird quantum states where we can't really[br]separate the state of one Qubit from the
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state of or other Qubits. So it's kind of[br]like if we want to try to make a small
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change to one of two Qubits in our[br]system, we also changing other Qubits
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there. So we can never like separate the[br]bits, the Qubits out like we can with a
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classical computer. And this is another[br]resource that we can use in quantum
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computing to solve certain problems faster[br]than we could with a classical computer.
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Now, the catch, as I said, is that we, of[br]course, do not, we do not want to only
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make computation with our Qubits, Qubits[br]register, but we also want to read out the
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result of our computation. And if we try[br]that. So we make like computation. And
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when we want to measure the state of our[br]quantum register, we have a small problem
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because, well, the measurement process is[br]actually quite complicated. But in a very
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simplified way, you can just imagine, that[br]God is trying some dice here. And then if
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we have a quantum vector, a quantum state[br]vector that has like this amplitude on the
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left. So a one to a n. And then we will[br]pick. He or she would pick a state
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randomly from the possible states. And the[br]probability of getting a given state as a
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result is proportional, as is that before[br]to the square of the absolute value of the
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amplitude. So that means we can perform[br]computation on all of the possible input
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states of our function. But when we read[br]out the result, we will only get one of
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the possible results. So it's kind of like[br]destroys at the first glimpse the utility
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of quantum computing because we can do[br]like computation on all states in
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parallel, but we cannot read out the[br]result. So not a very interesting computer
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because we can't learn about the output.[br]So to say or not easily at least. But it
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turns out that there's actually a way of[br]still using quantum computing to be faster
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than a classical computer. And the first[br]kind of practical algorithm for a search
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problem, notably the search problem that[br]we discussed before, was given by Love
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Grover, who was a researcher at the Bell[br]Labs, and who found the Grover algorithm
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that is named after him. That's basically[br]a search algorithm which can prove it can,
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as we will see, solved the search problem[br]that we have in a much more efficient way
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than any classical computer could. And in[br]my opinion, it's still one of the most
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beautiful quantum algorithms because it's[br]very simple and it's very powerful and
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does also prove, unlike for other[br]algorithms like the factorization
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algorithms from Shor that the Grover[br]algorithm can be will be faster always
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than any classical computer classical[br]algorithm. So in my opinion, it's a very
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nice example of really a quantum algorithm[br]that is more powerful than a classical
0:14:11.889,0:14:20.609
one. Let's see how it works. So they're[br]three steps again and the algorithm. First
0:14:20.609,0:14:26.769
we initialize our Qubit register, our[br]state vector to a superposition of the
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four possible output values, so 00 01[br]10 and 10, again, all with equal
0:14:33.730,0:14:40.440
probability in this case, zero amplitude.[br]Then we evaluate the function on this
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input state here and what the function[br]then does. So we made some special
0:14:44.619,0:14:50.490
encoding here that basically marks the[br]solution of our problem by changing the
0:14:50.490,0:14:54.980
sign of the amplitude of the corresponding[br]state. We can see that in the output state
0:14:54.980,0:15:01.449
here, the 01 state has a sign which is[br]negative, which means that it's the
0:15:01.449,0:15:06.300
solution of the problem that we search.[br]Still, if we were to the read out now
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directly, we wouldn't be able to learn[br]anything about the solution, because as
0:15:10.410,0:15:14.899
you can see, the amplitude is still equal[br]for all of the four states. So if you
0:15:14.899,0:15:20.050
would make a read out now, we would only[br]get like one of the four possible states
0:15:20.050,0:15:24.490
at random so we wouldn't learn anything[br]with a hundred percent probability about
0:15:24.490,0:15:29.350
the solution of our problem. In order to[br]do that, we need to apply another step to
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so-called Grover or Diffusion, diffusion[br]operator, which now takes this phase
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difference or the sign difference between[br]these individual quantum states and
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applies a quantum operator to that, that[br]basically transfers the amplitude from all
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of the states that are not a solution to a[br]problem to the states that is the
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solution. And for on this case, with two[br]Qubits here and with four possible values,
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there's only one step we need. And after[br]executing that, you can see that now the
0:15:58.959,0:16:04.119
amplitude of our solution state is one[br]versus very. But the amplitude of the
0:16:04.119,0:16:09.579
other states is all zero. So that's great,[br]because now we can just do a Qubit
0:16:09.579,0:16:14.389
measurement and then we will have a[br]hundred percent probability find a
0:16:14.389,0:16:18.839
solution to our search problem. And that's[br]where kind of like the magic of quantum
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mechanics shows, because you can evaluate[br]its function only once. So remember that
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in the first step we only call the search[br]function once of all of the values in
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parallel. So from the computational[br]complexity, we are much lower than the
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classical algorithm, but still we are able[br]to find 100 percent position in this case
0:16:38.170,0:16:45.209
to see which state is the solution to our[br]search problem. So and that's working not
0:16:45.209,0:16:49.799
only for the case of two Qubits, but also[br]with larger Qubit registers. So for
0:16:49.799,0:16:54.529
example, if you would take 10 Qubits, you[br]would need to execute a few more of these
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steps, two and three. So instead of one[br]iteration, you would need 25 iterations,
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for example, here, which is still much[br]better than the 1024 iterations that you
0:17:04.760,0:17:09.010
would need if you would really look into[br]every possible solution of the function in
0:17:09.010,0:17:15.870
the classical algorithm. So the speed up[br]here is very good for, so to say, all of
0:17:15.870,0:17:21.630
the like. It's quadratical for the[br]solution space. And if you like, look at
0:17:21.630,0:17:28.550
the complexity plot again, we can now[br]compare our classical algorithm with the
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quantum algorithm on the Grover search.[br]And as you can see, the time complexity
0:17:34.130,0:17:39.690
or the number of variations of F that we[br]need is only a square root of N, where N
0:17:39.690,0:17:44.550
is the size of the search space,[br]which shows that that we have really a
0:17:44.550,0:17:48.420
speed advantage hier of the quantum[br]computer versus the classical computer.
0:17:48.420,0:17:54.180
And nice thing is the larger our search[br]space becomes, the more dramatic our speed
0:17:54.180,0:17:58.550
up will be, because for example, for a[br]search space with one million
0:17:58.550,0:18:02.510
elements. We will only have to evaluate[br]the search function 1000 times instead of
0:18:02.510,0:18:14.480
one million times. So that's quite so to[br]say a speed up in that sense. Now, how can
0:18:14.480,0:18:20.260
we build a system that realizes this[br]quantum algorithm? Here, I show on the
0:18:20.260,0:18:25.440
quantum processor that I built with my[br]colleagues at the Saclay during my PhD. So
0:18:25.440,0:18:28.730
if you want more information about this,[br]you should check out my last talk. I just
0:18:28.730,0:18:33.210
want to go briefly over the different[br]aspects here. So we use a so called
0:18:33.210,0:18:39.600
superconducting Qubits, transmit Qubits[br]for realizing our quantum computer. A
0:18:39.600,0:18:44.980
quantum processor. You can see the chip[br]here on the top. It's about one centimeter
0:18:44.980,0:18:49.870
across. You can see the two Qubits in the[br]middle. The other, like snake like
0:18:49.870,0:18:53.920
structures are coupling a wave guides[br]where we can manipulate the Qubits using
0:18:53.920,0:18:58.740
microwaves. So we use frequencies that are[br]similar to the ones that are used by
0:18:58.740,0:19:03.870
mobile phones to manipulate and read out[br]our Qubits. And if you look in the
0:19:03.870,0:19:09.240
middle, you can see the red area, which[br]contains the Qubit, each Qubit itself. And
0:19:09.240,0:19:13.000
then there's another zoom in here, which[br]contains the actual qubit structure, which
0:19:13.000,0:19:18.410
is just some two layers of aluminum that[br]have been placed on top of each other and
0:19:18.410,0:19:23.040
which create, when they are cooled, to a[br]very low temperature, a so-called
0:19:23.040,0:19:27.660
superconducting state, where we can use[br]the superconducting face between these two
0:19:27.660,0:19:34.400
values, layers to indicate to to realize[br]our Qubits. There's also coupler in the
0:19:34.400,0:19:39.120
middle. So this green element that you[br]see, which allows us to run quantum gate
0:19:39.120,0:19:49.110
operations between the two Qubits. To use[br]that in practice, we need to put this in a
0:19:49.110,0:19:53.021
delusion crisis that which is really like[br]just a very fancy refrigerator, you could
0:19:53.021,0:19:59.380
say, you cool it down to about 10 milli K.[br]So very low temperature just above the
0:19:59.380,0:20:04.300
absolute zero temperature. You can see the[br]sample holder here on the left side with
0:20:04.300,0:20:08.270
the chip mounted to it. So this whole[br]thing is put in the delusion fridge and
0:20:08.270,0:20:13.000
it's cool down to the temperature. And[br]then we can, as I said, manipulated by
0:20:13.000,0:20:18.950
using his microwave transmission lines.[br]And what we did is we implemented the
0:20:18.950,0:20:24.000
Grover search for the two Qubits. So we[br]ran this algorithm that I discussed
0:20:24.000,0:20:29.430
before. I don't want to go to too much[br]into the details. The results are obtained
0:20:29.430,0:20:35.090
by running this algorithm many times. And[br]as you can see, we have achieved not a
0:20:35.090,0:20:39.080
hundred percent success probability, but[br]over 50 percent for the most cases, which
0:20:39.080,0:20:44.180
is like, yeah, not perfect, of course, but[br]it's good enough to, in our case, show
0:20:44.180,0:20:49.350
that there was really a quantum speedup[br]possible. And if you ask why, okay, why is
0:20:49.350,0:20:53.560
not 100 percent probability possible or[br]why can't we build larger systems with
0:20:53.560,0:20:57.400
data, what kept us from, for example,[br]building a 100 or 1000 qubit quantum
0:20:57.400,0:21:03.230
processor? Well, there's several things on[br]this, of course, that we have like we make
0:21:03.230,0:21:07.540
errors when we manipulate the Qubits. So[br]the microwave signals are not perfect, for
0:21:07.540,0:21:11.520
example. So we introduce small errors when[br]like making two Qubit and single Qubit
0:21:11.520,0:21:16.550
interactions. We also need a really high[br]degree of connectivity if we want to build
0:21:16.550,0:21:20.170
a large scale quantum computer. So if[br]every Qubit is connected to every other
0:21:20.170,0:21:24.490
Qubit, for example, that would make one[br]million connections for 1000 Qubit code
0:21:24.490,0:21:28.290
processors, which processor which is just[br]on the engineering side, very hard to
0:21:28.290,0:21:33.790
realize. And then also our Qubits has[br]errors because they can the environment
0:21:33.790,0:21:39.170
that the Qubits are in, like the chip and[br]the vicinity there also introduces noise
0:21:39.170,0:21:43.241
that will destroy our quantum state and[br]that limits how many operations we can
0:21:43.241,0:21:50.160
perform on a single Qubit. So is possible[br]solution, which is the surface code
0:21:50.160,0:21:55.390
architecture which was introduced in 2009[br]already actually by David DiVincenzo from
0:21:55.390,0:21:58.770
the Jülich Research Center. And the idea[br]here is that we do not have a quantum
0:21:58.770,0:22:03.400
process of a full connectivity. So we do[br]not connect every Qubit to every other
0:22:03.400,0:22:08.780
Qubit. Instead, we only connect a Qubit to[br]its four neighbors via so-called tunable
0:22:08.780,0:22:12.060
coupler. And this is, of course, much[br]easier because you don't need so many
0:22:12.060,0:22:15.830
connections on a chip. But it turns out[br]that you can still run most of the quantum
0:22:15.830,0:22:19.840
algorithms that you could also run with a[br]fully connected processor. You just have
0:22:19.840,0:22:25.000
to pay like a penalty for the limited[br]connectivity. And the nice thing is also
0:22:25.000,0:22:30.410
that you can encode a single logical[br]Qubit. So Qubit that we want to do
0:22:30.410,0:22:35.820
calculations with as for example, five[br]physical Qubits. And so all of these
0:22:35.820,0:22:40.700
Qubits here that are on the chip would[br]together form one logical Qubit, which
0:22:40.700,0:22:43.910
would then allow us to do error[br]corrections so we can, if there had been
0:22:43.910,0:22:47.750
some error of one of the Qubits, for[br]example, of relaxation or a defacing
0:22:47.750,0:22:52.350
error, then we can use the other Qubits[br]that we prepared in exactly the same of
0:22:52.350,0:22:56.520
same way to correct this error and[br]continue doing the calculations. And this
0:22:56.520,0:23:00.460
is quite important because in these[br]superconducting Qubit systems, there are
0:23:00.460,0:23:04.600
always error present errors present, and[br]we will not probably be able to eliminate
0:23:04.600,0:23:09.480
all of them. So we need to find a way to[br]correct the errors, while we perform the
0:23:09.480,0:23:18.270
computation. Now the Google processor[br]follows the surface code approach, here I
0:23:18.270,0:23:23.510
show you an image from the Nature article[br]which was released, I think, one months
0:23:23.510,0:23:28.420
ago. So it's a very impressive system, I[br]find, it contains 50 trees superconducting
0:23:28.420,0:23:34.340
Qubits, 86 couplers, tunable couplers[br]between those Qubits and they achieve
0:23:34.340,0:23:40.410
fidelity. So the success probability, if[br]you like, for performing one and two Qubit
0:23:40.410,0:23:45.880
gates, which is higher than 99 percent. So[br]this is already pretty, very, very good.
0:23:45.880,0:23:52.360
And almost enough fidelity to realize[br]quantum error correction as I discussed
0:23:52.360,0:23:57.520
before. And with the system, you can[br]really run quite complex quantum
0:23:57.520,0:24:03.850
algorithms, much more complex than the[br]ones that we run in 2012. So the paper,
0:24:03.850,0:24:07.730
for example, they run sequences with 10 to[br]20 individual quantum operations or
0:24:07.730,0:24:14.870
Quantum Gates. And just to give you an[br]impression of the crisis study, a
0:24:14.870,0:24:21.760
cryogenic engineering and microwave[br]engineering here, this is so to say, the
0:24:21.760,0:24:26.620
delusion crisis that where the Qubit ship[br]is mounted and you can see that it's quite
0:24:26.620,0:24:31.780
a bit more complex than the system we had[br]in 2012. So it really looks way more like
0:24:31.780,0:24:39.590
a professional quantum computer, I would[br]say. If you ask a physicist now, why would
0:24:39.590,0:24:45.130
you build such a system? The answer would[br]be, of course. Well, it's awesome. So why
0:24:45.130,0:24:51.060
not? But it turns out that if an[br]organization like Google gives like 100 or
0:24:51.060,0:24:55.510
200 million US dollars for realizing such[br]research, they also want to see some
0:24:55.510,0:25:02.710
results. So that's why the team, of[br]course, under John Martinez tried to use
0:25:02.710,0:25:08.940
this quantum process for something, that[br]shows how powerful or dead, so to say, can
0:25:08.940,0:25:17.980
outperform a classical computer. And this[br]sounds easy, but actually it's not so not
0:25:17.980,0:25:22.840
so easy to find a problem that is both[br]doable on this quantum computer, which has
0:25:22.840,0:25:28.440
like 50 Qubits and a bit more than 50[br]Qubits and like 80 couplers. But it's not
0:25:28.440,0:25:33.040
possible to simulate on a classical[br]computer. So we could think, for example,
0:25:33.040,0:25:38.830
about the factoring of numbers into prime[br]components, which is, of course, always
0:25:38.830,0:25:43.331
like the motivation of certain agencies to[br]push for quantum computing, because that
0:25:43.331,0:25:47.620
would allow them to read everyone's email.[br]But unfortunately, in both, the number of
0:25:47.620,0:25:53.150
Qubits that he would require for this and[br]the number of operations is much too high
0:25:53.150,0:25:58.100
to be able to realize something like this[br]on this processor. The next thing, which
0:25:58.100,0:26:01.730
would be very interesting is the[br]simulation of quantum systems. So if you
0:26:01.730,0:26:06.130
have like molecules or other quantum[br]systems that have many degrees of freedom,
0:26:06.130,0:26:10.610
it's very difficult to simulate those on[br]classical computers. On a quantum computer
0:26:10.610,0:26:14.930
you could do it efficiently. But again,[br]since the Google team did not do this, I
0:26:14.930,0:26:19.990
assume the quantum computer was just or[br]they didn't have like a feasible problem
0:26:19.990,0:26:24.240
where they could actually perform such a[br]simulation that would not be not be
0:26:24.240,0:26:28.830
performing well or like calculable on a[br]classical computer. So but in the near-
0:26:28.830,0:26:32.620
term, in the future, this might actually[br]be very relevant application of such a
0:26:32.620,0:26:38.150
processor. The last possibility would be[br]to run, for example, the search algorithm
0:26:38.150,0:26:42.430
that we discussed before. But again, for[br]the number of Qubits that are in the
0:26:42.430,0:26:47.690
system and the size of the search space,[br]it's still not possible because the
0:26:47.690,0:26:52.190
algorithm requires too many steps. And the[br]limited coherence times of Qubits in this
0:26:52.190,0:26:56.690
processor make it impossible to to[br]run this kind of like algorithm there, at
0:26:56.690,0:27:04.740
least to my knowledge. So what what they[br]did then, was therefore to perform a
0:27:04.740,0:27:09.410
different kind of experiment, one that was[br]doable with the processor, which is so-
0:27:09.410,0:27:15.320
called randomized benchmarking. And in[br]this case, what you do is that you instead
0:27:15.320,0:27:19.900
of like running an algorithm that does[br]something actually useful, like a search
0:27:19.900,0:27:24.200
algorithm, you run just a random sequence[br]of gates. So you have, for example, your
0:27:24.200,0:27:28.730
53 Qubits and then you run first like some[br]single Qubit gates. So you changed the
0:27:28.730,0:27:33.910
Qubit values individually. Then you run[br]two Qubit gates between random Qubits to
0:27:33.910,0:27:37.630
create like a superposition and an[br]entangled state. And in the end, it just
0:27:37.630,0:27:43.590
read out the resulting qubit state from[br]your register. And this is also very
0:27:43.590,0:27:48.850
complex operation. So you really need a[br]very high degree of like control of your
0:27:48.850,0:27:53.840
quantum processor, which the Martinez is,[br]the Google team was able to achieve here.
0:27:53.840,0:27:59.270
It's not it's just not solving a really[br]practical problem yet, so to say. But on
0:27:59.270,0:28:03.960
the other hand, it's the it's it's the[br]system. It's an algorithm that can be run
0:28:03.960,0:28:08.160
on the quantum computer easily, but which[br]is, as we will see, very difficult to
0:28:08.160,0:28:13.600
simulate or reproduce on a classical[br]system. And the reason that it's so
0:28:13.600,0:28:17.540
difficult to reproduce on a classical[br]system is that, if you want to simulate
0:28:17.540,0:28:21.200
the action of these quantum gates that we[br]run on the quantum computer using a
0:28:21.200,0:28:26.770
classical machine, a classical computer,[br]then for every Qubit that we add, roughly
0:28:26.770,0:28:31.990
the size of our problem, space quadruples.[br]So you can imagine if you have like two
0:28:31.990,0:28:36.500
Qubits, then it's very easy to simulate[br]that you can do it on like your iPhone or
0:28:36.500,0:28:42.000
like your computer, for example. If you[br]add more and more Qubits store, you can
0:28:42.000,0:28:46.760
see that the problem size becomes really[br]really big really fast. So if you have
0:28:46.760,0:28:51.280
like 20 Qubits, 30 Qubits, for example,[br]you cannot do it on a personal computer
0:28:51.280,0:28:55.700
anymore. You will need like supercomputer.[br]And then if you keep increasing the number
0:28:55.700,0:29:00.510
of Qubits, then at some point in this[br]case, 50 Qubits or 53 Qubits, it would be
0:29:00.510,0:29:04.870
impossible even for the fastest[br]supercomputers that we have right now. And
0:29:04.870,0:29:09.090
that's what is called the so-called[br]quantum supremacy regime here for this
0:29:09.090,0:29:15.180
randomized gate sequences, which is[br]basically just the area here on the curve.
0:29:15.180,0:29:20.300
That is C, that is still doable for this[br]quantum processor that Google realized.
0:29:20.300,0:29:25.760
But it's not simulatorable or verifiable[br]by any classical computer, even like a
0:29:25.760,0:29:32.620
supercomputer in a reasonable amount of[br]time. And if we can run something in this
0:29:32.620,0:29:37.640
regime here, it proves that we have a[br]quantum system that is able to do
0:29:37.640,0:29:41.860
computation, which is not classically[br]reproducible. So it's something that
0:29:41.860,0:29:46.220
really can only be done on a quantum[br]computer. And that's why running this kind
0:29:46.220,0:29:50.750
of experiment is is interesting, because[br]it really shows us that quantum computers
0:29:50.750,0:29:55.050
can do things that classical computers[br]cannot do, even if there are for the
0:29:55.050,0:30:01.550
moment not really useful. And the gate[br]sequence that they run looks something
0:30:01.550,0:30:06.670
like this. We can see again, like here[br]five, four of the Qubits that the Google
0:30:06.670,0:30:11.420
team has. And they run sequences of[br]operations of different lengths, then
0:30:11.420,0:30:14.960
perform a measurement and then just sample[br]the output of their measurements. So what
0:30:14.960,0:30:20.750
they get as a result is a sequence of long[br]bit strings, so zeros and ones. For each
0:30:20.750,0:30:26.710
experiment, they run and to reproduce the,[br]to check that a quantum computer is
0:30:26.710,0:30:30.830
actually doing the right thing, you have[br]to compare it to the results of a
0:30:30.830,0:30:37.310
classical simulation of this algorithm.[br]And that's, of course, a problem now,
0:30:37.310,0:30:42.870
because, we just said that we realized the[br]quantum computer, a quantum processor,
0:30:42.870,0:30:48.440
which is able to do this computation on 53[br]Qubits and that no classical computer can
0:30:48.440,0:30:54.670
verify that. So the question is now, how[br]can they prove or show that what the
0:30:54.670,0:30:58.240
quantum computer calculates is actually[br]the correct answer or that he does not
0:30:58.240,0:31:01.790
just produce some garbage values? And[br]that's a very interesting question,
0:31:01.790,0:31:07.320
actually. And the way they did it here is[br]by extrapolation. So instead of, for
0:31:07.320,0:31:11.820
example, solving the full circuits, so[br]that contains all of the connections and
0:31:11.820,0:31:17.240
all of the gates of the full algorithm,[br]they created simplified circuits in two
0:31:17.240,0:31:21.570
different ways. So, for example, they cut[br]they cut some of the connections between
0:31:21.570,0:31:26.330
the Qubits and the algorithms, so that the[br]problem space would become a bit smaller
0:31:26.330,0:31:30.350
or in the other case, with the allied[br]circuit, they just changed the operations
0:31:30.350,0:31:34.710
in order to allow for some shortcuts in[br]the classical computation of the classical
0:31:34.710,0:31:39.820
simulation of the algorithm. So in both[br]cases, they were able to then verify the
0:31:39.820,0:31:43.600
result of the quantum computation with this[br]classical simulation performed on a
0:31:43.600,0:31:48.850
supercomputer. And then they basically[br]just did this for a larger and larger
0:31:48.850,0:31:53.770
number of Qubits. They plotted the[br]resulting curve and they extrapolated that
0:31:53.770,0:31:58.960
to the supremacy regime to see that. OK.[br]Based on the error models that they
0:31:58.960,0:32:02.760
developed, based on the simulation, they[br]can with a certain confidence, of course,
0:32:02.760,0:32:06.930
say that probably the quantum computer is[br]doing the right thing even in the
0:32:06.930,0:32:11.920
supremacy regime, even though we can't[br]they cannot verify it using the classical
0:32:11.920,0:32:18.720
simulations. And in case the quantum[br]computer did wrong still, they have also
0:32:18.720,0:32:22.730
archive to the results. And maybe ten[br]years when we have better supercomputers,
0:32:22.730,0:32:28.240
we might be able to just go back to them[br]and then verify them against the 53, 53
0:32:28.240,0:32:31.920
Qubits processor here, by which time, of[br]course, they might already have like a
0:32:31.920,0:32:39.610
larger quantum processor again. So the key[br]results of this, I would say, are that for
0:32:39.610,0:32:43.940
the first time they show that really[br]quantum computer can beat a classical
0:32:43.940,0:32:49.220
computer, even though it is at a very[br]artificial and probably not very useful
0:32:49.220,0:32:53.280
problem. And what the experiment also[br]shows is that really, I would say an
0:32:53.280,0:32:59.060
astounding level of control of such a[br]large scale on medium size quantum
0:32:59.060,0:33:05.410
processor, because even five years ago,[br]six years ago, 2012, 2013, the systems
0:33:05.410,0:33:10.610
that we worked with mostly consisted of[br]three or four Qubits and we could barely
0:33:10.610,0:33:16.000
fabricate the chips and manipulate them to[br]get like algorithms running. And now if I
0:33:16.000,0:33:21.090
see like a 50 tree Qubit processor with[br]such a high degree of control and fidelity
0:33:21.090,0:33:25.530
there, I can really say that is really an[br]amazing progress in the last five years
0:33:25.530,0:33:30.600
that what was achieved, especially by the[br]Google Martinez team here. And I think it
0:33:30.600,0:33:34.200
is a very good wild milestone on the way[br]to fully work on quantum computer because
0:33:34.200,0:33:38.950
it nicely shows the limitations of the[br]current system and gives a good direction
0:33:38.950,0:33:44.590
on new areas of research, for example, an[br]error correction, where we can improve the
0:33:44.590,0:33:50.150
different aspects of the quantum[br]processor. The research has also been
0:33:50.150,0:33:55.330
criticized from various sides, so I just[br]want to iterate a few of the points
0:33:55.330,0:34:00.050
here. One of the criticisms is, of course,[br]that it doesn't do anything useful. So
0:34:00.050,0:34:05.840
there's really no applicability of this[br]experiment and why that's true. It's, of
0:34:05.840,0:34:11.450
course, very difficult to go from like a[br]basic, very simple quantum process of two
0:34:11.450,0:34:15.450
Qubits to a system that can really [br]factorize prime numbers or do anything
0:34:15.450,0:34:20.109
useful. So we will always need to find[br]problems that are both hard enough so that
0:34:20.109,0:34:24.210
we can solve them in a reasonable[br]timeframe. A couple of years, for example,
0:34:24.210,0:34:28.540
that still proved the progress that we[br]make on the road to quantum computing. So
0:34:28.540,0:34:33.070
in this sense, while quantum supremacy[br]does not really show anything useful in
0:34:33.070,0:34:37.690
terms of computation that is done. I think[br]it is still a very good problem as a
0:34:37.690,0:34:41.580
benchmark for any kind of quantum[br]processor, because it requires that you
0:34:41.580,0:34:46.110
have very good control over your system[br]and that you can run such a number of
0:34:46.110,0:34:50.621
gates at a very high fidelity, which is[br]really currently, I would say, the state
0:34:50.621,0:34:56.899
of the art. The research also took, took [br]some shortcuts. For example, they used
0:34:56.899,0:35:00.290
like a two Qubits, quantum gates, which [br]are not, as we call them, canonical
0:35:00.290,0:35:04.230
gates, which might be problematic [br]because if you want to run a quantum
0:35:04.230,0:35:07.900
algorithm on the system, you need[br]to implement certain quantum gates that
0:35:07.900,0:35:12.240
you need for that. And since they only[br]have like non canonical gates here, which
0:35:12.240,0:35:16.740
are still universal, by the way, they[br]could not do that directly, but with some
0:35:16.740,0:35:21.060
modification of the system, that should[br]also be possible. And the last criticism
0:35:21.060,0:35:25.640
might be that, okay, here you have a[br]problem that was engineered to match a
0:35:25.640,0:35:31.540
solution, which is of course that, okay,[br]we need some solution, as I said, some
0:35:31.540,0:35:36.520
problem that we can't realistically solve [br]on a such a system. I think, though, also
0:35:36.520,0:35:40.230
like the other points, if you want to[br]build a large scale quantum processor, you
0:35:40.230,0:35:45.030
need to define reasonable milestones and[br]having such a benchmark that other groups,
0:35:45.030,0:35:49.720
for example, can also run that process[br]against is a very good thing because it
0:35:49.720,0:35:54.200
makes the progress visible and also makes[br]it easy to compare how different groups
0:35:54.200,0:35:59.820
or are companies or organizations [br]are are at competing on the
0:35:59.820,0:36:12.040
number of Qubits under control they have[br]about them. So, if you want to make a more
0:36:12.040,0:36:16.770
kind of Moore's Law for quantum computing,[br]there would be several possibilities that
0:36:16.770,0:36:22.550
you could do. Here I show you, for[br]example, the number of Qubits that have
0:36:22.550,0:36:28.620
been realized for superconducting systems[br]over the years. This is, of course
0:36:28.620,0:36:32.340
incomplete because it could like the[br]number of Qubits alone doesn't tell you
0:36:32.340,0:36:36.810
much about your system. I mean, we could[br]do a Qubit chip of 1000 or 10000 Qubits
0:36:36.810,0:36:41.230
today. But if you don't have the[br]connectivity and don't have to controllability
0:36:41.230,0:36:45.119
of individual Qubits, then this[br]chip wouldn't be good. So there are other
0:36:45.119,0:36:49.210
things, that we also need to take into[br]account here. As I said, just as like the
0:36:49.210,0:36:53.550
coupling between individual Qubits and the[br]coherence time and the fidelity of the
0:36:53.550,0:37:00.010
Qubit operations. So this is really just[br]one one very small aspect of this whole
0:37:00.010,0:37:03.470
whole problem space. But I think it shows[br]nicely that in the last years there was
0:37:03.470,0:37:07.790
really tremendous progress in terms of the[br]power of the superconducting systems,
0:37:07.790,0:37:15.350
because the original Qubit, which was[br]developed in at NYC in Japan by
0:37:15.350,0:37:20.710
Professor Nakamura, was done in like[br]around 2000. So that very, very bad
0:37:20.710,0:37:24.920
coherence time, very bad properties. But[br]still it showed for the first time that he
0:37:24.920,0:37:28.970
could coherently control such a system.[br]And then it didn't take long for other
0:37:28.970,0:37:32.390
groups, for example, to Quantronics[br]Group and so Saclay, to pick up on this
0:37:32.390,0:37:37.480
work and to do to keep improving it. So[br]after a few years, we already had Qubits
0:37:37.480,0:37:42.250
of a few hundred or even a microsecond of[br]coherence time, which was like in like
0:37:42.250,0:37:46.100
three or orders of magnitude better than[br]what we had before. And there were other
0:37:46.100,0:37:51.490
advances then made by groups in the US,[br]for example, in Yale, the ShowCoupLab,
0:37:51.490,0:37:56.010
which developed new Qubit architectures[br]that allowed us to couple the Qubits more
0:37:56.010,0:37:59.570
efficiently with each other and to again[br]have better control of them manipulating
0:37:59.570,0:38:04.910
them. And then there's also groups like[br]the research group at IBM or companies
0:38:04.910,0:38:09.410
like WeGetty that took again these[br]ideas and that added engineering and their
0:38:09.410,0:38:14.130
own research on top of that in order to[br]make the systems even better. So in 2018,
0:38:14.130,0:38:19.610
we already had systems with 17 or 18[br]Qubits in them. And now with this Google
0:38:19.610,0:38:25.440
and UC Santa Barbara work, we have the[br]first systems with more than 50 Qubits
0:38:25.440,0:38:32.510
after not even 20 years, which I think is[br]quite some progress in this area. And of
0:38:32.510,0:38:38.520
course, if you ask me how close we are to[br]and actually working quantum computer,
0:38:38.520,0:38:44.860
it's still very difficult to say, I find,[br]because we've proven the group prove the
0:38:44.860,0:38:49.840
quantum supremacy for its randomized[br]algorithm. But in order to do something
0:38:49.840,0:38:56.370
applicable or useful with such a quantum[br]system, I think we need like at least
0:38:56.370,0:39:03.440
again, 50 maybe 200 additional Qubits and[br]a larger number of Qubit operations. But
0:39:03.440,0:39:07.299
it's really hard to say. That's why I also[br]say don't believe in this chart because
0:39:07.299,0:39:11.890
there's also, of course, a lot of work in[br]the theory of quantum algorithms, because
0:39:11.890,0:39:16.360
up to now we are still discovering new[br]approaches of doing quantum simulations
0:39:16.360,0:39:19.800
for examples. And right now, there are a[br]lot of research groups that are looking
0:39:19.800,0:39:24.120
for ways to make these medium scale[br]quantum computers. So quantum computers
0:39:24.120,0:39:29.940
with 50 or 100 Qubits already useful for[br]using quantum simulations. So it's really
0:39:29.940,0:39:35.420
an interplay between what the theory can[br]give us in terms of quantum algorithm and
0:39:35.420,0:39:40.070
what in terms of experimental realization[br]we can build as a quantum processor. So in
0:39:40.070,0:39:44.390
my opinion, quantum simulation will[br]definitely be something that where we will
0:39:44.390,0:39:49.390
see the first applications in the next. I[br]would say three to five years. Other
0:39:49.390,0:39:54.900
things, optimizations. I have to admit I[br]am less an expert and I think they're a
0:39:54.900,0:39:58.810
bit more complex. So we will probably see[br]the first applications in those areas a
0:39:58.810,0:40:04.011
bit later. And the big motivation for like[br]the three letter agencies always is,
0:40:04.011,0:40:10.350
of course, the factoring out the breaking[br]of cryptosystems, which is the most
0:40:10.350,0:40:14.619
challenging one, though, because in order[br]to do that, you would both need very large
0:40:14.619,0:40:19.850
numbers of Qubits. So at least 8000[br]Qubits for an 8000 bits RSA key, for
0:40:19.850,0:40:23.831
example. And you would also need a very[br]large amount of Qubit operations because
0:40:23.831,0:40:29.520
you need to run the sure operation. And[br]that involves a lot of steps for the
0:40:29.520,0:40:34.350
quantum processor. And so to say the most,[br]I would say from my perspective
0:40:34.350,0:40:39.550
unrealistic application of superconducting[br]quantum processes in the next year. But I
0:40:39.550,0:40:43.320
think, if somebody would build a quantum[br]computer, maybe we would also not just
0:40:43.320,0:40:52.749
know about it. So who knows? So to[br]summarize, quantum computers, quantum
0:40:52.749,0:40:57.020
processors are getting really, seriously[br]complex and very impressive. So we have
0:40:57.020,0:41:02.260
seen tremendous progress in the last five[br]years. I still think that we are like five
0:41:02.260,0:41:06.840
years away from building really practical[br]quantum computers and there are still some
0:41:06.840,0:41:11.510
challenges. For example, an error[br]correction in the Quantum Gatefidelity and
0:41:11.510,0:41:15.500
indeed, again, general architecture of[br]these systems that we need to overcome.
0:41:15.500,0:41:18.690
And they might also be some challenges[br]which we haven't even identified yet with
0:41:18.690,0:41:22.750
which we might only encounter at a later[br]stage when trying to build really large
0:41:22.750,0:41:28.390
scale quantum processors. And as a last[br]point, I just want to stress again, that
0:41:28.390,0:41:33.700
quantum computing research is not only[br]done by Google or by IBM, there a lot
0:41:33.700,0:41:37.540
of groups in the world involved in this[br]kind of research, both in theory and an
0:41:37.540,0:41:43.030
experiment. And as I said before, a lot of[br]the breakthroughs that we use today for
0:41:43.030,0:41:47.410
building quantum processes were done in[br]very different places like Japan, Europe,
0:41:47.410,0:41:52.690
USA. So it's really, I would say, a global[br]effort. And you should also, when you
0:41:52.690,0:41:58.281
look, when you see this marketing PR that[br]companies like Google and IBM do, maybe
0:41:58.281,0:42:03.869
not believe all of the hype they're[br]creating and keep on down to earth views,
0:42:03.869,0:42:10.950
so to say, of the limits and the potential[br]of quantum computing. So that's it. And I
0:42:10.950,0:42:13.940
would be happy to take on your questions[br]now. And if you have any
0:42:13.940,0:42:19.160
feedback, there's also my Twitter handle[br]and my email address. And I think we also
0:42:19.160,0:42:23.540
have some time for questions here right[br]now. Thank you.
0:42:23.540,0:42:32.430
Applause
0:42:32.430,0:42:37.050
Herald: Thank you, Andreas. We have almost[br]20 minutes for Q and A. If you're leaving
0:42:37.050,0:42:42.560
now, please do so very quietly and if you[br]can avoid it, just don't do it. Thank you.
0:42:42.560,0:42:47.390
Okay. Q and A. You know the game. There's[br]eight microphones in this room, so just
0:42:47.390,0:42:53.580
queue behind them and we will do our best[br]to get everyone sorted out sequentially.
0:42:53.580,0:42:58.490
We will start with a question[br]from the Internet.
0:42:58.490,0:43:01.859
Signal-Angel: Thank you. Do you have[br]information about the energy consumption
0:43:01.859,0:43:07.840
of a quantum computer[br]over the calculation power?
0:43:07.840,0:43:11.729
Andreas: Yeah, that's an interesting[br]point. I mean, for superconducting quantum
0:43:11.729,0:43:16.490
computers, there are like several costs[br]associated. I think right now the biggest
0:43:16.490,0:43:20.970
cost is probably of keeping the system[br]cooled down. So as that you need very low
0:43:20.970,0:43:25.570
temperatures, 20 or 10 millikelvin. In[br]order to achieve that, you need the so-
0:43:25.570,0:43:29.490
called delusion crisis that and these[br]systems that consume a lot of energy and
0:43:29.490,0:43:36.300
also materials like helium mixtures, which[br]are expensive and like maybe not so well,
0:43:36.300,0:43:40.510
kind of like a real material right now. I[br]think that would be the biggest
0:43:40.510,0:43:46.290
consumption in terms of energy use. I[br]honestly don't have so much of an idea. I
0:43:46.290,0:43:50.060
mean, the manipulation of the Qubit system[br]is done via microwaves and the power that
0:43:50.060,0:43:54.070
goes into the system is very small[br]compared to any of the power that we use
0:43:54.070,0:43:58.330
for cooling the system. So I would say for[br]the foreseeable future, the power
0:43:58.330,0:44:02.370
consumption should be dominated by like[br]the cooling and the setup costs and the
0:44:02.370,0:44:06.180
cost of the electronics as well. So the[br]classical electronics that that controls
0:44:06.180,0:44:10.440
the Qubit, which can also be quite[br]extensive for large system. So the Qubit
0:44:10.440,0:44:14.690
chip itself should be very should be[br]really negligible in terms of energy
0:44:14.690,0:44:18.200
consumption.[br]Herald: Thank you. Microphone number one
0:44:18.200,0:44:22.560
please.[br]Mic 1: Hello. I have a question in regards
0:44:22.560,0:44:28.320
to quantum simulation. So I would have[br]thought that with 53 Qubits,
0:44:28.320,0:44:34.900
there would already be something[br]interesting to do, since I think their
0:44:34.900,0:44:41.680
border the limit for more or less exact[br]quantum chemistry calculations on
0:44:41.680,0:44:46.930
classical computers is that there are 10[br]to 20 particles. So is there a more
0:44:46.930,0:44:53.720
complicated relation from particles to[br]Qubits that's missing here or what's the
0:44:53.720,0:44:57.570
problem?[br]Andreas: Yeah. So in the paper I couldn't
0:44:57.570,0:45:02.920
find an exact reason why they choose this[br]problem. I think there are probably two
0:45:02.920,0:45:09.960
aspects. One is that you don't have in the[br]system the like arbitrary Qubit control.
0:45:09.960,0:45:14.940
So to say you cannot run like any[br]Hamiltonian or quantum algorithm that you
0:45:14.940,0:45:18.660
want. You are like limited in terms of[br]connectivity. So it's possible that they
0:45:18.660,0:45:25.100
were not able to run any quantum algorithm[br]for simulation, which was not easy to run
0:45:25.100,0:45:28.810
also on a classical system, you know, so.[br]But I'm really not not sure why they
0:45:28.810,0:45:33.000
didn't. I think just if they would have a[br]have had this chance to do a quantum
0:45:33.000,0:45:36.630
simulation, they would probably have done[br]that instead, because that's, of course,
0:45:36.630,0:45:41.530
more impressive than randomization or[br]randomized algorithms. So because they
0:45:41.530,0:45:45.869
didn't do it, I think it was just probably[br]too complicated or not possible to realize
0:45:45.869,0:45:49.949
on the system. Yeah. Okay. So it's this.[br]But again, I don't know for sure yet.
0:45:49.949,0:45:52.789
Thank you.[br]Herald: Yes, and also speaking as a sometimes
0:45:52.789,0:45:58.270
quantum chemist, you can't directly map[br]Qubits to to atoms. They're not two level
0:45:58.270,0:46:02.880
systems. And you don't I mean, you usually[br]also simulate electrons and not just
0:46:02.880,0:46:07.310
atoms, but I'm not a speaker. We can[br]discuss later. Maybe microphone number two
0:46:07.310,0:46:10.869
please.[br]Mic 2: Thanks. Can you compare this
0:46:10.869,0:46:16.530
classic or general quantum computer to the[br]one by D-wave? That's one of the quantum
0:46:16.530,0:46:22.480
computers by a AWS offered. They have two[br]thousand Qubits or something.
0:46:22.480,0:46:26.050
Andreas: Yeah, that's a very interesting[br]question. So D-wave system is this so-
0:46:26.050,0:46:32.020
called adiabatic quantum computer, to[br]my knowledge. So this in this case the
0:46:32.020,0:46:36.750
computation works a bit differently. It's[br]the normal with this quantum computer that
0:46:36.750,0:46:40.560
Google produced. You have a gate sequence[br]that you run on your input Qubits and then
0:46:40.560,0:46:44.290
you get a result that you read out. With[br]the D-wave system it's more that you like
0:46:44.290,0:46:48.560
engineer like in Hamiltonian, which is[br]also which also consists of local
0:46:48.560,0:46:53.160
interactions between different Qubits. And[br]then you slowly changed this Hamiltonian
0:46:53.160,0:46:58.320
in order to like change to the ground[br]state of the system to a solution of a
0:46:58.320,0:47:02.680
problem that you're looking for. So. So[br]it's a different approach to quantum
0:47:02.680,0:47:09.520
computation. They also claimed that they[br]can can achieve what I did, achieve a
0:47:09.520,0:47:14.270
quantum supremacy, I think in a different[br]way for like an optimization problem. But
0:47:14.270,0:47:19.859
to my knowledge, the proof they have is[br]less rigid probably than, what the Google
0:47:19.859,0:47:23.610
Group produced here. So but again, I'm not[br]like an expert on that, a bit of quantum
0:47:23.610,0:47:29.800
computing. So I'm more like a gate based[br]person. So, yeah, I think though, the
0:47:29.800,0:47:34.570
proof that here the Google show is more[br]convincing in terms of like reproduce
0:47:34.570,0:47:40.300
reproducibility and really make the proof[br]that you are actually doing something that
0:47:40.300,0:47:47.490
cannot be done on a classical computer.[br]D-Wave will see the different view though.
0:47:47.490,0:47:53.850
Herald: All right. Let's go to the back.[br]Number seven, please. Hello. 7. You just
0:47:53.850,0:47:58.630
waved to me.[br]Mic 7: Hey, uh, hello. Uh, I was reading
0:47:58.630,0:48:06.369
that earlier this year IBM released the[br]first commercial Q one system or whatever
0:48:06.369,0:48:11.760
the name is. And you were mentioning[br]before to keep our expectations down to
0:48:11.760,0:48:18.520
Earth. So my question is, what kind of[br]commercial expectations is IBM actually
0:48:18.520,0:48:22.921
creating?[br]Andreas: Mm hmm. So I spoke to some
0:48:22.921,0:48:30.369
companies here in Germany that are[br]collaborating with IBM or D-Wave or Google
0:48:30.369,0:48:35.290
as well. And to ask what they're actually[br]doing with the quantum computers. They are
0:48:35.290,0:48:41.090
the the companies offer. And I think the[br]answer is that right now, a lot of
0:48:41.090,0:48:45.500
commercially, a lot of companies are[br]investigating this as something that could
0:48:45.500,0:48:50.670
potentially be very useful or very[br]relevant in five to 10 years. So they want
0:48:50.670,0:48:54.751
to get some experience and they want to[br]start collaborating. I don't think, at
0:48:54.751,0:49:00.040
least I don't know any reproduction use of[br]these systems where the quantum computer
0:49:00.040,0:49:05.130
would do some calculations, that would not[br]be doable on a classical system. But
0:49:05.130,0:49:08.560
again, I don't have a full overview of[br]that. I think now it's mostly for
0:49:08.560,0:49:12.890
experimentation and forgetting to notice[br]systems. I think the companies or most of
0:49:12.890,0:49:17.260
the customers there probably expect that[br]in five years or 10 years, the system will
0:49:17.260,0:49:21.030
systems will really be powerful enough to[br]do some useful computations with them as
0:49:21.030,0:49:24.520
well.[br]Herald: Thanks. All right. The Internet,
0:49:24.520,0:49:27.270
please.[br]Signal-Angel: With a quantum computer, you
0:49:27.270,0:49:32.260
can calculate things in parallel. But[br]there is this usability requirement. So
0:49:32.260,0:49:36.820
how much faster is a quantum[br]computer at the end of the day?
0:49:36.820,0:49:42.440
Andreas: Mm hmm. Yeah, it's true, so that[br]if you want to and, if you want to realize
0:49:42.440,0:49:46.700
classical algorithm, you have to do it in[br]a reversible way. But to my knowledge, you
0:49:46.700,0:49:51.920
can from an efficiency perspective,[br]implement any classical non reversible
0:49:51.920,0:49:59.210
algorithm as a reversible algorithm[br]without loss in complexity. So you can
0:49:59.210,0:50:02.510
have also like for a reversible[br]computation, you have universal gaits like
0:50:02.510,0:50:07.291
the control not gate that you can use to[br]express any logic function that you
0:50:07.291,0:50:12.580
require. You might need some additional[br]Qubits in compared to the amount of the
0:50:12.580,0:50:16.220
classical bits that you need for the[br]computation. But in principle, there is
0:50:16.220,0:50:20.009
nothing that keeps you from implementing[br]any classical function on a quantum
0:50:20.009,0:50:24.670
computer. In terms of actual runtime, of[br]course it depends on how fast you can run
0:50:24.670,0:50:28.760
individual operations. Right now, a single[br]Qubits operation, for example, on this
0:50:28.760,0:50:34.820
Google machine takes about I think 20 to[br]40 nanoseconds. So in that sense, the
0:50:34.820,0:50:39.010
quantum computers are probably much slower[br]than classical computers. But the idea is
0:50:39.010,0:50:43.109
anyway that you do only really the[br]necessary computations that you can't do
0:50:43.109,0:50:46.450
on a classical machine, on a quantum[br]computer and anything else you can do on a
0:50:46.450,0:50:52.410
normal classical system. So the quantum[br]process in this sense is only like a like
0:50:52.410,0:50:56.990
inside a core processor, like a GPU, in[br]that sense, I would say.
0:50:56.990,0:50:59.850
Herald: All right. Microphone number four,[br]please.
0:50:59.850,0:51:05.270
Mic 4: On the slide that shows Richard[br]Feynman, you said that quantum computers
0:51:05.270,0:51:14.020
were invented to simulate quantum systems.[br]And can you please elaborate on that?
0:51:14.020,0:51:17.760
Herald: You went past, huh?[br]Andreas: Yeah. So I don't have to link to
0:51:17.760,0:51:21.830
the lecture here. Unfortunately, the link[br]is broken, but you can find that online.
0:51:21.830,0:51:27.130
It's a 1982 lecture from Feynman, where he[br]discusses like how you would actually go
0:51:27.130,0:51:32.780
about simulating a quantum system, because[br]as we have shown like the if you want to
0:51:32.780,0:51:36.849
simulate a full quantum system, you need to[br]simulate the density matrix of the system
0:51:36.849,0:51:42.414
and that takes about that take, it takes[br]an exponential amount of memory and
0:51:42.414,0:51:46.849
computation in terms of like the number of[br]Qubits or quantum degrees of freedom that
0:51:46.849,0:51:51.590
you want to simulate. And with a classical[br]Turing machine, you couldn't do that in an
0:51:51.590,0:51:55.980
efficient way because every time you add a[br]single Qubit, you basically quadruple your
0:51:55.980,0:52:00.320
computational requirement. And that's[br]really where the idea came from. I think
0:52:00.320,0:52:04.860
from Feynman to think about a computing[br]system that would use quantum mechanics in
0:52:04.860,0:52:09.109
order to be able to do these kind of[br]simulations, because he saw probably that
0:52:09.109,0:52:13.260
for large quantum systems it would never[br]be possible to run, at least with our
0:52:13.260,0:52:16.190
current understanding of classical[br]computing. It would never be possible to
0:52:16.190,0:52:20.390
run a quantum simulation of a quantum[br]system on a classical computer in an
0:52:20.390,0:52:23.550
efficient way. Does that answer the[br]question?
0:52:23.550,0:52:25.380
Mic 4: Yeah.[br]Andreas: Okay.
0:52:25.380,0:52:28.290
Herald: All right. Microphone eight,[br]please.
0:52:28.290,0:52:35.820
Mic 8: As a physicist who's now doing[br]analog circuit design. I'm kind of
0:52:35.820,0:52:41.620
wondering why all the presentations about[br]quantum computers always use stage zero
0:52:41.620,0:52:45.880
and 1 and not multiple states. Is that a[br]fundamental limitation or is that just
0:52:45.880,0:52:49.530
just a simplification for the sake of the[br]presentation?
0:52:49.530,0:52:52.730
Andreas: So you mean why you don't use[br]like higher Qubit states or like...
0:52:52.730,0:52:57.540
Mic 8: Multi valued logic or even[br]continuous states?
0:52:57.540,0:53:01.330
Andreas: So in principle, the quantum bits[br]that we're using, they don't they're not
0:53:01.330,0:53:05.090
really two level systems. So there is not[br]only level zero and one, but also level
0:53:05.090,0:53:10.520
two tree and so on. You could use them, of[br]course, but the computational power of the
0:53:10.520,0:53:15.609
system is given as the number of states,[br]or like m for example, race to the power
0:53:15.609,0:53:20.240
of the number of Qubits. So M to the power[br]of N. So in that sense, if you add like
0:53:20.240,0:53:26.750
another state, you only change like. Like[br]a small affected and adding another Qubit.
0:53:26.750,0:53:30.550
So it's usually not very interesting to[br]add more states. What he would do instead,
0:53:30.550,0:53:35.380
is just add more Qubits to your system.[br]And for continuous variable quantum
0:53:35.380,0:53:39.660
mechanic quantum computation. I think[br]there is some use cases where this might
0:53:39.660,0:53:43.870
outperform like the digital quantum[br]computers, especially if you can engineer
0:53:43.870,0:53:48.980
your system to like mimic the Hamiltonian[br]of the system that you want to simulate.
0:53:48.980,0:53:54.050
So I think in this sense, in these cases,[br]it makes a lot of sense. For other cases
0:53:54.050,0:53:57.720
where you say, OK, you want to run a[br]general quantum computation, then like
0:53:57.720,0:54:01.179
such a digital quantum computer is[br]probably the best solution. And you could
0:54:01.179,0:54:07.820
also just add that run like a continuous[br]simulation of a quantum system on such a
0:54:07.820,0:54:13.460
gate based quantum system, just like the[br]linearly in the same order of complexity,
0:54:13.460,0:54:17.850
I would say. Does that answer the[br]question?
0:54:17.850,0:54:23.470
Mic 8: I think I delude myself to have[br]understood that the non diagonal elements
0:54:23.470,0:54:28.450
in the density matrix grow much faster[br]than the number of states in any and any
0:54:28.450,0:54:32.170
diagonal matrix element.[br]Andreas: I guess you could say like that.
0:54:32.170,0:54:37.530
Yeah, I have to think about.[br]Herald: All right. Number three, please.
0:54:37.530,0:54:43.320
Mic 3: What do you have to say about the[br]scepticism of people like Nikolai that
0:54:43.320,0:54:51.100
claim that inherent nice will be a[br]fundamental problem in scaling this
0:54:51.100,0:54:54.820
quantum computers?[br]Andreas: I mean, it's a valid concern, I
0:54:54.820,0:55:01.410
think. As of today, we don't have even for[br]a single Qubit shown error correction.
0:55:01.410,0:55:04.840
There are some first experiments, for[br]example, by the ShowCoup Lab in Yale that
0:55:04.840,0:55:08.970
showed some of the elements of error[br]correction for a single Qubit system, but
0:55:08.970,0:55:15.230
we haven't even managed today to keep a[br]single Qubit alive indefinitely. So that's
0:55:15.230,0:55:19.220
why I would say it's an open question.[br]It's a valid criticism. I think the next
0:55:19.220,0:55:23.160
five years will show if we are actually[br]able to run this quantum errors and if our
0:55:23.160,0:55:26.310
error models themselves are correct[br]because they only correct for certain
0:55:26.310,0:55:30.809
errors or if there's anything else that[br]keeps us from like building a large scale
0:55:30.809,0:55:35.400
system. So I think it's a totally valid[br]point.
0:55:35.400,0:55:40.990
Herald: Microphone five, please.[br]Mic 5: There has been a study on
0:55:40.990,0:55:48.830
factarising on adiabatic machines, which[br]requires a lock squared N Qubits while
0:55:48.830,0:55:58.260
Shor requires Log N. But as the adiabatic[br]systems have much higher Qubit numbers,
0:55:58.260,0:56:05.140
they were able to factorize on these[br]machines, much larger numbers than on the
0:56:05.140,0:56:11.870
normal devices. And that's something that[br]never shows up in the discussion. Do you
0:56:11.870,0:56:17.320
want to comment on that? Have you read the[br]study? What do you think? Are adiabatic
0:56:17.320,0:56:23.200
machines, bogus? Or, is that worth while[br]resolved?
0:56:23.200,0:56:26.130
Andreas: I'm not. Yeah, as I said, like an[br]expert at adiabatic quantum
0:56:26.130,0:56:31.980
computing. I know that there were some[br]like studies or investigations of the
0:56:31.980,0:56:37.690
D-wave system. Like I haven't read this[br]particular study about factorization. I
0:56:37.690,0:56:40.940
think adiabatic quantum computing is a[br]valid approach as well to quantum
0:56:40.940,0:56:48.520
computing. I just I'm not just just not[br]sure if currently like the results were
0:56:48.520,0:56:54.849
like shown with the same amount of like[br]rigidity or like rigid proves like for the
0:56:54.849,0:56:58.380
gate based quantum computer. But yeah, I'm[br]I really would have to look at the study
0:56:58.380,0:57:02.730
to to see that.[br]Herald: Can you maybe quickly say the
0:57:02.730,0:57:09.270
authors. So it's on the record. Yeah. If[br]your mike is still on number five.
0:57:09.270,0:57:14.140
Mic 5: Sorry, I don't.[br]Herald: Okay, no problem. Thank you. All
0:57:14.140,0:57:15.790
right.[br]Andreas: But yeah, I don't think adiabatic
0:57:15.790,0:57:19.660
quantum computing is like and I[br]think adiabatic quantum computing is a
0:57:19.660,0:57:24.190
valid choice or valid approach for doing[br]quantum computation as well.
0:57:24.190,0:57:29.339
Mic 5: So I can give you that. I can[br]search for the authors later and give it
0:57:29.339,0:57:30.759
to you.[br]Andreas: Okay. Okay. It would be great.
0:57:30.759,0:57:33.029
Thank you.[br]Herald: Thank you. Microphone four,
0:57:33.029,0:57:36.199
please.[br]Mic 4: What do you say about IBM's claim
0:57:36.199,0:57:41.100
that Google's supremacy claim is invalid[br]because the problem was not really hard?
0:57:41.100,0:57:45.840
Andreas: Yeah. So basically IBM, I think[br]said, okay, if you do some optimizations
0:57:45.840,0:57:49.810
on the way you simulate the systems, then[br]you can reduce this computation time from
0:57:49.810,0:57:55.290
10000 years to like maybe a few hours or[br]so. I think it's, of course, valid. It
0:57:55.290,0:57:59.910
might be a valid claim. I don't know if it[br]really invalidates the result because as I
0:57:59.910,0:58:04.760
said, like the computational power of like[br]the classical systems, they will also will
0:58:04.760,0:58:09.700
also increase in the coming years. Right[br]now, you could say that maybe if we
0:58:09.700,0:58:14.839
haven't achieved quantum supremacy in[br]regards to elect 2019 hardware, then maybe
0:58:14.839,0:58:19.220
we should just like look at the 2015[br]hardware and then we can say, okay, there,
0:58:19.220,0:58:24.369
probably we achieved that. In any case, I[br]think the most what's most impressive
0:58:24.369,0:58:28.930
about this result for me is not like, if[br]we are really in the supremacy regime or
0:58:28.930,0:58:34.200
maybe not. That's really the amount of..,[br]the degree of controlability of the
0:58:34.200,0:58:37.290
Qubits system that this group has[br]achieved. I think that's really the
0:58:37.290,0:58:40.920
important point here, regardless of[br]whether they actually achieved the
0:58:40.920,0:58:46.190
supremacy or not. Because it shows that[br]these kind of systems seem to be a good
0:58:46.190,0:58:50.250
architecture choice for building large[br]scale quantum processes. And this alone is
0:58:50.250,0:58:54.680
very valuable, I think, as a guide to[br]future research direction, regardless of
0:58:54.680,0:58:59.750
whether this is actually, you know, they[br]achieved this or not. Yeah, but yeah, I
0:58:59.750,0:59:05.760
can understand, of course, the criticism.[br]Mic 4: OK. One thing. The article is
0:59:05.760,0:59:11.099
called Quantum Annealing for Prime[br]Factorization appeared in Nature in
0:59:11.099,0:59:18.739
December 18. Authors Jiang, A. Britt, Alex[br]J. McCaskey, S. Humble and Kais.
0:59:18.739,0:59:22.190
Andreas: Okay, great. I think we'll have a[br]look at that again. Thanks.
0:59:22.190,0:59:25.359
Herald: All right. Microphone 6, do you[br]have a short question?
0:59:25.359,0:59:33.990
Mic 6: Yeah, hopefully. It is known that[br]it is not very easy to understand how
0:59:33.990,0:59:41.000
large quantum superposition goes into a[br]macroscopic state. So in the macroscopic
0:59:41.000,0:59:47.340
physical description. So apparently there[br]are a couple of things not understood. So
0:59:47.340,0:59:51.970
is there anything you know about when you[br]go two thousand, ten thousand, million
0:59:51.970,1:00:00.310
Qubits, could you expect the quantum[br]behavior to break down? Are there any
1:00:00.310,1:00:07.150
fundamental argument that this will not[br]happen or is this not a problem considered
1:00:07.150,1:00:09.760
recently?[br]Andreas: Huh, Okay. I'm not sure if I
1:00:09.760,1:00:13.089
fully understand the question. It's mostly[br]about like if you say like quantum
1:00:13.089,1:00:17.820
mechanics or some like scale variance so[br]that if you go to a certain scale and some
1:00:17.820,1:00:22.160
time, at some point you have like a[br]irreversibility or like a something like
1:00:22.160,1:00:27.010
that. Yeah. I mean, I think that a large[br]quantum systems that occur naturally, I
1:00:27.010,1:00:30.210
don't know. I like Bose Einstein[br]condensate, for example, has a lot of
1:00:30.210,1:00:33.640
degrees of freedom that are not[br]controlled, of course, but that also
1:00:33.640,1:00:39.420
quantum mechanical and there it seems to[br]work. So personally, I would think that
1:00:39.420,1:00:43.780
there is no such limit. But I mean, who[br]knows? It's like that's why we do like
1:00:43.780,1:00:47.960
experimental physics. So we will see as if[br]we reached it. But from like the theory of
1:00:47.960,1:00:52.099
quantum mechanics right now, there is no[br]indication that this should be such a
1:00:52.099,1:00:55.670
limit to my knowledge. [br]Herald: All right, so maybe we will see
1:00:55.670,1:00:57.870
you again in five years.[br]Andreas: Yeah.
1:00:57.870,1:01:00.490
Herald. So please thank Andreas, until I[br]ask once again. Thanks.
1:01:00.490,1:01:02.184
Applause
1:01:02.184,1:01:05.654
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1:01:05.654,1:01:28.000
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