字幕列表 影片播放 列印英文字幕 [MUSIC PLAYING] JOE BARDIN: Welcome to virtual March meeting. Today, my talk is about the control of transmon qubits using a CMOS integrated chip operating at cryogenic temperatures. Outline of my talk is as follows. I'm going to start by explaining how transmons are controlled. I'm really just going to review this. I'll review what transmons are, how we control them, what the considerations in terms of control are. Once we have the basics down, I'll go over how people do this today, what kind of hardware is used, and really importantly, why it's not scalable to future fault tolerant systems. Once I've motivated the work, I'll present the design and implementation of a cryo-CMOS controller followed by experimental characterization. So this is a basic diagram of a transmon qubit. The qubit itself is made up of a nonlinear LC resonator. Here we have, instead of just one Josephson junction replacing the inductor in a parallel LC resonator, we have two. This is a squid, which acts as a flux tunable nonlinear inductor. You can tune the effective value of this inductance through an external bias that threads a flux through the loop. We also have an XY drive port on here, which we can use to couple energy at the resonant frequency of the qubit into the circuit. It turns out if you turn-- you cool this down to temperatures low enough, such that thermal energy in the environment is lower than the effective photon of a-- or effective temperature of a photon in the resonator, then it behaves quantum mechanically. And its nonlinearity gives us a really nice feature called anharmonicity, which means that the spacing between each of these levels is different. What that means is that, if we want to drive from the 0 to 1 state, we want to drive at omega 01. If we want to go from 1 to 2 or back, we drive at omega 1, 2, and so forth. And all these are different frequencies. The more nonlinear the qubit is, the more-- the bigger the differences between each of these spacings, and the easier it is to address an individual spacing. So if we can constrain our drive signals to just omega 01, then we can just address the 01 subsystem, and it behaves as an ideal 2-level qubit. So the transmon qubit is this circuit, and when we operate it, we typically want to be in just a 01 subspace, which means our drive signal at the RF port needs to be bandlimited, such that we don't hit omega 12. To put some numbers on this, typical frequencies for omega 01 are 4 to 8 gigahertz, which means that we really need to cool to the 10 millikelvin range so that we have sufficiently suppressed thermal noise in the resonator. And our anharmonicity, or difference between omega 01 and omega 12 expressed in hertz is about 150 to 350 megahertz. As I'll mention shortly, this is an engineerable parameter, as you see here based on the C in the resonator. If we write the Hamiltonian system in the lab frame, we find we get this form. You have two terms. First you have, this sigma Z term, which is describing a natural rotation about the negative z-axis at the qubit frequency. And then you have a drive term due to this-- this drive source here. And that causes a rotation around sigma y. If you look at what's going on, you see that this term is causing it to rotate around the negative z-axis. Whereas this term is causing a y rotation. We usually like to think about it not in the lab frame, but in the rotating frame. So if we write the rotating wave approximation, we get a slightly different expression, but we no longer have the sigma z rotation, and things are easier to think about. So if we drive at omega 01 with sine omega 01t and a phase pi minus phi d, where this as a controlled variable and some envelope of function, we find that the Hamiltonian looks like this. And we have a sigma x and sigma y term, and their weights are dependent on the phase of this carrier signal. So if we control the carrier signal, we control the rotation about sigma x and sigma y, or the rotation about some axis, which axis the vector we're rotating about is. It's going to be in the x, y plane, but we can control where it lies. And the amount of rotation is determined by the envelope. So we can set this envelope to determine how far we rotate. And we can set the phase, as I mentioned before, to set which axis we rotate about. So basically, when we design our control pulses, we want to engineer these things to get what we want. So how do we pick the envelope? Well, there are a couple of considerations. We have a finite coherence time. For transmon qubits, this might be 50 microseconds. It might be shorter, depending on what the exact circuit is, but we can engineer this anharmonicity by choosing c. Larger anharmonicity means we can have more bandwidth in our pulses, which means we can make them quicker. So we'd want smaller c to do fast gates. On the other hand, the dephasing time, T2, is determined by the frequency fluctuations of the qubit, and we want to be insensitive to charge noise so that, if we move around-- if our charge moves, then the frequency doesn't jitter and-- causing dephasing. So it turns out what the beauty of the transmon is, if you put a big capacitance, you really desensitize yourself to the charge. You really flatten these curves out, and so charge noise doesn't hurt you as bad. So there's these conflicting design criteria. You want a small capacitor for nonlinearity. You want a big capacitor for large T2. Because of this, we typically end up with 150 to 350 megahertz range for our anharmonicity, which gives us single qubit gate times in 10 to 30 nanoseconds range. And we have coherence times typically 30 to 100 microseconds. So how do we actually shape the pulses? Well, we want to avoid the omega 12 transition. We want the pulse to be as quick as possible. If were to use rectangular pulse, we'd get this sink side lobes. And we-- it doesn't roll off very fast. We want to do something more clever than that. Gaussian pulses have been quite popular for a long time. You usually have to truncate them or have some limiting function you multiply them with so that they don't go on for all of infinity, because a Gaussian never really ends. Another kind of convenient pulse that has well-defined start and stop sign-- start and stop time is the raised cosine you can see here. And you can see the spectrum of all these different pulses. So the Gaussian is without a limiting function, so it would pick up some side lobes also, but you can see both the Gaussian and raised cosine roll off much quicker and allow us to-- because of that, we can do much quicker pulses than if we were just using rectangular shaping, as you might do if you were driving, say, a spin qubit. So in this work, we'll use raised cosine, but I do want to acknowledge Gaussian, as well. Is this all we want? Even with this raised cosine, we'd still like to make the pulses as short as possible. So people like to do things like second order shaping. In addition, as you drive the qubit, it's a nonlinear thing. Its frequency changes. So depending on, if you want to drive a pi pulse, 180 degree rotation, or a pi over 2 pulse, which is typically half the amplitude, you might need to drive at a different frequency for the two. So there's a stark shift that you might need to compensate. So to get rid of-- so one thing that's used is drag. Drag-- we put in a derivative term that's weighted. This is in quadrature if you want to think in the microwave terms. So you have a sine and a cosine carrier term. And if you do it right, with drag of 1 you get a notch at some frequency that you can set. If you set that at omega 12, you can avoid the omega 12 transition by adding this extra modulation tone. And typically there is-- you also want to do an amplitude dependent offset to compensate the stark shift. When you see the work we've done, we haven't done this more advanced shaping, but we'll-- it's something for future work. So I wanted to introduce it anyways. So a couple practical issues-- how strong should these pulses be? I could go through all this math, but essentially you're going to end up integrating the envelope amplitude, and you're going to find, when you get out, some-- for a raised cosine pulse, some level. And it's typically, depending on if you're raised cosine, Gaussian, other types here, or rectangular, you're somewhere in the 50 to 500 microvolt pulse amplitude at the port of a qubit. Now, we need to really lightly couple the qubit, because we don't want it to cohere the qubit through coupling to our 50 ohm source. So you're typically using [INAUDIBLE] farrad type capacitor to couple. So you're very weakly coupled, and only a small fraction of the energy that's available at that port makes it. Just to put some numbers, this is maybe negative 65 DBM, negative 70 DBM of power available at that port, but it's attenuated by about another 30 dB before you get to the qubit. Sorry, another 60 dB, not 30. Another important thing is how much noise can there be on the drive line? Noise here will cause up down transitions, which will hurt your coherence. We really don't want this. So you can write an expression. I've written it in a way that looks nice to microwave engineers, where the rate is the bandwidth over which you couple times the ratio of the effective temperature of this resistor, assuming it's going to put out white noise, thermal noise, to the temperature of a photon at the qubit frequency. That's-- at 1 gigahertz, a photon will be 50 millikelvin. At 5 gigahertz, it would be 250 millikelvin. I already said these. We can plug in for this, the delta omega. It's the ratio of the qubit frequency, the omega 01 to the effective q due to the drive circuit. So if the only thing dequeueing the qubit were the drive circuit, that would be this value. And this is-- inversely, this is 1 over the t1 due to the drive circuit. We typically set that to be about a millisecond, which corresponds to a q of about 40 million for a 5 gigahertz qubit. You can do some simplification, and if you were to set this 1 over the rate of transition, so effectively how much your qubit de-coheres due to the noise on this line, and make that equivalent to how much the qubit relaxes due to damping by this resistor, if you make those two things equal, you find the amount of noise you can take on the driveline is one photon worth of noise. That's independent of the coupling, so it's an easy thing to remember-- is that we really want to have thermal noise on here equal or less than the equivalent photon energy. We cool these things to 10 millikelvin so we can take a little bit more noise than just the noise-- the thermal noise of the attenuator-- actually, quite a bit more, because it's exponentially suppressed with cooling, but not that much more. So that's the basics. How is it done today? What kind of hardware do we use, and why do we want a different approach? This is a block diagram of the basic configuration of Google's electronics from a high picture. I've highlighted the x, y drive, because that's what this talk is about. You can see that the one channel-- this is driving one qubit-- has two decks. We use in phase and quadrature modulation due to the single side band mixing. So we create two side bands. We up convert it, filter, attenuate quite a bit. Let's see, 43 dB of attenuation, so roughly the ratio of temperature. Actually, not quite, but-- and then a couple of the qubit. So if we're doing a big experiment, I would say, at least that where we are right now, this is the right way to do things. My philosophy is that we should do things brute force until we can't, because getting the qubit physics sorted out and everything is more important than integrating electronics and doing the electronics in the most scalable manner when we're just carrying out basic experiments. So I would say this is the right way to do a small scale experiment, like 100 qubits. But we still require-- so this is 72 qubit. It's not the quantum supremacy chip, but it's another chip that we're measuring before. 72 qubits requires 240 AWGs, 84 up converters, 12 down converters, 24 high speed ADCs, 160 coaxes to the cryostat, 168 coaxes down superconducting. These are not cheap. There was an article in "Tech Review" a couple months ago about this shortage of these. And something that I think is really crazy is it takes 3 terabits per second. Now, these are narrowband pulses. They're not broadband. There's not that much information in the pulses, and yet we take 3 terabits a second to continuously drag this thing. So for small scale demo, I think this is the right way to do it, but we need to think about other things as we're moving forward. What is the ultimate end game? Well, this is essentially where we are now. This is a 72 cubic processor. We're just on the cusp of being able to do things you can't do with a classical computer. In fact, just within the last couple months. But our long term goal is to be over here. And at least if we're using transmon qubits with their associated error rates, and we want to do something like surface code, we're going to need a million of these qubits. And we need to find some way to make this connection. So how are we going to get from here to here in terms of control? So this is where we are. This is-- I'm going to use 54 qubits as a number, and you can see this isn't even all the cables you'd have. If we want to scale to a million or so using this, what does it look like? Well, this is one. If we scale to-- you could see all the cables in here. Not much extra room to put stuff if we do things exactly the same. So if we want to go to 540, I'm just making a point here how much we-- how far we need to go. 8,000, 13,800, a million-- that's how far we are in terms of building systems from where we want to go. Clearly we have to do something different. So how do we do things today? We have classical computer, high speed digital bus-- that's where that 3 terabits a second was going. We have racks of equipment, coax cables going to the cryostat down to the chip. This is good for 72. It's probably good for 500. It might be good for 1,000, but it's not good for a million. One approach-- and this is not the only approach is to take this part and bring it a lot closer to the qubits. And then we have to figure out how, say, if we put it at 4 kelvin, we have to figure out how to get down to the qubits, but we might be able to use superconductors for that. At 4 Kelvin, we can get quite a bit cooling capacity. With a standard cold head, you can get a watt and a half. If you do something closer to what CERN does, you can get kilowatts. So it's not that outlandish to think about cooling large arrays, but we need to make these low power and scalable. And then we need some really reduced data set going to the classical computer, and all the error correction layers, and so forth. So here we're thinking about how can we simplify x, y control, and before showing architecture-- the architecture we've used, I want to make a point-- is that this is really a brute force approach. We're using high speed DACs to generate narrowband signals. And these DACs, if you look at the data sheets, are able to generate-- this is an example. It's a little bit higher speed DAC than what we're using, but it's just one that's available from analog devices. And this is an example of a spectrum from basically DC to 900 megahertz, where they populate it with 157 modulated tones, and they left a dead band in the middle. Now, if you're working in communications, this is important, because you don't want these different signals to have inter modulation products with each other and fill in this space, which would give interference if you were trying to use that gap for a signal. So they make these DACs really high performance to be able to do things like that, because that's really the driving market for a lot of these DACs in terms of development. The cost is that they're very power hungry, and they don't optimize things like data rates and so forth. So it can do this, but we just want to do this. We just want to have a nicely shaped spectrum that we can control. And I would say that this is really overkill, and if we want to have scalable systems, we need to find some other way to do it. And this talk is really-- the work we're going to show is really a first step. So what were our goals here? Well, long term, we have a set of goals here, and then we have some goals for this initial work. And we really relax the specs a bit because we've designed this controller without models to figure out how the transistors are going to work cold. So we had some headroom for that. So for our initial work, we want to work at about 3 kelvin. We want to be in a couple milliwatt power consumption range, which is about three orders of magnitude lower than that chip I showed on the previous slide. We'd like to operate over a broad frequency range. It could be more fine tuned for a more permanent solution. We'd like to have about 10 milliamps-- or millivolts of amplitude so that we have margin, because we're designing it without real good models, and we might have less in the end if we don't over design. We'd like to be able to pick a couple well-defined wave forms and play them back rather than sending a continuous stream. So we pick four bits, or 16 wave forms. It'll be able to operate in a 10 to 30 nanoseconds pulse duration, not hit the 1 to 2 transition, and have performance that is able to hit the fidelities needed for error correction. So just a bit of a spoiler is that we weren't actually able to characterize these last two, and that's work in progress. So first, I'd like to explain that the approach we took to wave from generation. So it's much different than the approach that you would take if you were just making a DAC. So basically, what we realized is that, if we don't try and do things like drag, we just need a symmetric envelope. Raised cosine or Gaussian-- they're both symmetric. So what we did was we built an array of programmable current sources, and then have the appropriate enabling functions to create this kind of wedding cake shaped current wave form. And so we can program the amplitudes and so forth. And if we filter this, we get rid of the steps, and it looks like a nice, smooth, symmetric envelope. So this gives us the e of t. We then need to put it on a carrier. So we have a mixer to do that. We have an off chip-- a low signal and a limiting amplifier to drive the mixer. And then we have some filtering to give us-- to get rid of the harmonics and end up with a nice modulated signal. So this is all fine and good. We could control-- but we don't have phase control here. So we need to add another quadrature to get phase control so that we can do vector modulation-- sine plus cosine. If you weight the two, you can give an arbitrary carrier phase. And if we don't do anything else, if we just have a quadrature, we only get 90 degrees. So we have to add a polarity switch so that we can do plus and minus in each quadrature to get the full 360. So that's the full picture here. We generate the quadrature carriers off chip for simplicity, but that can be put on chip in the future. So this is the part I already described. In addition, we have this wave form memory that can store 16 different wave form configurations. And then we have four select lines to pick them, and a trigger signal to enable a pulse. So I'll go quickly. This is not a circuits conference, so I won't spend too much time on circuits, but there's a state machine to generate those pulse wave forms. That just turns on the current sources. Turns this one on, and this, this, this, then goes backwards down the current sources, so you get an increasing pulse. This has a nice feature, doing it this way, is that if we just try to change-- take one of these and use it to make it, and turn it up, and up, and up, then back down, we might have issues where we're non-monotonic. That is, if we set it, say, halfway to full scale then move up, it might actually move down because of things that go wrong when you cool. By doing this kind of thermometer turning on like this, then turning back down, we get guaranteed monotonicity, which is nice in the pulse. Each of these current sources has 8 bits of control, which is a little less than the 14 bits that are typically used in a DAC, but we have enough degrees of freedom that we can make a wide range of wave forms to compensate for that. After creating the staircase current, we modulate it on to a carrier. We want to be very careful, because we're trying to get as low power as possible. We want to be very careful to not dissipate a lot of power on the LOs. So this-- we have an amplification chain that is really optimized for power consumption to dissipate something like 100, 200 microwatts per channel. There's a tunable balun and a differential stage. This is made with what are called standard cells mostly, and then there's a mixer. There's that polarity switch to switch which way currents went through the mixer. So currently the route-- let's say polarity is high. It'll go this way, and then say like this-- back down to here, or it'll go the other way, depending on how the polarity switches are set. And then we couple out and combine in the current domain at the output. The chip was made a 28 nanometer CMOS process. You can see the critical things, the transformers, The DACs are quite small. In fact, this chip is-- it could be a lot smaller. It's bond pad limited. That is, we're limited by I/O, not by the chip periphery. All this is empty. This is more or less empty. We packaged it. You can see it's mounted, and I cut out on a printed circuit board to keep the RF lines really short. The clock's coming over here, and then there is digital programming supplies coming off the sides. It's matched to 100 ohms, so we have a Klopfenstein taper transforming that to the output. The yellow signals come in here and here. As you can see, that's pretty tight, and there might be some coupling from here to here, and here to here. We're driving the qubit on resonance, so that could be a problem. So we need to take care of that externally for this chip. In the future, you could cancel that out on chip, actually. So we packaged it. Tested it first at room temperature. This is an example where we're driving the qubit with an RF of 5.6-- or the chip with an RF of 5.6 gigahertz, negative 10 DBMs, so 100 microwatt of RF signal. Clock at 2 gigahertz and negative 20 DBM clock signal. So this is going into the quadrature hybrid external. This is going into an external balun. So any losses haven't been taken out. And you can see this is going through the 16 different wave forms. These are just kind of arbitrarily wave forms, like stepping here, and I think one of these is Gaussian. One is raised cosine, and so forth. So we could get wave forms like this up to eight gigahertz RF, even beyond a little bit, and with up to 3 gigahertz clock. So once we tested it at room temperature, we want to test cold. This is the basic setup for how the chip was mounted. We have-- in the Google software back end, we have some interfaces to the chip. We used digital AWGs, so just putting out switching wave forms to connect to the trigger and select. We use a microprocessor to send the SPI to program the chip. And then we clock it with a CW source and provide the carrier with another CW source so that the carrier splits here, and I'll explain why in a second. So at the output of the chip, we have two couplers, and I'll explain the function of these momentarily. Then it goes to a 20 dB pad. We had a little too much power, and so we had this. Then we have another 20 dB cold so that we reduce the thermal noise, because 3 kelvin, of course, is too much. So these couplers are used. The second one is so that we can couple a signal out to monitor at room temperature, which is quite useful, to make sure the chip is working as expected. Then the other one-- we have a vector modulator. We go and recombine, and that's to cancel out any LO leakage so that we're not driving Rabi oscillations unintentionally. We also hooked up the standard qubit electronics through this path so that we could do baseline measurements. Finally, we completed the setup with the z control, frequency control the qubit. And a readout chain so that we could make measurements. So once we got this all set up, the first thing we wanted to do is make sure that LO leakage, which we expected to happen and would drive Rabi oscillations, is negligible. Well, first, we looked at the wave forms at the monitor port. You see that you don't get that much information from that, because we have coupling, and it's weak signals to start with. You don't have much signal to noise, but these are typical signals that would be using a gate operation. So that's the first thing to look at. Next, we looked at feed through cancellation. So canceling out those Rabi oscillations that would happen because of LO feed through. So the way we did this was we first reset the qubit to the ground state. Then we waited for a certain amount of time and made a readout pulse-- applied a read out pulse and measured the state. We varied this delay so that we could trace out any kind of Rabi oscillations. And before we applied any cancellation, we saw this kind of chevron curve. And so for this, the qubit was set about here as the qubit frequency. And you can see clear Rabi oscillations, so something like a period of about 300 nanoseconds, which is pretty quick. So this is kind of really not desirable. It would really mess our experiments up. So we applied-- so we play with the vector modulator, and we're able to [INAUDIBLE] all this out. You can see now this timescale is 500 nanoseconds. This is 20 microseconds, which is longer than the coherence time of the qubit. And you see really negligible one state population at the end, something like 4%. So the cancellation worked, and this was actually stable over the course of days. So it's practical. And as I mentioned, you could just add another channel. We have a vector modulator. You could just add another channel of control to put this on a chip. Once we cancelled out the LO feed through, we did Rabi experiments. So where we just applied an x pulse of varying amplitude. So we're doing a Rabi amplitude experiment, then a read out pulse. What you'd expect from this, of course, is sinusoidal oscillations, and what we saw when we just swept using the raw DAC codes was something like this, which really doesn't look nice. So for this, we were sweeping the overall envelope amplitude, which is controlled by a current source, which turned out to be non-monotonic. So the reason you see all these wiggles is not because the measurement was noisy, but actually because the DAC was not increasing linearly. It was going up and down. And so what we did was we used a spectrum analyzer and measured the power at the monitor port to calibrate this axis. And once we did that, you can see all of a sudden it really cleaned things up. We view this as OK. We have to do calibration in a system like this anyways, and what really matters is you can find a point, say, right here. So this experiment kind of showed that we can control the envelope amplitude. We haven't said anything about phase, so we did another experiment that's similar to a-- that helps bring out the phase. So what we did here was we reset the qubit, then applied three pulses. So these are x pulses that-- with varying amplitude. Then we applied a pi over 2 pulse around-- with varying phase. And then we read it out in the end. And if you simulate and figure out exactly what should happen, the probability of finding a qubit in the zero state at the end looks something like this, where you get this-- these peaks. So we then ran the experiment with standard and our hardware, and found-- this is what we got at the standard hardware. It looks almost identical to that last plot. Ours was a little more fuzzy. We attribute this to the fact that we didn't calibrate the amplitude for this-- of the pulses. But nonetheless, the general shape is still there, and the peaks are about the same between the two curves. So this-- we view as showing that we have coherent control. If you look kind of more proof of coherent control is that, if you look at the residuals between the ideal curve and what we measured, this is standard this is the CMOS chip. And you can see there's really structure in here. That is, there's this bright part here, this dark part here, which is kind of indicative that we could calibrate it out. Then we measure two state population. This is to characterize, do we have more bandwidth than we're expecting or something like that. Are we driving two state? What we did for this was applied a bunch of pi pulses, and at the end measured the probability of being in a two state. We swept the pulse duration from 70 nanoseconds down to about 6 nanoseconds. And we saw, as expected, not much two state population until we got really short pulses. So this is doing about what we'd expect. Finally, we want to make sure we weren't blasting the qubit with noise. That's a concern, given that we have active current sources. And we so we measured T1, and we got almost identical curves within the measurement error for the standard and custom hardware. So a comparison is shown here. Really the critical things are that our chip was less than 2 milliwatts. The standard approach is a watt. 2 milliwatts is even getting close to where you can think about cooling down large numbers of these. The data rate required to control the chip-- we had to send those four control lines. We had to send a trigger, so it all adds up to about half a gigabit per second. It's about 50 times lower than the standard solution, although you can make it a lot lower just by putting a sequencer on chip without much extra power. So in summary, if we're going to build big systems, we're going to need something like this. This isn't the only way to do it, but cryogenically cooled controllers is one option. We've demonstrated one with two milliwatts of power, or actually less than that. In the future, we need to-- if we're going to make more of these, we really need a random-- perform randomized benchmarking and really quantify the actual fidelities we can achieve. And if people want more information, there's an open access paper with all the details. And the link is here. So if you want information, pause it. I'd like to end with just a picture of the team. A lot of people contributed to this work through the measurements or the hardware, software stack, and so forth. So I'd like to acknowledge the team. All right, thank you. [MUSIC PLAYING]
B1 中級 使用低溫CMOS集成電路(QuantumCasts)控制傳蒙量子比特。 (Control of transmon qubits using a cryogenic CMOS integrated circuit (QuantumCasts)) 7 0 林宜悉 發佈於 2021 年 01 月 14 日 更多分享 分享 收藏 回報 影片單字