MARISSA GIUSTINA: Quantum computing--

it's been all over the news lately, often

accompanied by an air of mystique

or an assortment of fantastic promises.

But what does "quantum" mean in the context

of computer hardware?

What distinguishes a quantum computer from a regular one?

What does a quantum computer look like?

How do we build it?

My name is Marissa Giustina, and I'm

a research scientist in the Google AI Quantum Hardware Lab.

I'd like to unpack those questions.

And hopefully, in about five minutes,

the term "quantum computer" will have just a little more meaning

for you.

We're working to build devices that we can interact with.

That is, devices we can control and read out,

which behave reliably according to a simple quantum model.

In other words, we're building quantum computing hardware.

Quantum hardware can be used as a tool

for approaching certain kinds of computational problems.

So our ongoing efforts are both to develop the hardware

and to develop algorithms that leverage this hardware.

Let's start with the first question.

What does it mean for hardware to be quantum?

For that, we'll talk for a moment about quantum mechanics.

A model is the physicist's tool to make predictions

about what will happen when we put

the universe into a certain configuration

and poke it in a certain way.

For example, if you'd never built a skyscraper before,

you might make a Lego version before building it full scale.

That's a model.

Models can also be expressed in the language of mathematics.

The most fundamental model of nature we know

was developed in the early 20th century

and is known as quantum mechanics.

The word "mechanics" refers to the mechanisms

by which things happen.

The word "quantum" refers to discrete quantities

of energy or some other physical quantity.

Within quantum mechanics, energy comes in packets,

sometimes called photons.

And you cannot have fractional packets.

So what's a quantum object?

People sometimes think of a quantum object as being tiny

and a quantum leap as being large.

However the word "quantum" doesn't

dictate an object's size.

Actually, a quantum object is one

that relates in a well-defined way

to a single quantum of energy.

For instance, the photon I mentioned before is a quantum

object.

A photon is a single particle of energy.

Similarly, atoms are quantum objects.

An electron flying around an atomic nucleus

may be excited into a higher orbit

only by a particular quantum of energy.

There is no halfway point between the lower

orbit and the upper orbit.

If the wrong energy is provided, there simply

isn't a corresponding orbit for the electron to land in.

In a nutshell, a quantum object is one whose observable

behavior reflects that nature only offers

energy in discrete packets.

Now onto the next question.

What differentiates quantum computing hardware

from a regular computer?

In essence, quantum hardware lives

in a richer world than its conventional counterpart.

Let's consider a simple, abstract, quantum object,

which is entirely described by the fact

that it can be in one of two different energy levels.

Let's call those levels 0 and 1.

You can interpret those brackets around the 0

to mean this is a quantum energy level called "0."

And likewise for the "1."

Here, for example is a quantum energy state named "psi."

Recall the classical bit of information, a switch that

can take one of two values--

0 and 1.

Because of the apparent similarity between our quantum

object and that classical bit of information,

we call this quantum analog a quantum bit, or qubit.

One peculiar feature about quantum mechanics

is the existence of superpositions.

A superposition is like a special mixture

of the energy levels 0 and 1, where the weight of each energy

level is given by complex constants C0 and C1.

If we measure the energy of our qubit,

we will sometimes observe 0, and sometimes 1,

where the value of sometimes is given by the constants.

An individual measurement will yield an outcome of 0 or 1.

There are no other options.

But before the measurement occurs,

we know at most the chances of getting a 0 or a 1.

We can't know the actual outcome for sure until we measure it.

Therefore, when we want to talk about the energy

state of the qubit before we've made the measurement,

we use this superposition to represent that the qubit hasn't

decided yet which outcome to display,

even though the chances of getting each outcome are fixed.

Now, even admitting that this superposition business

is a little unusual.

We can accept that it's easy enough to represent one qubit.

We just wrote it down right there.

Thinking about more qubits gets increasingly difficult.

Suppose we add a second qubit.

If these were conventional switches,

we could think about each switch independently.

But qubits are different.

Just as one qubit can be in a superposition state,

two qubits can share a superposition state,

where, for instance, the measurement outcome

is unknown, but will certainly be the same for both objects--

or opposite for both objects.

For example, here's a state where

a blue qubit and a yellow qubit are together

in a superposition state.

Here, they're correlated to each other.

Before the measurement, it cannot be known whether

the blue qubit will turn up 0 or 1.

But a measurement of both qubits will certainly always give

the same answer for each.

Similarly, in this case, measuring the blue and yellow

qubits will always give opposite outcomes.

This means that in order to fully describe two qubits,

we need to consider C's for all possible measurement outcomes

we could see.

To describe three qubits, we need eight C's.

Describing four qubits takes 16 C's, and so on.

Each time we add another qubit, it

takes twice as much information to describe

the whole pile of them.

That is the crux of what differentiates

quantum hardware.

The quantum system lives in a richer space,

so that representing n qubits with a classical computer

requires 2 to the n numbers.

But does this mean that a quantum memory with 100 qubits

corresponds to a conventional memory with 2

to the 100th bits?

Not so fast.

Quantum hardware is very effective at encoding

and processing certain kinds of information.

But it cannot efficiently mimic many useful aspects of its

classical counterpart.

When we say that a picture is worth 1,000 words,

we don't abolish words entirely in favor of pictures.

Adding quantum hardware to our modern computing capabilities

would be like adding pictures to a communication strategy that,

up to now, used only words.

So what does quantum hardware do well?

The exponentially growing complexity of quantum systems

also gives a clue about where quantum hardware could

be useful.

In the fields of chemistry and materials development,

simulation of molecules could be a powerful technique

to learn about the properties of a new molecule

before fully synthesizing it in the lab.

However, our ability to simulate chemistry on computers

is limited.

At its heart, chemistry is an application

of quantum mechanics.

And each electron we add to a model

doubles the number of parameters, crippling computers

with expensive calculations already

for very small molecules.

Suppose instead that we could build chemistry models out

of a quantum Lego set.

Then the model would be built with the same physics that

governs the system being modeled.

In fact, chemistry and materials simulations

have appeared as an appealing near-term problem

to approach using quantum hardware.

We've finally reached the last question.

What does a quantum computer look like,

and how do we build it?

Let's take a quick look at the actual hardware

we're building at Google.

Our qubits are resonant electrical circuits

made of patterned aluminum on a silicon chip

that slosh electrical current back and forth at two

different energy levels to encode the quantum 0 and 1

states.

Here's an example of one of our quantum chips.

Each chip features 72 qubits.

As you can see, it's about the size of a quarter.

We want each qubit to behave as one single quantum object,

with two levels.

Any other particle interacting with a qubit

from its environment pulls it away from this two-level ideal.

So creating a clean qubit environment

is a critical challenge.

At the same time, we want to be able to control

the qubits efficiently, adding and removing quanta of energy

and letting pairs of qubits interact

to exchange energy with each other on demand.

These requirements seem to oppose each other.

Ideal qubits should be perfectly clean to interact with nothing.

But then in specific cases, we want

them to interact very strongly.

This gives one insight into the tensions and challenges

of building good quantum hardware.

A first step toward building clean qubits

is to build the qubit circuits out

of superconducting materials, which

experience no electrical loss.

Superconductors perform only at very low temperatures.

And we operate our qubits in a cryostat

at less than 50 millikelvin, just

a fraction of a degree above absolute zero.

The cold temperatures and vacuum inside a cryostat

also contribute to keeping the qubit environment clean.

The cryostat consists of a series

of nested plates and cans.

The warmest stage is at the top, and it gets colder

as you go down.

All the equipment in the central core of the cryostat

is responsible for getting things cold.

Our hardware is installed around the edges

and on the bottom, coldest plate.

Each qubit chip must be mounted in a package, which

holds the chip at millikelvin temperatures and bridges

the gap between big cables and a small chip.

To address the packaged chip, electronics

outside the cryostat send signals

through cables in the cryostat.

Each cable must carry electrical signals from room temperature

all the way down to the coldest stage,

while leaking only the smallest amount of heat.

A large heat load would prevent the cryostat

from reaching its millikelvin base temperature.

A collection of filters and amplifiers

outfits each cable for its specific task.

The electronics outside the cryostat

are controlled by code running on a computer.

They generate precisely calibrated electrical signals,

shaped pulses of microwave radiation, which

are sent to control and read out the qubits.

This entire system-- from chip to cryostat, cables to code--

is all necessary to run our quantum hardware.

I hope you have enjoyed digging into some quantum computing

basics with me in these last few minutes.

We talked about the meaning of the word

"quantum," in particular, as it relates to computer hardware.

Considering the idea of a single qubit in superposition,

and then adding more qubits, we saw that each time we

add another qubit, it takes twice as much information

to describe the whole pile of them.

That's what really distinguishes a quantum computer

from a regular one.

Finally, I hope you enjoyed the quick lab tour

to get a basic sense of what our quantum computer looks like,