The contents of this metal cylinder could either revolutionize technology or be completely useless— it all depends on whether we can harness the strange physics of matter at very, very small scales.
To have even a chance of doing so, we have to control the environment precisely: the thick tabletop and legs guard against vibrations from footsteps, nearby elevators, and opening or closing doors.
The cylinder is a vacuum chamber, devoid of all the gases in air.
Inside the vacuum chamber is a smaller, extremely cold compartment, reachable by tiny laser beams.
Inside are ultra-sensitive particles that make up a quantum computer.
So what makes these particles worth the effort?
In theory, quantum computers could outstrip the computational limits of classical computers.
Classical computers process data in the form of bits.
Each bit can switch between two states labeled zero and one.
A quantum computer uses something called a qubit, which can switch between zero, one, and what’s called a superposition.
While the qubit is in its superposition, it has a lot more information than one or zero.
You can think of these positions as points on a sphere: the north and south poles of the sphere represent one and zero.
A bit can only switch between these two poles, but when a qubit is in its superposition, it can be at any point on the sphere.
We can’t locate it exactly— the moment we read it, the qubit resolves into a zero or a one.
But even though we can’t observe the qubit in its superposition, we can manipulate it to perform particular operations while in this state.
So as a problem grows more complicated, a classical computer needs correspondingly more bits to solve it, while a quantum computer will theoretically be able to handle more and more complicated problems without requiring as many more qubits as a classical computer would need bits.
The unique properties of quantum computers result from the behavior of atomic and subatomic particles.
These particles have quantum states, which correspond to the state of the qubit.
Quantum states are incredibly fragile, easily destroyed by temperature and pressure fluctuations, stray electromagnetic fields, and collisions with nearby particles.
That’s why quantum computers need such an elaborate set up.
It’s also why, for now, the power of quantum computers remains largely theoretical.
So far, we can only control a few qubits in the same place at the same time.
There are two key components involved in managing these fickle quantum states effectively: the types of particles a quantum computer uses, and how it manipulates those particles.
For now, there are two leading approaches: trapped ions and superconducting qubits.
A trapped ion quantum computer uses ions as its particles and manipulates them with lasers.
The ions are housed in a trap made of electrical fields.
Inputs from the lasers tell the ions what operation to make by causing the qubit state to rotate on the sphere.
To use a simplified example, the lasers could input the question: what are the prime factors of 15?
In response, the ions may release photons— the state of the qubit determines whether the ion emits photons and how many photons it emits.
An imaging system collects these photons and processes them to reveal the answer: 3 and 5.
Superconducting qubit quantum computers do the same thing in a different way: using a chip with electrical circuits instead of an ion trap.
The states of each electrical circuit translate to the state of the qubit.
They can be manipulated with electrical inputs in the form of microwaves.
So: the qubits come from either ions or electrical circuits, acted on by either lasers or microwaves.
Each approach has advantages and disadvantages.
Ions can be manipulated very precisely, and they last a long time, but as more ions are added to a trap, it becomes increasingly difficult to control each with precision.
We can’t currently contain enough ions in a trap to make advanced computations, but one possible solution might be to connect many smaller traps that communicate with each other via photons rather than trying to create one big trap.
Superconducting circuits, meanwhile, make operations much faster than trapped ions, and it’s easier to scale up the number of circuits in a computer than the number of ions.
But the circuits are also more fragile, and have a shorter overall lifespan.
And as quantum computers advance, they will still be subject to the environmental constraints needed to preserve quantum states.
But in spite of all these obstacles, we’ve already succeeded at making computations in a realm we can’t enter or even observe.
I'm going to tell you about one of the world's largest problems and how it can be solved.
I'd like to start with a little experiment.
Could you put your hand up if you wear glasses or contact lenses, or you've had laser refractive surgery?
Now, unfortunately, there are too many of you for me to do the statistics properly.
But it looks like -- I'm guessing -- that it'll be about 60 percent of the room because that's roughly the fraction of developed world population that have some sort of vision correction.
The World Health Organization estimates -- well, they make various estimates of the number of people who need glasses -- the lowest estimate is 150 million people.
They also have an estimate of around a billion.
But in fact, I would argue that we've just done an experiment here and now, which shows us that the global need for corrective eyewear is around half of any population.
And the problem of poor vision, is actually not just a health problem, it's also an educational problem, and it's an economic problem, and it's a quality of life problem.
Glasses are not very expensive.
They're quite plentiful.
The problem is, there aren't enough eye care professionals in the world to use the model of the delivery of corrective eyewear that we have in the developed world.
There are just way too few eye care professionals.
So this little slide here shows you an optometrist and the little blue person represents about 10,000 people and that's the ratio in the U.K.
This is the ratio of optometrists to people in sub-Saharan Africa.
In fact, there are some countries in sub-Saharan Africa where there's one optometrist for eight million of the population.
How do you do this?
How do you solve this problem?
I came up with a solution to this problem, and I came up with a solution based on adaptive optics for this.
And the idea is you make eye glasses, and you adjust them yourself and that solves the problem.
What I want to do is to show you that one can make a pair of glasses.
I shall just show you how you make a pair of glasses.
I shall pop this in my pocket.
I'm short sighted.
I look at the signs at the end, I can hardly see them.
So -- okay, I can now see that man running out there, and I can see that guy running out there.
I've now made prescription eyewear to my prescription.
Next step in my process.
So, I've now made eye glasses to my prescription.
Okay, so I've made these glasses and ...
Okay, I've made the glasses to my prescription and ...
...
I've just ...
And I've now made some glasses.
That's it.
(Applause) Now, these aren't the only pair in the world.
In fact, this technology's been evolving.
I started working on it in 1985, and it's been evolving very slowly.
There are about 30,000 in use now.
And they're in fifteen countries.
They're spread around the world.
And I have a vision, which I'll share with you.
I have a global vision for vision.
And that vision is to try to get a billion people wearing the glasses they need by the year 2020.
To do that -- this is an early example of the technology.
The technology is being further developed -- the cost has to be brought down.
This pair, in fact, these currently cost about 19 dollars.
But the cost has to be brought right down.
It has to be brought down because we're trying to serve populations who live on a dollar a day.
How do you solve this problem?
You start to get into detail.
And on this slide, I'm basically explaining all the problems you have.
How do you distribute?
How do you work out how to fit the thing?
How do you have people realizing that they have a vision problem?
How do you deal with the industry?
And the answer to that is research.
What we've done is to set up the Center for Vision in the Developing World here in the university.
If you want to know more, just come have a look at our website.
Thank you.
(Applause)