Quantum computing is really complicated, right? Far more complicated than conventional computing, surely. But, wait. Do I even understand how my laptop works? Probably not. I don’t even understand how a doorknob works. I mean, I can use a doorknob. But don’t ask me to design one, or even draw a picture of the inner mechanism.
We have this illusion (it has the technical name in the illusion of explanatory depth) that we understand things we know how to use. We don’t. Think about it. Do you know how a toilet works? A freezer? A goddamn doorknob? If you think you do, try to explain it. Try to explain how you would build it. Use pictures if you like. Change your mind about understanding it yet?
We don’t use quantum computers so we don’t have the illusion we understand how they work. This has two side effects: (1) we think conventional computing is generally well-understood or needs no explanation, and (2) we accept the idea that quantum computing is hard to explain. This, in turn, causes us to try way too hard at explaining it.
Perhaps by now you are thinking maybe I don’t know how my own computer works. Don’t worry, I googled it for you. This was the first hit.
Imagine if a computer were a person. Suppose you have a friend who’s really good at math. She is so good that everyone she knows posts their math problems to her. Each morning, she goes to her letterbox and finds a pile of new math problems waiting for her attention. She piles them up on her desk until she gets around to looking at them. Each afternoon, she takes a letter off the top of the pile, studies the problem, works out the solution, and scribbles the answer on the back. She puts this in an envelope addressed to the person who sent her the original problem and sticks it in her out tray, ready to post. Then she moves to the next letter in the pile. You can see that your friend is working just like a computer. Her letterbox is her input; the pile on her desk is her memory; her brain is the processor that works out the solutions to the problems; and the out tray on her desk is her output.
That’s all. That’s the basic first layer understanding of how this device you use everyday works. Now google “how does a quantum computer work” and you are met right out of the gate with an explanation of theoretical computer science, Moore’s law, the physical limits of simulation, and so on. And we haven’t even gotten to the quantum part yet. There we find qubits and parallel universes, spooky action at a distance, exponential growth, and, wow, holy shit, no wonder people are confused.
What is going on here? Why do we try so hard to explain every detail of quantum physics as if it is the only path to understanding quantum computation? I don’t know the answer to that question. Maybe we should ask a sociologist. But let me try something else. Let’s answer the question how does a quantum computer work at the same level as the answer above to how does a computer work. Here we go.
How does a quantum computer work?
Imagine if a quantum computer were a person. Suppose you have a friend who’s really good at developing film. She is so good that everyone she knows posts their undeveloped photos to her. Each morning, she goes to her letterbox and finds a pile of new film waiting for her attention. She piles them up on her desk until she gets around to looking at them. Each afternoon, she takes a photo off the top of the pile, enters a dark room where she works at her perfected craft of film development. She returns with the developed photo and puts this in an envelope addressed to the person who sent her the original film and sticks it in her out tray, ready to post. Then she moves to the next photo in the pile. You can’t watch your friend developing the photos because the light would spoil the process. Your friend is working just like a quantum computer. Her letterbox is her input; the pile on her desk is her classical memory; while the film is with her in the dark room it is her quantum memory; her brain and hands are the quantum processor that develops the film; and the out tray on her desk is her output.
Measure twice, cut once. So the old proverb goes. It certainly it makes sense if you only have enough material to build a thing. However, and I see this all too often in otherwise very smart people, too much measuring leads to over optimisation and inaction, not enough cutting. Whereas, I like cut several times, toss things out, try new cutting instruments, and so on. I almost never measure. Ultimately, this is the story of Quantum Physics for Babies. I just did it. It wasn’t carefully planned, nor was there a spark or ah-ha moment which spawned the idea. I started, I failed, I started again.
So, I started to rationalize. Why did I write this book? And, is it important? In particular, is it important for all children, not just my own? (because it is always important to find a way to discuss your passion with your own kids.) I think the answer to “is it important?” is yes. In this talk I’ll walk you through the various levels of rationalisation I’ve went through. Each has an element of truth to it, both for myself personally and what the experts on the topic of early childhood education espouse.
A huge fraction of any newborn’s library will begin with the word “first”: “First Words”, “First book of numbers”, “First alphabet book”, and so on. One quickly gets the impression that these are essential reference books for the early learner. But beyond the obvious things—letters, numbers, shapes, three letter words—are a myriad of books about animals, and mostly farm animals.
Here is another example. Do you know what these birds are? My children seem to know and can identify the difference between a penguin and a puffin. Why? Why are there more books about puffins than there are puffins and no books about transistors when you are probably sitting on a billion of them right now. In your phone lives a few billion transistors making up, by the standards of only decade ago anyway, a supercomputer. A child today will probably spend their entire life closer to computer than they will an animal of comparable size. I’m not suggesting than all books on animals be replaced by physics for babies books, but we could maybe replace a few.
, which invites international high-school students for a week of intensive training on quantum technology. Indeed, many of these students eventually become PhD students in Quantum Information Theory. Other efforts include school incursions and the new QUANTUM: The Exhibition which is an all-ages, hands-on exploratory exhibit.
On the other side of the border (remember: the wall is on the souther border), IBM has recently released the “Quantum Experience”, an app that lets you program a quantum computer, a real quantum computer. You create an algorithm and then jump in the queue for it to run on real device housed in IBM’s labs. Here they are video conferencing with a school in South Africa and hosting local students.
mathematics is the language by which scientists of all fields communicate—from philosophy to physics. And by mathematics, I don’t mean numbers. Scientists communicate ideas through mental pictures which are often represented by symbols invented just for that purpose. Here is an example: think about a ball. Maybe it is a baseball, or a basketball, or—if you are in Europe—a socc…err… football. Maybe it is the Earth or the Sun. Now try to get rid of the details: the stitching, the colors, the size. What is left? A sphere. You just performed the process of abstraction. A sphere is an idea, a mental image that you can’t touch—it doesn’t exist!
Why is this important, anyway? Well, if I can prove things about spheres, then that ought to apply to any ball in the real world. So, formulas for area and volume, for example, equally apply to baseballs, basketballs, soccer balls, and any other ball. Mathematics is a very powerful way of answering infinitely many questions at once!
