Quantum Entanglement for Toddlers

quantum-entanglement-for-babies

I wrote a book a while back called Quantum Entanglement for Babies. But, now all those babies are grown into toddlers! I’ve been asked what is next on their journey to quantum enlightenment. Surely they have iPads now and know how to scroll, and so I give you Quantum Entanglement for Toddlers, the infographic!

Below is a lower-res version. Here is a high-res version (5MB). Contact me for the SVG.

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My Speech to 500 Australian Teenage Schoolboys About Mathematics

I suppose I should start with who I am and what I do and perhaps why I am here in front of you. But I’m not going to do that, at least not yet. I don’t want to stand here and list all my accomplishments so that you may be impressed and that would convince you to listen to me. No. I don’t want to do that because I know it wouldn’t work. I know that because it wouldn’t have worked on me when I was in your place and someone else was up here.

Now, of course you can tell by my accent that I wasn’t literally down there. I was in Canada. And I sure as hell wasn’t wearing a tie. But I imagine our priorities were fairly similar: friends, getting away parents, maybe sports (in my case hockey of course and yours maybe footy), but most importantly… mathematics! No. Video games. 

I don’t think there is such a thing as being innately gifted in anything. Though, I am pretty good at video games. People become very good at things they practice. A little practice leads to a small advantage, which leads to opportunities for better practice, and things snowball. The snowball effect. Is that a term you guys use in Australia? I mean, it seems like an obvious analogy for a Canadian. It’s how you make a snowman after all. You start with a small handful of snow and you start to roll it on the ground. The snow on the ground sticks to the ball and it gets bigger and bigger until you have a ball as tall as you! 

Practice leads to a snowball effect. After a while, it looks like you are gifted at the thing you practiced, but it was really just the practice. Success then follows from an added sprinkling of luck and determination. That’s what I want to talk to you about today: practice.

I don’t want to use determination in the sense that I was stubbornly defiant in the face of adversity. Though, from the outside it might look that way. You can either be determined to avoid failure or determined to achieve some objective. Being determined to win is different from being determined not to lose. 

There is something psychologically different between winning and not losing. You see, losing implies a winner, which is not you. But winning does not require a loser, because you can play against yourself. This was the beauty of disconnected video games of 80’s and 90’s. You played against yourself, or maybe “the computer”. That doesn’t mean it was easy. I’ll given anyone here my Nintendo if they can beat Super Mario Bros. in one go. (I’m not joking. I gave my children the same offer and they barely made it past the first level). It was hard and frustrating, but no one was calling you a loser on the other end. And when you finally beat the game, you could be proud. Proud of yourself and for yourself. Not for the fake internet points you get on social media, but for you. 

I actually really did want to talk to you today about mathematics. What I want to tell you is that, when I was your age, I treated mathematics like a video game. I wanted to win. I wanted to prove to myself that I could solve every problem. Some nights I stayed up all night trying to solve a single problem. You know how they say you can’t have success without failure? This is a perfect example. The more you fail at trying to solve a maths problem, the more you understand when you finally do solve it. And what came along with failing and eventually succeeding in all those maths problems? Practice.

Well I don’t know much about the Australian education system and culture. But I’m guessing from Hollywood you know a bit about highschool in North America. I’m sure you know about prom, and of course about Prom King and Prom Queen. What you may not know is that the King and Queen’s court always has a jester. That is, along with King and Queen, each year has a Class Clown — the joker, the funny guy. I wasn’t the prom king, or queen. But I did win the honour of class clown.

When I finished highschool, I was really good at three things: video games, making people laugh, and mathematics. I promise you, there is no better combination. If there was a nutrition guide for the mind, it would contain these three things. Indeed, now more than ever before, you need to be three types of smart. You need to be quick, reactive, and adaptive — the skills needed to beat a hard video game. You need emotional intelligence, you need to know what others are thinking and feeling — how to make them laugh. And finally you need to be able to solve problems, and all real problems require maths to solve them. 

There are people in the world, lots of people — billions, perhaps — who look in awe at the ever increasing complexity of systems business, government, schools, and technology, including video games. They look, and they feel lost. Perhaps you know someone that can’t stand new technology, or change in general. Perhaps they don’t even use a piece of technology because they believe they will never understand how to use it. 

You all are young. But you know about driving, voting, and paying taxes, for example. Perhaps it looks complicated, but at least you believe that you can and will be able to do it when the time comes. Imagine feeling that such things were just impossible. That would be a weird feeling. You brain can’t handle such dissonance. So you would need to rationalise it in one way or another. You’d say it’s just not necessary, or worse, it’s something some “other” people do. At that point, for your brain to maintain a consistent story, it will start to reject new information and facts that aren’t consistent with your new story. 

This is all sounds far fetched, but I guarantee you know many people with such attitudes. To make them sound less harmful, they call them “traditional”. How do otherwise “normal” people come to hold these views? It’s actually quite simple: they fear, not what they don’t understand, but what they have convinced themselves is unnecessarily complicated. I implore you, start today, start right now. Study maths. It is the only way to intellectually survive in a constantly changing world.

Phew that was a bit depressing. Let me give you a more fun and trivial example. Just this weekend I flew from Sydney to Bendigo. The flight was scheduled to be exactly 2 hours. I was listening to an audiobook and I wondered if I would finish it during the flight. Seems obvious right? If there was less than 2 hours left in the audiobook, then I would finish. If not, then I would not finish. But here’s the thing, audiobooks are read soooo slow. So, I listen to them at 1.25x speed. There was 3 hours left. Does anyone know the answer?

Before I tell you, let me remind you, not many people would ask themselves this question. I couldn’t say exactly why, but in some cases it’s because the person has implicitly convinced themselves that such a question is just impossible to answer. It’s too complicated. So their brain shuts that part of inquiry off. Never ask complicated questions it says. Then this happens: an entire world — no most of the entire universe — is closed off. Don’t close yourself off from the universe. Study maths.

By the way, the answer. It’s not the exact answer but here was my quick logic based on the calculation I could do in my head. If I had been listening at 1.5x speed, then every hour of flight time would get through 1.5 hours of audiobook. That’s 1 hour 30 minutes. So two hours of flight time would double that, 3 hours of audiobook. Great. Except I wasn’t listening at 1.5x speed. I was listening at a slower speed and so I would definitely get through less than 3 hours. The answer was no. 

In fact, by knowing what to multiple or divide by what, I could know that I would have exactly 36 minutes left of the audiobook. Luckily or unluckily, the flight was delayed and I finished the book anyway. Was thinking about maths pointless all along? Maybe. But since flights are scheduled by mathematical algorithms, maths saved the day in the end. Maths always wins.

How about another. Who has seen a rainbow? I feel like that should be a trick question just to see who is paying attention. Of course, you have all seen a rainbow. As you are trying to think about the last time you saw a rainbow, you might also be thinking that they are rare — maybe even completely random things. But now you probably see the punchline — maths can tell you exactly where to find a rainbow.

Here is how a rainbow is formed. Notice that number there. That angle never changes. So you can use this geometric diagram to always find the rainbow. The most obvious aspect is that the rainbow exits the same general direction that the sunlight entered the raindrop. So to see a rainbow, the sun has to be behind you.

And there’s more. If the sun is low in the sky, the rainbow will be high in the sky. And if the sun is high, you might not be able to see a rainbow at all. But if you take out the garden hose to find it, make sure you are looking down. Let me tell you my favourite rainbow story. I was driving the family to Canberra. We were driving into the sunset at some point when I drove through a brief sun shower. Since the sun was shining and it was raining, one of my children said, “Maybe we’ll see a rainbow!”

Maybe. Ha. A mathematician knows no maybes. As they looked out their windows, I knew — yes — we would see a rainbow. I said, after passing through the shower, “Everyone look out the back window and look up.” Because the sun was so low, it was apparently the most wonderful rainbow ever seen. I say apparently because I couldn’t see it, on account of me driving. But no matter. I was content in knowing I could conjure such beauty with the power of mathematics.

I could have ended there, since I’m sure you are all highly convinced to catch up on all your maths lessons and homework. However, since I have time, I will tell you a little bit about what maths has enabled me to get paid to do. Namely, quantum physics and computation. Maybe you’ve heard about quantum physics? Maybe you’ve heard about uncertainty (the world is chaotic and random), or superposition (things can be in two places at once and cats can be dead and alive at the same time), or entanglement (what Einstein called spooky action at a distance).

But I couldn’t tell you more about quantum physics than that without maths. This is not meant to make it sound difficult. It should make it sound beautiful. This is quantum physics. It’s called the Schrodinger Equation. That’s about all there is to it. All that stuff about uncertainty, superposition, entanglement, multiple universes, and so on—it’s all contained in this equation. Without maths, we would not have quantum physics. And without quantum physics, we would not have GPS, lasers, MRI, or computers — no computers to play video games and no computers to look at Instagram. Thank a quantum physicist for these things.

Quantum physics also helps us understand the entire cosmos. From the very first instant of the Big Bang born out of a quantum fluctuation to the fusing of Hydrogen into Helium inside stars giving us all energy and life on Earth to the most exotic things in our universe: black holes. These all cannot be understood without quantum physics. And that can’t be understood without mathematics.

And now I use the maths of quantum physics to help create new computing devices that may allow us to create new materials and drugs. This quantum computer has nothing mysterious or special about it. It obeys an equation just as the computers you carry around in your pockets do. But the equations are different and different maths leads to different capabilities. 

I don’t want to put up those equations, because if I showed them to even my 25 year-old self, I would run away screaming. But then again, I didn’t know then what I know now, and what I’m telling you today. Anyone can do this. It just takes time. Every mathematician has put in the time. There is no secret recipe beyond this. Start now.

The minimal effort explanation of quantum computing

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.

⟨B|raket|S⟩

Welcome to ⟨B|raket|S⟩! The object is to close brakets, the tools of the quantum mechanic!

Created by Me, Chris Ferrie!

2 PLAYERS | AGES 10+ | 15 MINUTES

Welcome to ⟨B|raket|S⟩! The object is to close brakets, the tools of the quantum mechanic! You’ll need to create these quantum brakets to maximize your probability of winning. But, just like quantum physics, there is no complete certainty of the winner until the measurement is made!

No knowledge of quantum mechanics is require to play the game, but you will learn the calculus of the quantum as you play. Later in the rules, you’ll find out how your moves line up with the laws of quantum physics.

What you need

A deck of ⟨B|raket|S⟩ cards, a coin, and a way to keep score.

The instructions are here.

I suggest getting the cards printed professionally. All the cards images are in the cards folder. I printed the cards pictured above in Canada using https://printerstudio.ca. However, they also have a worldwide site (https://printerstudio.com).

You can print your own cards using a desktop printer with this file.

You can laser cut your own pieces using this file.

Open Source

Oh, and this game is free and open source. You can find out more at the GitHub repository: https://github.com/csferrie/Brakets/.

Journal | September 2018

It was a busy month of extra-curriculars, making the most of our last weeks in Canada before returning to greet the Aussie summer.

Eureka!

The big aha! moment was finally understanding the pleas to remove “for babies” from the titles of the Baby University books. On 17 September I visited two elementary schools in the suburbs of Chicago: Rollins Elementary School and May Watts Elementary.

I had a great time at both, but I knew I had to carefully navigate “for babies”. So, I did read the title and immediately asked, “are there any babies here?” “No!” was the expected and resounding answer. I think I won them over with that. But when the cover image popped up on screen I still heard a few “hey! It says for babies” from the audience. The school avoided the “for babies” problem by selling my two picture books, Goodnight Lab and Scientist, Scientist, Who do you See?.

I can sympathize with teachers and librarians when they tell me about the difficulty in reading the “for babies” books. I am also honored that my baby books want a wider audience! In the meantime, while we figure out a solution to the “for babies” problem in the classroom, I think I’ll stick to reading the picture books at schools.

Reading!

Children’s Literature Recommendations

Twinkle Twinkle Little Star, I Know Exactly What You Are by Julia Kregenow and Carmen Saldaña

Filled with rhyming facts about stars that can be sung to the cadence of the classic nursery rhyme. Easy to read and look at for all ages.

How Did I Get Here? by Philip Bunting

Adorable illustrations accompany the history of the universe from the Big Bang, through conception (yep), until now. Easy for the the kids to listen to and point at.

Adult Literature September Reads

Humility Is the New Smart by Edward D. Hess and Katherine Ludwig

I found this difficult to read because it is heavy on repeating buzzwords and technobabble. There are some great nuggets of wisdom in here which are drawn from well-laid-out examples of people and companies that have put humility ahead of arbitrary measures of merit.

How not to be Wrong by Jordan Ellenberg

This book is about math applied to real life. Some of the explanations are abstract and others follow closely with recent, and mostly quirky, stories. I thoroughly enjoyed it. However, I suspect that the author demands a little too much from the casual reader.

Currently reading: Scale by Geoffrey West

Writing!

We are in the final editorial stages of ABC’s of Engineering, Robotics for Babies, and Neural Networks for Babies, all co-authored by my friend Sarah Kaiser. Look for these in January of 2019. They are going to be awesome. Conversations about them included the sentence, “I hate to have to tell you this… but we can’t rickroll babies.”

5b2c752fNae7923f1

One of the questions I get most is are you working on any books for older kids? Yes, yes I am. But at the moment it is too early to give anything away. Stay tuned!

I completed a few more early manuscripts in the Red Kangaroo Physics series. Next year, they will begin to be translated (or untranslated 😄) and available in English. If this is news to you, this is a series of picture books each of which discusses a topic in physics. The story follows a dialogue between me and a curious Red Kangaroo. The first 15 are available now in Chinese.

Arithmetic! (academic news)

Both my students recently submitted their first papers and presented them at an international conference this month. Congrats to Maria and Akram!

I finally got the advertisements up for two postdoctoral positions which are funded by a $3 million grant from the Australian government. This is a collaboration with Gerardo Paz Silva, Howard Wiseman, and Andrea Morello that I am keen to get going.

Mostly an exercise in catharsis, I am reminding myself to say no to every invitation to chair, organise, or join a committee. My future self won’t heed this warning—so here’s hoping it is another thing that gets easier and less time consuming with practice.

Events!

Lots of great opportunities this past month. I met many great people and learned a lot!

  • I gave a public lecture at the Institute for Quantum Computing on 13 September call Big Ideas for Little Minds. I won’t say too much about it as it will be posted online soon. I also gave the same talk at Google on 19 September, which will also appear on Talks at Google.

  • I finally met (in person) Cara Florance my co-author of ABC’s of Biology, Organic Chemistry for Babies, and Evolution for Babies! We did a joint event at the MIT Coop bookstore. How did it go? Well, Cara built a DIY cloud chamber and had a Geiger counter—’nuff said. I also met an MIT professor that bought a copy of Statistical Physics for Babies for every student in his class 😳!
  • I joined Nikola Tesla for some reading, banter, and science demonstrations at the Rochester Museum and Science Center. This was the first time I read 8 Little Planets and was really pleased with the response from both the children and parents! The science centre itself was awesome and I even got a private showing of musical Tesla coils!

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Just hanging out in a Faraday cage ⚡⚡⚡

A post shared by Chris Ferrie (@chris_ferrie) on

  • I got to visit Sourcebooks headquarters in Chicago. It was great to meet all the people behind the scenes that make the children’s books possible. Everyone I met was so passionate about making books, especially the amazing Dominique Raccah!
  • Check out a quick discussion about Baby University on Global TV’s The Morning Show. It’s a great opportunity to reach a large television audience. Too bad the time is so short and the questions so quick!
  • I did some reading and activities at the Oxford County Library in Ingersoll on 6 September. It was amazing to see how close members of a small community are with their library. The librarians even knew the interests of the children! Very eye opening as this has not been my experience in Sydney.

Up next!

October is going to be another busy month. We need to get settled back into Sydney and I don’t even want to think about the backlog of administration I have been ignoring at the uni. But I am also really excited for Quantum Gates, Jumps, and Machines and of course the release of 8 Little Planets!

The power of simulation: birthday paradox

The birthday paradox goes… in a room of 23 people there is a 50-50 chance that two of them share a birthday.

OK, so the first step in introducing a paradox is to explain why it is a paradox in the first place. One might think that for each person, there is 1/365 chance of another person having the same birthday as them. Indeed, I can think of only one other person I’ve met that has the same birthday as meand he is my twin brother! Since I’ve met far more than 23 people, how can this be true?

This reasoning is flawed for several reasons, the first of which is that the question wasn’t asking about if there was another person in the room with a specific birthdayany pair of people (or more!) can share a birthday to increase the chances of the statement being true.

The complete answer gets heavy into the math, but I want to show you how to convince yourself it is true by simulating the experiment. Simulation is programming a computer or model to act as if the real thing was happening. Usually, you set this up so that the cost of simulation is much less than doing the actual thing. For example, putting a model airplane wing in a wind tunnel is a simulation. I’ve simulate the birthday paradox in a computer programming language called Python and this post is available in notebook-style here. Indeed, this is much easier than being in a room with 23 people.

Below I will not present the code (again, that’s over here), but I  will describe how the simulation works and present the results.

The simulation

Call the number of people we need to ask before we get a repeated birthday n. This is what is called a random variable because its value is not known and may change due to conditions we have no control over (like who happens to be in the room).

Now we simulate an experiment realising a value for n as follows.

  1. Pick a random person and ask their birthday.
  2. Check to see if someone else has given you that answer.
  3. Repeat step 1 and 2 until a birthday is said twice.
  4. Count the number of people that were asked and call that n.

Getting to step 4 constitutes a single experiment. The number that comes out may be n = 2 or n = 100. It all depends on who is in the room. So we repeat all the steps many many times and look at how the numbers fall. The more times we repeat, the more data we obtain and the better our understanding of what’s happening.

Here is what it looks like when we run the experiment one million times.

exponemil
Simulating the birthday paradox. On the horizontal axis is n, the number of people we needed to ask before a repeated birthday was found. We did the experiment one million times and tallied the results.

So what do all those numbers mean? Well, let’s look at how many times n = 2 occurred, for example. In these one million trials, the result 2 occurred 2679 times, which is relatively 0.2679%. Note that this is close to 1/365 ≈ 0.274%, which is expected since the probability that the second person has the same as the first is exactly 1/365. So each number of occurrences divided by one million is approximately the probability that we would see that number in a single experiment.

We can then plot the same data considering the vertical axis the probability of needing to see n people before a repeated birthday.

prob
Same as the previous plot but now each bar is interpreted as a probability.

Adding up the value of each of these bars sums to 100%. This is because one of the values must occur when we do an experiment. OK, so now we can just add up these probabilities starting at n = 2 and increasing until we get to 50%. Visually, it is the number which splits the coloured area above into two equal parts. That number will be the number of people we need to meet to have a 50-50 shot at getting a repeated birthday. Can you guess what it will be?

Drum roll… 23! Tada! The birthday paradox simulated and solved by simulation!

But, wait! There’s more.

What about those leap year babies? In fact, isn’t the assumption that birthdays are equally distributed wrong? If we actually tried this experiment out in real life, would we get 23 or some other number?

Happily, we can test this hypothesis with real data! At least for US births, you can find the data over at fivethirteight’s github page. Here is what the actual distribution looks like.

dist_birth.png
Distribution of births in US from 1994-2014, by day of year.

Perhaps by eye it doesn’t look too uniform. You can clearly see 25 Dec and 31 Dec have massive dips. Much has been written about this and many beautiful visualizations are out there. But, our question is whether this has an effect on the birthday paradox. Perhaps the fact that not many people are born on 25 Dec means it is easy to find a shared birthday on the remaining days, for example. Let’s test this hypothesis by simulating the experiment with the real distribution of birthdays.

To do this, we perform the same 4 steps as above, but randomly sampling answers from the actual distribution of birthdays. The result of another one million experiments is plotted below.

truehist.png
Simulating the birthday paradox on the true distribution of births. On the horizontal axis is n, the number of people we needed to ask before a repeated birthday was found. We perform the experiment one million times and tallied the results.

And the answer is the same! The birthday paradox persists with the actual distribution of birthdays.

Nerd sniping

The above discussion is very good evidence that the birthday paradox is robust to the actual distribution of births. However, it does not constitute a mathematical proof. An experiment can only provide evidence. So I will end this with a technical question for those mathematical curiosos out there. (What I am about to do is also called Nerd Sniping.)

Here is the broad problem: quantify the above observation. I think there is more than one question here. For example, it should be possible to bound the 50-50 threshold as a function of the deviation from a uniform distribution.

(Cover image credit: Ed g2s, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=303792)

My visit to a Chinese kindergarten class

I think this means it went well.

Recently, I had a video chat with the kindergarten class of Dragon Bay Kindergarten in Beijing. It was a lot of fun to see how excited the children and teachers were to read my books. They even had an entire Science Fair based around my Physics for Babies books!

Beijing_babyphys.png

During our video call, the students and teachers asked many questions. I’ve transcribed them here.

Student questions

How can I see atoms in the real world?

We can not see atoms with our eyes. They are too small. We can use other ways to take pictures of atoms. In the labs where I work, physicists shine laser light on the atoms. The electrons take the energy to move up in their energy levels. When they fall back down, they release light that we can see with a camera.

Can you introduce particles and entanglement to us?

Atoms themselves are made of even smaller things called particles. Electrons are one kind of particle. Not all particles make atoms though. Photons, what light is made of, are another kind of particle which is not part of an atom.
Entanglement is tricky to explain in everyday language. It is something we see in the math of quantum physics. Even scientists today argue about how to understand it. But, we can use the math to show us how to build quantum technology where entanglement is used.

What does an atom look like? How are they different?

Electron microscopes take pictures of atoms which look like blurry little balls. Most atoms look the same but some are bigger than others. When electrons move between energy levels, they send out light at very specific colors. Each atom makes a different color, which is how we can tell them apart.

How do you know everything was made by atoms?

We can see them with today’s technology!

How can I touch the atom?

Since everything is made of atoms, you are touching them right now!

Why don’t you wear the clothes of a physicist?

In pictures of scientists, they are often wearing lab coats. In real life, physicists do not wear lab coats. Some work in a lab and others, like me, work in an office with computers and whiteboards.

Teacher questions

What made you think that babies need to learn about quantum entanglement?

A lot of science is a language which we learn by listening and talking to other scientists, just like learning your first language. So, the sooner you start to hear the language, the sooner you will speak it.

Will entangled particles always be measured the same or can they just be influenced?

Entanglement has a quality to it which might not make it perfect. Experimental technology is always a bit unreliable. But perfect entanglement, like that described in the book, means that particles will be measured the same every time.

Do your children like and understand your books?

My children like the books and can often repeat some of the sentences. I talk with them about it, but they will not be doing any quantum physics research yet.

How does your work place look like?

There are labs. Some use lasers which means they must be dark. Some have big refrigerators which keep things really really cold. Above the labs is office space. Here it looks like a regular office, but with whiteboards that have lots of math on them.