# Explain to 10 year old — Why do 3D mental pictures usually suffice for high-dimensional geometry?

My 10 year old daughter is trying to read this book — please explain in Simple English that she'll grasp. Kindly see the embolded phrases below. The author doesn't expound why the 3D "mental pictures" are "usually enough". Scilicet, why doesn't "this impoverished vision" hinder high-dimensional geometry, or at least deprive or forestall you from learning all about it?

In the same way, a point in three-dimensional space is described by a list of three coordinates (x,y,z). And nothing except habit and craven fear keeps us from pushing this further. A list of four numbers can be thought of as a point in four-dimensional space, and a list of ten numbers, like the California temperatures in our table, is a point in ten-dimensional space. Better yet, think of it as a ten-dimensional vector.
Wait, you may rightfully ask: How am I supposed to think about that? What does a ten-dimensional vector look like?
It looks like this:

That’s the dirty little secret of advanced geometry. It may sound impressive that we can do geometry in ten dimensions (or a hundred, or a million . . .), but the mental pictures we keep in our mind are two- or at most three-dimensional. That’s all our brains can handle. Fortunately, this impoverished vision is usually enough.
High-dimensional geometry can seem a little arcane, especially since the world we live in is three-dimensional (or four-dimensional, if you count time, or maybe twenty-six-dimensional, if you’re a certain kind of string theorist, but even then, you think the universe doesn’t extend very far along most of those dimensions). Why study geometry that isn’t realized in the universe?
One answer comes from the study of data, currently in extreme vogue. Remember the digital photo from the four-megapixel camera: it’s described by 4 million numbers, one for each pixel. (And that’s before we take color into account!) So that image is a 4-million-dimensional vector; or, if you like, a point in 4-million-dimensional space. And an image that changes with time is represented by a point that’s moving around in a 4-million-dimensional space, which traces out a curve in 4-million-dimensional space, and before you know it you’re doing 4-million-dimensional calculus, and then the fun can really start.

Ellenberg, How Not to Be Wrong (2014), pages 338-9.

• Why would you want to explain this to a 10 year old? If you want to teach her geometry, start with something more accessible. Commented Jun 5, 2021 at 1:57
• @MoisheKohan The OP said that his daughter is trying to read this (popular science/math) book, not that he is teaching her geometry or anything else.
– Adam
Commented Jun 5, 2021 at 14:16
• @Adam: This is still OP's parental responsibility to guide their child in her reading. I would give the same advice to a parent asking "How do I explain to my 10 year old what's happening in the movie "50 shades of grey" "(or another movie of the same nature). The fact that a 10 year old wants to see this movie (or already did) is not a good excuse. A caveat: Once in a blue moon one meets a 10 year old child who can understand abstract math (happened to me once). I was assuming an average 10 year old. Commented Jun 5, 2021 at 14:38
• @MoisheKohan The comparison is more than a little over the top. It's a pop-sci book, not a textbook for a course. Reading a pop-sci book is pretty normal; I have fond memories of reading Stephen Hawking's book around the same age. I doubt that I retained anything testably concrete after reading it but that isn't the point. Anyway, she can stop reading the book if she changes her mind.
– Adam
Commented Jun 6, 2021 at 14:12
• Also asked at math.codidact.com/posts/282013
– JRN
Commented Jul 6, 2021 at 7:45

## 4 Answers

Well, to start, "usually enough" is ambiguous enough to allow a bit of wiggle room. That said, there are plenty of times where knowing how dimensions 1, 2, and 3 act to start to see the special cases break down and see the general pattern. For example, Jordan is hinting at vector spaces in the cited section. Dimension 1 is a special case where vector addition is just regular addition, but when you move to dimension 2 you start to see that there is something different going on. e.g. You can't do things like multiply 2D vectors like you could in 1D. (Or at least, there isn't just one way of doing it. You can multiply component-wise, or view them as complex numbers, or use the 3D cross product or inner product to get a scalar result, etc.) Once you keep on going to 3D, some more of the stuff particular to 1 and 2 dimensions falls away. 3D has its own peculiarities, but there is a continuous core set of facts/axioms that keeps on going "all the way up" forming the concept of a vector space. Some parts of this core even continue to infinite dimensional spaces.

Now, you can't expect this core set of vector space axioms to tell you everything. Those California temperatures are probably a time series and the images have a 2D spatial structure and these structures aren't captured by viewing them as raw vectors. But that's all structure that they have in addition to their vector structure, not instead of. i.e. We have some sort of foundation on which to build.

Part of learning to do higher dimensional geometry is learning which aspects of your low dimensional intuition are good or not. I can't visualize two smooth $$2$$-planes meeting transversely at a point, which I know happens in $$\mathbb{R}^4$$. But I am experienced enough to know that, when thinking about dimensions and transversality, I need to compute, because my two and three dimensional experience will lead me astray.

Similarly, my visual intuition tells me that the diagonal of a unit cube is only a bit longer than the side; certainly not more than twice as long: But in 1,000,000 dimensional space, the diagonal is 1,000 times the side length! Again, I have spent enough time on high dimensional computations to know that I need to compute with the Pythagorean theorem when I have a high dimensional vector with many nonzero entries, because all those small squares can add up to something big.

I think part of Jordan's statement is based on the fact that he is experienced enough to know where the traps are, so what remains seems clear and trouble free.

• Similarly, possibly counter-intuitively, a unit sphere's volume is an ever-shrinking fraction of a "unit" (well, ok, edge-length 2) (hyper-) cube's volume. Also said as "high-dimensional spheres are not very round" or similar. :) Commented Jun 17, 2021 at 20:24

Because the 2/3-dimensional visualisations are equally unnecessary. Some mathematicians who naturally think along visual lines find them a useful way to structure their thoughts, but (for mathematicians not still in the pre-formal stage of their development), it's just a tool to help them reason about some more formal system. Other mathematicians do not use such tools (for example, those of us with aphantasia certainly do not), and so the visualisation cannot be essential to the process.

• Precisely. Visualization in mathematics is not the same as literal 2 or 3 dimensional seeing. In fact, the real way we "see" things in higher dimensions is largely linear algebra. At least if you want to say something which is not just fuzzy hand waving, real calculations are largely accomplished by some sort of linear algebra (of course there are exceptions). The real lesson of higher dimensional geometry is structure takes place of visualization. To say mental pictures are literal 2 or 3 dimensional pictures misses the point entirely. At least for me... Commented Jun 19, 2021 at 19:25
• @JamesS.Cook I'm lead to believe that there do exist mathematicians who see literal 2-ish dimensional images in their heads and make use of these for various purposes (I've even had some of those mathematicians attempt to draw said pictures for me, though I've never been able to get much out of them, probably because I have to translate them back out of picture form before I can actually do anything with them, at which point it would have been easier to just have the translated form to start with). Commented Jun 19, 2021 at 19:42
• I think that is correct. I draw pictures in two dimensions to understand relationships between maps on sets. However, I think calling them "visualization" in the same sense as say visualization of certain aspects of curves (say curvature or torsion) is a stretch. Literal 2 or 3 dimensional spatial perception is different than making diagrams to organize concepts. In this sense I discourage looking for visualization, it is not the same sort of visualization as that which students sometimes desire in say Calculus III. I say this as someone who spent too much time aiming for... Commented Jun 19, 2021 at 20:01
• literal visualization of various objects. Pictures can be helpful, but I think looking for them is a hang-up for a lot of students of geometry. A better question would be, how can I calculate this in a specific example. Commented Jun 19, 2021 at 20:03

If you want to show the detailed displacement pattern of a cantilever beam you can use the mode shape vector. In 1D, the mode shape vector of 6 degree of freedom (DOF) lumped mass cantilever beam (which is basically a line with 6 mass points dots) will contain 6 entries. Each entry suggests the position of a lumped mass point (DOF). If you use only 2 mass points (DOF), you get just two values and can show an inclined line. But that would be way too erroneous. You could use 3 to 4 dots and get a very good approximation though. In this case, the structure is 1D. But the deformation vector goes up to 6 Dimension? So I think, vectors only contain refined information in a mathematical sense.

The photo example is similar. Lets say there are 10000 pixels in the image. Assume a red apple and so each of these pixels are filled with red color and its variants. If you want to show a green apple you fill those pixels with green and its variants. But there will still be only 10000 pixels. And the pixel positions are still the same. So if you want to explain this through vectors, each pixel would need 3 entries: $$\{\textrm{x coordinate},\textrm{y coordinate},\textrm{intensity of red color}\}$$ In this case, the position of pixels determine the shape of the object. Once the positions are fixed, we need colors to differentiate. Colors are only adding more information. Similarly higher dimensions add only more information.

Physical dimensions are only 3. And that's it. Period. There are no higher dimensions in the physical realm. It's a dangerous lie when someone says they are able to visualize 10-dimensional physical space. The extra dimensions can be seen only as additional details/information such as: details/time/temperature/color/etc.