Tag Archives: conceptual metaphor

The great math mystery

The great math mystery

Last night Nova aired The great math mystery, a documentary that describes mathematicians’ ideas about whether math is discovered or invented, whether it is “out there” or “in our head”. It was well-done. Things were explained clearly using images and metaphors, although they did show Maxwell’s equations as algebra (without explaining it). The visual illustrations of connections between Maxwell’s equations and music and electromagnetic waves was one of the best parts of the documentary.

In my opinion they made good choices of mathematical ideas to cover, but I imagine a lot of research mathematicians will have a hissy that they didn’t cover XXX (their subject).

The applications to physics dominated the show (that is not a complaint), but someone did mention the remarkable depth of number theory. Number theory is deep pure math that has indeed had some applications, but that’s not why some of the greatest mathematicians in the world have spent their lives on the subject. I believe logic and proof was never mentioned, and that is completely appropriate for a video made for the general public. Some mathematicians will disagree with that last sentence.

Where does math live?

The question,

Does math live

  • In an ideal world separate from the physical world,
  • in the physical world, or
  • in our brains?

has a perfectly clear answer: It exists in our brains.

Ideal world

The notion that math lives in an ideal world, as Plato supposedly believed, has no evidence for it at all.

I suppose you could say that Plato’s ideal world does exist — in our brains. But that wouldn’t be quite correct: We have a mental image of Plato’s ideal world in our brains, but that image is not the whole ideal world: If we know about triangles, we can imagine the Ideal Triangle to be in his world, but we have to know about the zeta function or the monster group to visualize them to be in his world. Even then, the monster group in our brain is just a collection of neurons connected to concepts such as “largest sporadic simple group” or “contains\[2^{46} \cdot 3^{20} \cdot 5^9 \cdot 7^6 \cdot 11^2 \cdot 13^3 \cdot 17 \cdot 19 \cdot 23 \cdot 29 \cdot 31 \cdot 41 \cdot 47 \cdot 59 \cdot 71\]elements” — but there is not a neuron for each element! We don’t have that many neurons.

The size of the monster group does not live in my brain. I copied it from Wikipedia.

Real world

Our collective experience is that math is extraordinarily useful for modeling many aspects of the real world. But in what sense does that mean it exists in the real world?

There is a sense in which a model of the real world exists in our brains. If we know some of the math that explains certain aspects of the real world, our brains have neuron connections that make that math live in our brain and in some sense in the model of the real world that is in our brain. But does that mean the math is “out there”? I don’t see why.

Math is a social endeavor

One point that usually gets left out of discussions of Platonism is this: Some math exists in any individual person’s brain. But math also exists in society. The math floating around in the individual brains of people is subject to frequent amendments to those people’s understanding because they interact with the real world and in particular with other people.

In particular, theoretical math exists in the society of mathematicians. It is constantly fluctuating because mathematicians talk to each other. They also explain it to non-mathematicians, which as everyone know can bring new insights into the brain of the person doing the explaining.

So I think that the best answer to the question, where does math live? is that math is a bunch of memes that live in our social brain.

References

I have written about these issues before:

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Functions: Metaphors, Images and Representations

Please read this post at abstractmath.org. I originally posted the document here but some of the diagrams would not render, and I haven’t been able to figure out why. Sorry for having to redirect.

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Images and metaphors in math

About this post

This post is the new revision of the chapter on Images and Metaphors in abstractmath.org.

Images and metaphors in math

In this chapter, I say something about mental represen­tations (metaphors and images) in general, and provide examples of how metaphors and images help us understand math – and how they can confuse us.

Pay special attention to the section called two levels!  The distinction made there is vital but is often not made explicit.

Besides mental represen­tations, there are other kinds of represen­tations used in math, discussed in the chapter on represen­tations and models.

Mathe­matics is the tinkertoy of metaphor. –Ellis D. Cooper

Images and metaphors in general

We think and talk about our experiences of the world in terms of images and metaphors that are ultimately derived from immediate physical experience.  They are mental represen­tations of our experiences.

See Thinking about thought.

Examples

Images

We know what a pyramid looks like.  But when we refer to the government’s food pyramid we are not talking about actual food piled up to make a pyramid.  We are talking about a visual image of the pyramid.    

Metaphors

We know by direct physical experience what it means to be warm or cold.  We use these words as metaphors
in many ways: 

  • We refer to a person as having a warm or cold personality.  This has nothing to do with their body temperature.
  • When someone is on a treasure hunt we may tell them they are “getting warm”, even if they are hunting outside in the snow.

Children don’t always sort meta­phors out correctly. Father: “We are all going to fly to Saint Paul to see your cousin Petunia.” Child: “But Dad, I don’t know how to fly!”

Other terminology

  • My use of the word “image” means mental image. In the study of literature, the word “image” is used in a more general way, to refer to an expression that evokes a mental image..
  • I use “metaphor” in the sense of conceptual metaphor. The word metaphor in literary studies is related to my use but is defined in terms of how it is expressed.
  • The metaphors mentioned above involving “warm” and “cold”
    evoke a sensory experience, and so could be called an image as well. 
  • In math education, the phrase concept image means the mental structure associated with a concept, so there may be no direct connection with sensory experience.  
  • In abstractmath.org, I use the phrase metaphors and images to talk about all our mental represen­tations, without trying for fine distinctions.

Mental represen­tations are imperfect

One basic fact about metaphors and images is that they apply only to certain aspects of the situation.

  • When someone is getting physically warm we would expect them to start sweating.
  • But if they are getting warm in a treasure hunt we don’t expect them to start sweating. 
  • We don’t expect the food pyramid to have a pharaoh buried underneath it, either.

Our brains handle these aspects of mental represen­tations easily and usually without our being conscious of them.  They are one of the primary ways we understand the world.

Images and metaphors in math

Half this game is 90% mental. –Yogi Berra

Types of represen­tations

Mathe­maticians who work with a particular kind of mathe­matical object
have mental represen­tations of that type of object that help them
understand it.  These mental represen­tations come in many forms.  Most of them fit into one of the types below, but the list shouldn’t be taken too seriously: Some represen­tations fit more that of these types, and some may not fit into any of them except awkwardly.

  • Visual
  • Notation
  • Kinetic
  • Process
  • Object

All mental represen­tations are conceptual metaphors. Metaphors are treated in detail in this chapter and in the chapter on images and metaphors for functions.  See also literalism and Proofs without dry bones on Gyre&Gimble.

Below I list some examples. Many of them refer to the arch function, the function defined by $h(t)=25-{{(t-5)}^{2}}$.

Visual image

Geometric figures



The arch function

  • You can picture the arch function in terms of its graph, which is a parabola.     This visualization suggests that the function has a single maximum point that appears to occur at $t=5$. That is an example of how metaphors can suggest (but not prove) theorems.
  • You can think of the arch function
    more physically, as like the Gateway Arch. This metaphor is suggested by the graph.

Interior of a shape

  • The interior of a closed curve or a sphere is called that because it is like the interior in the everyday sense of a bucket or a house.
  • Sometimes, the interior can be described using analytic geometry. For example, the interior of the circle $x^2+y^2=1$ is the set of points \[\{(x,y)|x^2+y^2\lt1\}\]
  • But the “interior” metaphor is imperfect: The boundary of a real-life container such as a bucket has thickness, in contrast to the boundary of a closed curve or a sphere. 
  • This observation illustrates my description of a metaphor as identifying part of one situation with part of another. One aspect is emphasized; another aspect, where they may differ, is ignored.

Real number line

  • You may think of the real
    numbers
    as lying along a straight line (the real line) that extends infinitely far in both directions.  This is both visual and a metaphor (a real number “is” a place on the real line).
  • This metaphor is imperfect because you can’t draw the whole real line, but only part of it. But you can’t draw the whole graph of the curve $y=25-(t-5)^2$, either.

Continuous functions

No gaps

“Continuous functions don’t have gaps in the graph”.    This is a visual image, and it is usually OK.

  • But consider the curve defined by $y=25-(t-5)^2$ for every real $x$ except $x=1$. It is not defined at $x=1$ (and so the function is discontinuous there) but its graph looks exactly like the graph in the figure above because no matter how much you magnify it you can’t see the gap.
  • This is a typi­cal math example that teachers make up to raise your consciousness.

  • So is there a gap or not?
No lifting

“Continuous functions can be drawn without lifting the chalk.” This is true in most familiar cases (provided you draw the graph only on a finite interval). But consider the graph of the function defined by $f(0)=0$ and \[f(t)=t\sin\frac{1}{t}\ \ \ \ \ \ \ \ \ \ (0\lt t\lt 0.16)\]
(see Split Definition). This curve is continuous and is infinitely long even though it is defined on a finite interval, so you can’t draw it with a chalk at all, picking up the chalk or not. Note that it has no gaps.

Keeping concepts separate by using mental “space”

I personally use visual images to remember relationships between abstract objects, as well.  For example, if I think of three groups, two of which are isomorphic (for example $\mathbb{Z}_{3}$ and $\text{Alt}_3$), I picture them as in three different places in my head with a connection between the two isomorphic ones.

Notation

Here I give some examples of thinking of math objects in terms of the notation used to name them. There is much more about notation as mathe­matical represen­tation in these sections of abmath:

Notation is both something you visualize in your head and also a physical represen­tation of the object.  In fact notation can also be thought of as a mathe­matical object in itself (common in mathe­matical logic and in theoretical computing science.)   If you think about what notation “really is” a lot,  you can easily get a headache…

Symbols

  • When I think of the square root of $2$, I visualize the symbol “$\sqrt{2}$”. That is both a typographical object and a mathe­matically defined symbolic represen­tation of the square root of $2$.
  • Another symbolic represen­tation of the square root of $2$ is “$2^{1/2}$”. I personally don’t visualize that when I think of the square root of $2$, but there is nothing wrong with visualizing it that way.
  • What is dangerous is thinking that the square root of $2$ is the symbol “$\sqrt{2}$” (or “$2^{1/2}$” for that matter). The square root of $2$ is an abstract mathe­matical object given by a precise mathe­matical definition.
  • One precise defi­nition of the square root of $2$ is “the positive real number $x$ for which $x^2=2$”. Another definition is that $\sqrt{2}=\frac{1}{2}\log2$.

Integers

  • If I mention the number “two thousand, six hundred forty six” you may visualize it as “$2646$”. That is its decimal represen­tation.
  • But $2646$ also has a prime factorization, namely $2\times3^3\times7^2$.
  • It is wrong to think of this number as being the notation “$2646$”. Different notations have different values, and there is no mathe­matical reason to make “$2646$” the “genuine” represen­tation. See represen­tations and Models.
  • For example, the prime factor­ization of $2646$ tells you imme­diately that it is divisible by $49$.

When I was in high school in the 1950’s, I was taught that it was incorrect to say “two thousand, six hundred and forty six”. Being naturally rebellious I used that extra “and” in the early 1960’s in dictating some number in a telegraph mes­sage. The Western Union operator corrected me. Of course, the “and” added to the cost. (In case you are wondering, I was in the middle of a postal Diplomacy game in Graustark.)

Formulas

Set notation

You can think of the set containing $1$, $3$ and $5$ and nothing else as represented by its common list notation $\{1, 3, 5\}$.  But remember that $\{5, 1,3\}$ is another notation for the same set. In other words the list notation has irrelevant features – the order in which the elements are listed in this case.


Kinetic

Shoot a ball straight up

  • The arch function could model the height over time of a physical object, perhaps a ball shot vertically upwards on a planet with no atmosphere.
  • The ball starts upward at time $t=0$ at elevation $0$, reaches an elevation of (for example) $16$ units at time $t=2$, and lands at $t=10$.
  • The parabola is not the path of the ball. The ball goes up and down along the $x$-axis. A point on the parabola shows it locaion on the $x$ axis at time $t$.
  • When you think about this event, you may imagine a physical event continuing over time, not just as a picture but as a feeling of going up and down.
  • This feeling of the ball going up and down is created in your mind presumably using mirror neuron. It is connected in your mind by a physical connection to the understanding of the function that has been created as connections among some of your neurons.
  • Although $h(t)$ models the height of the ball, it is not the same thing as the height of the ball.  A mathe­matical object may have a relationship in our mind to physical processes or situations, but it is distinct from them.

Remarks

  1. This example involves a picture (graph of a function).  According to this report, kinetic
    understanding can also help with learning math that does not involve pictures. 
    For example, when I think of evaluating the function ${{x}^{2}}+1$ at 3, I visualize
    3 moving into the x slot and then the formula $9^2+1$ transforming
    itself into $10$. (Not all mathematicians visualize it this way.)
  2. I make the point of emphasizing the physical existence in your brain of kinetic feelings (and all other metaphors and images) to make it clear that this whole section on images and metaphors is about objects that have a physical existence; they are not abstract ideals in some imaginary ideal space not in our world. See Thinking about thought.

I remember visualizing algebra I this way even before I had ever heard of the Transformers.

Process 

It is common to think of a function as a process: you put in a number (or other object) and the process produces another number or other object. There are examples in Images and metaphors for functions.

Long division

Let’s divide $66$ by $7$ using long division. The process consists of writing down the decimal places one by one.

  1. You guess at or count on your fingers to find the largest integer $n$ for which $7n\lt66$. That integer is $9$.
  2. Write down $9.$ ($9$ followed by a decimal point).
  3. $66-9\times7=3$, so find the largest integer $n$ for which $7n\lt3\times10$, which is $4$.
  4. Adjoin $4$ to your answer, getting $9.4$
  5. $3\times10-7\times4=2$, so find the largest integer $n$ for which $7n\lt2\times10$, which is $2$.
  6. Adjoin $2$ to your answer, getting $9.42$.
  7. $2\times10-7\times2=6$, so find the largest integer for which $7n\lt6\times10$, which is $8$.
  8. Adjoin $8$ to your answer, getting $9.428$.
  9. $6\times10-7\times8=4$, so find the largest integer for which $7n\lt4\times10$, which is $5$.
  10. Adjoin $5$ to your answer, getting $9.4285$.

You can continue with the procedure to get as many decimal places as you wish of $\frac{66}{7}$.

Remark

The sequence of actions just listed is quite difficult to follow. What is difficult is not understanding what they say to do, but where did they get the numbers? So do this exercise!


Exercise worth doing:

Check that the procedure above is exactly what you do to divide $66$ by $7$ by the usual method taught in grammar school:




Remarks
  • The long division process produces as many decimal places as you have stamina for. It is likely for most readers that when you do long division by hand you have done it so much that you know what to do next without having to consult a list of instructions.
  • It is a process or procedure but not what you might want to call a function. The process recursively constructs the successive integers occurring in the decimal expansion of $\frac{66}{7}$.
  • When you carry out the grammar school procedure above, you know at each step what to do next. That is why is it a process. But do you have the procedure in your head all at once?
  • Well, instructions (5) through (10) could be written in a programming language as a while loop, grouping the instructions in pairs of commands ((5) and (6), (7) and (8), and so on). However many times you go through the while loop determines the number of decimal places you get.
  • It can also be described as a formally defined recursive function $F$ for which $F(n)$ is the $n$th digit in the answer.
  • Each of the program and the recursive definition mentioned in the last two bullets are exercises worth doing.
  • Each of the answers to the exercises is then a mathematical object, and that brings us to the next type of metaphor…

Object

A particular kind of metaphor or image for a mathematical concept is that of a mathematical object that represents the concept.

Examples

  • The number $10$ is a mathematical object. The expression “$3^2+1$” is also a mathematical object. It encapsulates the process of squaring $3$ and adding $1$, and so its value is $10$.
  • The long division process above finds the successive decimal places of a fraction of integers. A program that carries out the algorithm encapsulates the process of long division as an algorithm. The result is a mathematical object.
  • The expression “$1958$” is a mathematical object, namely the decimal represen­tation of the number $1958$. The expression
    “$7A6$” is the hexadecimal represen­tation of $1958$. Both represen­tations are mathematical objects with precise definitions.

Represen­tations as math objects is discussed primarily in represen­tations and Models. The difference between represen­tations as math objects and other kinds of mental represen­tations (images and metaphors) is primarily that a math object has a precise mathematical definition. Even so, they are also mental represen­tations.

Uses of mental represen­tations

Mental represen­tations of a concept make up what is arguably the most important part of the mathe­matician’s understanding of the concept.

  • Mental represen­tations of mathe­matical objects using metaphors and images are necessary for understanding and communicating about them (especially with types of objects that are new to us) .
  • They are necessary for seeing how the theory can be applied.
  • They are useful for coming up with proofs. (See example below.) 

Many represen­tations

 Different mental represen­tations of the same kind of object
help you understand different aspects of the object. 


Every important mathe­matical object
has many different kinds of represen­tations
and mathe­maticians typically keep
more that one of them in mind at once.

But images and metaphors are also dangerous (see below).

New concepts and old ones

We especially depend on metaphors and images to understand a math concept that is new to us .  But if we work with it for awhile, finding lots of examples, and
eventually proving theorems and providing counterexamples to conjectures, we begin to understand the concept in its own terms and the images and metaphors tend to fade away from our awareness.

Then, when someone asks us about this concept that we are now experts with, we
trundle out our old images and metaphors – and are often surprised at how difficult and misleading our listener finds them!

Some mathe­maticians retreat from images and metaphors because of this and refuse to do more than state the definition and some theorems about the concept. They are wrong to do this. That behavior encourages the attitude of many people that

  • Mathe­maticians can’t explain things.
  • Math concepts are incomprehensible or bizarre.
  • You have to have a mathe­matical mind to understand math.

In my opinion the third statement is only about 10 percent true.

All three of these statements are half-truths. There is no doubt that a lot of abstract math is hard to understand, but understanding is certainly made easier with the use of images and metaphors. 

Images and metaphors on this website

This website has many examples of useful mental represen­tations.  Usually, when a chapter discusses a particular type of mathe­matical object, say rational numbers, there will be a subhead entitled “Images and metaphors for rational numbers”.  This will suggest ways of thinking about them that many have found useful. 

Two levels of images and metaphors

Images and metaphors have to be used at two different levels, depending on your purpose. 

  • You should expect to use rich view for understanding, applications, and coming up with proofs.
  • You must limit yourself to the rigorous view when constructing and checking proofs.

Math teachers and texts typically do not make an explicit distinction between these views, and you have to learn about it by osmosis. In practice, teachers and texts do make the distinction implicitly.  They will say things
like, “You can think about this theorem as …” and later saying, “Now we give a rigorous proof of the theorem.”  Abstractmath.org makes this distinction explicit in many places throughout the site.

The
rich view

The kind of metaphors and images discussed in the mental represen­tations section above make math rich, colorful and intriguing to think about.  This is the rich view of math.  The rich view is vitally important.  

  • It is what makes math useful and interesting.
  • It helps us to understand the math we are working with.
  • It suggests applications.
  • It suggests approaches to proofs.
Example

You expect the ball whose trajectory is modeled by the function h(t) above  to slow down as it rises, so the derivative of h must be smaller at t
= 4
 than it is at t = 2.  A mathe­matician might even say that that is an “informal proof” that $h'(4)<h'(2)$.  A rigorous proof is given below.

The rigorous view: inertness

When we are constructing a definition or proof we cannot
trust all those wonderful images and metaphors. 

  • Definitions must
    not use metaphors.
  • Proofs must use only logical reasoning based on definitions and
    previously proved theorems.

For the point of view of doing proofs, math
objects must be thought of as inert (or static),
like your pet rock. This means they

  • don’t move or change over time, and
  • don’t interact with other objects, even other mathe­matical objects.

(See also abstract object).

  • When
    mathe­maticians say things like, “Now we give a rigorous proof…”, part of what they mean is that they have to forget about all the color
    and excitement of the rich view and think of math objects as totally
    inert. Like, put the object under an anesthetic
    when you are proving something about it.
  • As I wrote previously, when you are trying to understand arch function $h(t)=25-{{(t-5)}^{2}}$, it helps to think of it as representing a ball thrown directly upward, or as a graph describing the height of the ball at time $t$ which bends over like an arch at the time when the ball stops going upward and begins to fall down.
  • When you proving something about it, you must be in the frame of mind that says the function (or the graph) is all laid out in front of you, unmoving. That is what the rigorous mode requires. Note that the rigorous mode is a way of thinking, not a claim about what the arch function “really is”.
  • When in rigorous mode,  a mathe­matician will
    think of $h$ as a complete mathe­matical object all at once,
    not changing over time. The
    function is the total relationship of the input values of the input parameter
    $t$ to the output values $h(t)$.  It consists of a bunch of interrelated information, but it doesn’t do anything and it doesn’t change.

Formal proof that $h'(4)<h'(2)$

Above, I gave an informal argument for this.   The rigorous way to see that $h'(4)\lt h'(2)$ for the arch function is to calculate the derivative \[h'(t)=10-2t\] and plug in 4 and 2 to get \[h'(4)=10-8=2\] which is less than $h'(2)=10-4=6$.

Note the embedded
phrases
.

This argument picks out particular data about the function that
prove the statement.  It says nothing about anything slowing down as $t$
increases.  It says nothing about anything at all changing.

Other examples

  • The rigorous way to say that “Integers go to infinity in both directions” is something like this:  “For every integer n there is an integer k such that k < n  and an integer m such that n < m.”
  • The rigorous way to say that continuous functions don’t have gaps in their graph is to use the $\varepsilon-\delta $ definition of continuity.
  • Conditional assertions are one important aspect of mathe­matical reasoning in which this concept of unchanging inertness clears up a lot of misunderstanding.   “If… then…” in our intuition contains an idea of causation and of one thing happening before another (see also here).  But if objects are inert they don’t cause anything and if they are unchanging then “when” is meaningless.

The rigorous view does not apply to all abstract objects, but only to mathe­matical objects.  See abstract objects for examples.

Metaphors and images are dangerous

The price of metaphor is eternal vigilance.–Norbert Wiener

Every
mental represen­tation has flaws. Each oneprovides a way of thinking about an $A$ as a kind of $B$ in some respects. But the represen­tation can have irrelevant features.  People new to the subject will be tempted to think  about $A$ as a kind of $B$ in inappropriate respects as well.  This is a form of cognitive dissonance.

 It may be that most difficulties students have with abstract math are based on not knowing which aspects of a given represen­tation are applicable in a given situation.  Indeed, on not being consciously aware that in general you must restrict the applicability of the mental pictures that come with a represen­tation.

In abstractmath.org you will sometimes see this statement:  “What is wrong with this metaphor:”  (or image, or represen­tation) to warn you about the flaws of that particular represen­tation.

Example

The graph of the arch function $h(t)$ makes it look like the two arms going downward become so nearly vertical that the curve has vertical asymptotes
But it does not have asymptotes.  The arms going down are underneath every point of the $x$-axis. For example, there is a point on the curve underneath the point $(999,0)$, namely $(999, -988011)$.

Example

A set is sometimes described as analogous to A container. But consider:  the integer 3 is “in” the set of all odd integers, and it is also “in” the set $\left\{ 1,\,2,\,3 \right\}$.  How could something be in two containers at once?  (More about this here.)

An analogy can be help­ful, but it isn’t the same thing as the same thing. – The Economist

Example

Mathe­maticians think of the real numbers as constituting a line infinitely long in both directions, with each number as a point on the line. But this does not mean that you can think of the line as a row of points. See density of the real line.

Example

We commonly think of functions as machines that turn one number into another.  But this does not mean that, given any such function, we can construct a machine (or a program) that can calculate it.  For many functions, it is not only impractical to do, it is theoretically
impossible to do it.
They are not href=”http://en.wikipedia.org/wiki/Recursive_function_theory#Turing_computability”>computable. In other words, the machine picture of a function does not apply to all functions.

Summary


The images and metaphors you use
to think about a mathe­matical object
are limited in how they apply.


The images and metaphors you use to think about the subject
cannot be directly used in a proof.
Only definitions and previously proved theorems can be used in a proof.

Final remarks

Mental represen­tations are physical represen­tations

It seems likely that cognitive phenomena such as images and metaphors are physically represented in the brain as collec­tions of neurons connected in specific ways.  Research on this topic is pro­ceeding rapidly.  Perhaps someday we will learn things about how we think physi­cally that actually help us learn things about math.

In any case, thinking about mathe­matical objects as physi­cally represented in your brain (not neces­sarily completely or correctly!) wipes out a lot of the dualistic talk about ideas and physical objects as
separate kinds of things.  Ideas, in partic­ular math objects, are emergent constructs in the
physical brain. 

About metaphors

The language that nature speaks is mathe­matics. The language that ordinary human beings speak is metaphor. Freeman Dyson

“Metaphor” is used in abstractmath.org to describe a type of thought configuration.  It is an implicit conceptual identification
of part of one type of situation with part of another. 

Metaphors are a fundamental way we understand the world. In particular,they are a fundamental way we understand math.

The word “metaphor”

The word “metaphor” is also used in rhetoric as the name of a type of figure of speech.  Authors often refer to metaphor in the meaning of  thought configuration as a conceptual metaphor.  Other figures of speech, such as simile and synecdoche, correspond to conceptual metaphors as well.

References for metaphors in general cognition:

Fauconnier, G. and Turner, M., The Way We Think: Conceptual Blending And The Mind’s Hidden Complexities . Basic Books, 2008.

Lakoff, G., Women, Fire, and Dangerous Things. The University of Chicago Press, 1986.

Lakoff, G. and Mark Johnson, Metaphors We Live By
The University of Chicago Press, 1980.

References for metaphors and images in math:

Byers, W., How mathe­maticians Think.  Princeton University Press, 2007.

Lakoff, G. and R. E. Núñez, Where mathe­matics Comes
From
. Basic Books, 2000.

Math Stack Exchange list of explanatory images in math.

Núñez, R. E., “Do Real Numbers Really Move?”  Chapter
in 18 Unconventional Essays on the Nature of mathe­matics, Reuben Hersh,
Ed. Springer, 2006.

Charles Wells,
Handbook of mathe­matical Discourse.

Charles Wells, Conceptual blending. Post in Gyre&Gimble.

Other articles in abstractmath.org

Conceptual and computational

Functions: images and metaphors

Real numbers: images and metaphors

represen­tations and models

Sets: metaphors and images

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Representations of mathematical objects

This is a long post. Notes on viewing.

About this post

A mathematical object, or a type of math object, is represented in practice in a great variety of ways, including some that mathematicians rarely think of as "representations".  

In this post you will find examples and comments about many different types of representations as well as references to the literature. I am not aware that anyone has considered all these different ideas of representation in one place before. Reading through this post should raise your consciousness about what is going on when you do math.  

This is also an experiment in exposition.  The examples are discussed in a style similar to the way a Mathematica command is discussed in the Documentation Center, using mostly nonhierarchical bulleted lists. I find it easy to discover what I want to know when it is written in that way.  (What is hard is discovering the name of a command that will do what I want.)

Types of representations

Using language

  • Language can be used to define a type of object.
  • A definition is intended to be precise enough to determine all the properties that objects of that type all have.  (Pay attention to the two uses of the word "all" in that sentence; they are both significant, in very different ways.)
  • Language can be used to describe an object, exhibiting properties without determining all properties.
  • It can also provide metaphors, making use of one of the basic tools of our brain to understand the world. 
  • The language used is most commonly mathematical English, a special dialect of English.
  • The symbolic language of mathematics (distinct from mathematical English) is used widely in calculations. Phrases from the symbolic language are often embedded in a statement in math English. The symbolic language includes among others algebraic notation and logical notation. 
  • The language may also be a formal language, a language that is mathematically defined and is thus itself a mathematical object. Logic texts generally present the first order predicate calculus as a formal language. 
  • Neither mathematical English nor the symbolic language is a formal language. Both allow irregularities and ambiguities.

Mathematical objects

The representation itself may be a mathematical object, such as:

  • A linear representation of a group. Not only are the groups mathematical objects, so is the representation.
  • An embedding of a manifold into Euclidean space. A definition given in a formal language of the first order predicate calculus of the property of commutativity of binary operations. (Thus a property can be represented as a math object.)

Visual representations

A math object can be represented visually using a physical object such as a picture, graph (in several senses), or diagram.  

  • The visual processing of our brain is our major source of knowledge of the world and takes about a fifth of the brain's processing power.  We can learn many things using our vision that would take much longer to learn using verbal descriptions.  (Proofs are a different matter.)
  • When you look at a graph (for example) your brain creates a mental representation of the graph (see below).

Mental representations

If you are a mathematician, a math object such as "$42$", "the real numbers" or "continuity" has a mental representation in your brain.  

  • In the math ed literature, such a representation is called "mental image", "concept image", "procept", or "schema".   (The word "image" in these names is not thought of as necessarily visual.) 
  • The procept or schema describe all the things that come to mind when you think about a particular math object: The definition, important theorems, visual images, important examples, and various metaphors that help you understand it. 
  • The visual images occuring in a mental schema for an object may themselves be mental representations of physical objects. The examples and theorems may be mental representations of ideas you learned from language or pictures, and so on.  The relationships between different kinds of representations get quite convoluted.

Metaphors

Conceptual metaphors are a particular kind of mental representation of an object which involve mentally associating some aspects of the objects with some aspects of something else — a physical object, an image, an action or another abstract object.

  • A conceptual metaphor may give you new insight into the object.
  • It may also mislead you because you think of properties of the other object that the math object doesn't have.
  • A graph of a function is a conceptual metaphor.
  • When you say that a point on a graph "rises as it goes from left to right" your metaphor is an action. 
  • When you say that the cosets of a normal subgroup of a group "get along" with the group multiplication, your metaphor identifies a property they have with an aspect of human behavior.

Properties of representations

A representation of a math object may or may not

  • determine it completely
  • exhibit some of its properties
  • suggest easy proofs of some theorems
  • provide a useful way of thinking about it
  • mislead you about the object's properties
  • mislead you about what is significant about the object

Examples of representations

This list shows many of the possibilities of representation.  In each case I discuss the example in terms of the two bulleted lists above. Some of the examples are reused from my previous publications.

Functions

Example (F1) "Let $f(x)$ be the function defined by $f(x)=x^3-x$."

  • This is an expression in mathematical English that a fluent reader of mathematical English will recognize gives a definition of a specific function.
  • (F1) is therefore a representation of that function.  
  • The word "representation" is not usually used in this way in math.  My intention is that it should be recognized as the same kind of object as many other representations.
  • The expression contains the formula $x^3-x$.  This is an encapsulated computation in the symbolic language of math. It allows someone who knows basic algebra and calculus to perform calculations that find the roots, extrema and inflection points of the function $f$.  
  • The word "let" suggests to the fluent reader of mathematical English that (F1) is a definition which is probably going to hold for the next chunk of text, but probably not for the whole article or book.
  • Statements in mathematical English are generally subject to conventions.  In a calculus text (F1) would automatically mean that the function had the real numbers as domain and codomain.
  • The last two remarks show that a beginner has to learn to read mathematical English. 
  • Another convention is discussed in the following diatribe.

Diatribe 

You would expect $f(x)$ by itself to mean the value of $f$ at $x$, but in (F1) the $x$ has the property of a bound variable.  In mathematical English, "let" binds variables. However, after the definition, in the text the "$x$" in the expression "$f(x)$" will be free, but the $f$ will be bound to the specific meaning.  It is reasonable to say that the term "$f(x)$" represents the expression "$x^3-x$" and that $f$ is the (temporary) name of the function. Nevertheless, it is very common to say "the function $f(x)$" to mean $f$.  

A fluent reader of mathematical English knows all this, but probably no one has ever said it explicitly to them.  Mathematical English and the symbolic language should be taught explicitly, including its peculiarities such as "the function $f(x)$".  (You may want to deprecate this usage when you teach it, but students deserve to understand its meaning.)

The positive integers

You have a mental representation of the positive integers $1,2,3,\ldots$.  In this discussion I will assume that "you" know a certain amount of math.  Non-mathematicians may have very different mental representations of the integers.

  • You have a concept of "an integer" in some operational way as an abstract object.
  • "Abstract object" needs a post of its own. Meanwhile see Mathematical Objects (abstractmath) and the Wikipedia articles on Mathematical objects and Abstract objects.
  • You have a connection in your brain between the concept of integer and the concept of listing things in order, numbering them by $1,2,3,\ldots$.
  • You have a connection in your brain between the concept of an integer and the concept of counting a finite number of objects.  But then you need zero!
  • You understand how to represent an integer using the decimal representation, and perhaps representations to other bases as well. 
  • Your mental image has the integer "$42"$ connected to but not the same as the decimal representation "42". This is not true of many students.
  • The decimal rep has a picture of the string "42" associated to it, and of course the picture of the string may come up when you think of the integer $42$ as well (it does for me — it is a an icon for the number $42$.)
  • You have a concept of the set of integers. 
  • Students need to be told that by convention "the set of integers" means the set of all integers.  This particularly applies to students whose native language does not have articles, but American students have trouble with this, too.
  • Your concept of  "the set of integers" may have the icon "$\mathbb{N}$" associated with it.  If you are a mathematician, the icon and the concept of the set of integers are associated with each other but not identified with each other.
  • For me, at least, the concept "set of integers" is mentally connected to each integer by the "element of" relation. (See third bullet below.)
  • You have a mental representation of the fact that the set of integers is infinite.  
  • This does not mean that your brain contains an infinite number of objects, but that you have a representation of infinity as a concept, it is brain-connected to the concept of the set of integers, and also perhaps to a proof of the fact that $\mathbb{N}$ is infinite.
  • In particular, the idea that the set of integers is mentally connected to each integer does not mean that the whole infinite number of integers is attached in your brain to the concept of the set of integers.  Rather, the idea is a predicate in your brain.  When it is connected to "$42$", it says "yes".  To "$\pi$" it says "No".
  • Philosophers worry about the concept of completed infinity.  It exists as a concept in your brain that interacts as a meme with concepts in other mathematicians' brains. In that way, and in that way only (as far as I am concerned) it is a physical object, in particular an object that exists in scattered physical form in a social network.

Graph of a function

This is a graph of the function $y=x^3-x$:

Graph of a cubic function

  • The graph is a physical object, either on a screen or on paper
  • It is processed by your visual system, the most powerful sensory management system in your brain
  • It also represents the graph in the mathematical sense (set of ordered pairs) of the function $y=x^3-x$
  • Both the mathematical graph and the physical graph are represented by modules in your brain, which associates the two of them with each other by a conceptual metaphor
  • The graph shows some properties of the function: inflection point, going off to infinity in a specific way, and so on.
  • These properties are made apparent (if you are knowledgeable) by means of the powerful pattern recognition system in your brain. You see them much more quickly than you can discover them by calculation.
  • These properties are not proved by the graph. Nevertheless, the graph communicates information: for example, it suggests that you can prove that there is an inflection point near $(0,0)$.
  • The graph does not determine or define the function: It is inaccurate and it does not (cannot) show all of the graph.
  • More subtle details about this graph are discussed in my post Representations 2.

Continuity

Example (C1) The $\epsilon-\delta$ definition of the continuity of a function $f:\mathbb{R}\to\mathbb{R}$ may be given in the symbolic language of math:

A function $f$ is continuous at a number $c$ if \[\forall\epsilon(\epsilon\gt0\implies(\forall x(\exists\delta(|x-c|\lt\delta\implies|f(x)-f(c)|\lt\epsilon)))\]

  • To understand (C1), you must be familiar with the notation of first order logic.  For most students, getting the notation right is quite a bit of work.  
  • You must also understand  the concepts, rules and semantics of first order logic.  
  • Even if you are familiar with all that, continuity is still a difficult concept to understand.
  • This statement does show that the concept is logically complicated. I don't see how it gives any other intuition about the concept. 

Example (C2) The definition of continuity can also be represented in mathematical English like this:

A function $f$ is continuous at a number $c$ if for any $\epsilon\gt0$ and for any $x$ there is a $\delta$ such that if $|x-c|\lt\delta$, then $|f(x)-f(c)|\lt\epsilon$. 

  • This definition doesn't give any more intuition that (C1) does.
  • It is easier to read that (C1) for most math students, but it still requires intimate familiarity with the quirks of math English.
  • The fact that "continuous" is in boldface signals that this is a definition.  This is a convention.
  • The phrase "For any $\epsilon\gt0$" contains an unmarked parenthetic insertion that makes it grammatically incoherent.  It could be translated as: "For any $\epsilon$ that is greater than $0$".  Most math majors eventually understand such things subconsciously.  This usage is very common.
  • Unless it is explicitly pointed out, most students won't notice that  if you change the phrase "for any $x$ there is a $\delta$"  to "there is a $\delta$ for any $x$" the result means something quite different.  Cauchy never caught onto this.
  • In both (C1) and (C2), the "if" in the phrase "A function $f$ is continuous at a number $c$ if…" means "if and only if" because it is in a definition.  Students rarely see this pointed out explicitly.  

Example (C3) The definition of continuity can be given in a formally defined first order logical theory

  • The theory would have to contain function symbols and axioms expressing the algebra of real numbers as an ordered field. 
  • I don't know that such a definition has ever been given, but there are various semi-automated and automated theorem-proving systems (which I know little about) that might be able to state such a definition.  I would appreciate information about this.
  • Such a definition would make the property of continuity a mathematical object.
  • An automated theorem-proving system might be able to prove that $x^3-x$ is continuous, but I wonder if the resulting proof would aid your intuition much.

Example (C4) A function from one topological space to another is continuous if the inverse of every open set in the codomain is an open set in the domain.

  • This definition is stated in mathematical English.
  • All definitions start with primitive data. 
  • In definitions (C1) – (C3), the primitive data are real numbers and the statement uses properties of an ordered field.
  • In (C4), the data are real numbers and the arithmetic operations of a topological field, along with the open sets of the field. The ordering is not mentioned.
  • This shows that a definition need not mention some important aspects of the structure. 
  • One marvelous example of this is that  a partition of a set and an equivalence relation on a set are based on essentially disjoint sets of data, but they define exactly the same type of structure.

Example (C4) "The graph of a continuous function can be drawn without picking up the chalk".

  • This is a metaphor that associates an action with the graph.
  • It is incorrect: The graphs of some continuous functions cannot be drawn.  For example, the function $x\mapsto x^2\sin(1/x)$ is continuous on the interval $[-1,1]$ but cannot be drawn at $x=0$. 
  • Generally speaking, if the function can be drawn then it can be drawn without picking up the chalk, so the metaphor provides a useful insight, and it provides an entry into consciousness-raising examples like the one in the preceding bullet.

References

  1. 1.000… and .999… (post)
  2. Conceptual blending (post)
  3. Conceptual blending (Wikipedia)
  4. Conceptual metaphors (Wikipedia)
  5. Convention (abstractmath)
  6. Definitions (abstractmath)
  7. Embodied cognition (Wikipedia)
  8. Handbook of mathematical discourse (see articles on conceptual blendmental representationrepresentationmetaphor, parenthetic assertion)
  9. Images and Metaphors (abstractmath).
  10. The interplay of text, symbols and graphics in math education, Lin Hammill
  11. Math and the modules of the mind (post)
  12. Mathematical discourse: Language, symbolism and visual images, K. L. O’Halloran.
  13. Mathematical objects (abmath)
  14. Mathematical objects (Wikipedia)
  15. Mathematical objects are “out there?” (post)
  16. Metaphors in computing science ​(post)
  17. Procept (Wikipedia)
  18. Representations 2 (post)     
  19. Representations and models (abstractmath)
  20. Representations II: dry bones (post)
  21. Representation theorems (Wikipedia) Concrete representations of abstractly defined objects.
  22. Representation theory (Wikipedia) Linear representations of algebraic structures.
  23. Semiotics, symbols and mathematical visualization, Norma Presmeg, 2006.
  24. The transition to formal thinking in mathematics, David Tall, 2010
  25. Theory in mathematical logic (Wikipedia)
  26. What is the object of the encapsulation of a process? Tall et al., 2000.
  27. Where mathematics comes from, by George Lakoff and Rafael Núñez, Basic Books, 2000. 
  28. Where mathematics comes from (Wikipedia) This is a review of the preceding book.  It is a permanent link to the version of 04:23, 25 October 2012.  The review is opinionated, partly wrong, not well written and does not fit the requirements of a Wikipedia entry.  I recommend it anyway; it is well worth reading.  It contains links to three other reviews.

Notes on Viewing  

This post uses MathJax. If you see mathematical expressions with dollar signs around them, or badly formatted formulas, try refreshing the screen. Sometimes you have to do it two or three times.

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Metaphors in computing science 2

In Metaphors in Computer Science 1, I discussed some metaphors used when thinking about various aspects of computing.  This is a continuation of that post.

Metaphor: A program is a list of instructions.

  • I discussed this metaphor in detail in the earlier post.
  • Note particularly that the instructions can be in a natural or a programming language. (Is that a zeugma?)  Many writers would call instructions in a natural language an algorithm.
  • I will continue to use “program” in the broader sense.

Metaphor: A programming language is a language.

  • This metaphor is a specific conceptual blend that associates the strings of symbols that constitute a program in a computer language with text in a natural language.
  • The metaphor is based on some similarities between expressions in a programming language and expressions in a natural language.
    • In both, the expressions have a meaning.
    • Both natural and programming languages have specific rules for constructing well-formed expressions.
  • This way of thinking ignores many deep differences between programming languages and natural languages. In particular, they don’t talk about the same things!
  • The metaphor has been powerful in suggesting ways of thinking about computer programs, for example semantics (below) and ambiguity.

Metaphor: A computer program is a list of statements

  • A consequence of this metaphor is that a computer program is a list of symbols that can be stored in a computer’s memory.
  • This metaphor comes with the assumption that if the program is written in accordance with the language’s rules, a computer can execute the program and perhaps produce an output.
  • This is the profound discovery, probably by Alan Turing, that made the computer revolution possible. (You don’t have to have different physical machines to do different things.)
  • You may want me to say more in the heading above: “A computer program is a list of statements in a programming language that satisfies the well-formedness requirements of the language.”  But the point of the metaphor is only that a program is a list of statements.  The metaphor is not intended to define the concept of “program”.

Metaphor: A program in a computer language has meanings.

A program is intended to mean something to a human reader.

  • Some languages are designed to be easily read by a human reader: Cobol, Basic, SQL.
    • Their instructions look like English.
    • The algorithm can nevertheless be difficult to understand.
  • Some languages are written in a dense symbolic style.
    • In many cases the style is an extension of the style of algebraic formulas: C, Fortran.
    • Other languages are written in a notation not based on algebra:  Lisp, APL, Forth.
  • The boundary between “easily read” and “dense symbolic” is a matter of opinion!

A program is intended to be executed by a computer.

  • The execution always involves translation into intermediate languages. 
    • Most often the execution requires repeated translation into a succession of intermediate languages.
    • Each translation requires the preservation of the intended meaning of the program.
  • The preservation of intended meaning is what is usually called the semanticsof a programming language.
    • In fact, the meaning of the program to a person could be called semantics, too.
    • And the human semantics had better correspond in “meaning” to the machine semantics!
  • The actual execution of the program requires successive changes in the state of the computer.
    • By “state” I mean a list of the form of the electrical charges of each unit of memory in the computer.
    • Or you can restrict it to the relevant units of memory, but spelling that out is horrifying to contemplate.
    • The resulting state of the machine after the program is run is required to preserve the intended meaning as well as all the intermediate translations.
    • Notice that the actual execution is a series of physical events.  You can describe the execution in English or in some notation, but that notation is not the actual execution.

References

Conceptual blend (Wikipedia)

Conceptual metaphors (Wikipedia)

Images and Metaphors (article in abstractmath)

Semantics in computer science (Wikipedia)

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