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mathematics , the science of structure, order, and relation that has evolved from elemental practices of counting, measuring, and describing the shapes of objects. It deals with logical reasoning and quantitative calculation, and its development has involved an increasing degree of idealization and abstraction of its subject matter. Since the 17th century, mathematics has been an indispensable adjunct to the physical sciences and technology, and in more recent times it has assumed a similar role in the quantitative aspects of the life sciences.

In many cultures—under the stimulus of the needs of practical pursuits, such as commerce and agriculture—mathematics has developed far beyond basic counting. This growth has been greatest in societies complex enough to sustain these activities and to provide leisure for contemplation and the opportunity to build on the achievements of earlier mathematicians.

All mathematical systems (for example, Euclidean geometry ) are combinations of sets of axioms and of theorems that can be logically deduced from the axioms. Inquiries into the logical and philosophical basis of mathematics reduce to questions of whether the axioms of a given system ensure its completeness and its consistency. For full treatment of this aspect, see mathematics, foundations of .

This article offers a history of mathematics from ancient times to the present. As a consequence of the exponential growth of science, most mathematics has developed since the 15th century ce , and it is a historical fact that, from the 15th century to the late 20th century, new developments in mathematics were largely concentrated in Europe and North America . For these reasons, the bulk of this article is devoted to European developments since 1500.

Italian-born physicist Dr. Enrico Fermi draws a diagram at a blackboard with mathematical equations. circa 1950.

This does not mean, however, that developments elsewhere have been unimportant. Indeed, to understand the history of mathematics in Europe, it is necessary to know its history at least in ancient Mesopotamia and Egypt, in ancient Greece, and in Islamic civilization from the 9th to the 15th century. The way in which these civilizations influenced one another and the important direct contributions Greece and Islam made to later developments are discussed in the first parts of this article.

India’s contributions to the development of contemporary mathematics were made through the considerable influence of Indian achievements on Islamic mathematics during its formative years. A separate article, South Asian mathematics , focuses on the early history of mathematics in the Indian subcontinent and the development there of the modern decimal place-value numeral system . The article East Asian mathematics covers the mostly independent development of mathematics in China, Japan, Korea, and Vietnam.

essay about the nature of mathematics

The substantive branches of mathematics are treated in several articles. See algebra ; analysis ; arithmetic ; combinatorics ; game theory ; geometry ; number theory ; numerical analysis ; optimization ; probability theory ; set theory ; statistics ; trigonometry .

essay about the nature of mathematics

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Title18 Unconventional Essays on the Nature of Mathematics
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Editionillustrated
PublisherSpringer, 2006
ISBN0387257179, 9780387257174
Length326 pages
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R S T I Chapter 2: THE NATURE OF MATHEMATICS

 

P R

Mathematics is the science of patterns and relationships. As a theoretical discipline, mathematics explores the possible relationships among abstractions without concern for whether those abstractions have counterparts in the real world. The abstractions can be anything from strings of numbers to geometric figures to sets of equations. In addressing, say, "Does the interval between prime numbers form a pattern?" as a theoretical question, mathematicians are interested only in finding a pattern or proving that there is none, but not in what use such knowledge might have. In deriving, for instance, an expression for the change in the surface area of any regular solid as its volume approaches zero, mathematicians have no interest in any correspondence between geometric solids and physical objects in the real world.

A central line of investigation in theoretical mathematics is identifying in each field of study a small set of basic ideas and rules from which all other interesting ideas and rules in that field can be logically deduced. Mathematicians, like other scientists, are particularly pleased when previously unrelated parts of mathematics are found to be derivable from one another, or from some more general theory. Part of the sense of beauty that many people have perceived in mathematics lies not in finding the greatest elaborateness or complexity but on the contrary, in finding the greatest economy and simplicity of representation and proof. As mathematics has progressed, more and more relationships have been found between parts of it that have been developed separately—for example, between the symbolic representations of algebra and the spatial representations of geometry. These cross-connections enable insights to be developed into the various parts; together, they strengthen belief in the correctness and underlying unity of the whole structure.

Mathematics is also an applied science. Many mathematicians focus their attention on solving problems that originate in the world of experience. They too search for patterns and relationships, and in the process they use techniques that are similar to those used in doing purely theoretical mathematics. The difference is largely one of intent. In contrast to theoretical mathematicians, applied mathematicians, in the examples given above, might study the interval pattern of prime numbers to develop a new system for coding numerical information, rather than as an abstract problem. Or they might tackle the area/volume problem as a step in producing a model for the study of crystal behavior.

The results of theoretical and applied mathematics often influence each other. The discoveries of theoretical mathematicians frequently turn out—sometimes decades later—to have unanticipated practical value. Studies on the mathematical properties of random events, for example, led to knowledge that later made it possible to improve the design of experiments in the social and natural sciences. Conversely, in trying to solve the problem of billing long-distance telephone users fairly, mathematicians made fundamental discoveries about the mathematics of complex networks. Theoretical mathematics, unlike the other sciences, is not constrained by the real world, but in the long run it contributes to a better understanding of that world.

 

S , T

Because of its abstractness, mathematics is universal in a sense that other fields of human thought are not. It finds useful applications in business, industry, music, historical scholarship, politics, sports, medicine, agriculture, engineering, and the social and natural sciences. The relationship between mathematics and the other fields of basic and applied science is especially strong. This is so for several reasons, including the following:

= is not simply a shorthand way of saying that the acceleration of an object depends on the force applied to it and its mass; rather, it is a precise statement of the quantitative relationship among those variables. More important, mathematics provides the grammar of science—the rules for analyzing scientific ideas and data rigorously.

 

I

Using mathematics to express ideas or to solve problems involves at least three phases: (1) representing some aspects of things abstractly, (2) manipulating the abstractions by rules of logic to find new relationships between them, and (3) seeing whether the new relationships say something useful about the original things.

Mathematical thinking often begins with the process of abstraction—that is, noticing a similarity between two or more objects or events. Aspects that they have in common, whether concrete or hypothetical, can be represented by symbols such as numbers, letters, other marks, diagrams, geometrical constructions, or even words. Whole numbers are abstractions that represent the size of sets of things and events or the order of things within a set. The circle as a concept is an abstraction derived from human faces, flowers, wheels, or spreading ripples; the letter A may be an abstraction for the surface area of objects of any shape, for the acceleration of all moving objects, or for all objects having some specified property; the symbol + represents a process of addition, whether one is adding apples or oranges, hours, or miles per hour. And abstractions are made not only from concrete objects or processes; they can also be made from other abstractions, such as kinds of numbers (the even numbers, for instance).

Such abstraction enables mathematicians to concentrate on some features of things and relieves them of the need to keep other features continually in mind. As far as mathematics is concerned, it does not matter whether a triangle represents the surface area of a sail or the convergence of two lines of sight on a star; mathematicians can work with either concept in the same way. The resulting economy of effort is very useful—provided that in making an abstraction, care is taken not to ignore features that play a significant role in determining the outcome of the events being studied.

After abstractions have been made and symbolic representations of them have been selected, those symbols can be combined and recombined in various ways according to precisely defined rules. Sometimes that is done with a fixed goal in mind; at other times it is done in the context of experiment or play to see what happens. Sometimes an appropriate manipulation can be identified easily from the intuitive meaning of the constituent words and symbols; at other times a useful series of manipulations has to be worked out by trial and error.

Typically, strings of symbols are combined into statements that express ideas or propositions. For example, the symbol for the area of any square may be used with the symbol for the length of the square's side to form the proposition = . This equation specifies how the area is related to the side—and also implies that it depends on nothing else. The rules of ordinary algebra can then be used to discover that if the length of the sides of a square is doubled, the square's area becomes four times as great. More generally, this knowledge makes it possible to find out what happens to the area of a square no matter how the length of its sides is changed, and conversely, how any change in the area affects the sides.

Mathematical insights into abstract relationships have grown over thousands of years, and they are still being extended—and sometimes revised. Although they began in the concrete experience of counting and measuring, they have come through many layers of abstraction and now depend much more on internal logic than on mechanical demonstration. In a sense, then, the manipulation of abstractions is much like a game: Start with some basic rules, then make any moves that fit those rules—which includes inventing additional rules and finding new connections between old rules. The test for the validity of new ideas is whether they are consistent and whether they relate logically to the other rules.

Mathematical processes can lead to a kind of model of a thing, from which insights can be gained about the thing itself. Any mathematical relationships arrived at by manipulating abstract statements may or may not convey something truthful about the thing being modeled. For example, if 2 cups of water are added to 3 cups of water and the abstract mathematical operation 2+3 = 5 is used to calculate the total, the correct answer is 5 cups of water. However, if 2 cups of sugar are added to 3 cups of hot tea and the same operation is used, 5 is an incorrect answer, for such an addition actually results in only slightly more than 4 cups of very sweet tea. The simple addition of volumes is appropriate to the first situation but not to the second—something that could have been predicted only by knowing something of the physical differences in the two situations. To be able to use and interpret mathematics well, therefore, it is necessary to be concerned with more than the mathematical validity of abstract operations and to also take into account how well they correspond to the properties of the things represented.

Sometimes common sense is enough to enable one to decide whether the results of the mathematics are appropriate. For example, to estimate the height 20 years from now of a girl who is 5' 5" tall and growing at the rate of an inch per year, common sense suggests rejecting the simple "rate times time" answer of 7' 1" as highly unlikely, and turning instead to some other mathematical model, such as curves that approach limiting values. Sometimes, however, it may be difficult to know just how appropriate mathematical results are—for example, when trying to predict stock-market prices or earthquakes.

Often a single round of mathematical reasoning does not produce satisfactory conclusions, and changes are tried in how the representation is made or in the operations themselves. Indeed, jumps are commonly made back and forth between steps, and there are no rules that determine how to proceed. The process typically proceeds in fits and starts, with many wrong turns and dead ends. This process continues until the results are good enough.

But what degree of accuracy is good enough? The answer depends on how the result will be used, on the consequences of error, and on the likely cost of modeling and computing a more accurate answer. For example, an error of 1 percent in calculating the amount of sugar in a cake recipe could be unimportant, whereas a similar degree of error in computing the trajectory for a space probe could be disastrous. The importance of the "good enough" question has led, however, to the development of mathematical processes for estimating how far off results might be and how much computation would be required to obtain the desired degree of accuracy.

Copyright © 1989, 1990 by American Association for the Advancement of Science

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To arrive at the edge of the world's knowledge, seek out the most complex and sophisticated minds, put them in a room together, and have them ask each other the questions they are asking themselves.

ON THE NATURE OF MATHEMATICAL CONCEPTS: WHY AND HOW DO MATHEMATICIANS JUMP TO CONCLUSIONS?

In 1997, my son George Dyson   handed me a batch of comments dated Oct. 29— Edge #29 ("What Are Numbers, Really? A Cerebral Basis For Number Sense") , by Stanislas Dehaene and Nov. 7— Edge #30 (the subsequent Reality Club discussion) by a group of Edge  researchers. I read it all with great interest, and then my head started spinning.

Anyone interested in the psychology (or even psycho-pathology) of mathematical activity could have had fun watching me these last weeks. And now here I am with an octopus of inconclusive ramblings on the Foundations bulging my in "essays" file and a proliferation of hieroglyphs in the one entitled "doodles." It is so much easier to do mathematics than to philosophize about it. My group theoretic musings, the doodles, have been a refuge all my life.

Although I am a mathematician, did research in group theory and have taught in various mathematics departments (Berkeley, U of Ill in Chicago, and others), my move to Canada landed me in the philosophy department of the University of Calgary. That is where I got exposed to the philosophy of Mathematics and of the Sciences and even taught in these realms, although my main job was teaching logic which led to a book on Gödel's theorems. To my mind the pure philosophers, those who believe there are problems that they can get to grips with by pure thinking, are the worst.

If I am right, you Reality people all have a definite subject of research and a down to earth approach to it. That is great.

There are two issues in your group's commentary that I would like to address and possibly clarify.

For a refutation of Platonism George Lakoff appeals to non standard phenomena on the one hand and to the deductive incomplenetess of geometry and of set theory on the other. First of all these two are totally different situations, to each of which the Platonist would have an easy retort. The first one is simply a matter of the limitation inherent in first order languages: they are not capable of fully characterizing the "intended Models," the models that the symbolisms are meant to describe. The Platonist will of course exclaim: "If you do not believe in the objective existence of those standard models, how can you tell what is standard and what is not?" The deductive incompleteness of a theory such as geometry or set theory, however, simply means that the theory leaves some sentences undecided. Here the Platonist will point out that your knowledge of the object envisaged is incomplete and encourage you to forge ahead looking for more axioms, i.e., basic truths!

Incidentally I consider myself an Intuitionist not a Platonist.

I wonder whether it is appropriate for me to send you my rather lengthy discourse on non standard phenomena. You may find it tedious. Yet I believe that the question, how it is possible for us to form ideas so definite that we can make distinctions transcending the reach of formal languages? is pertinent to your topic "what are numbers really?" It is very difficult to put these phenomena into a correct perspective without explaining at least a little bit how they come about.

The other contribution is a simple illustration of the naive mathematical mind at work on the number 1729! And a remark about a prodigy.

—Verena Huber-Dyson

VERENA HUBER-DYSON is a mathematician who received her PhD from the University of Zurich in 1947. She has published research in group theory, and taught in various mathematics departments such as UC Berkeley and University of Illinois at Chicago. She is now emeritus professor from the philosophy department of the University of Calgary where she taught logic and philosophy of the sciences and of mathematics, which led to a book on Gödel's theorems published in 1991.

Notation: x for products: 2 x 3 =6, ^3 for cubes: 2^3 = 8, ^exponent: 2^11 = 2048.

While engaged in the mathematical endeavor, we simply jump, hardly ever asking "why" or "how." It is the only way we know of grappling with the mathematical problem that we are out to understand, to articulate as a question and to answer by a theorem or a whole theory. What drives our curiosity is a question for psychologists. Only after the jump has landed us on a viable branch can the labor of proving the theorem or constructing a coherent theory set in. The record of the end result, usually a presentation at a conference, a paper in a learned journal or a chapter in a book, is laid out in a sequence of rational deductions from clearly stated premises and rarely conveys the process by which it has been arrived at.

The question of why we have no other choice but to jump has received a remarkably precise answer through Gödel's Proof of Incompleteness in 1931 and Tarski's analysis of the concept of Truth in the thirties in Poland. Since then the development of a rigorous concept of an algorithm has led to a proliferation of so-called undecidability and inseparability results underscoring the limitations of the formal method.

The question of how we jump has many aspects. First: What does the jumping consist of? What are we doing when we jump? What is going on in our minds when we are hunting down a mathematical phenomenon? And then: What is guiding us? How come we jump to CORRECT conclusions? Even if the guess was not quite correct, it usually was a good hunch that, properly adjusted, will open up new territory. Where do these hunches come from? Probably the simplest recorded answer to that question goes back to Plato and has spawned a school of thought in the Foundations of Mathematics that bears his name. It puts those hunches on a par with our spontaneous reactions to physical messages—"smell that? someone must be roasting a lamb in the next clearing," "there is a storm brewing in the South West, I can feel it in my bones." According to Plato's view, mathematical objects exist eternally and immutably in a realm of ideas, an abstract reality accessible, if only dimly, to pure reasoning. That is how we discover them and their properties. By now, what with 2000 years of escalating experience with mathematics and painstaking critical analyses of its tenets, Platonism is no longer the accepted view in the Foundations. But, if nothing else, it is a wonderful allegory and an extremely useful working hypothesis.

To put it bluntly, while at work a mathematician is too busy concentrating on deciphering the hints he can gather from the trail he is following to stop and bother asking how the trail got here. It is enough for him to have a good hunch that the trail will lead to the goal.

The following is a slightly polished version of my spontaneous response to the assortment of EDGE comments on Stanislas Dehaene's question  "What Are Numbers, Really? A Cerebral Basis For Number Sense"  and the subsequent discussion at  The Reality Club . After a simple illustration of how we ponder, jump and then fill in the steps I address some general considerations raised on EDGE, which leads me to an exposition of the limitation phenomena.

Although keeping technicalities to a minimum, both conceptually and typographically, I am careful to be precise and correct. In our field the smallest inaccuracy can have disastrous consequences leading head on into contradictions.

1729 AN EXAMPLE OF MATHEMATICAL REASONING

Stanislas Dehaene brings up the Ramanujan-G.H.Hardy anecdote concerning the number 1729. The idea of running through the cubes of all integers from 1 to 12 in order to arrive at Ramanujan's spontaneous recognition of 1729 as the smallest positive integer that can be written in two distinct ways as the sum of two integral cubes is inappropriate and obscures the workings of the naive mathematical mind. To be sure, a computer-mind could come up with that list at a wink. But what would induce it to pop it up when faced with the number 1729 if not prompted by some hunch? Here is a more likely account:

Confronted with 1729 you will recognize at a glance that:

Now all those 3's in the above expressions spring to attention, you fleetingly call up THE EQUATIONS

and JUMP to the conclusion that the choice of (1,9; 3,9) for a,b; c,d will give you the smallest positive integer that can be written as the sum the cubes of two integers (a+b) and d and also of a different pair a and (c+d). You have a well trained instinct. But, if called upon, it will be a simple matter to fill in that jump by a proof, the fixed coefficients 3 ruling out smaller choices for b,c,d, once the minimal possible value 1 is chosen for a.

ANALYSIS OF A TRAIN OF THOUGHT

The best way to understand the process encoded above in technical shorthand is via a metaphor, which should be spun out at leisure. Say you are driving into a strange town, and, for some reason or other, a building complex catches your attention. It does not just pop into your field of vision; at first glance you see it as a museum, a villa, a church, or whatever. And then, depending on your particular interests and background, you may recognize its shape, size and purpose, muse over its style, venture a guess as to its vintage, and so forth.

Upon meeting 1729, your first reaction will probably be to break it up into the sum of 1000 and 729, because of our habit of counting in decimal notation. Stop for a moment to consider what would have been facing Ramanujan if Taxi cab companies were favoring binary notation! [11011000001 = 11011000000 + 1 = 11^3 x 100^3 + 1^3 = 101^3 x 10^3 + 11^3 x 11^3 = 1111101000 + 1011011001]. On the other hand, if you are one of those people obsessed with prime factorization you'll "see" the product 7 x 13 x 19 when somebody says "1729" to you while a before-Thompson-and-Feit but after-Burnside group theorist will say "Aha that is an interesting number, all groups of order 1729 are solvable," and anyone with engineering experience immediately thinks of the 1728 cubic inches contained in a cubic foot  [1] . But a historian of Mathematics will see 1729 as the year of Euler's friend and benefactress Catherine the Great's birth.

Next you decide, more or less deliberately, how to investigate the phenomenon. Do you drive to the nearest kiosk, buy a "Baedecker," search for that building and read through all you can find in there about it before you make up your mind about what you want to know? In other words, assuming you have a kiosk full of lists handy in your own mind, do you run through all the integral cubes smaller than 1729? If so, why cubes?

If you have that kind of mind you probably would first run through the squares before getting to the cubes. The less methodical tourist, eager to enjoy rather than out to complete his (or her) knowledge, may choose to investigate in a haphazard way, spurred on by curiosity, guided by experience, using skills automatically while impulsively following hunches, prowling, sniffing, looking behind bushes, and then jump to rational conclusions.

Now return to Ramanujan and see how the first thing that springs to the naive eye beholding the number 729 is that adding 81 = 9^2 turns it into 810, whereupon 10 drops its disguise, shows one of its true natures as the sum of 1 and 9 and, lo and behold, all those powers of 3 start tumbling in. All the while you are aware of the pattern ii), just below the threshold of consciousness, exactly as a driver is aware of the traffic laws and of the coordinated efforts of his body and his jeep. That is how you find your way through the maze of mathematical possibilities to the "interesting" breakdown of 1729 into two distinct sums of integral cubes.

When you stop to ask yourself what is so great about that, something clicks in your mind: you are facing a positive integer with a certain property, you know that

That knowledge, always hovering below the threshold of consciousness, prompts the question whether 1729 might in fact be the LEAST positive integer expressible in distinct ways as the sum of two cubes. Having another look at the representation of 1729 as a sum of various powers of 3 as held in your mind's eye and exhibited in the third line of i) above, the more or less conscious awareness of ii) invites you to break up those sums of cubes according to the pattern iii) where you assume—"without loss of generality"—that a < d = a + b, and hence c < b. At this point the solution a = 1, b = c^2 = d and c = 3 surfaces by inspection as "obviously" yielding the minimal value for (a + b)^3 + d^3.

ABOUT MATHEMATICAL ACTIVITY

I have gone through this simple illustrative example at such length in order to underscore a few of my pet contentions:

What we sorely need is a phenomenological study of mathematical practice. Polya and Lakatos had independently started out on that path, I do not know to what extent it has been followed up. Mathematicians are well aware of how they work, whether by themselves or in teams. But their goals are results that must be presented in a conclusive and "clean" form that makes them publicly accessible, at least within the profession, a form that necessarily obscures the path that led to them, just as the most beautiful tombstone will sum up a life but give no inkling of how it really has been lived, to use an observation by Claude Chevalley  [2] .

a) Much mathematical reasoning is done subconsciously, just as we automatically obey traffic rules and handle our cars, whether we know why and how they work or not. Symbolic notation is an "artificial aid" used to secure a hold like a piton, to survey a situation like a geological map and to encode general patterns for repeated application. But it is not mathematics. Mathematics can be done without symbols by a particularly "gifted" individual, like, e.g., Ramanujan. What that gift consists of is one of the questions raised in the EDGE piece. Obviously we are not all of us born with it. Nor do I believe that all people born as potential mathematicians become actual ones. Tenacity of motivation, an uncluttered and receptive mind, an unerring ability to concentrate the mind's focus on long intricate chains of reasoning and relational structures, the self discipline needed for snatching such a mind out of vicious circles, these are only a few characteristics that spring to mind. They can be cultivated. Experience will train the judgment to distinguish between blind alleys and sound trails and to divine hidden animal paths through the wilderness.

b) Free association plays an important role, an agility of mind that allows reasoning to jump ahead with a sure touch, after which comes the dogged toil of constructing proofs.

c) Conceptual visualization is an indispensable attendant to mathematical thinking. Formalization is only a tool and may encourage lazy thinking! Look at the freshmen who enroll in math because they assume they won't be expected to produce coherent arguments or to write grammatical text, that bureaucratic neatness in "plugging in numbers and turning the crank" will suffice to pass the course.

It is fascinating to browse through some of the essays on the Foundations of Mathematics by the topologist and logician L.E.J. Brouwer, the father of Intuitionism. You will find very few formulas in them, and yet they are rigorously reasoned, tightly and succinctly, more so than many formal texts.  [3]

d) That practice, familiarity, experience and experimentation are important prerequisites for successful mathematical activity goes without saying. But less obvious and just as important is a tendency to "day dream," an ability to immerse oneself in contemplation oblivious of all surroundings, the way a very small child will abandon himself to his blocks. Anecdotes bearing witness to the enhancement of creative concentration by total relaxation abound, ranging from Archimedes' inspiration in a bath tub to Alfred Tarski's tales of theorems proved in a dental chair.

THE EVOLUTION OF MATHEMATICAL CONCEPTS

The tenet that MATHEMATICAL OBJECTS ARE MENTAL CONSTRUCTS conceived by the human species for the purpose of forging its way through life and environment is compelling. How could we orient ourselves in space without discerning dimensions and estimating distances, how could we keep track of possessions and offsprings without a sense for numbers (cardinals), groupings and hierarchies (ordinals)?

Maybe the prototypical shepherd just kept a heap of pebbles handy by his cave, one for each sheep, to make sure by MATCHING that at the end of the day he had his whole flock together ÷ the first occurrence of the mathematical arrow. The next guy paid attention to the pecking order among his charges and chose his pebbles accordingly. And then ÷ much later ÷ one with a poetic twist of mind gave individual names to his sheep and picked pebbles to match their personalities in looks, color, shape and mood so that, if one went missing, he could tell by looking at the leftover pebble which one of his flock to search for where, according to the culprit's specific idiosyncrasies. Finally, with all that time on their hands, some of the shepherds started creating poetry or inventing music, others projected and extrapolated their minds into higher realms of mathematics ÷ and started wondering.

Here is the beginning of mathematics, not only arithmetic, the whole works, structures (you start grouping your flock, and those groups will interact), mappings and probably even the concept of infinity, "what if those ewes keep lambing and lambing till I run out of pebbles..." Pretty soon these concepts become PHENOMENA and begin evolving in interaction with their creators and with the uses they are put to.

When the ANTHROPOLOGIST has told his story and the PHENOMENO- LOGIST has had a look at how a mathematician's mind works it is for the NEURO PHYSIOLOGISTS to figure out what is going on in the brain of those shepherds and their descendants. The PSYCHOLOGY of mathematical activity ÷ and obsession ÷ also deserves attention and is bound to shed light on the mystery of the prodigy.

The view of mathematical "objects" as mental constructs forever caught up in a dynamic process of evolution was succinctly articulated by L.E.J. Brouwer, the Dutch topologist who, during the first quarter of this century, founded the school of INTUITIONISM as the most compelling alternative to PLATONISM. Occasionally Intuitionism is accused of leading into solipsism. But the understanding of mathematical intuition as a sense for charting one's way around an environment including fellow creatures implies that its tools, the concepts, must be evolving by joint and competing efforts of a community. Very much in keeping with what I understand is Stanislas Dehaene's view. With Brouwer I believe in preverbal mathematical perception, where by perception I mean an activity, a process of "seeing as", picking out of patterns and imposing frames of reference.

Friedrich Wilhelm Nietzsche (1844-1900) had a keen understanding of the anthropological evolution of mathematics and rational thinking. His Der Wille zur Macht (The Will to Power, 1887) contains poignantly expressed insights into the genesis of the laws of Logic, many of them anticipating Intuitionism!

George Lakoff's stress on image schemes and conceptual metaphors is compelling, especially his suggestion of "expansion to abstract mathematics by metaphorical projections from our sensory-motor experience". Yes we do have mathematical bodies! On a primordially homogenous environment we impose a grid commensurate in size and compatible in shape with our bodies as we know them from direct experience. One step further, we project our bodies beyond what is immediately perceivable, spurred on by a tenacious intention "to make sense of it all". Have you ever noticed how many mathematicians are rock climbers? The process of mulling over a mathematical problem displays a striking similarity to that of surveying a cliff before the ascent; of visualizing and comparing alternate routes, from the big lines of ridges, ledges and chimneys down to the details of toe and finger holds, and then weighing possibilities of what might be encountered beyond the visible; all in perfectly focused concentration, projecting ahead, extrapolating, performing so-called "Gedankenexperimente" (thought experiments) and sensing them throughout one's bones and muscles. And finally setting off to break trail through the folds of a brain!

Already in 1623 Blaise Pascal articulated in his PensŽes (thoughts) the observation that the abstract schemata we impose on the world in order to interact meaningfully with it are shaped by the experience of our bodies.  [4]

During the last half century the evolution of so-called CATEGORY THEORY out of algebraic topology has developed a dynamic language of diagrams in which the abstract concepts of universal algebra find their natural habitat.  [5]  "Diagram chasing" ÷ a systematic form of hand waving ÷ is a way of making sense of the abstract structural and conceptual under-pinnings of mathematics, including Arithmetic and Geometry, Logic and set theory, as well as of the juxtaposition between discrete and continuous phenomena. It turns out that Topoi, a particularly prolific species of categories, have the structure of intuitionistic Logic ÷ an amazing corroboration of INTUITIONISM. F. W. Lawvere at SUNY Buffalo, a pioneer in the field since the early sixties, and his associates are beginning to make significant contributions to cognitive science.

As to PLATONISM, whether deliberately or inadvertently, most mathematicians still act and talk as if they were dealing with objects that are part and parcel of the furniture of their Universe. I do it myself, and so does George Lakoff when he refers to the straight line and the reals. It is such a convenient make-believe stance, not to be confounded, however, with the deep allegorical truths revealed in the poetry of Plato's dialogues.

But there is more to be said when we stop to contemplate what we call REALITY. Think how often a writer will create characters only to find them taking on a life of their own, doing things or getting into trouble that their creator had not intended for them at all. So, the positive integers are mental constructs. They are tools shaped by the use they are intended for. And through that use they take on a patina of reality! Nor do they rattle about in isolation. They interrelate, they pick up individual personalities through interaction, by their position in the natural ordering, by splitting into primes, by what they are good for, in what contexts they play what roles.

And before we know it we have a problem on our hands like Fermat's Last Theorem! Its statement can be explained to every child, using a bit of hand waving and the ever handy dots. Through generations the belief in its truth had grown for ever more entrenched. No counter example was found, but no proof was in sight either until Andrew Wiles  [6]  succeeded in blazing the final trail to the goal through abstract territory, rugged and disconnected in places and prepared by the toil of his peers in others. To the experts the proof is illuminating, but not to the ordinary mathematician in the street. By now our tools are so highly developed that they bring us information about our own creations that we cannot fathom with the unaided mathematical senses, even though it may concern situations whose meaning we can understand perfectly well. In physics and astronomy we are used to similar situations: our instruments can reach physical phenomena way beyond the reach of our physical bodies. The interpretations of these messages from beyond are encoded in theories of our own construction.

The method of FORMALIZATION is by now widely accepted, used and discussed. But it has limitations and is trailing some baffling "non-standard" phenomena in its wake. In order to put these into proper perspective a technical digression is needed.

FORMAL THEORIES

While mathematics is forging mental tools for charting our way through the world, our brains playing very much the part of our senses, things become so intricate that we need artifacts for keeping track of those constructs. That is where symbols come in ÷ algebraic notation, diagrams, technical languages and so forth ÷ as mechanisms for storing and surveying insights and for communicating about them. Extension of this method to the analysis of mathematical reasoning itself leads to so-called meta mathematics and symbolic logic.

Allowing the articulation of "axioms" and of rules of deduction governing their use, the systematic construction of formal languages leads to FORMALIZED THEORIES consisting of theorems, i.e., well formed sentences (wfs' for short) obtained from axioms by chains of deductions according to those rules.

A formal proof is a finite sequence of wfs' starting with axioms, hanging together by the formal rules and ending with the theorem proved by it. The formalized theory itself becomes a topic for theoretical investigation since it is bound to have properties that go beyond what we put into it. Will it be formally consistent in the sense that the negation of a theorem will never show up as a theorem too? Is it formally complete ,i.e., does every sentence have a proof unless its negation has one? These are typical problems for the meta-theory.

The choice of axioms is not arbitrary. We are guided by common sense of mathematical perception, by criteria that deserve investigations to which the EDGE group seems to be making valuable contributions. As we acquire and develop intuitive concepts of sets, spaces, geometries, algebraic structures and all the rest, we try to grasp them by characteristic properties and are led to basic postulates.

Occasionally sustained experience reveals that the original construction was not fully determinate, that the axioms are not complete. They don't suffice to pin down the intended concept uniquely. Some sentence A ÷ Euclid's fifth postulate for instance ÷ is left undecided by what was considered an axiomatic characterization of the concept ÷ of, say, a geometry. Both A and its negation not-A are formally consistent with the axioms. Well, for some purposes it is useful to assume Euclid's parallel axiom for geometry, or well-foundedness for sets, at other times it may be handy to deal with bottomless sets or crooked squares. The tools are evolving as we are using, refining and adjusting them. Such experiences that at first look like failures deepen conceptual understanding and expand mathematical horizons.

The situation of the arithmetic N over the natural numbers 0,1,2,3,... and that of the ordered field R of the reals are more subtle. In both cases we "know exactly" what structure we have in mind, there is no question of bifurcation of concepts. Yet in the case of N a complete axiomatization founders on the requirement of effectiveness while, even though completely formalizable, the elementary theory of R, has so-called non-standard models, as does every theory of an infinite structure

ELEMENTARY THEORIES

These phenomena are a manifestation of the precarious balance between algorithmic precision and expressive power inherent in every formal language and its logic. The most popular, widely taught formalization is the first order predicate calculus, also called elementary logic, a formalization of reasoning in so-called first order predicate languages. That apparatus leads from "elementary axioms" to "elementary" theories.

The important requirement for any formalization is the existence of both a "mechanism" (algorithm) for deciding, given any well formed sentence (wfs) of the language concerned, whether or not that wfs is an axiom, and one for deciding of any given configuration of wfs's whether or not it is an instance of one of the rules. The resulting concept of a formal proof is decidable, i.e., there exists an algorithm, which, when fed any finite sequence of wfs', will come up with the "answer yes" (0) or the "answer no" (1) according as that sequence is a formal proof in the system or not. The resulting axiomatizable theory will in general only be effective in the sense that there exists an algorithmic procedure for listing all and only those wfs' that are theorems. That does by no means guarantee a decision procedure for theoremhood. In fact most common theories have been proven undecidable.

To start with, a familiar structure like N or R will serve as the so-called STANDARD MODEL or INTENDED INTERPRETATION for the elementary theory meant to describe it. Observe that the notion of a standard model presupposes some basic concept of mathematical reality and truth. Gödel talks of "inhaltliches Denken" (formal thinking) in juxtaposition to "formales Denken" (formal thinking). His translators use the term 'contentual'. 'Intentional' might be just as good a choice.

Of course one might dodge the need for a metaphysical position by using terms like "preverbal" or "informal".

But that does not make the problem go away. If we want to talk about standard models, if we want our theories to describe something ÷ approximately and formally ÷ what is it that we want them to describe? A question that would not disturb a Platonist like Gödel. The formalist's way out is to throw away the ladder once he has arrived at his construction and to concentrate on the questions of formal consistency and formal completeness, purely syntactic notions.

A theory is formally consistent if and only if for no wfs A both A and not-A are theorems and formally complete if and only if for every wfs A either A or not-A is a theorem.

To an extreme formalist the existence of an abstract object coincides with the formal consistency of the properties describing it. If at all, he will draw his models from yet another theory, most likely some, necessarily incomplete, formalization or other of elementary set theory, presumed ÷ but only presumed ÷ to be consistent. An unsatisfactory strategy.

We, however, are left with the conundrum of Mathematical Truth and the semantic notions that depend on a "meaning" attached to the theory. With respect to an interpretation of its language over a structure S a theory, formalized or not, is

Granted a clear and distinct idea of the structures N and R we talk of the sets of all wfs' that are true under the intended interpretations on N and on R as True Elementary Arithmetic, TN, and as the True Theory TR of the Reals.

Consider an EXAMPLE: Leaving aside the question where N comes from, I should think that we all know what we mean by the wfs

(F^3) for ALL positive integers x, y and z: the sum of the cubes of x and y is not equal to the cube of z.

F is short for FERMAT. To explain it to a naive computer mind, we would say: "Make two lists as follows; in the left one, L, write down successively the results of adding the cubes of two positive integers, 1^3 + 1^3, 1^3 + 2^3, 2^3 +2^3, 1^3 + 3^3, 2^3 + 3^3, 3^3 + 3^3,..., and into the right one, R, put all the cubes 1^3 (1), 2^3 (8), 3^3 (27), 4^3 (64), 5^3 (125) and so on. Now run through both lists comparing the entries. (F^3) claims that you will never find the same number showing up both on the left and on the right". A computer can easily compile these lists in so orderly a fashion and run through them so systematically that, for each bound N, it will, after a computable number of steps, say f(N) of them, have calculated and compared all pairs of numbers in L and in R smaller than N. You will probably agree that this tedious explanation makes it sufficiently clear what we mean here by ALL. You may want to use nicer language like talking about NEVER finding a matching pair. The purpose of symbolization, however, is not only orderliness, but clarification. The dual to the so-called UNIVERSAL QUANTIFIER (for all) is the EXISTENTIAL QUANTIFIER. Just think for a moment, assuming (F^3) were false, how easy it would be for your patient computer to prove that. It would only have to go on long enough until it found a COUNTER EXAMPLE, i.e., a positive integer that shows up in both lists, R and L. Having done so it would have proved

In 1753, using clever transformations of the problem, Euler succeeded in proving the restriction (F^3) of Fermat's theorem to cubes. But Fermat's general Conjecture

has only been proved conclusively a few years ago by means of techniques way beyond elementary arithmetic. It should be noted here that variable exponentiation is not part of the language of N but can be paraphrased in it. In the above procedure you will have to organize your left list according to an enumeration of triples (x,y,n) and the right one according to pairs (z,n).

The capacity to visualize an ongoing sequence of calculations and comparisons leads to an understanding of what is meant by the truth of (F). Yet, in spite of many efforts, its proof had to wait till algebraic geometry and number theory had achieved the maturity necessary to allow its construction.

We have a pretty good understanding of what we mean when we claim that ALL integers ÷ or all pairs or triples of them ÷ have a certain property, provided that we understand the property itself. The most manageable kind of properties that integers may have are what we call recursive or computable. They are susceptible to a decision procedure as illustrated by the example of checking for fixed n and any given triple of integers x,y,z whether or not the sum of the n-th powers of the first two is equal to that of the third.

A property P of triples of numbers is called recursive if and only if its so-called characteristic function that takes on value 0 at the triple (m,n,q) if that triple has the property and value 1 otherwise (its decision function) is computable by an algorithm like a Turing machine, or, equivalently, is recursive.

The amazing ÷ often elusive ÷ power of the universal quantifier brought home by Gödel's incompleteness proof, discussed in the next section, is again manifest in the intrinsic difficulties with which the conclusive proof of Fermat's theorem is fraught.

ELEMENTARY ARITHMETIC

Based on a naive concept of Truth, every true theory of a definite structure is complete and consistent in both senses, a pretty useless observation. For, a byproduct of Gödel's Incompleteness proof of 1931 [7]  is the non-formalizability of elementary arithmetic, TN, and with it of many other theories.

EVERY SOUND AXIOMATIZATION OF ELEMENTARY ARITHMETIC IS INCOMPLETE.

The most natural candidate for axiomatizing TN goes back to Giuseppe Peano (1895) and consists of the recursive rules for addition, multiplication and the natural ordering on the set N of non negative integers built up from 0 by the successor operation that leads from n to n+1, together with the Principle P of Mathematical Induction, which postulates that every set of numbers containing 0 and closed under the successor operation exhausts all of N, or, equivalently, that every property enjoyed by 0 and inherited by successors is universal. P is a principle that adults may consider a definition of the set N, while children will ÷ in my experience ÷ take it for granted. But, if you want to articulate it in the language of the first order predicate calculus you run into trouble. As illustrated in example (F) elementary languages can quantify over individuals. But quantification over so-called HIGHER ORDER items like properties is beyond its scope. P is a typical sentence of second order logic.

PEANO ARITHMETIC, PA, is the first order approximation to second order arithmetic obtained by replacing P with the following schema of infinitely many axioms

one for each wff (well formed formula) W of the elementary language of arithmetic.

Reformulating (PW) in terms of proofs rather than truth sheds light on it and illustrates how one might want to go about replacing the basic concept of truth in mathematics by a primitive notion of proof. Writing W(x) for "x has property W" the Principle of Proof by Mathematical Induction reads

Note how appealing this formulation is: Given any number n, you only have to start with the proof given by 1) and then apply the method of 2) n times to obtain a proof of the sentence W(n). But there is a subtlety here. So understood, the principle only guarantees that, for every number n, a proof of W(n) can be found, a typical "for all ÷ there exists ÷" claim. Its power lies, however, in the "there exists-for all ÷" form of the conclusion as exhibited above.

These may sound like nit-picking distinctions, but they are of great proof-theoretic significance. For instance, from the consistency of PA, proved by means transcending PA, follows:

If g is the Gödel number of the Gödel sentence G then:

is a theorem of PA.

However G itself, namely the sentence

is not a theorem of PA.

G is the sentence that truthfully claims its own unprovability. Much deep work is required to establish this result rigorously.

Occasionally proofs by mathematical induction are confused with arguments based on so-called 'inductive reasoning', a term used in philosophical discussions of logic and the sciences ÷ yet another reason for all these elaborations.

Axiomatized but undecidable theories are a fortiori incomplete. In 1939 Tarski proved that

THERE IS A FINITELY AXIOMATIZABLE FRAGMENT OF PA ALL OF WHOSE CONSISTENT EXTENSIONS ARE UNDECIDABLE.  [8]

And yet, if we accept an intentional concept of truth, we seem to obtain a complete theory from Peano's mere handful of axioms together with that one marvelous second order tool P on which so much of our mathematical thinking hinges. For:

ALL MODELS OF PEANO'S SECOND ORDER AXIOM SYSTEM ARE ISOMORPHIC.

Still, any attempt to formalize second order arithmetic is again doomed to founder on the cliffs identified by Gödel and Tarski. The juxtaposition of these claims is and ought to be baffling. In fact they bring home the discrepancy between the naive and the formalist concept of a model. From the naive point of view they mean that higher order logic cannot be completely formalized. Even so completeness proofs for it are widely hailed ÷ at the price of allowing all sorts of non-isomorphic models even for second order Peano Arithmetic. Enough of that for now. Fermat's last theorem may well be beyond the scope of elementary Peano Arithmetic. In other words, (F) is presumably left undecided by PA. A few mathematically interesting theorems expressible in the language of PA with that property are already known. They are embeddable in stronger but still convincing first order theories, some elementary set theory or other.

After all that we are faced with the question where new axioms come from, in other words with THE PROBLEM OF THE NATURE OF MATHEMATICAL TRUTH. To declare "OK, as of October 27, 1995, the day that Wiles was awarded the Prix Fermat by the town of Toulouse, (F) shall be added to the list of axioms for elementary arithmetic" would seem quite inappropriate. We want more intuitively obvious first principles.

NON STANDARD MODELS

In amazing contrast to TN the first order theory TR of the ordered field of the REALS has been successfully and completely formalized ÷ starting with Euclid's axioms, improved by Hilbert just before the turn of the century and completed as well as proved complete by Tarski about the time of the Second World War. My immediate reaction when I first heard of this feat was shock and distrust of those Berkeley logicians. "How could that be? The reals are so much more complicated than the integers. Aren't the natural numbers defined as the non negative integral reals?" Well, the solution of that conundrum lies in the

LIMITATION OF EXPRESSIVE POWER INHERENT IN FORMAL LANGUAGES.

As a matter of fact, the natural numbers are not "elementarily definable" among the reals; there is no wff of the language of R that picks out the natural numbers among the reals.

Moreover, in spite of its completeness, TR has non-isomorphic models! It has countable models, uncountable ones, Archimedean as well as Non-Archimedean ones; some harbor hyperreals, others only standard reals... What is going on? First the chicken-or-egg question must be faced: what comes first, the model or the theory? Ever since the elaborations by Tarski in 1934 and by Mal'cev in 1936 of the results by Lšwenheim of 1915, and by Skolem of 1920 (a brief exposition will follow below) we understand that first order chickens are prone to lay a medley of eggs, some "real" in the Platonic sense of being standard and others weird, artificial, substitutes, freaks, in short non-standard. The Ur-hen, the axiomatization, originated from a standard egg, the "intended interpretation", a natural mathematical construct like our everyday arithmetic of the positive integers, or, more sophisticated, the real number system of the 19th century. After the chicken has grown to maturity it starts laying models, and, roaming through the virtual reality of model theory instead of free ranging in Platonic realms, it comes up with non-standard eggs. The only constraint on those is consistency and the verification of the axioms, i.e., the genetic chicken code. These models are hatched within the confines of some entrenched formalization of set theory.

What really lies at the basis of non standard objects like hyper reals is ÷ again ÷ the limitation inherent in first order languages. In the elementary language of real number theory we cannot distinguish between Archimedean and non Archimedean orderings and that opens the door to constructions that were scorned by my teachers although they might use infinitesimals as a handy figure of speech the way we still talk Platonically. We thought that Cauchy and Weierstrass' arithmetization of analysis had done away with that alleged abuse of language, but now it is back en vogue again and very useful too (see below).

NON STANDARD PHENOMENA are closely connected with the SEMANTIC COMPLETENESS OF ELEMENTARY LOGIC, first proved by Gödel in 1930 [9] and extended in many ways since, in particular by Henkin who also dealt with formalizations of higher order logic. The underlying meta theorem rests on two facts, one inherent in the finitary nature of a formal deduction, the second involving non- constructive instructions for building a model

WHENEVER ALL FINITE SUBSETS OF A SET OF WFS' ARE CONSISTENT THEN SO IS THE ENTIRE SET and EVERY CONSISTENT SET OF WFS' HAS A MODEL.

By definition Semantic Completeness of a formal calculus means EQUIVALENCE BETWEEN FORMAL DERIVABILITY AND SEMANTIC VALIDITY where validity stands for truth under all interpretations, i.e. in all models.

At first this looks like an amazing result especially in view of currently rampant incompleteness. It is unfortunate that popular literature so often fails to make a clear distinction between the two concepts of semantic and of syntactic completeness (pp.10,11). Only the experienced reader will automatically know from the context which notion is at stake.

As a matter of fact the completeness of first order logic is achieved at a price: the expressive poverty of the formal language. Completeness proofs for higher order logic are ensnared in the same kind of bargain. They are based on a concept of model that to the naive mind seems contrived. Elementary languages are incapable of distinguishing between arbitrarily large finiteness and infinity, and so are forced to tolerate the infinitely small. Consider the infinite set of wfs' 0 < a < 1, a + a < 1, a + a + a < 1,..,a + a + a +...+ a < 1,... and let U be its union with TR, the set of all wfs' that are true in the field R of the reals. Every finite subset V of U has a model: just take R and interpret a by 1/n, where n is the number of symbols occurring in that finite set V. By 1) then the whole set U is consistent and so, by 2) it and with it the elementary theory of the reals has a model which harbors an element satisfying all these inequalities, i.e., a non- Archimedean, non-standard, or hyper, real a. It is positive and yet smaller than any fraction 1/n, n a positive integer.

Ruled by its logic, the language cannot prohibit such anomalies. But there is a silver lining to this shortcoming: Because of the consistency of infinitesimals with TR every truth about the reals that can be expressed in the elementary language of R holds for all reals ÷ standard or not ÷ and so, by Gödel's completeness theorem, it has a formal proof. And if the approach via infinitesimals is smoother that is just great. One cannot help but marvel at the native instinct with which the seventeenth century mathematicians went about their work

Similarly, any first order theory of N, including TN, has models that contain infinitely large integers. The elementary theory of finite groups has infinite models and so in fact does every first order theory of arbitrarily large finite models.

All this is meant to explain that these non standard phenomena have no bearing on the question whether Platonism is an appropriate view of the origin of Mathematics. I am deliberately not using the word "correct". Whether Platonism is "true" seems an ill posed question, luring into vicious circles. How can we contemplate the truth of this, that or the other "ism" before we have a clear and distinct idea of what ÷ if anything ÷ we mean by the Truth of a theory?

The existence of non standard models should NOT be confounded with the occurrence of incomplete concepts like that of a geometry or that of a set. In the case of hyperreals we are running into limitations of the formal language while dealing with complete theories, in the second case we are simply facing the fact that the intuitive concept, say of a geometry or a set, that we had in mind when setting up the formalization is not completely fathomed yet, in both senses of completeness. Of course the easiest reaction is to say, "that concept is out there, let us go look more closely and we shall eventually find its complete characterization". In this frame of mind Gödel is reputed to have been convinced that we shall eventually understand enough about sets to come up with new axioms that will decide the continuum hypothesis. But in other cases the expedient policy will allow a concept to bifurcate ÷ sailors have no trouble with non-Euclidean geometries.

The big question is where our standard concepts come from, how do we all know what we mean by the Standard Reals? How can we distinguish between Archimedean orderings and non Archimedean ones, when we cannot make the distinction in first order language? Well we can always resort to hand waving when words fail. We can indeed communicate about them beyond the confines of formalism. They are conceptions, constructions, structures, figments of our imagination, of the human mind that is our common heritage. Other creatures may have other ways of making sense of and finding their way in a Universe that we are sharing with them.

This century has seen the development of a powerful tool, that of formalization, in commerce and daily life as well as in the sciences and mathematics. But we must not forget that it is only a tool. An indiscriminate demand for fool proof rules and dogmatic adherence to universal policies must lead to impasses. The other night, watching a program about the American Civil Liberties Union I was repeatedly reminded of Gödel's Theorem: every system is bound to encounter cases which it cannot decide, snags that will confront its user with a choice between either running into a contradiction or jumping out of the system . That is when, with moral issues at stake, cases of precedence are decided by thoughtful judgment going back to first principles of ethics, in the sciences alternate hypotheses are formed and in mathematics new axioms crop up.

Returning to my question, think of mathematics as a jungle in which we are trying to find our way. We scramble up trees for lookouts, we jump from one branch to another guided by a good sense of what to expect until we are ready to span tight ropes (proofs) between out posts (axioms) chosen judiciously. And when we stop to ask what guides us so remarkably well, the most convincing answer is that the whole jungle is of our own collective making ÷ in the sense of being a selection out of a primeval soup of possibilities. Monkeys are making of their habitat something quite different from what a pedestrian experiences as a jungle.

To sum it all up I see mathematical activity as a jumping ahead and then plodding along to chart a path by rational toil.

The process of plodding is being analyzed by proof theory, a prolific branch of meta mathematics. Still riddled with questions is the jumping.

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Nature by numbers: The hidden beauty of mathematics

L iving with a mathematician this year has made me realise the unsung contribution mathematics makes when it comes to providing us with the reasoning to better appreciate the beauty of nature. I’d always thought fractal symmetry, which cropped up in my physical chemistry lectures, was solely a chemical concept. You can probably imagine my surprise when I realised that this characteristic actually stemmed from mathematics. It came as an even greater shock to discover that many natural phenomena are, in fact, fractal to some degree. The Fibonacci sequence, which you may think exists only in the pages of a Dan Brown novel, is also visible in some of nature’s most exquisite structures. So, just how many of us are aware of the way in which mathematics provides us with the reasoning to be able to praise the intrinsic beauty of nature? This is exactly what I hope to achieve in this article; to show you how mathematics, something some of us may have dreaded at school, actually explains a lot of the things we see around us.

Fractal symmetry is when the same pattern is seen at increasingly small scales. In fractal symmetry, you find the same pattern within the pattern, which is why this can also be referred to as self-similarity. The best example to think of is a tree. The trunk of a tree separates into branches which then separate into smaller branches and then twigs, and these get smaller and smaller. In this way, we see a repetition. Another example is the Romanesco broccoli, but my favourite would have to be the Lotus effect. The Lotus leaves have a rough surface with micro- and nano-structures including waxy crystals that contribute to making the surface superhydrophobic. This means that any water droplets on the lotus leaves are strongly repelled and slide off the surface. While doing so, they take up the dust particles from the leaves in order to reduce the surface tension, resulting in the cleaning of the lotus leaves. This is an example of self-cleaning in nature and it is the fractal symmetry of the waxy crystals on the surface of the leaves that provides the enhanced hydrophobicity which makes this possible.

Fractal symmetry is when the same pattern is seen at increasingly small scales. In fractal symmetry, you find the same pattern within the pattern, which is why this can also be referred to as self-similarity

Another type of symmetry I wish to discuss is the so-called wallpaper symmetry. This is the mathematical classification of a two-dimensional repetitive pattern inspired by honeycomb structures. Besides often being seen in architecture and other arts such as textiles, this structure has found great use in the field of chemical catalysis. One of the finest examples of the use of catalysis is in catalytic converters used to turn pollutant gases such as nitrogen oxides and carbon monoxides into nitrogen dioxide and carbon dioxide gases, which are safer alternatives. The support for the precious rhodium or platinum metal catalysts used is cordierite monolith. The metal is dispersed on the honeycomb structure of the support which provides a larger surface area to optimise the flow of gases over the catalyst. This is a fine example of symmetry observed in nature that has now been employed on a large industrial scale and is something used by many of us every day.

Fractal and wallpaper symmetry are the two types I wanted to discuss. However, this article would be incomplete without a nod to the spirals that are too often seen in nature. Some of these spirals arise due to the golden ratio of 1.618[…] which is the most irrational number we can get. Put simply, it is the furthest away we can be from a fraction. In this way, the golden ratio gives the best spiral with no gaps. Hence, flower petals and pinecones are guided by the golden ratio, which is related to the Fibonacci sequence. In the Fibonacci sequence, each number is the sum of the two numbers preceding it. What we find is that if we take the ratio of any two numbers from the Fibonacci sequence, we get values very close to the golden ratio. In nature, the flowers and the shells are not genetically, or in any other way, programmed to abide by the mathematics of the Fibonacci sequence. This is purely a result of evolutionary design. Petals and seeds find that the golden ratio offers the best packing with minimum gaps. I find it absolutely amazing that a series of numbers on a piece of paper can explain why many elements in nature have chosen to adopt this particular configuration.

This article would be incomplete without a nod to the spirals that are too often seen in nature. Some of these spirals arise due to the golden ratio of 1.618[…] which is the most irrational number we can get

In addition to mathematics, you could not have avoided noticing the not-so-subtle mention of chemistry in this article. As I researched more into maths, I could easily find myself making connections with chemistry and much of the material I have studied to date. Thinking back to one of the conversations I’ve had with my flatmates in the kitchen, it’s clear that mathematics provides the key to untie the knots in many fields both within and outside STEM. As a chemist, I certainly see how fundamental a role mathematics plays. In this article, I hope I have enabled you to at least begin to appreciate just how much a bunch of numbers can explain to us about the universe.

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THE NATURE OF MATHEMATICS AND TEACHING

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Nature of Mathematics

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essay about the nature of mathematics

Why the Book of Nature is Written in the Language of Mathematics

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essay about the nature of mathematics

  • Dustin Lazarovici 28  

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The essay traces the following idea from the presocratic philosopher Heraclitus, to the Pythagoreans, to Newton’s Principia : Laws of nature are laws of proportion for matter in motion. Proportions are expressed by numbers or, as the essay proposes, even identical to real numbers. It is argued that this view is still relevant to modern physics and helps us understand why physical laws are mathematical.

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essay about the nature of mathematics

Reichenbach’s Lecture “The Problem of Laws of Nature”

essay about the nature of mathematics

Introduction: Nature and Its Mathematics

essay about the nature of mathematics

Physics and Mathematics

Unless stated otherwise, Presocratic fragments are quoted in the translation by Burnet ( 1920 ).

On these questions, see, e.g., Kurtz ( 1971 ); Jones ( 1972 ); Schadewaldt ( 1978 ); Kirk et al. ( 1983 ).

The Pythagorean influence on Plato is undeniable (the Platonic character Timaeus is commonly identified as a Pythagorean). Placing Heraclitus in the same lineage is more contentious. Plato criticizes Heraclitus on the basis that if everything were in flux, truth and knowledge would not be possible ( Cratylus 402a ff.). Heraclitus calls Pythagoras an “imposter” (fr. B129 DK), someone who has studied many things but lacks understanding (B40 DK). Heraclitus was not an easy fellow. Nonetheless, a reconciliation of these great thinkers is not only possible but plausible, and I set forth the connections as they seem correct to me.

árritos , which translates more literally to ineffable or inexpressible ; also alogon .

Although Newton had developed a more abstract differential calculus in his Method of Fluxions (completed 1671, but not published until 1736), it was not used in the Principia (first published 1687).

Ideally, it needs what Dürr, Goldstein, and Zanghì ( 1992 ) named primitive ontology (see Lazarovici and Reichert ( 2022 ) for a recent discussion) or what John Bell ( 2004 , Chap. 7) called local beables .

I will also not discuss the ontological status of other mathematical objects. Both a selective realism and full-blown Platonism are consistent with the view I propose in regard to numbers.

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Acknowledgements

I owe most of the insights explored in this essay to Detlef Dürr, who owed just as much to his friend Reinhard Lang. I thank Yoav Beirach and Enrico Piergiacomi for very helpful comments and Stephen Lyle for his excellent copy editing.

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Dipartimento di Fisica, Università di Genova, Genova, Italy

Nino Zanghì

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Lazarovici, D. (2024). Why the Book of Nature is Written in the Language of Mathematics. In: Bassi, A., Goldstein, S., Tumulka, R., Zanghì, N. (eds) Physics and the Nature of Reality. Fundamental Theories of Physics, vol 215. Springer, Cham. https://doi.org/10.1007/978-3-031-45434-9_26

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COMMENTS

  1. The Nature of Mathematics Free Essay Example

    The Nature of Mathematics. Download. Essay, Pages 3 (502 words) Views. 15521. In our contemporary world, the usefulness of mathematics is inevitable. It gives us a way of apprehending patterns, quantifying relationships, and predicting the future. It also helps us understand the world and we use the world to understand math as well.

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    ting more out of mathematics than what we put in," is developed by Mark Steiner in a separate essay. The analogy between mathematics and physics raises the question of explanation in mathematics. It is not enough to know that a given phenomenon occurs; one should also know why. Stewart Shapiro, quoting from the book Inference to the Best Expla-

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    These essays don't share any common program or ideology. The standard for admission was: Nothing boring! Nothing trite, nothing tr- ial! Every essay is challenging, thought-provoking, and original. Back in the 1970s when I started writing about mathematics (instead of just doing mathematics), I had to complain about the literature.

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    Mathematics was treated as a body of knowledge, an ideal form that exists on its own, which the human mind may or may not sense. Aristotle, Plato's student, believed that mathematicians ...

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    The Nature of Mathematics (These paragraphs are reprinted with permission from Everybody Counts: A Report to the Nation on the Future of Mathematics Education. ©1989 by the National Academy of Sciences. Courtesy of the National Academy Press, Washington, D.C.) Mathematics reveals hidden patterns that help us understand the world around us.

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    Mathematics is the abstract study of topics such as quantity (numbers), [2] structure, [3] space, [2] and change. [4][5][6] There is a range of views among mathematicians and philosophers as to the exact scope and definition of mathematics. [7][8] Mathematicians seek out patterns (Highland & Highland, 1961, 1963) and use them to formulate new conjectures.. Mathematicians resolve the truth or ...

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    M ATHEMATICAL I NQUIRY. Chapter 2: THE NATURE OF MATHEMATICS. Mathematics relies on both logic and creativity, and it is pursued both for a variety of practical purposes and for its intrinsic interest. For some people, and not only professional mathematicians, the essence of mathematics lies in its beauty and its intellectual challenge.

  12. ON THE NATURE OF MATHEMATICAL CONCEPTS: WHY AND HOW DO ...

    ON THE NATURE OF MATHEMATICAL CONCEPTS: WHY AND HOW DO MATHEMATICIANS JUMP TO CONCLUSIONS? Notation: x for products: 2 x 3 =6, ^3 for cubes: 2^3 = 8, ^exponent: 2^11 = 2048. ... It is fascinating to browse through some of the essays on the Foundations of Mathematics by the topologist and logician L.E.J. Brouwer, the father of Intuitionism. You ...

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    ented articles. These essays don't share any common program or ideology. The standard for admission was: Nothing boring! Nothing trite, nothing triv-ial! Every essay is challenging, thought-provoking, and original. Back in the 1970s when I started writing about mathematics (instead of just doing mathematics), I had to complain about the ...

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    R´enyi. The first essay is a delightful Socratic dialogue, perhaps no more unhistorical than those of Plato, on the nature of mathematics. It ends with an impassioned speech by Socrates on the virtue of using the mathematical method in philosophy—in strong contrast to Rota's views (see below). Celluci.

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  17. Nature by numbers: The hidden beauty of mathematics

    L iving with a mathematician this year has made me realise the unsung contribution mathematics makes when it comes to providing us with the reasoning to better appreciate the beauty of nature. I'd always thought fractal symmetry, which cropped up in my physical chemistry lectures, was solely a chemical concept. You can probably imagine my surprise when I realised that this characteristic ...

  18. Mathematics and the Nature of Knowledge—An Introductory Essay

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    These in turn, subject to the constraints and opportunities of the social context of practice, give rise to the realised theories of learning mathematics, teaching mathematics, and the related use of mathematical texts and curriculum materials in the classroom (Ernest, 1989a). Such a model is partially validated by empirical work (Ernest and ...

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  21. 18 Unconventional Essays on the Nature of Mathematics

    These essays don't share any common program or ideology. The standard for admission was: Nothing boring! Nothing trite, nothing tr- ial! Every essay is challenging, thought-provoking, and original. Back in the 1970s when I started writing about mathematics (instead of just doing mathematics), I had to complain about the literature.

  22. Why the Book of Nature is Written in the Language of Mathematics

    The essay traces the following idea from the presocratic philosopher Heraclitus, to the Pythagoreans, to Newton's Principia: Laws of nature are laws of proportion for matter in motion. Proportions are expressed by numbers or, as the essay proposes, even identical to real numbers. It is argued that this view is still relevant to modern physics ...