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Material Type: Notes; Class: Number Theory & Math Reasoning; Subject: Mathematics; University: Colgate University; Term: Unknown 1989;
Typology: Study notes
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Section 1: (Binary) Operations
It is assumed that you learned in Math 250 about sets and mathematical induction, the content of Section 0, and we will begin with binary operations. Technically:
Def: For a set S, any function S × S → S is a (binary) operation. (Such creatures as “unary operations” exist, i.e., functions S → S, as well as “ternary”, S × S × S → S, etc., but we are only interested in the binary ones, so we will usually drop the “binary” part of the term.)
So we know many, many (binary) operations on IR; for example, (a, b) 7 → a^3 + sin(3b + 7). But of course the term is intended to capture under a single word some familiar ideas that have some things in common while still not being identical:
∫ (^) b a (f^ +^ g)(x)dx^ ==^
∫ (^) b a f^ (x)dx^ +^
∫ (^) b a g(x)dx.
∗ a b c d a a b c d b d c b a c c c d d d d d c c
means
a ∗ a = a a ∗ b = b a ∗ c = c a ∗ d = d b ∗ a = d b ∗ b = c b ∗ c = b b ∗ d = a c ∗ a = c c ∗ b = c c ∗ c = d c ∗ d = d d ∗ a = d d ∗ b = d d ∗ c = c d ∗ d = c
A ∪ B = {x ∈ S : x ∈ A or x ∈ B or both} A ∩ B = {x ∈ S : x ∈ A and x ∈ B} A 4 B = {x ∈ S : x ∈ A or x ∈ B but not both} = (A ∪ B) − (A ∩ B)
These are called “union,” “intersection,” and “symmetric difference,” respectively. So if X = { 4 , 7 }, then P(X) = {∅, { 4 }, { 7 }, X}, and
∪ ∅ { 4 } { 7 } X ∅ ∅ { 4 } { 7 } X { 4 } { 4 } { 4 } X X { 7 } { 7 } X { 7 } X X X X X X
If we really think of binary operations as functions, it is reasonable to use “Polish notation” (named for mathematicians from Poland who first used it): denoting the sum of a and b by +(a, b). Some older calculators use “reverse Polish notation,” essentially (a, b)+: punching “5-Enter-3-Plus” to get the sum of 5 and 3. But of course most common is “infix” notation, putting the symbol for the operation between the operands: the sum of a and b is denoted a + b. Sometimes, especially if the operation is some kind of “multiplication”, we will simply denote it by juxtaposition: the “product” of a and b is denoted ab. We will do this a lot in learning about groups, because each group has only one operation, so it can’t be misunderstood.
Most operations are too badly behaved to have any good properties in common, though, so we usually impose at least one or two conditions to restrict to those that act a little more like our most familiar examples. The two usual conditions are
Def: An operation ∗ on a set S is commutative iff, for every two elements a, b of S, a ∗ b = b ∗ a (i.e., the function ∗ associates the ordered pairs (a, b) and (b, a) to the same element of S). And ∗ is associative iff, for all elements a, b, c of S, (a ∗ b) ∗ c = a ∗ (b ∗ c).
We know addition and multiplication of real numbers, addition of vectors and addition of ma- trices, pointwise addition and multiplication of functions all are both commutative and associative. Addition and multiplication modulo n are commutative and associative on ZZn — in both cases, commutativity is easy because addition and multiplication in ZZ is commutative, and associativity is a bit more complicated to check because long division by n must be done twice on both sides of the equals sign. Multiplication of matrices is associative but not commutative. Composition of functions is associative (more on this below), but it is not commutative: If f, g : IR → IR are given by f (x) = x + 1 and g(x) = 2x, then (f ◦ g)(x) = 2x + 1 but (g ◦ f )(x) = 2x + 2, so f ◦ g 6 = g ◦ f.
Because associativity is more complicated to define, and usually also to check, it’s a bit surprising that it is more basic than commutativity; but it turns out that a non-commutative operation is somewhat inconvenient, but a non-associative operation is a mess to work with. The usual example of a non-associative operation is the cross-product of 3-vectors:
(i × i) × j = 0 × j = 0 but i × (i × j) = i × k = −j.
But a simpler non-example is subtraction of real numbers: (3 − 2) − 1 = 0 but 3 − (2 − 1) = 2. That is why we usually think of subtraction, not as an operation in its own right, but as adding the negative.
Commutativity is very nice when it is available, but we know that matrix multiplication is not commutative (though it is associative), so sometimes we make do without it. Unlike associativity,