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Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

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Page 1: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Preliminaries/ Chapter 1: Introduction

Page 2: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Definitions: from Abstract to Linear Algebra

Page 3: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Let A be a set, with a binary function : A A → A defined on it.

1. <A, > is a semigroup if is associative:

(ab)c = a(bc)

2. <A, > is a group if also:

(i) there exists some such that for all a:

a = a = a

(ii) for all a, there is some -a such that:

= a-a = -aa

3. <A, > is an abelian (or commutative) group if also: ab = ba

Page 4: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Let be another binary function defined on A.

4. <A, , > is a ring if <A, > is an abelian group, and also:

(i) is associative: (ab)c = a(bc)

(ii) a(bc) = (ab)ac), and

(ab)c = (ac)bc)

5. The ring <A, , > is a field if <A, > and

<A-{}, > are both abelian groups, the latter

with identity element, where ≠ .

Page 5: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Let V be a set, and let F be a field. Let +: V V → V and ◦: F V → V be two binary functions defined on them.

6. V is a vector space over the field F if <V, +> is an abelian group, and for all a, b ϵ F, u, v ϵ V:

a◦(u + v) = (a◦u) + (a◦v)

(ab)◦u = (a◦u) + (b◦u)

(ab)◦u = a◦(b◦u)

◦u = u

Page 6: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.
Page 7: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

(p. 8) Homomorphism: φ sends empirical domain A into R in such a way that ≥ and + preserve the properties of and ○≿

Isomorphism: a 1-1 homomorphism.

(N.b. These defs are a little different from logic, which differ from logic.)

Page 8: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

HomomorphismIsomorphism

Page 9: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

HomomorphismIsomorphism

Page 10: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

HomomorphismIsomorphism

Page 11: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

HomomorphismIsomorphism

Page 12: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.
Page 13: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.
Page 14: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.
Page 15: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Homomorphism

Page 16: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Let A be some set.

An equivalence relation on A is any (binary) reflexive (a~a), symmetric (if a~b, then b~a), and transitive (if a~b, and b~c, then a~c relation.

Let [a]~ = {b ϵ A: a~b}

The quotient set of A wrt ~ is A/~ = {[a]~ : a ϵ

A}

Proposition. The following are equivalent:

(i) [a]~ = [b]

~

(ii) [a]~ ∩ [b]

~ is nonempty

(iii) a ~ b

Page 17: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

A partition of A is any collection P = {pi : i ϵ I}

of nonempty subsets of A such that: (i) UP = A, and (ii) p

i∩p

j = (i ≠ j).

Proposition. Any partition P is the quotient set of the relation: a~b iff a, b ϵ p

i, for some p

i ϵ

P.

Proposition. The quotient set of any equivalence relation is a partition.

Proposition. There is a bijection from equivalence relations on A to partitions of A that maps the former onto their quotient sets.

Page 18: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Let q(a) = [a]~

Let φ: A → R be such that

(i) if a ~ b, then φ(a) = φ(b)

Proposition. There exists a unique surjection

ψ: A/~ → Range(φ), where φ = ψ○q. ψ is an injection iff φ also observes:

(ii) if φ(a) = φ(b), then a ~ b

Page 19: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

. . . . a b c ~ d ~ e f . . .≻ ≻ ≻ ≻

Weak Order: is transitive and connected ≿(total)

Allowed: c ~ d ~ e but c ≠ d = e

Simple Order: antisymmetric weak order

. . . . a b c ~ d ~ e f . . .≻ ≻ ≻ ≻If x ~ y, then x = y

Page 20: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

. . . . a b c f ≻ ≻ ≻ ≻ . . .When order is preserved, a b iff φ(a) ≥ φ(b), ≿weak orders may be treated as simple orders

by using quotient sets:

a = [a]~ = {b : a ~ b}

Order is then given as:

a b≿ iff a' b' for≿ some a' ϵ a, b' ϵ b

iff a' b' for ≿ every a' ϵ a, b' ϵ b

a b≻ iff a' b', for every a' ϵ ≻ a, b' ϵ b

a ~ b iff a = b

Page 21: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Three ways to assign numbers to things

1. Ordinal measurement

a b iff φ(a) ≥ φ(b)≿2. Counting of units

Standard sequences

3. Solving inequalities

b ~ a○a, and c a○b might imply: ≿ φ(c)/φ(a) ≥ 3

φ is ordinal, additive

Page 22: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Chapter 2: Construction of Numerical Functions

Page 23: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

1. Ordinal Measurement

a b iff φ(a) ≥ φ(b)≿

Page 24: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Ordering Theorems for a simple order <A, >≿Desideratum: φ:A → R such that a b iff φ(a) ≥ φ(b) ≿Theorem 1. If A is countable, we have such a φ.

Def. B A is order dense in A iff for any a b ≻there is c ϵ B: a c b≿ ≿

Theorems 2, 3. There is a denumerable order dense B A iff φ exists and is 1-1. φ is unique up to monotonically strictly increasing transformations.

Page 25: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

2. Counting of units

Additive representations

φ(a○b) = φ(a) + φ(b)

Page 26: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Ordered Semigroup<A, , (B = A), ○ >≿

1. <A, > is a simple order≿2. [ok]

3. If a b, then c○a c○b≿ ≿4. If a b, then a○c b○c≿ ≿5. (a○b)○c = a○(b○c)

6. a○b a [≻ pos.]

7. If a b, then for some c, a b○c [≻ ≿ reg.]

8. {n: b na} is finite [≻ Arch.]

Page 27: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Ordered Local Semigroup<A, , B, ○ >≿

1. <A, > is a simple order≿2. If a○b exists, and a c, b d, then c○d exists ≿ ≿3. If c○a exists, and a b, then c○a c○b≿ ≿4. If a○c exists, and a b, then a○c b○c≿ ≿5. (a○b), (a○b)○c exist iff (b○c), a○(b○c) do, in

which case: (a○b)○c = a○(b○c)

6. If a○b exists, then a○b a [≻ pos.]

7. If a b, then for some c, b○c exists, and a ≻ ≿b○c [reg.]

8. {n: na exists and b na} is finite [≻ Arch.]

Page 28: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Theorem 4. Let <A, , B, ○ > be a positive, ≿regular, Archimedean ordered local semigroup.

There is a φ: A → R+ such that:

(i) a b iff φ(a) ≥ φ(b)≿ (ii) if a○b exists, then φ(a○b) = φ(a) + φ(b)

If φ': A → R+ also satisfies (i) and (ii), then

φ'(a) = βφ(a),

for some β > 0, and all nonmaximal a in A.

Page 29: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Theorem 4'. Set: φ as in Theorem 4. the l.u.b. of Range(φ), A' the nonmaximal elements of A, and B' the set of nonmaximal concatenations.

Then φ is an isomorphism of <A', , B', ○ > ≿into <R, ≥ , R , +>.

Page 30: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

<A, , ○> is a ≿ simply ordered group iff

<A, > is a simple order≿<A, ○> is a group

If a b, then a○c b○c and c○a c○b. ≿ ≿ ≿<A, , ○> is also ≿ Archimedean if (with the

identity element e) a e, then na b, for ≻ ≻some n.

Theorem 5 (Holder's Theorem) An Archimedean simply ordered group is isomorphic to a subgroup of <R, ≥, +>, and the isomorphism is unique up to scaling by a positive constant.

Page 31: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Ordered Local Semiring<A, , B, ≿ >

1. <A, , B, ≿ > is a simple order

2. <A, , B≿ *, > is a simple order, using the weaker associativity axiom:

If ab and bc exist, then (ab)c exists iff a(bc) does, in which case, they are identical.

3. If (ab)c exists, then so does (ac)(bc), and they are identical.

If a(bc) exists, then so does (ab)(ac), and they are identical.

4.For any a, there exists some a(bc)

Page 32: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Theorem 6. Let <A, , B, ≿ > be a regular, positive, Archimedean ordered semiring. Then there is a unique φ: A → R+ such that

1. a b iff φ(a) ≥ φ(b)≿2. If ab exists then φ(ab) = φ(a) + φ(b)

3. If ab exists, then φ(ab) = φ(a)φ(b)

Page 33: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Archimedean Ordered Ring<A, , ≿ >

1. <A, > is a ring with zero element θ;

2. <A, , ≿ > is an Archimedean ordered group;

3. If a θ, and b c, then a≻ ≻ b a≻ c and ba ≻ca.

Corollary. An Archimedean ordered ring is isomorphic to a subring of < R, ≥, +, >. This isomorphism is unique.

Page 34: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

3. Solving inequalities

Page 35: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

a1○a

5 a≻

3○a

4 a≻

1○a

2 a≻

5 a≻

4 a≻

3

a≻2 a≻

1

x1 + x

5 – x

3 – x

4 > 0

x3 + x

4 – x

1 – x

2 > 0

x1 + x

2 – x

5 > 0

x5 – x

4 > 0

x4 – x

3 > 0

x3 – x

2 > 0

x2 – x

1 > 0

1 0 -1 -1 1

-1 -1 1 1 0

1 1 0 0 -1

0 0 0 -1 1

0 0 -1 1 0

0 -1 1 0 0

-1 1 0 0 0

x1

x2

x3

x4

x5

Ax > 0

Page 36: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Ax '>' 0, Bx = 0

Theorem 7. There is a solution x to the above inequalities iff the polyhedron (in Rn) whose corners are the m' row vectors of A does not intersect the subspace spanned by the row vectors of B.

'1 01

mixan

iiij

''1 01

mixbn

iiij

Page 37: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.
Page 38: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.
Page 39: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.
Page 40: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Theorem 7. Let A and B be m' by n and m'' by n matrices, respectively. There exists an x ϵ Rn such that Bx = 0 and the m' elements of Ax are positive

if and only if

there does not exist a pair λ ϵ Rm', μ ϵ Rm'' such that (i) AT λ = BTμ, (ii) λ

i > 0, and (iii) 1Tλ = 1.

Page 41: Preliminaries/ Chapter 1: Introduction. Definitions: from Abstract to Linear Algebra.

Lemma 7. Suppose the m row vectors of A are linearly independent. Then for any t ϵ Rm, there is some x ϵ Rn such that Ax = t.

Lemma 8. There exists an x ϵ Rn such that (i) the m elements of Ax are nonnegative, and (ii) zTx < 0.

if and only if

There does not exist a y ϵ Rm such that (i) the m elements of y are nonnegative, and (ii) ATy = z.