Lecture 3 Interacting Hopf monoids and graphical linear algebra - - PowerPoint PPT Presentation

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Lecture 3 Interacting Hopf monoids and graphical linear algebra - - PowerPoint PPT Presentation

Lecture 3 Interacting Hopf monoids and graphical linear algebra Plan relational intuitions Frobenius monoids the equations of interacting Hopf monoids linear relations rational numbers, diagrammatically Relational intuitions


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SLIDE 1

Lecture 3

Interacting Hopf monoids and graphical linear algebra

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SLIDE 2

Plan

  • relational intuitions
  • Frobenius monoids
  • the equations of interacting Hopf monoids
  • linear relations
  • rational numbers, diagrammatically
slide-3
SLIDE 3

Relational intuitions

  • We have been saying that numbers go from left to right in diagrams
  • this is a functional, input/output interpretation
  • J.C. Willems - Behavioural approach in control theory
  • Engineers create functional behaviour from non-functional

components

  • The physical world is NOT functional
  • Functional thinking is fundamentally non-compositional
  • From now on, we will take a relational point of view, a diagram is a

contract that allows certain numbers to appear on the left and on the right

The input/output framework is totally inappropriate for dealing with all but the most special system interconnections. [The input/output representation] often needlessly complicates matters, mathematically and conceptually. A good theory of systems takes the behavior as the basic notion. J.C. Willems, Linear systems in discrete time, 2009

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SLIDE 4

Intuition upgrade

  • Intuition so far is this as a function +: D×D→D
  • From now it will be as a relation of type DxD → D
  • Composition is relational composition
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SLIDE 5

Mirror images

x y , x+y () , 0 x , x x x , () x y x+y , 0 , () x x , x () , x

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SLIDE 6

Adding meets adding

p q r p+q r p q+r

x y z x+y z x y+z

x = p+q z = q+r p=x+y r=y+z

Provided addition yields abelian group (i.e. there are additive inverses), the two are the same relation

y=-q

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SLIDE 7

More adding meets adding

x+y x y x+y

since x and y are free, this is the identity relation

x

empty relation

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SLIDE 8

Copying meets copying

x x x x x x x x x x

clearly both give the same relation

x x x x

identity relation

x

empty relation

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SLIDE 9

Two Frobenius structures

=

= = =

+ special / strongly separable equations + “bone” equations

= =

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SLIDE 10

Plan

  • relational intuitions
  • Frobenius monoids
  • the equations of interacting Hopf monoids
  • rational numbers and linear relations
  • graphical linear algebra
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SLIDE 11

Frobenius monoids

=

= = = = = =

Frobenius monoid

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SLIDE 12

Snakes

= =

Snake lemma

=

(Frob)

=

(Unit)

=

(Counit)

Proof: “cup” “cap”

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SLIDE 13

Normal forms

  • In B, we saw that every

diagram can be factorised into comonoid structure ; monoid structure, this gave us centipedes

  • In Frob, every diagram

can be factored into monoid structure ; comonoid structure, these are often referred to as spiders

= = = = = = =

Special Frobenius monoid =

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SLIDE 14

Spiders in special Frobenius monoids 1

  • In a special Frobenius monoid every connected

diagram is equal to one of the form

  • which suggests the “spider notation”

. . . . . .

1 2 m 1 2 n

. . . . . .

1 2 m 1 2 n

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SLIDE 15

Spiders in special Frobenius monoids 2

  • In general, diagrams are collections of spiders
  • when two spiders connect, they fuse into one
  • i.e. any connected diagram of type m→n is equal
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SLIDE 16

Plan

  • relational intuitions
  • Frobenius monoids
  • the equations of interacting Hopf monoids
  • rational numbers and linear relations
  • graphical linear algebra
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SLIDE 17

Black and white cups and caps

=

{( ✓ x y ◆ , ()) | x + y = 0 } {( ✓ x x ◆ , ())}

=

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SLIDE 18

Scalars meet scalars

if multiplication on the left by p is injective (e.g. if p ≠ 0 in a field)

p

x px

p

px =

if multiplication on the left by p is surjective (e.g. if p ≠ 0 in a field)

p p

x px=py y =

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SLIDE 19

Interacting Hopf Monoids

(Bonchi, S., Zanasi, ’13, ’14)

= = =

Copying

= = =

Copyingop

= = =

Adding

= = = =

Adding meets Copying

= = =

Addingop

= = = =

Addingop meets Copyingop Antipode = = = = = Antipodeop = = = = =

H Hop

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SLIDE 20

White monoid (adding) Black comonoid (copying) White comonoid (adding-op) Black monoid (copying-op)

Hopf Hopf Frobenius

Frobenius

= = = = = = = = = = = =

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SLIDE 21

Interacting Hopf Monoids

Adding meets Addingop

=

= = Copying meets Copyingop

=

= = = = Cups and Caps

p p p p (p ≠ 0)

= = Scalars

  • cf. ZX-calculus (Coecke, Duncan)
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SLIDE 22

= = =

Copying

= = =

Copyingop

= = =

Adding

= = = =

Adding meets Copying

= = =

Addingop

= = = =

Addingop meets Copyingop Antipode = = = = = Antipodeop = = = = = Adding meets Addingop

=

= = Copying meets Copyingop

=

= = = = Cups and Caps

p p p p (p ≠ 0)

= = Scalars

Symmetry 1 - colour inversion Symmetry 2 - mirror image

IH

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SLIDE 23

Redundancy

  • Generators are expressible in terms of other

generators, e.g. Lemma

= = = =

so

= =

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SLIDE 24

Plan

  • relational intuitions
  • Frobenius monoids
  • the equations of interacting Hopf monoids
  • rational numbers and linear relations
  • graphical linear algebra
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SLIDE 25

Linear subspaces

  • Suppose that V is a vector space over field k
  • A linear subspace U⊆V is a subset that
  • contains the zero vector, 0∈V
  • closed under addition, if u,u’ ∈ U then u+u’ ∈ U
  • closed under scalar multiplication, if u ∈ U and p ∈ k

then p⋅u ∈ U

  • e.g. R2 is an R-vector space. What are the linear

subspaces?

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SLIDE 26
  • Suppose that U, V, W are k vector spaces,
  • R ⊆ U×V is a subspace and
  • S ⊆ V×W is a subspace
  • Show that the relational composition R;S⊆U×W is a

subspace

Exercise

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SLIDE 27
  • PROP of linear relations over the rationals
  • arrows m to n are subspaces of Qm × Qn
  • composed as relations
  • monoidal product is direct sum
  • IH is isomorphic to LinRel

LinRel

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SLIDE 28

Where did the rationals come from?

  • Recall
  • in B, the (1,1) diagrams were the natural numbers
  • in H, the (1,1) diagrams were the integers
  • In IH, the (1,1) diagrams include the rationals p/q

p q

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SLIDE 29

Some Lemmas

if q ≠ 0:

p q p q

=

q q

=

q q q p

=

q p

q q

=

q q q q

=

q q q q q

=

q

suppose q,s ≠ 0:

p q r s

=

sp = qr

p s

=

p q q s r s q s r q s s

= =

r q

=

p q

=

p q s s

=

r q q s

=

r q s q r s

=

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SLIDE 30

Rational arithmetic

(q,s ≠ 0)

p q r s

=

p q r s s s q q sp sq qr qs sp qr sq

= = =

sp+qr sq

p q r s

=

p r s q

=

rp sq

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SLIDE 31

Keep calm and divide by zero

  • it’s ok, nothing blows up
  • of course, arithmetic with 1/0 is not quite as nice

as with proper rationals.

  • two ways of interpreting 0/0 (0 · /0 or /0 · 0)

= =

= =

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SLIDE 32

Projective arithmetic++

  • Projective arithmetic identifies numbers with one-

dimensional spaces (lines) of Q

2

  • one for each rational p : { (x,px) | x ∈ Q }
  • and “infinity” : { (0, x) | x ∈ Q }
  • The extended system includes all the subspaces of

Q

2, in particular:

  • the unique zero dimensional space { (0, 0) }
  • the unique two dimensional space { (x,y) | x,y ∈ Q }

(x, 1/2 x) (x, 2x)

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SLIDE 33

Plan

  • relational intuitions
  • Frobenius monoids
  • the equations of interacting Hopf monoids
  • rational numbers and linear relations
  • graphical linear algebra
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SLIDE 34

Factorisations

  • Every diagram can be factorised as a span or a cospan of matrices
  • This gives us the two different ways one can think of spaces

solutions of a list of homogeneous equations

linear combinations

  • f basis vectors

x+y=0 x y z 2y-z=0

2

x y z

x+y=0 2y-z=0

2

x y z

Cospans

a[1, -1, 0] a

b[0, 1, 2]

2

b

a[1, -1, 0]+b[0,1,2]

2

a b

Spans

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SLIDE 35

Image and kernel

  • Definition
  • The kernel of A is
  • The cokernel of A is
  • The image of A is
  • The coimage of A is

A A

AT AT

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SLIDE 36

Injectivity

Injective matrices are the monos in MatZ

  • Theorem. A is injective iff

A A

=

⇒ ⇐

A F A G

= ⇒

A F A G

=

A A

F

=

G

    

  • ?

? ? ? ?

A

  • ?

? ? ? ?

A

    

is pullback in MatZ

A F A G

= ⇒

F

=

G

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SLIDE 37

Surjectivity

  • Surjective matrices are the epis in MatZ, i.e.
  • Theorem. A is surjective iff

A A

= A A F G

= ⇒

F

=

G

Proof: Bizarro of last slide

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SLIDE 38

Injectivity and kernel

  • Theorem. A is injective iff ker A = 0

⇒ ⇐

A A

=

A A

=

A A

=

A

= =

A

=

A A

=

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SLIDE 39

Surjectivity and image

  • Theorem. A is surjective iff im(A)=codomain

A A

=

A

=

Proof: bizarro of last slide

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SLIDE 40

Invertible matrices

  • Theorem: A is invertible with inverse B iff

A B

=

⇒ ⇐

so A is injective

A B A A

= =

bizarro argument yields other half

A A B B

= =

A A B

= =

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SLIDE 41

Summary

  • We have done a bit of linear algebra without mentioning
  • vectors, vector spaces and bases
  • linear dependence/independence, spans of a vector list
  • dimensions
  • Similar stories can be told for other parts of linear algebra:

decompositions, eigenvalues/eigenspaces, determinants

  • much of this is work in progress: check out the blog! :)