Gadgets and Anti-Gadgets Leading to a Complexity Dichotomy Tyson - - PowerPoint PPT Presentation

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Gadgets and Anti-Gadgets Leading to a Complexity Dichotomy Tyson - - PowerPoint PPT Presentation

Gadgets and Anti-Gadgets Leading to a Complexity Dichotomy Tyson Williams University of Wisconsin-Madison Joint with: Jin-Yi Cai (University of Wisconsin-Madison) Michael Kowalczyk (Northern Michigan University) Tyson Williams (UW-M) Gadgets


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SLIDE 1

Gadgets and Anti-Gadgets Leading to a Complexity Dichotomy

Tyson Williams University of Wisconsin-Madison Joint with: Jin-Yi Cai (University of Wisconsin-Madison) Michael Kowalczyk (Northern Michigan University)

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 1 / 19

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SLIDE 2

#VertexCover

Definition

A vertex cover of a graph is a set of vertices such that each edge of the graph is incident to at least one vertex in the set.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 2 / 19

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SLIDE 3

#VertexCover

Definition

A vertex cover of a graph is a set of vertices such that each edge of the graph is incident to at least one vertex in the set.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 2 / 19

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SLIDE 4

#VertexCover

Definition

A vertex cover of a graph is a set of vertices such that each edge of the graph is incident to at least one vertex in the set.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 2 / 19

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SLIDE 5

#VertexCover

Definition

A vertex cover of a graph is a set of vertices such that each edge of the graph is incident to at least one vertex in the set.

X

  • Tyson Williams (UW-M)

Gadgets and Anti-Gadgets ITCS 2012 2 / 19

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SLIDE 6

Systematic Approach to #VertexCover

G = (V, E)

  • (u,v)∈E

OR(σ(u), σ(v)) = 1 · 1 · 1 · 1 · 1 · 1 = 1

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 3 / 19

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SLIDE 7

Systematic Approach to #VertexCover

G = (V, E)

  • (u,v)∈E

OR(σ(u), σ(v)) = 1 · 1 · 1 · 1 · 1 · 1 = 1

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 3 / 19

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SLIDE 8

Systematic Approach to #VertexCover

G = (V, E) σ : V → {0, 1}

1 1 1

  • (u,v)∈E

OR(σ(u), σ(v)) = 1 · 1 · 1 · 1 · 1 · 1 = 1

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 3 / 19

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SLIDE 9

Systematic Approach to #VertexCover

G = (V, E) σ : V → {0, 1}

1 1 1

OR OR OR OR OR OR

  • (u,v)∈E

OR(σ(u), σ(v)) = 1 · 1 · 1 · 1 · 1 · 1 = 1

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 3 / 19

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SLIDE 10

Systematic Approach to #VertexCover

G = (V, E) σ : V → {0, 1}

1 1 1

OR OR OR OR OR OR

  • (u,v)∈E

OR(σ(u), σ(v)) = 1 · 1 · 1 · 1 · 1 · 1 = 1

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 3 / 19

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SLIDE 11

Systematic Approach to #VertexCover

G = (V, E) σ : V → {0, 1}

1 1

OR OR OR OR OR OR

  • (u,v)∈E

OR(σ(u), σ(v)) = 1 · 1 · 0 · 1 · 1 · 1 = 0

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 3 / 19

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SLIDE 12

Systematic Approach to #VertexCover

G = (V, E) σ : V → {0, 1} #VertexCover(G) =

  • σ:V →{0,1}
  • (u,v)∈E

OR(σ(u), σ(v))

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 3 / 19

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SLIDE 13

Generalize

  • σ:V →{0,1}
  • (u,v)∈E

OR (σ(u), σ(v))

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 4 / 19

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SLIDE 14

Generalize

  • σ:V →{0,1}
  • (u,v)∈E

OR (σ(u), σ(v)) Input Output p q OR(p, q) 1 1 1 1 1 1 1

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 4 / 19

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SLIDE 15

Generalize

  • σ:V →{0,1}
  • (u,v)∈E

f(σ(u), σ(v)) Input Output p q OR(p, q) 1 1 1 1 1 1 1 Input Output p q f(p, q) w 1 x 1 y 1 1 z where w, x, y, z ∈ C

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 4 / 19

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SLIDE 16

Generalize

Partition Function: Z(·) Z(G) =

  • σ:V →{0,1}
  • (u,v)∈E

f(σ(u), σ(v)) Input Output p q OR(p, q) 1 1 1 1 1 1 1 Input Output p q f(p, q) w 1 x 1 y 1 1 z where w, x, y, z ∈ C

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 4 / 19

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SLIDE 17

Main Result

Theorem (Dichotomy Theorem)

Over 3-regular graphs G, the counting problem for any (binary) complex-weighted function f Z(G) =

  • σ:V →{0,1}
  • (u,v)∈E

f(σ(u), σ(v)) is either computable in polynomial time or #P-hard.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 5 / 19

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SLIDE 18

Main Result

Theorem (Dichotomy Theorem)

Over 3-regular graphs G, the counting problem for any (binary) complex-weighted function f Z(G) =

  • σ:V →{0,1}
  • (u,v)∈E

f(σ(u), σ(v)) is either computable in polynomial time or #P-hard. Furthermore, the complexity is efficiently decidable.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 5 / 19

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SLIDE 19

Outline

1 Main result 2 Related work 3 Define Holant function 4 Proof sketch

Anti-Gadgets

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 6 / 19

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SLIDE 20

Related Work: Dichotomy Theorems

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 7 / 19

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Related Work: Dichotomy Theorems

Symmetric f

f(0, 1) = f(1, 0)

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 7 / 19

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SLIDE 22

Related Work: Dichotomy Theorems

Symmetric f

f(0, 1) = f(1, 0)

3-regular graphs with weights in

{0, 1} [Cai, Lu, Xia 08] {0, 1, −1} [Kowalczyk 09] R [Cai, Lu, Xia 09] C [Cai, Kowalczyk 10]

k-regular graphs with weights in

R [Cai, Kowalczyk 10] C [Cai, Kowalczyk 11]

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 7 / 19

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SLIDE 23

Related Work: Dichotomy Theorems

Symmetric f

f(0, 1) = f(1, 0)

3-regular graphs with weights in

{0, 1} [Cai, Lu, Xia 08] {0, 1, −1} [Kowalczyk 09] R [Cai, Lu, Xia 09] C [Cai, Kowalczyk 10]

k-regular graphs with weights in

R [Cai, Kowalczyk 10] C [Cai, Kowalczyk 11]

This work: Asymmetric f 3-regular graphs with weights in

C

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 7 / 19

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SLIDE 24

Definition of Holant Function

Partition Function

f f f f f f

  • σ:V →{0,1}
  • (u,v)∈E

f (σ(u), σ(v))

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 8 / 19

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SLIDE 25

Definition of Holant Function

Partition Function

Assignments to vertices Functions on edges

f f f f f f

  • σ:V →{0,1}
  • (u,v)∈E

f (σ(u), σ(v))

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 8 / 19

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SLIDE 26

Definition of Holant Function

Partition Function

Assignments to vertices Functions on edges

f f f f f f

  • σ:V →{0,1}
  • (u,v)∈E

f (σ(u), σ(v)) Holant Function

Assignment to edges Functions on vertices

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 8 / 19

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SLIDE 27

Definition of Holant Function

Partition Function

Assignments to vertices Functions on edges

f f f f f f

  • σ:V →{0,1}
  • (u,v)∈E

f (σ(u), σ(v)) Holant Function

Assignment to edges Functions on vertices

=3 =3 =3 =3 f f f f f f

  • σ:E→{0,1}
  • v∈V

gv

  • σ |E(v)
  • Tyson Williams (UW-M)

Gadgets and Anti-Gadgets ITCS 2012 8 / 19

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SLIDE 28

Definition of Holant Function

Holant({f}|{=3}) is a counting problem defined

  • ver (2,3)-regular bipartite

graphs. Holant Function

Assignment to edges Functions on vertices

=3 =3 =3 =3 f f f f f f

  • σ:E→{0,1}
  • v∈V

gv

  • σ |E(v)
  • Tyson Williams (UW-M)

Gadgets and Anti-Gadgets ITCS 2012 8 / 19

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SLIDE 29

Definition of Holant Function

Holant({f}|{=3}) is a counting problem defined

  • ver (2,3)-regular bipartite

graphs. Degree 2 vertices take f. Degree 3 vertices take =3. Holant Function

Assignment to edges Functions on vertices

=3 =3 =3 =3 f f f f f f

  • σ:E→{0,1}
  • v∈V

gv

  • σ |E(v)
  • Tyson Williams (UW-M)

Gadgets and Anti-Gadgets ITCS 2012 8 / 19

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SLIDE 30

Example Holant Problems

Holant({OR2}|{=3}) is #VertexCover on 3-regular graphs.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 9 / 19

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SLIDE 31

Example Holant Problems

Holant({OR2}|{=3}) is #VertexCover on 3-regular graphs. Holant({NAND2}|{=3}) is #IndependentSet on 3-regular graphs.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 9 / 19

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SLIDE 32

Example Holant Problems

Holant({OR2}|{=3}) is #VertexCover on 3-regular graphs. Holant({NAND2}|{=3}) is #IndependentSet on 3-regular graphs. Holant({=2}|{AT-MOST-ONE}) is #Matching.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 9 / 19

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Example Holant Problems

Holant({OR2}|{=3}) is #VertexCover on 3-regular graphs. Holant({NAND2}|{=3}) is #IndependentSet on 3-regular graphs. Holant({=2}|{AT-MOST-ONE}) is #Matching. Holant({=2}|{EXACTLY-ONE}) is #PerfectMatching.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 9 / 19

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General Bipartite Holant Definition

More generally, Holant(G |R) is a counting problem defined over bipartite graphs. g1 g2 g3 g4 r1 r2 r3

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 10 / 19

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SLIDE 35

General Bipartite Holant Definition

More generally, Holant(G |R) is a counting problem defined over bipartite graphs. g1 g2 g3 g4 r1 r2 r3

  • σ:E→{0,1}
  • v∈V

fv

  • σ |E(v)
  • Tyson Williams (UW-M)

Gadgets and Anti-Gadgets ITCS 2012 10 / 19

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SLIDE 36

Symmetric vs Asymmetric Function

=3 =3 =3 =3 f f f f f f

Input Output p q f(p, q) w 1 x 1 y 1 1 z

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 11 / 19

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SLIDE 37

Symmetric vs Asymmetric Function

=3 =3 =3 =3 f f f f f f

Input Output p q f(p, q) w 1 x 1 y 1 1 z

=3 =3 =3 =3

f f f f f f

Define p to be on the tail Define q to be on the head

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 11 / 19

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SLIDE 38

Symmetric vs Asymmetric Function

(2,3)-regular

=3 =3 =3 =3 f f f f f f

Input Output p q f(p, q) w 1 x 1 y 1 1 z Directed 3-regular

=3 =3 =3 =3

f f f f f f

Define p to be on the tail Define q to be on the head

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 11 / 19

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SLIDE 39

Strategy for Proving #P-hardness

#VertexCover is #P-hard over 3-regular graphs. Holant({OR2}|{=3}) is #VertexCover on 3-regular graphs.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 12 / 19

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Strategy for Proving #P-hardness

#VertexCover is #P-hard over 3-regular graphs. Holant({OR2}|{=3}) is #VertexCover on 3-regular graphs. Our problem is Holant({f}|{=3}). Goal: simulate OR2 using f.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 12 / 19

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Strategy for Proving #P-hardness

#VertexCover is #P-hard over 3-regular graphs. Holant({OR2}|{=3}) is #VertexCover on 3-regular graphs. Our problem is Holant({f}|{=3}). Goal: simulate OR2 using f. First step: Holant({OR2}|{=3}) ≤P

m Holant({f} ∪ U |{=3})

where U is the set of all unary functions.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 12 / 19

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SLIDE 42

Strategy for Proving #P-hardness

#VertexCover is #P-hard over 3-regular graphs. Holant({OR2}|{=3}) is #VertexCover on 3-regular graphs. Our problem is Holant({f}|{=3}). Goal: simulate OR2 using f. First step: Holant({OR2}|{=3}) ≤P

m Holant({f} ∪ U |{=3})

where U is the set of all unary functions. Second step: Holant({f} ∪ U |{=3}) ≤P

T Holant({f}|{=3})

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 12 / 19

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SLIDE 43

Strategy for Proving #P-hardness

#VertexCover is #P-hard over 3-regular graphs. Holant({OR2}|{=3}) is #VertexCover on 3-regular graphs. Our problem is Holant({f}|{=3}). Goal: simulate OR2 using f. First step: Holant({OR2}|{=3}) ≤P

m Holant({f} ∪ U |{=3})

where U is the set of all unary functions. Second step: Holant({f} ∪ U |{=3}) ≤P

T Holant({f}|{=3})

Obtain U via interpolation.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 12 / 19

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SLIDE 44

Interpolation

A degree n polynomial is uniquely defined by

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 13 / 19

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SLIDE 45

Interpolation

A degree n polynomial is uniquely defined by

n + 1 coefficients

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 13 / 19

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SLIDE 46

Interpolation

A degree n polynomial is uniquely defined by

n + 1 coefficients, or evaluations at n + 1 (different) points.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 13 / 19

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SLIDE 47

Interpolation

A degree n polynomial is uniquely defined by

n + 1 coefficients, or evaluations at n + 1 (different) points.

Interpolation is evaluations → coefficients.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 13 / 19

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SLIDE 48

Interpolation

A degree n polynomial is uniquely defined by

n + 1 coefficients, or evaluations at n + 1 (different) points.

Interpolation is evaluations → coefficients. Construct unary functions gi such that evaluation points are gi(0)

gi(1).

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 13 / 19

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SLIDE 49

Interpolation

A degree n polynomial is uniquely defined by

n + 1 coefficients, or evaluations at n + 1 (different) points.

Interpolation is evaluations → coefficients. Construct unary functions gi such that evaluation points are gi(0)

gi(1).

Distinct evaluation points ⇐ ⇒ unary functions pairwise linearly independent, as length-2 vectors (gi(0), gi(1)).

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 13 / 19

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SLIDE 50

Construction of Unary Functions

Projective Gadget Recursive Gadget Unary Function

. . . . . .

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 14 / 19

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SLIDE 51

Matrix Representation

Left side indexes the row. Right side indexes the column. High order bit on top.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 15 / 19

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SLIDE 52

Matrix Representation

Left side indexes the row. Right side indexes the column. High order bit on top. w x y z ⊗2     w x y z    

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 15 / 19

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SLIDE 53

Matrix Representation

Left side indexes the row. Right side indexes the column. High order bit on top. w x y z ⊗2     w x y z    

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 15 / 19

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SLIDE 54

Matrix Representation

Left side indexes the row. Right side indexes the column. High order bit on top. w x y z ⊗2     w x y z     w x y z ⊗2     w y x z    

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 15 / 19

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SLIDE 55

Matrix Representation

Left side indexes the row. Right side indexes the column. High order bit on top. w x y z ⊗2     w x y z     w x y z ⊗2     w y x z     Matrix of the composition is the product of the component matrices.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 15 / 19

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SLIDE 56

Anti-Gadget Construction

Want set of matrix powers to form an infinite set of pairwise linearly independent matrices.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 16 / 19

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SLIDE 57

Anti-Gadget Construction

Want set of matrix powers to form an infinite set of pairwise linearly independent matrices. If this matrix has this property, then we are done. w x y z ⊗2     w x y z    

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 16 / 19

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SLIDE 58

Anti-Gadget Construction

Want set of matrix powers to form an infinite set of pairwise linearly independent matrices. If this matrix has this property, then we are done. w x y z ⊗2     w x y z     Otherwise, some power k is a multiple of the identity matrix.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 16 / 19

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SLIDE 59

Anti-Gadget Construction

Want set of matrix powers to form an infinite set of pairwise linearly independent matrices. If this matrix has this property, then we are done. w x y z ⊗2     w x y z     Otherwise, some power k is a multiple of the identity matrix. Using only k − 1 compositions creates an anti-gadget.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 16 / 19

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SLIDE 60

Anti-Gadget Construction

Want set of matrix powers to form an infinite set of pairwise linearly independent matrices. If this matrix has this property, then we are done. w x y z ⊗2     w x y z     Otherwise, some power k is a multiple of the identity matrix. Using only k − 1 compositions creates an anti-gadget.     w x y z ⊗2     w x y z        

−1

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 16 / 19

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SLIDE 61

Anti-Gadget Construction

Want set of matrix powers to form an infinite set of pairwise linearly independent matrices. If this matrix has this property, then we are done. w x y z ⊗2     w x y z     Otherwise, some power k is a multiple of the identity matrix. Using only k − 1 compositions creates an anti-gadget.         w x y z        

−1 w

x y z ⊗2−1

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 16 / 19

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SLIDE 62

Anti-Gadget Technique

        w x y z        

−1 w

x y z ⊗2−1

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 17 / 19

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SLIDE 63

Anti-Gadget Technique

        w x y z        

−1 w

x y z ⊗2−1 w x y z ⊗2     w y x z    

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 17 / 19

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SLIDE 64

Anti-Gadget Technique

        w x y z        

−1 w

x y z ⊗2−1 w x y z ⊗2     w y x z     The composition of these two gadgets yields...

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 17 / 19

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SLIDE 65

Anti-Gadget Technique

        w x y z        

−1 w

x y z ⊗2−1 w x y z ⊗2     w y x z     The composition of these two gadgets yields...     1

y x x y

1    

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 17 / 19

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SLIDE 66

First Lemma Using Anti-Gadgets

Lemma

For w, x, y, z ∈ C, if wz = xy, wxyz = 0, and |x| = |y|, then there exists a recursive gadget whose matrix powers form an infinite set of pairwise linearly independent matrices.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 18 / 19

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SLIDE 67

First Lemma Using Anti-Gadgets

Lemma

For w, x, y, z ∈ C, if wz = xy, wxyz = 0, and |x| = |y|, then there exists a recursive gadget whose matrix powers form an infinite set of pairwise linearly independent matrices.

Corollary

For w, x, y, z ∈ C as above, Holant({f}|{=3}) is #P-hard.

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 18 / 19

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SLIDE 68

Thank You

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 19 / 19

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SLIDE 69

Thank You

Paper and slides available on my website. www.cs.wisc.edu/~tdw

Tyson Williams (UW-M) Gadgets and Anti-Gadgets ITCS 2012 19 / 19