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Antoine Deza (McMaster) based on joint work with Frédéric Meunier (Paris Est) Pauline Sarrabezolles (Paris Est) Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming

Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

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Page 1: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Antoine Deza (McMaster)

based on joint work with Frédéric Meunier (Paris Est)

Pauline Sarrabezolles (Paris Est)Tamon Stephen (Simon Fraser)

Tamás Terlaky (Lehigh)Feng Xie (Microsoft)

Colourful linear programming

Page 2: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

S, p general position

Carathéodory Theorem

Given a set S of n points in dimension d, then there exists an open simplex generated by points in S containing p

Page 3: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

S, p general position

Carathéodory Theorem

Given a set S of n points in dimension d, then there exists an open simplex generated by points in S containing p

Page 4: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Given a set S of n points in dimension d, the simplicial depth of p is the number of open simplices generated by points in S containing p [Liu 1990]

Original Sorting ProblemSimplicial Depth

S, p general position

Page 5: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

depthS(p)=1

S, p general position

Original Sorting ProblemSimplicial Depth

Given a set S of n points in dimension d, the simplicial depth of p is the number of open simplices generated by points in S containing p [Liu 1990]

Page 6: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

depthS(p)=2

S, p general position

Original Sorting ProblemSimplicial Depth

Given a set S of n points in dimension d, the simplicial depth of p is the number of open simplices generated by points in S containing p [Liu 1990]

Page 7: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

depthS(p)=3

S, p general position

Original Sorting ProblemSimplicial Depth

Given a set S of n points in dimension d, the simplicial depth of p is the number of open simplices generated by points in S containing p [Liu 1990]

Page 8: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

depthS(p)=4

S, p general position

Original Sorting ProblemSimplicial Depth

Given a set S of n points in dimension d, the simplicial depth of p is the number of open simplices generated by points in S containing p [Liu 1990]

Page 9: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

depthS(p)=4

S, p general position

Original Sorting ProblemSimplicial Depth

Given a set S of n points in dimension d, the simplicial depth of p is the number of open simplices generated by points in S containing p [Liu 1990]

Page 10: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

depthS(p)=9

S, p general position

Original Sorting ProblemSimplicial Depth

Given a set S of n points in dimension d, the simplicial depth of p is the number of open simplices generated by points in S containing p [Liu 1990]

Page 11: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

depthS (p)=5

Deepest point bounds in dimension 2 [Kárteszi 1955], [Boros, Füredi 1984], [Bukh, Matoušek, Nivasch 2010]

3 32 2( ) max ( ) ( )

27 24p Sn nO n depth Op n+ ≤ ≤ +

S, p general position

Deepest Point in Dimension 2

Page 12: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Deepest Point in Dimension d

11

1 1( ) max ( ) ( )1( 1) 2 ( 1)!p

d dd S

dd

nO n depth n O

d dp n

d+

+

+ ≤ ≤ + ++ +

Deepest point bounds in dimension d [Bárány 1982]

S, p general position

Page 13: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

11

1 1( ) max ( ) ( )1( 1) 2 ( 1)!p

d dd S

dd

nO n depth n O

d dp n

d+

+

+ ≤ ≤ + ++ +

• tight upper bound

• lower bound uses Colourful Carathéodory theorem

… breakthrough [Gromov 2010] & further improvements

Deepest point bounds in dimension d [Bárány 1982]

S, p general position

Deepest Point in Dimension d

Page 14: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Carathéodory Theorem

Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, and p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1), there exists a colourful simplex containing p [Bárány 1982]

Page 15: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Carathéodory Theorem

Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, and p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1), there exists a colourful simplex containing p [Bárány 1982]

Page 16: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Carathéodory Theorem

Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, and p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1), there exists a colourful simplex containing p [Bárány 1982]

Page 17: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Carathéodory Theorem

Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, and p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1), there exists a colourful simplex containing p [Bárány 1982]

Page 18: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Carathéodory Theorem

Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, and p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1), there exists a colourful simplex containing p [Bárány 1982]

Page 19: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Carathéodory Theorem

Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, and p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1), there exists a colourful simplex containing p [Bárány 1982]

Page 20: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Simplicial Depth

depthS (p)=1

S, p general position p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1)

Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, the colourful simplicial depth of p is the number of open colourful simplexes generated by points in S containing p

Page 21: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

depthS (p)=2

S, p general position p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1)

Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, the colourful simplicial depth of p is the number of open colourful simplexes generated by points in S containing p

Colourful Simplicial Depth

Page 22: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

depthS (p)=3

S, p general position p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1)

Colourful Simplicial Depth

Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, the colourful simplicial depth of p is the number of open colourful simplexes generated by points in S containing p

Page 23: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

depthS (p)=16

S, p general position p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1)

Colourful Simplicial Depth

Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, the colourful simplicial depth of p is the number of open colourful simplexes generated by points in S containing p

Page 24: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

11

( ) 1( ) max ( ) ( )1( 1) 2 ( 1)!

dS

d

p

dd d

nd O n depth n O ndd d

pµ ++

+ ≤ ≤ + ++ +

with

[Bárány 1982]:

… breakthrough [Gromov 2010] & further improvements

Deepest point bounds in dimension d [Bárány 1982]

S, p general position

Deepest Point in Dimension d

,( ) min ( )

p SSd tpe h pdµ =

( ) 1dµ ≥

Page 25: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

max ( )1p S d

ndepth p c

d

≥ +

[Bárány 1982]

[Wagner 2003]

[Gromov 2010]

simpler proofs: [Karazev 2012], [Matoušek, Wagner 2012]d=3: [Král’, Mach, Sereni 2012]

S, p general position

( 1)

1( 1)d ddcd +

+≥+

2( 1)!( 1)d

dcd d

≥+ +

2

( 1)

1( 1)d ddcd +

+≥+

Deepest Point in Dimension d

Page 26: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Research Directions

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

Generalize the sufficient condition of Bárány for the existence of a colourful simplex

Improve lower bound for

Computational approaches for for small d.

Obtain an efficient algorithm to find a colourful simplex : Colourful Linear Programming Feasibility problem

,( ) min ( )

p SSd tpe h pdµ =

( )dµ

Page 27: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Research Directions

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

Generalize the sufficient condition of Bárány for the existence of a colourful simplex

Improve lower bound for

Computational approaches for for small d.

Obtain an efficient algorithm to find a colourful simplex : Colourful Linear Programming Feasibility problem

,( ) min ( )

p SSd tpe h pdµ =

( )dµ

Page 28: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

[Bárány 1982] Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, and p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1), then there exists a colourful simplex containing p

[Holmsen, Pach, Tverberg 2008] and [Arocha, Bárány, Bracho, Fabila, Montejano 2009] Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, and p ∈ conv(Si ∪ Sj) for 1 ≤ i < j ≤ d +1, then there exists a colourful simplex containing p

[Meunier, D. 2013] Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, if for 1 ≤ i < j ≤ d +1 there exists k≠i, k≠j, such that for all xk∈Sk the ray [xk p) intersects conv(Si ∪ Sj) in a point distinct from xk, then there exists a colourful simplex containing p

Colourful Carathéodory Theorems

Page 29: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

[Meunier, D. 2013] Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, if for 1 ≤ i < j ≤ d +1 there exists k≠i, k≠j, such that for all xk∈Sk the ray [xk p) intersects conv(Si ∪ Sj) in a point distinct from xk, then there exists a colourful simplex containing p

Colourful Carathéodory Theorems

Page 30: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

[Meunier, D. 2013] Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d, if for i ≠ j the open half-space containing p and defined by an i-facet of a colourful simplex intersects Si ∪ Sj, then there exists a colourful simplex containing p

further generalization in dimension 2

Colourful Carathéodory Theorems

Page 31: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

In a graph, if there is a vertex with an odd degree…

Given One, Get Another One

Page 32: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Given One, Get Another One

In a graph, if there is a vertex with an odd degree…

Page 33: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Given One, Get Another One

In a graph, if there is a vertex with an odd degree… then there is another one

Page 34: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Given One, Get Another One

In a graph, if there is a vertex with an odd degree… then there is another one

Duoid / oik room partitioning Todd 1974, Edmonds 2009]

(Exchange algorithm: generalization of Lemke-Howson for finding a Nash equilibrium for a 2 players game)

Polynomial Parity Argument PPA(D) [Papadimitriou 1994]

(Hamiltonian circuit in a cubic graph, Borsuk-Ulam, …)

Page 35: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

[Meunier, D. 2013] Given colourful set S = S1 ∪ S2… ∪ Sd+1 in dimension d with |Si|=2, if there is a colourful simplex containing p then there is another one

Given One, Get Another One

Page 36: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

[Meunier, D. 2013] Any condition implying the existence of a colourful simplex containing p actually implies that the number of such simplices is at least d+1

Given One, Get Another One

S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Page 37: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Research Directions

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

Generalize the sufficient condition of Bárány for the existence of a colourful simplex

Improve lower bound for

Computational approaches for for small d.

Obtain an efficient algorithm to find a colourful simplex : Colourful Linear Programming Feasibility problem

,( ) min ( )

p SSd tpe h pdµ =

( )dµ

Page 38: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

[Bárány 1982]

,( ) min ( )

p SSd tpe h pdµ =

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

1 ( )dµ≤

Page 39: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

[Bárány 1982] 1 ( )d dµ+ ≤,

( ) min ( )p SSd tpe h pdµ =

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

Page 40: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

[Bárány 1982]

[D.,Huang,Stephen,Terlaky 2006]

1 ( )d dµ+ ≤22 ( ) 1d d dµ≤ ≤ +

,( ) min ( )

p SSd tpe h pdµ =

( )dµ even for odd d

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

Page 41: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

[Bárány 1982]

[D.,Huang,Stephen,Terlaky 2006]

1 ( )d dµ+ ≤22 ( ) 1d d dµ≤ ≤ +

,( ) min ( )

p SSd tpe h pdµ =

2 )max(3 , ) ( ) for 35

d dd d dµ+ ≤ ≥[Bárány, Matoušek 2007]

even for odd d

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

( )dµ

Colourful Simplicial Depth Bounds

Page 42: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

1 ( )d dµ+ ≤22 ( ) 1d d dµ≤ ≤ +

,( ) min ( )

p SSd tpe h pdµ =

even for odd d

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

[Bárány 1982]

[D.,Huang,Stephen,Terlaky 2006]

[Bárány, Matoušek 2007]

( )dµ3 ( ) for 3d d dµ≤ ≥

Colourful Simplicial Depth Bounds

Page 43: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

1 ( )d dµ+ ≤22 ( ) 1d d dµ≤ ≤ +

,( ) min ( )

p SSd tpe h pdµ =

[Stephen,Thomas 2008]

even for odd d

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

[Bárány 1982]

[D.,Huang,Stephen,Terlaky 2006]

[Bárány, Matoušek 2007]

( )dµ

3 ( ) for 3d d dµ≤ ≥

Colourful Simplicial Depth Bounds

2( 2) ( ) for 84

d d dµ + ≤ ≥

Page 44: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

1 ( )d dµ+ ≤22 ( ) 1d d dµ≤ ≤ +

,( ) min ( )

p SSd tpe h pdµ =

2

max(3 , ) ( ) for 35

d dd d dµ+ ≤ ≥2

2( 2) ( 2) / 4 ( ) for 8

4d d d dµ

+ + ≤ ≥

2( 1) ( ) for 42

d d dµ + ≤ ≥

[D.,Stephen, Xie 2011]

[Bárány 1982]

[D.,Huang,Stephen,Terlaky 2006]

[Bárány, Matoušek 2007]

[Stephen,Thomas 2008]

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

Page 45: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

( ) even for odd d dµ

,( ) min ( )

p SSd tpe h pdµ =

22( 1) ( ) 1 for 4

2d d d dµ

+ ≤ ≤ + ≥

(2) 5µ = (3) 10µ =(1) 2µ =

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

2conjecture: ( ) 1d dµ = +

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

Colourful Simplicial Depth Bounds

Page 46: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

23 ( ) 1d d dµ≤ ≤ +

,( ) min ( )

p SSd tpe h pdµ =

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

Page 47: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

,( ) min ( )

p SSd tpe h pdµ =

9 (3) 10µ≤ ≤

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

Page 48: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

,( ) min ( )

p SSd tpe h pdµ =

9 (3) 10µ≤ ≤( ) even for odd d dµ

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

Page 49: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

,( ) min ( )

p SSd tpe h pdµ =

(3) 10µ =

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

Page 50: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

,( ) min ( )

p SSd tpe h pdµ =

(3) 10µ =

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

Page 51: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

,( ) min ( )

p SSd tpe h pdµ =

(3) 10µ =

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

Page 52: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

,( ) min ( )

p SSd tpe h pdµ =

(3) 10µ =

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

Page 53: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

,( ) min ( )

p SSd tpe h pdµ =

(3) 10µ =

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

Colourful Simplicial Depth Bounds

Page 54: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

(3) 10µ =

,( ) min ( )

p SSd tpe h pdµ =

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

depthS(p)=10

Colourful Simplicial Depth Bounds

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Transversal

color 1color 2color 3

colourful set of d points (one colour missing)

-transversal (o2,p2)

g1

g2

g3

o1

o2

o3

p1

p2

p3

2

Page 56: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

color 1color 2color 3

colourful set of d points (one colour missing)

2 -transversal (o2,p2) spans the antipode of g1

iff (o2,p2,g1) is a colourful simplex

antipode of g1

g1

g2

g3

o1

o2

o3

p1

p2

p3

Transversal

Page 57: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Combinatorial (topological) Octahedra

color 1color 2color 3

pair of disjoint -transversals

octahedron [(o1,p1),(o2,p2)]

ig1

g2

g3

o1

o2

o3

p1

p2

p3

Page 58: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

color 1color 2color 3

origin-containing octahedra

2d

g1

g2

g3

o1

o2

o3

p1

p2

p3

octahedron [(o1,p1),(o2,p2)]

colourful faces span the whole sphere if it contains the origin (creating d+1 colourful simplexes)

Octahedron Lemma

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color 1color 2color 3

octahedron not containing the origin

octahedron [(o1,p3),(o3,p1)] does not contain p

g1

g3

o1

o2

o3

p1

p2

p3

g2

Octahedron Lemma

Page 60: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

color 1color 2color 3

octahedron not containing the origin

g1

g3

o1

o2

o3

p1

p2

p3

g2

octahedron [(o1,p3),(o3,p1)] spans any antipode an even number of times

Octahedron Lemma

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Given 2 disjoint transversals T1 and T2, and T1 spans x (antipode of x),

either octahedron (T1,T2) contains p,

or there exists a transversal T≠T1 consisting of points from T1 and T2 that spans x.

T2

T1

x

x

x

T1

T2

Octahedron Lemma

Page 62: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Research Directions

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

Generalize the sufficient condition of Bárány for the existence of a colourful simplex

Improve lower bound for

Computational approaches for for small d.

Obtain an efficient algorithm to find a colourful simplex : Colourful Linear Programming Feasibility problem

,( ) min ( )

p SSd tpe h pdµ =

( )dµ

Page 63: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Computational Approach

edge: colourful simplex containing p

g2

o2

p1

g3

o3

p2

p3

g1 o11S 2S 3S

1

2

3

combinatorial setting suggested by Imre Bárány

(d+1)-uniform (d+1)-partite hypergraph representation of colourful point configurations

Page 64: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Computational Approach(d+1)-uniform (d+1)-partite hypergraph representation

of colourful point configurations

1S 2S 3S

1

2

3

g2

g3 o2

o3

p1

p2

p3

g1 o1

necessary conditions:

• every vertex belongs to at least 1 edge.

• even number of edges induced by subsets Xi of Si of size 2 reformulation of the Octahedron Lemma

Page 65: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Computational Approach(d+1)-uniform (d+1)-partite hypergraph representation

of colourful point configurations

1S 2S 3S

1

2

3

g2

g3 o2

o3

p1

p2

p3

g1 o1

if no hypergraph with t or less hyper-edges satisfies the 2 necessary conditions, then

⇒ computational proof that [D., Stephen, Xie 2013]

( )d tµ >

(4) 14µ ≥ isolated edge argument needed

Page 66: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Octahedral Systemsn-uniform n-partite hypergraph (S1,...,Sn ,E) with |Si | ≥ 2 such that the number of edges induced by subsets Xi of Si of size 2 for i=1,...n is even

Page 67: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Octahedral Systems

even number of edges if all |Si| are even for i = 1, ... , n

symmetric difference of 2 octahedral systems is octahedral

existence of non-realizable octahedral system

without isolated vertex

number of octahedral systems:

[D., Meunier, Sarrabezolles 2013]

1 1

| | (| | 1)

2

n n

i iS S− −∏ ∏

Page 68: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Octahedral Systems

a non-realizable octahedral system

1S 2S 3S

1

2

3

Page 69: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Octahedral Systems

a non-realizable octahedral system

p11S 2S 3S

1

2

3

Page 70: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Octahedral Systems

a non-realizable octahedral system

p11S 2S 3S

1

2

3 g2

g1

Page 71: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Octahedral Systems

a non-realizable octahedral system

p11S 2S 3S

1

2

3 g2

g1

o1

o2

Page 72: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Octahedral Systems

a non-realizable octahedral system

g2

o2

p1

g1

o1

1S 2S 3S

1

2

3

Page 73: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Octahedral Systems

a non-realizable octahedral system

g2

o2

p1

g1

o1

1S 2S 3S

1

2

3

Page 74: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Octahedral Systems

a non-realizable octahedral system

g2

o2

p1

g1

o1

1S 2S 3S

1

2

3

Page 75: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Octahedral Systems

a non-realizable octahedral system

g2

o2

p1

g1

o1

1S 2S 3S

1

2

3

Page 76: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Octahedral Systems

( ) ( 1)( 6) / 2 11d d dµ ≥ + + −

(4) 17µ =

Page 77: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Colourful Research Directions

p ∈ conv(S1) ∩ conv(S2) ∩ … ∩ conv(Sd+1) S, p general position and |S1|,|S2|,…,|Sd+1| ≥ d+1

1

( )max ( ) ( )1( 1)p

ddS

nddepth O ndd

p µ+

≥ + ++

Generalize the sufficient condition of Bárány for the existence of a colourful simplex

Improve lower bound for

Computational approaches for for small d.

Obtain an efficient algorithm to find a colourful simplex : Colourful Linear Programming Feasibility problem

[Bárány, Onn 1997] and [D., Huang, Stephen, Terlaky 2008]

,( ) min ( )

p SSd tpe h pdµ =

( )dµ

Page 78: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

( ) even for odd d dµ

,( ) min ( )

p SSd tpe h pdµ =

2( 1)( 6) / 2 11 ( ) 1 for 5d d d d dµ+ + − ≤ ≤ + ≥

(2) 5µ = (3) 10µ =(1) 2µ =

22 (5) 26µ≤ ≤

Colourful Simplicial Depth Bounds

(4) 17µ =

Page 79: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

( ) even for odd d dµ

,( ) min ( )

p SSd tpe h pdµ =

2( 1)( 6) / 2 11 ( ) 1 for 5d d d d dµ+ + − ≤ ≤ + ≥

(2) 5µ = (3) 10µ =(1) 2µ =

22 (5) 26µ≤ ≤

Colourful Simplicial Depth Bounds

(4) 17µ =

thank you

Page 80: Colourful linear programming - Fields Institute · Tamon Stephen (Simon Fraser) Tamás Terlaky (Lehigh) Feng Xie (Microsoft) Colourful linear programming. S, p general position Carathéodory

Tverberg Theoremn points can be partitioned into colours, with a point p in convex hull intersection. [Tverberg 1966]

1 11

nd

− + +

1 11

1

ndd

− + + + combinations to choose d+1 colours.

1max ( )

1( )1

11

d

p S

n nO ndpdepth

dd

µ µ − + ++ + +

=

If each combination has at least colourful simplices. [Bárány 82]

µ

S, p general position