Download - Geometric Representations of Graphs A survey of recent results and problems Jan Kratochvíl, Prague
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Geometric Geometric RepresentationsRepresentations of of Graphs Graphs
A survey of recent results and problems
Jan Kratochvíl, Prague
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Outline of the Talk
Intersection Graphs Recognition of the Classes Sizes of Representations Optimization Problems Interval Filament Graphs Representations of Planar Graphs
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Intersection Graphs
{Mu, u VG} uv EG Mu Mv
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Interval graphs INT
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Interval graphs INT
Circular Arc graphsCA
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Interval graphs INT
Circular Arc graphsCA
Circle graphs CIR
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Circular Arc graphsCA
Circle graphs CIR
Polygon-Circle graphs PC
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SEG
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SEG CONV
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SEG CONV
STRING
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INT
CA
CIR
PC
CONV
STR
SEG
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2. Complexity of Recognition
Upper bound Lower bound
• P
• NP NP-hard
• PSPACE
• Decidable
• Unknown
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
Tucker 1970
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
Tucker 1970
Bouchet 1985
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
Tucker 1970
Bouchet 1985
Koebe 1990
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
Tucker 1970
Bouchet 1985
Koebe 1990
J.K. 1991
J.K. 1991
J.K. 1991
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
Tucker 1970
Bouchet 1985
Koebe 1990
J.K. 1991
J.K. 1991
J.K. 1991J.K., Matoušek 1994
K-M 1994
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
Tucker 1970
Bouchet 1985
Koebe 1990
J.K. 1991
J.K. 1991
J.K. 1991J.K., Matoušek 1994
K-M 1994
Pach, Tóth 2001; Schaefer, Štefankovič 2001
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
Tucker 1970
Bouchet 1985
Koebe 1990
J.K. 1991
J.K. 1991
J.K. 1991J.K., Matoušek 1994
K-M 1994
Schaefer, Sedgwick, Štefankovič 2002
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
Tucker 1970
Bouchet 1985
Koebe 1990
J.K. 1991
J.K. 1991
J.K. 1991J.K., Matoušek 1994
K-M 1994
Schaefer, Sedgwick, Štefankovič 2002
?
?
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
Tucker 1970
Bouchet 1985
J.K. 1991
J.K. 1991
J.K. 1991J.K., Matoušek 1994
K-M 1994
Schaefer, Sedgwick, Štefankovič 2002
?
?
?
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Thm: Recognition of CONV graphs is in PSPACE
Reduction to solvability of polynomial inequalities in R:
x1, x2, x3 … xn R s.t.
P1(x1, x2, x3 … xn) > 0
P2(x1, x2, x3 … xn) > 0
…
Pm(x1, x2, x3 … xn) > 0 ?
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{Mu, u VG} uv EG Mu Mv
Mu
Mv
Mw
Mz
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Mu
Mv
Mw
Mz
Choose Xuv Mu Mv for every uv EG
Xuw
Xuz
Xuv
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Cu Cv Mu Mv uv EG
Mu
Mv
Mw
Mz
Replace Mu by Cu = conv(Xuv : v s.t. uv EG) Mu
Xuw
Xuz
Xuv
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Introduce variables xuv , yuv R s.t. Xuv = [xuv , yuv ] for uv EG
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Introduce variables xuv , yuv R s.t. Xuv = [xuv , yuv ] for uv EG
uv EG Cu Cv guaranteed by the choice Cu = conv(Xuv : v s.t. uv EG)
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Introduce variables xuv , yuv R s.t. Xuv = [xuv , yuv ] for uv EG
uv EG Cu Cv guaranteed by the choice Cu = conv(Xuv : v s.t. uv EG)
uv EG Cu Cv = separating lines
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Introduce variables xuv , yuv R s.t. Xuv = [xuv , yuv ] for uv EG
uv EG Cu Cv guaranteed by the choice Cu = conv(Xuv : v s.t. uv EG)
uw EG Cu Cw = separating lines
Cu
Cw
auwx + buwy + cuw = 0
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Introduce variables xuv , yuv R s.t. Xuv = [xuv , yuv ] for uv EG
uv EG Cu Cv guaranteed by the choice Cu = conv(Xuv : v s.t. uv EG)
uw EG Cu Cw = separating lines
Cu
Cw
auwx + buwy + cuw = 0
Representation is described by inequalities
(auwxuv + buwyuv + cuw) (auwxwz + buwywz + cuw) < 0 for all u,v,w,z s.t. uv, wz EG and uw EG
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INT
CA
CIR
PC
CONV
STR
SEG
INT
CA
CIR
PC
CONV
STR
SEG
Upper bound Lower bound
Gilmore, Hoffman 1964
Tucker 1970
Bouchet 1985
J.K. 1991
J.K. 1991
J.K. 1991J.K., Matoušek 1994
K-M 1994
Schaefer, Sedgwick, Štefankovič 2002
?
?
?
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Polygon-circle graphs representable by polygons of bounded size
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Polygon-circle graphs representable by polygons of bounded size
k-PC = Intersection graphs of convex k-gons inscribed to a circle
2-PC = CIR 3-PC 4-PC
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Polygon-circle graphs representable by polygons of bounded size
k-PC = Intersection graphs of convex k-gons inscribed to a circle
2-PC = CIR 3-PC 4-PC
PC = k-PC
k=2
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Example forcing large number of corners
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Example forcing large number of corners
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Example forcing large number of corners
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3-PC
CIR = 2-PC
PC
4-PC
5-PC
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3-PC
CIR = 2-PC
PC
4-PC
5-PC
J.K., M. Pergel 2003
?
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Thm: For every k 3, recognition of k-PC graphs is NP-complete.
Proof for k = 3.Reduction from 3-edge colorability of cubic
graphs.For cubic G = (V,E), construct H = (W,F)
so that
’(G) = 3 iff H 3-PC
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W = {u1, u2, u3, u4, u5, u6}
{ae, e E} {bv, v V}
F = {u1 u2, u2u3, u3u4, u4u5, u5u6 , u6u1}
{aebv, v e E}
{bubv, u,v V}
{bvui, v V, i = 2,4,6}
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{u1, u2, u3, u4, u5, u6}
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{u1, u2, u3, u4, u5, u6}
{ae, e E}
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{u1, u2, u3, u4, u5, u6}
{ae, e E}
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{u1, u2, u3, u4, u5, u6}
{ae, e E}
{bv, v V}
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{u1, u2, u3, u4, u5, u6}
{ae, e E}
{bv, v V}
’(G) = 3 H 3-PC
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{u1, u2, u3, u4, u5, u6}
{ae, e E}
{bv, v V}
’(G) > 3 H 3-PC
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{u1, u2, u3, u4, u5, u6}
{ae, e E}
{bv, v V}
’(G) > 3 H 3-PC
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3. Sizes of Representations
Membership in NP – Guess and verify a representation
Problem – The representation may be of exponential size
Indeed – for SEG and STRING graphs, NP-membership cannot be proven in this way
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STRING graphs
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STRING graphs
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Abstract Topological Graphs
G = (V,E), R { ef : e,f E } is realizable if G has a drawing D in the plane such that for every two edges e,f E,
De Df ef R
G = (V,E), R = is realizable iff G is planar
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Worst case functions
Str(n) = min k s.t. every STRING graph on n vertices has a representation with at most k crossing points of the curves
At(n) = min k s.t. every AT graph with n edges has a realization with at most k crossing points of the edges
Lemma: Str(n) and At(n) are polynomially equivalent
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STRING graphs requiring large representations Thm (J.K., Matoušek 1991):
At(n) 2cn
Thm (Schaefer, Štefankovič 2001):
At(n) n2n-2
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Sizes of SEG representations
Rational endpoints of segments Integral endpoints Size of representation = max coordinate of
endpoint (in absolute value)
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Sizes of SEG representations
Thm (J.K., Matoušek 1994) For every n, there is a SEG graph Gn with O(n2) vertices such that every SEG representation has size at least
22n
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Thm (Schaefer, Štefankovič 2001): At(n) n2n-2
Lemma: In every optimal representation of an AT graph, if an edge e is crossed by k other edges, then it carries at most 2k-1 crossing points.
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e
e crossed by e1, e2, … , ek
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e
e crossed by e1, e2, … , ek
(u1, u2, …, uk) - binary vector expressing the parity of the number of intersections of e and ei between the beginning of e and this location
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e
e crossed by e1, e2, … , ek
(u1, u2, …, uk) - binary vector expressing the parity of the number of intersections of e and ei between the beginning of e and this location
If the number of crossing points on e is 2k, two of these vectors are the same
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e
e crossed by e1, e2, … , ek
(u1, u2, …, uk) - binary vector expressing the parity of the number of intersections of e and ei between the beginning of e and this location
If the number of crossing points on e is 2k, two of this vectors are the same, and hence we find a segment on e where all other edges have even number of crossing points
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e
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e
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e
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e
2m crossing points with e4m crossing points with the circle
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e
2m crossing points with e4m crossing points with the circle
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e
2m crossing points with e4m crossing points with the circle
Circle inversion
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e
2m crossing points with e4m crossing points with the circle
Circle inversion
Symmetric flip
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e
2m crossing points with e4m crossing points with the circle
Circle inversion
Symmetric flip
2m crossing pointswith the circle, no newcrossing points arouse
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e
2m crossing points with e4m crossing points with the circle
Circle inversion
Symmetric flip
2m crossing pointswith the circle, no newcrossing points arouse
Reroute e along the semicircle with fewernumber of crossing points
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e
2m crossing points with e4m crossing points with the circle
Circle inversion
Symmetric flip
2m crossing pointswith the circle, no newcrossing points arouse
Reroute e along the semicircle with fewernumber of crossing points
Better realization - m < 2m
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4. Optimization problems
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INT
CA
CIR
PC
CONV
STR
SEG
Determining the chromatic number
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INT
CA
CIR
PC
CONV
STR
SEG
(G) k for fixed k
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INT
CA
CIR
PC
CONV
STR
SEG
Determining the independence number
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INT
CA
CIR
PC
CONV
STR
SEG
Determining the clique number
J.K., Nešetřil1989
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INT
CA
CIR
PC
CONV
STR
SEG
Determining the independence number - Interval filament graphs
IFAGavril 2000
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Interval filament graphs
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AA-mixed graphs
A A is a class of graphs.
G = (V,E) is AA-mixed if
E = E1 E2 and E2 is transitively oriented so that
xy E2 and yz E1 imply xz E1 , and
(V,E1) AA
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Mixed condition
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Thm (Gavril 2000): If WEIGHTED CLIQUE is polynomial in graphs from class A, A, then it is also polynomial in AA-mixed graphs.
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Thm (Gavril 2000): If WEIGHTED CLIQUE is polynomial in graphs from class A, A, then it is also polynomial in AA-mixed graphs.
Thm (Gavril 2000):
CO-IFA = (CO-INT)-mixed
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Thm (Gavril 2000): If WEIGHTED CLIQUE is polynomial in graphs from class A, A, then it is also polynomial in AA-mixed graphs.
Thm (Gavril 2000):
CO-IFA = (CO-INT)-mixedCorollary: WEIGHTED INDEPENDENT
SET is polynomial in IFA graphs
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Interval filament graphs
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INT
CA
CIR
PC
STR
INT
CA
CIR
PC
STR
Upper bound Lower bound
Gilmore, Hoffman 1964
Tucker 1970
Bouchet 1985
J.K. 1991Schaefer, Sedgwick, Štefankovič 2002
?
IFA IFA?
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6. Representations of Planar Graphs
Problem (Pollack 1990): Planar SEG ? Known: Planar CONV Koebe: Planar graphs are exactly contact graphs of disks. Corollary: Planar 2-STRING Problem (Fellows 1988): Planar 1-STRING ? De Fraysseix, de Mendez (1997): Planar graphs are contact
graphs of triangles De Fraysseix, de Mendez (1997): 3-colorable 4-connected
triangulations are intersection graphs of segments Noy et al. (1999): Planar triangle-free graphs are in SEG
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6. Representations of Co- Planar Graphs
J.K., Kuběna (1999): Co-Planar CONV Corollary: CLIQUE is NP-hard for CONV graphs Problem: Co-Planar SEG ?
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Thank youThank you
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6th International Czech-Slovak Symposium on
Combinatorics, Graph Theory, Algorithms and Applications
Prague, July 10-15, 2006
Honoring the 60th birthday of Jarik Nešetřil