online vertex colorings of random graphs without monochromatic subgraphs reto spöhel, eth zurich...
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Online Vertex Colorings of Random Graphs Without Monochromatic SubgraphsReto Spöhel, ETH ZurichJoint work with Martin Marciniszyn
Introduction
• Chromatic Number: Minimum number of colors needed to color vertices of a graph such that no two adjacent vertices have the same color.
• Generalization: Instead of monochromatic edges, forbid monochromatic copies of some other fixed graph F.
• Question: When are the vertices of a graph colorable with r colors without creating a monochromatic copy of some fixed graph F ?
• For random graphs: solved in full generality by Luczak, Rucinski, Voigt, 1992
F = K3, r = 2
Introduction
• ‚solved in full generality‘: Explicit threshold functionp0(F , r, n) such that
• In fact, p0(F , r, n) = p0(F , n), i.e., the threshold does not depend on the number of colors r (!)
• The threshold behaviour is even sharper than shown here.
• We transfer this result into an online setting, where the vertices of Gn, p have to be colored one by one, without seeing the entire graph.
Introduction: our results
• Explicit threshold functions p0(F , r, n) for online-colorability with r R 2 colors for a large class of forbidden graphs F , including cliques and cycles of arbitrary size.
• Unlike in the offline case, these thresholds
•depend on the number of colors r
•are coarse.
Introduction: related work
• Question first considered for the analogous online edge-coloring (‚Ramsey‘) problem•Friedgut, Kohayakawa, Rödl, Rucinski,
Tetali, 2003: F = K3, r = 2
•Marciniszyn, S., Steger, 2005+: F e.g. a clique or a cycle, r = 2
• Theory similar for edge- and vertex-colorings, but edge case is considerably more involved.
The online vertex-coloring game
• Rules:
• one player, called Painter
• random graph Gn, p , initially hidden
• vertices are revealed one by one along with induced edges
• vertices have to be instantly (‚online‘) colored with one of r R 2 available colors.
• game ends as soon as Painter closes a monochromatic copy of some fixed forbidden graph F.
• Question:
• How dense can the underlying random graph be such that Painter can color all vertices a.a.s.?
Example
F = K3, r = 2
Main result
• Theorem (Marciniszyn, S., 2006+)Let F be [a clique or a cycle of arbitrary size].
Then the threshold for the online vertex-coloring game with respect to F and with r R 2 available colors is
i.e.,
Bounds from ‚offline‘ graph properties
• Gn, p contains no copy of F
Painter wins with any strategy
• Gn, p allows no r-vertex-coloring avoiding F
Painter loses with any strategy
the thresholds of these two ‚offline‘ graph properties bound p0(n) from below and above.
Appearance of small subgraphs
• Theorem (Bollobás, 1981)Let F be a non-empty graph.The threshold for the graph property
‚Gn, p contains a copy of F‘
is
where
Appearance of small subgraphs
• m(F) is half of the average degree of the densest subgraph of F.
• For ‚nice‘ graphs – e.g. for cliques or cycles – we have
(such graphs are called balanced)
Vertex-colorings of random graphs
• Theorem (Luczak, Rucinski, Voigt, 1992)Let F be a graph and let r R 2.The threshold for the graph property
‚every r-vertex-coloring of Gn, p contains a monochromatic copy of F‘
is
where
Vertex-colorings of random graphs
• For ‚nice‘ graphs – e.g. for cliques or cycles – we have
(such graphs are called 1-balanced)
• . is also the threshold for the property
‚There are more than n copies of F in Gn, p ‘
• Intuition: For p [ p0 , the copies of F overlap in vertices, and coloring Gn, p becomes difficult.
• For arbitrary F and r we thus have
• Theorem Let F be [a clique or a cycle of arbitrary size].
Then the threshold for the online vertex-coloring game with respect to F and with r R 1 available colors is
• r = 1 Small Subgraphs
• r exponent tends to exponent for offline case
Main result revisited
Lower bound (r = 2)
• Let p(n)/p0(F, 2, n) be given. We need to show:
• There is a strategy which allows Painter to color all vertices of Gn, p a.a.s.
• We consider the greedy strategy: color all vertices red if feasible, blue otherwise.
• Proof strategy:• reduce the event that Painter fails to the
appearance of a certain dangerous graph F * in Gn, p .
• apply Small Subgraphs Theorem.
Lower bound (r = 2)
• Analysis of the greedy strategy:•color all vertices red if feasible, blue
otherwise.
after the losing move, Gn, p contains a blue copy of F, every vertex of which would close a red copy of F.
•For F = K4, e.g. or
Lower bound (r = 2)
Painter is safe if Gn, p contains no such ‚dangerous‘ graphs.
• LemmaAmong all dangerous graphs, F * is the one with minimal average degree, i.e., m(F *) % m(D) for all dangerous graphs D.
F *
D
Lower bound (r = 2)
• CorollaryLet F be a clique or a cycle of arbitrary size.Playing greedily, Painter a.a.s. wins the online vertex-coloring game w.r.t. F and with two available colors if
F *
Lower bound (r = 3)
• CorollaryLet F be a clique or a cycle of arbitrary size.Playing greedily, Painter a.a.s. wins the online vertex-coloring game w.r.t. F and with three available colors if
F 3*F *
Lower bound
• CorollaryLet F be a clique or a cycle of arbitrary size.Playing greedily, Painter a.a.s. wins the online vertex-coloring game w.r.t. F and with r R 2 available colors if
…
Upper bound
• Let p(n)[p0(F, r, n) be given. We need to show:
• The probability that Painter can color all vertices of Gn, p tends to 0 as n , regardless of her strategy.
• Proof strategy: two-round exposure & induction on r
•First round•n/2 vertices, Painter may see them all at once
•use known ‚offline‘ results
•Second round•remaining n/2 vertices
•Due to coloring of first round, for many vertices one color is excluded induction.
Upper bound
V1 V2
F °
1) Painter‘s offline-coloring of V1 creates many (w.l.o.g.) red copies of F °
2) Depending on the edges between V1 and V2, these copies induce a set Base(R) 4 V2 of vertices that cannot be colored red.
3) Edges between vertices of Base(R) are independent of 1) and 2)
Base(R) induces a binomial random graph
Base(R)
F
need to show: Base(R) is large enough for induction hypothesis to be applicable.
• There are a.a.s. many monochromatic copies of F‘° in V1 provided that
• work (Janson, Chernoff, ...) These induce enough vertices in (w.l.o.g.)
Base(R) such that the induction hypothesis is applicable to the binomial random graph induced by Base(R).
Upper bound
Generalization
• In general, it is smarter to greedily avoid a suitably chosen subgraph H of F instead of F itself.
general threshold function for game with r colors is
where
• Maximization over r possibly different subgraphs Hi F, corresponding to a „smart greedy“ strategy.
• Proved as a lower bound in full generality.
• Proved as an upper bound assuming
Thank you! Questions?
Similarly: online edge colorings
• Threshold is given by appearance of F*, yields threshold formula similarly to vertex case.
• Lower bound:
• Much harder to deal with overlapping outer copies!
• Works for arbitrary number of colors.
• Upper bound:
• Two-round exposure as in vertex case
• But: unclear how to setup an inductiveargument to deal with r ³ 3 colors.
F*
F_F°
?6
Online edge colorings
• Theorem (Marciniszyn, S., Steger, 2005+)Let F be a 2-balanced graph that is not a tree, for which at least one F_ satisfies
Then the threshold for the online edge-coloring game w.r.t. F and with two colors is
F *
F_
Online vertex colorings
• Theorem (Marciniszyn, S., 2006+)Let F be a 1-balanced graph for which at least one F ° satisfies
Then the threshold for the online vertex-coloring game w.r.t. F and with r R 1 colors is
F °
F *