On Aharoni-Bergers conjecture of rainbow matchings Jane Gao Monash - - PowerPoint PPT Presentation

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On Aharoni-Bergers conjecture of rainbow matchings Jane Gao Monash - - PowerPoint PPT Presentation

On Aharoni-Bergers conjecture of rainbow matchings Jane Gao Monash University Discrete Mathematics Seminar 2018 Joint work with Reshma Ramadurai, Ian Wanless and Nick Wormald Discrete Mathematics Seminar 2018 Joint work Jane Gao Monash


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On Aharoni-Berger’s conjecture of rainbow matchings

Jane Gao Monash University Discrete Mathematics Seminar 2018 Joint work with Reshma Ramadurai, Ian Wanless and Nick Wormald

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Ryser-Brualdi-Stein Conjecture

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Ryser-Brualdi-Stein Conjecture

Conjecture (Ryser-Brualdi-Stein)

An n × n Latin square contains a partial transversal of size n − 1. If n is

  • dd, there exists a full transversal.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Aharoni-Berger Conjecture

Conjecture (Ryser-Brualdi-Stein)

An n × n Latin square contains a partial transversal of size n − 1. If n is

  • dd, there exists a full transversal.

A stronger version:

Conjecture (Aharoni-Berger 09)

If G is a bipartite multigraph as the union of n − 1 matchings in G, each

  • f size n. Then G contains a full rainbow matching.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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The general graph case

Conjecture (Aharoni, Berger, Chudnovsky, Howard and Seymour 16)

If G is a general graph as the union of n − 2 matchings each of size n, then G contains a full rainbow matching.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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A trivial lower bound

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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State of art

Partial transversal in Latin square:

(2n + 1)/3 – Koksma (1969); (3/4)n – Drake (1977); n − √n – Brouwer et al. (1978) and independently by Woolbright (1978.) n − O(log2 n) – Shor (1982).

Full rainbow matching in bipartite (multi)graphs.

n − o(n) (Latin rectangle) – Haggkvist and Johansson (2008). (4/7)n – Aharoni Charbit and Howard (2015). (3/5)n – Kotlar and Ziv (2014). (2/3)n + o(n) – Clemens and Ehrenm¨ uller (2016). (2n − 1)/3 – Aharoni, Kotlar and Ziv (arXiv). n − o(n) – Pokrovskiy (arXiv).

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Our results

Theorem (G., Ramadurai, Wanless, Wormald 2017+)

If G is a general graph and |M| ≤ n − nc, where c > 9/10. Then M contains a full rainbow matching.

Theorem (G., Ramadurai, Wanless, Wormald 2017+)

Larger |M| if ∆(G) is smaller than n. Multigraph G with low multiplicity. Hypergraphs where no two vertices are contained in too many hyperedges. Keevash and Yepremyan (2017) — If G is an n-edge-coloured multigraph with low multiplicity, and each colour class contains (1 + ǫ)n edges, then there is a partial rainbow matching of size n − O(1).

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Our results

Theorem (G., Ramadurai, Wanless, Wormald 2017+)

If G is a general graph and |M| ≤ n − nc, where c > 9/10. Then M contains a full rainbow matching.

Theorem (G., Ramadurai, Wanless, Wormald 2017+)

Larger |M| if ∆(G) is smaller than n. Multigraph G with low multiplicity. Hypergraphs where no two vertices are contained in too many hyperedges. Keevash and Yepremyan (2017) — If G is an n-edge-coloured multigraph with low multiplicity, and each colour class contains (1 + ǫ)n edges, then there is a partial rainbow matching of size n − O(1).

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Our results

Theorem (G., Ramadurai, Wanless, Wormald 2017+)

If G is a general graph and |M| ≤ n − nc, where c > 9/10. Then M contains a full rainbow matching.

Theorem (G., Ramadurai, Wanless, Wormald 2017+)

Larger |M| if ∆(G) is smaller than n. Multigraph G with low multiplicity. Hypergraphs where no two vertices are contained in too many hyperedges. Keevash and Yepremyan (2017) — If G is an n-edge-coloured multigraph with low multiplicity, and each colour class contains (1 + ǫ)n edges, then there is a partial rainbow matching of size n − O(1).

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Randomised algorithm and the DE method

Intuitively... Take a surviving matching x, take a random edge in x and put it to the rainbow matching; Modify the remaining graph; Repeat. A randomised algorithm induces a sequence of random variables Z0, Z1, Z2, . . ..

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Randomised algorithm and the DE method

Intuitively... Take a surviving matching x, take a random edge in x and put it to the rainbow matching; Modify the remaining graph; Repeat. A randomised algorithm induces a sequence of random variables Z0, Z1, Z2, . . ..

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Randomised algorithm and the DE method

Intuitively... Take a surviving matching x, take a random edge in x and put it to the rainbow matching; Modify the remaining graph; Repeat. A randomised algorithm induces a sequence of random variables Z0, Z1, Z2, . . ..

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Randomised algorithm and the DE method

Intuitively... Take a surviving matching x, take a random edge in x and put it to the rainbow matching; Modify the remaining graph; Repeat. A randomised algorithm induces a sequence of random variables Z0, Z1, Z2, . . ..

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Randomised algorithm and the DE method

Intuitively... Take a surviving matching x, take a random edge in x and put it to the rainbow matching; Modify the remaining graph; Repeat. A randomised algorithm induces a sequence of random variables Z0, Z1, Z2, . . ..

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Randomised algorithm and the DE method

Suppose E(Zt+1 − Zt | history) = f (Zt/n) + small error. Then if we know a priori that Zt/n ≈ z(x) where x = t/n then dz dx = f (x). The DE method guarantees that Zt = z(t/n)n + small error, provided Z0 lies inside a “nice” open set; f is “nice” in that open set; |Zt+1 − Zt| is not too big.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Randomised algorithm and the DE method

Suppose E(Zt+1 − Zt | history) = f (Zt/n) + small error. Then if we know a priori that Zt/n ≈ z(x) where x = t/n then dz dx = f (x). The DE method guarantees that Zt = z(t/n)n + small error, provided Z0 lies inside a “nice” open set; f is “nice” in that open set; |Zt+1 − Zt| is not too big.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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DE method hard to apply for the rainbow matching problem

Suppose E(Zt+1 − Zt | history) = f (Zt/n) + small error, Overlap of Mi and Mj (|V (Mi) ∩ V (Mj)|) may be non-uniformly initially; The overlaps change in the process.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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DE method hard to apply for the rainbow matching problem

Suppose E(Zt+1 − Zt | history) = f (Zt/n) + small error, Overlap of Mi and Mj (|V (Mi) ∩ V (Mj)|) may be non-uniformly initially; The overlaps change in the process.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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DE method hard to apply for the rainbow matching problem

Suppose E(Zt+1 − Zt | history) = f (Zt/n) + small error, Overlap of Mi and Mj (|V (Mi) ∩ V (Mj)|) may be non-uniformly initially; The overlaps change in the process.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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  • dl nibble

Randomly partition matchings in M into chunks, each chunk containing ǫn matchings. In iteration i, matchings in chunk i are processed. In iteration i, For every matching in chunk i, randomly pick an edge x; “Artificially zap” each remaining vertex with a proper probability; Deal with vertex collisions.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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  • dl nibble

Randomly partition matchings in M into chunks, each chunk containing ǫn matchings. In iteration i, matchings in chunk i are processed. In iteration i, For every matching in chunk i, randomly pick an edge x; “Artificially zap” each remaining vertex with a proper probability; Deal with vertex collisions.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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  • dl nibble

Randomly partition matchings in M into chunks, each chunk containing ǫn matchings. In iteration i, matchings in chunk i are processed. In iteration i, For every matching in chunk i, randomly pick an edge x; “Artificially zap” each remaining vertex with a proper probability; Deal with vertex collisions.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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  • dl nibble

Randomly partition matchings in M into chunks, each chunk containing ǫn matchings. In iteration i, matchings in chunk i are processed. In iteration i, For every matching in chunk i, randomly pick an edge x; “Artificially zap” each remaining vertex with a proper probability; Deal with vertex collisions.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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A randomised algorithm

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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A randomised algorithm

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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A randomised algorithm

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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A randomised algorithm

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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A randomised algorithm

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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A randomised algorithm

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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A randomised algorithm

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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A randomised algorithm

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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A randomised algorithm

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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A randomised algorithm

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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How to zap vertices?

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Matching size and vertex degree

Every vertex is deleted with equal probability ➾ every surviving matchings are of approximately equal size

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Matching size and vertex degree

Every vertex is deleted with equal probability ➾ every surviving matchings are of approximately equal size |M(i)| ≈ r(xi)n

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Matching size and vertex degree

Every vertex is deleted with equal probability ➾ every surviving matchings are of approximately equal size |M(i)| ≈ r(xi)n degrees of each vertex decrease with approximately equal rate

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Matching size and vertex degree

Every vertex is deleted with equal probability ➾ every surviving matchings are of approximately equal size |M(i)| ≈ r(xi)n degrees of each vertex decrease with approximately equal rate d(j)

v (i) ≈ ǫdvg(xi)

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Matching size and vertex degree

Every vertex is deleted with equal probability ➾ every surviving matchings are of approximately equal size |M(i)| ≈ r(xi)n degrees of each vertex decrease with approximately equal rate d(j)

v (i) ≈ ǫdvg(xi)

here xi = iǫ.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Matching size and vertex degree

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Probability of vertex deletion

d(j)

v (i − 1)

≈ ǫg(xi−1)dv ≤ ǫg(xi−1)n |M(i − 1)| ≈ r(xi−1)n ➾ Every vertex is deleted with probability roughly maxv{d(j)

v (i − 1)}

|M(i − 1)| ≤ ǫg(xi−1) r(xi−1) = f (xi−1).

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Probability of vertex deletion

d(j)

v (i − 1)

≈ ǫg(xi−1)dv ≤ ǫg(xi−1)n |M(i − 1)| ≈ r(xi−1)n ➾ Every vertex is deleted with probability roughly maxv{d(j)

v (i − 1)}

|M(i − 1)| ≤ ǫg(xi−1) r(xi−1) = f (xi−1).

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Deducing the ODEs

E(|M(i)| − |M(i − 1)|) ≈ −2f (xi−1)|M(i − 1)|; E(dj

v(i) − dj v(i − 1))

≈ −f (xi−1)dj

v(i − 1).

Recall f (xi−1) = ǫg(xi−1) r(xi−1) |M(i − 1)| ≈ r(xi−1)n dj

v(i − 1)

≈ ǫg(xi−1). ➾ r′(x) = −2g(x); g′(x) = −g(x)2 r(x) .

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Deducing the ODEs

E(|M(i)| − |M(i − 1)|) ≈ −2f (xi−1)|M(i − 1)|; E(dj

v(i) − dj v(i − 1))

≈ −f (xi−1)dj

v(i − 1).

Recall f (xi−1) = ǫg(xi−1) r(xi−1) |M(i − 1)| ≈ r(xi−1)n dj

v(i − 1)

≈ ǫg(xi−1). ➾ r′(x) = −2g(x); g′(x) = −g(x)2 r(x) .

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Deducing the ODEs

E(|M(i)| − |M(i − 1)|) ≈ −2f (xi−1)|M(i − 1)|; E(dj

v(i) − dj v(i − 1))

≈ −f (xi−1)dj

v(i − 1).

Recall f (xi−1) = ǫg(xi−1) r(xi−1) |M(i − 1)| ≈ r(xi−1)n dj

v(i − 1)

≈ ǫg(xi−1). ➾ r′(x) = −2g(x); g′(x) = −g(x)2 r(x) .

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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ODE solution

The solution to the ODE with r(0) = 1 and g(0) = 1 is r(x) = (1 − x)2, g(x) = 1 − x. Thus r(x) > 0 for all x < 1. Let τ − 1 ≈ (1 − ǫ0)/ǫ be the second last iteration of the algorithm. If |M(i)| ≈ r(xi)n for every i, then |M(τ − 1)| ≈ r(1 − ǫ0)n = ǫ2

0n.

If ǫ2

0n ≥ (2+?)ǫn then we can process the last chunk of matchings greedily.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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ODE solution

The solution to the ODE with r(0) = 1 and g(0) = 1 is r(x) = (1 − x)2, g(x) = 1 − x. Thus r(x) > 0 for all x < 1. Let τ − 1 ≈ (1 − ǫ0)/ǫ be the second last iteration of the algorithm. If |M(i)| ≈ r(xi)n for every i, then |M(τ − 1)| ≈ r(1 − ǫ0)n = ǫ2

0n.

If ǫ2

0n ≥ (2+?)ǫn then we can process the last chunk of matchings greedily.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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ODE solution

The solution to the ODE with r(0) = 1 and g(0) = 1 is r(x) = (1 − x)2, g(x) = 1 − x. Thus r(x) > 0 for all x < 1. Let τ − 1 ≈ (1 − ǫ0)/ǫ be the second last iteration of the algorithm. If |M(i)| ≈ r(xi)n for every i, then |M(τ − 1)| ≈ r(1 − ǫ0)n = ǫ2

0n.

If ǫ2

0n ≥ (2+?)ǫn then we can process the last chunk of matchings greedily.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Proof sketch

Next we sketch a proof for the following simpler version.

Theorem

For any ǫ0 > 0 there exists N0 > 0 such that the following holds. If G is a simple graph and |M| ≤ (1 − ǫ0)n where n ≥ N0, then M contains a full rainbow matching.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Proof sketch

Let ǫ > 0 be sufficiently small so that ǫ2

0 ≥ 3ǫ. The matchings are then

partitioned into (1 − ǫ0)/ǫ chunks. We will specify ai, bi such that ai = O(ǫn), bi = O(ǫ2n) and for iteration i (0 ≤ i ≤ ((1 − ǫ0)/ǫ)), with high probability, (A1) |M(i)| is between (1 − iǫ)2n − ai and (1 − iǫ)2n + ai; (A2) d(j)

v (i) is at most ǫ(1 − iǫ)n + bi.

If (A1) and (A2) holds for every step, then by the beginning of the last iteration, |M| = ǫ2

0n + O(ǫn) ≥ 2ǫn,

and there are at most ǫn matchings left. We can process the last chunk greedily.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Proof sketch

Let ǫ > 0 be sufficiently small so that ǫ2

0 ≥ 3ǫ. The matchings are then

partitioned into (1 − ǫ0)/ǫ chunks. We will specify ai, bi such that ai = O(ǫn), bi = O(ǫ2n) and for iteration i (0 ≤ i ≤ ((1 − ǫ0)/ǫ)), with high probability, (A1) |M(i)| is between (1 − iǫ)2n − ai and (1 − iǫ)2n + ai; (A2) d(j)

v (i) is at most ǫ(1 − iǫ)n + bi.

If (A1) and (A2) holds for every step, then by the beginning of the last iteration, |M| = ǫ2

0n + O(ǫn) ≥ 2ǫn,

and there are at most ǫn matchings left. We can process the last chunk greedily.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Proof sketch

Let ǫ > 0 be sufficiently small so that ǫ2

0 ≥ 3ǫ. The matchings are then

partitioned into (1 − ǫ0)/ǫ chunks. We will specify ai, bi such that ai = O(ǫn), bi = O(ǫ2n) and for iteration i (0 ≤ i ≤ ((1 − ǫ0)/ǫ)), with high probability, (A1) |M(i)| is between (1 − iǫ)2n − ai and (1 − iǫ)2n + ai; (A2) d(j)

v (i) is at most ǫ(1 − iǫ)n + bi.

If (A1) and (A2) holds for every step, then by the beginning of the last iteration, |M| = ǫ2

0n + O(ǫn) ≥ 2ǫn,

and there are at most ǫn matchings left. We can process the last chunk greedily.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Proof sketch

Base case i = 0: |M(0)| = n for all M. ➾ (A1)✔ dv(0) = ǫn + O(√n log n) (standard concentration) ➾ (A2) with b0 = O(√n log n) ✔

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Proof sketch

Base case i = 0: |M(0)| = n for all M. ➾ (A1)✔ dv(0) = ǫn + O(√n log n) (standard concentration) ➾ (A2) with b0 = O(√n log n) ✔

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Proof sketch

Base case i = 0: |M(0)| = n for all M. ➾ (A1)✔ dv(0) = ǫn + O(√n log n) (standard concentration) ➾ (A2) with b0 = O(√n log n) ✔

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Proof sketch

Inductive step i + 1: Zap vertices so that every vertex is deleted with probability ǫg(xi)n + bi r(xi)n − ai = ǫ 1 − iǫ + O ǫai r(xi)n + bi r(xi)n

  • .

Then, with high probability dv(i + 1) ≤ dv(i) − ǫg(xi)n r(xi)n dv(i) + O(√n log n) ≤ (ǫ(1 − iǫ)n+bi)

  • 1 −

ǫ 1 − iǫ

  • + O(√n log n)

≤ ǫ(1 − (i + 1)ǫ)n + bi + O(√n log n) ➾ (A2) for iteration i + 1 with bi+1 = bi + K(√n log n). ✔ ➾ bi = O((1/ǫ)√n log n) for all 0 ≤ i ≤ τ. ✔

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Proof sketch

Inductive step i + 1: Zap vertices so that every vertex is deleted with probability ǫg(xi)n + bi r(xi)n − ai = ǫ 1 − iǫ + O ǫai r(xi)n + bi r(xi)n

  • .

Then, with high probability dv(i + 1) ≤ dv(i) − ǫg(xi)n r(xi)n dv(i) + O(√n log n) ≤ (ǫ(1 − iǫ)n+bi)

  • 1 −

ǫ 1 − iǫ

  • + O(√n log n)

≤ ǫ(1 − (i + 1)ǫ)n + bi + O(√n log n) ➾ (A2) for iteration i + 1 with bi+1 = bi + K(√n log n). ✔ ➾ bi = O((1/ǫ)√n log n) for all 0 ≤ i ≤ τ. ✔

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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Proof sketch

Inductive step i + 1: Zap vertices so that every vertex is deleted with probability ǫg(xi)n + bi r(xi)n − ai = ǫ 1 − iǫ + O ǫai r(xi)n + bi r(xi)n

  • .

Then, with high probability dv(i + 1) ≤ dv(i) − ǫg(xi)n r(xi)n dv(i) + O(√n log n) ≤ (ǫ(1 − iǫ)n+bi)

  • 1 −

ǫ 1 − iǫ

  • + O(√n log n)

≤ ǫ(1 − (i + 1)ǫ)n + bi + O(√n log n) ➾ (A2) for iteration i + 1 with bi+1 = bi + K(√n log n). ✔ ➾ bi = O((1/ǫ)√n log n) for all 0 ≤ i ≤ τ. ✔

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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SLIDE 60

Proof sketch

Inductive step i + 1: Zap vertices so that every vertex is deleted with probability ǫg(xi)n + bi r(xi)n − ai = ǫ 1 − iǫ + O ǫai r(xi)n + bi r(xi)n

  • .

Then, with high probability dv(i + 1) ≤ dv(i) − ǫg(xi)n r(xi)n dv(i) + O(√n log n) ≤ (ǫ(1 − iǫ)n+bi)

  • 1 −

ǫ 1 − iǫ

  • + O(√n log n)

≤ ǫ(1 − (i + 1)ǫ)n + bi + O(√n log n) ➾ (A2) for iteration i + 1 with bi+1 = bi + K(√n log n). ✔ ➾ bi = O((1/ǫ)√n log n) for all 0 ≤ i ≤ τ. ✔

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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SLIDE 61

Proof sketch

Inductive step i + 1: Zap vertices so that every vertex is deleted with probability ǫg(xi)n + bi r(xi)n − ai = ǫ 1 − iǫ + O ǫai r(xi)n + bi r(xi)n

  • .

Then, with high probability dv(i + 1) ≤ dv(i) − ǫg(xi)n r(xi)n dv(i) + O(√n log n) ≤ (ǫ(1 − iǫ)n+bi)

  • 1 −

ǫ 1 − iǫ

  • + O(√n log n)

≤ ǫ(1 − (i + 1)ǫ)n + bi + O(√n log n) ➾ (A2) for iteration i + 1 with bi+1 = bi + K(√n log n). ✔ ➾ bi = O((1/ǫ)√n log n) for all 0 ≤ i ≤ τ. ✔

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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SLIDE 62

Proof sketch

With high probability |M(i + 1)| = |M(i)| −

1 − iǫ + O ǫai r(xi)n + bi r(xi)n

  • |M(i)|

+O(√n log n + ǫ2n)

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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SLIDE 63

Proof sketch

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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SLIDE 64

Proof sketch

With high probability |M(i + 1)| = |M(i)| −

1 − iǫ + O ǫai r(xi)n + bi r(xi)n

  • |M(i)|

+O(√n log n + ǫ2n) = (1 − (i + 1)ǫ)2n ± ai + O(ǫai + bi + ǫ2n). ➾ (A1) for iteration i + 1 with ai+1 = (1 + Kǫ)ai + Kǫ2n. ✔ 1/ǫ iterations ➾ ai ≤ (1/ǫ)(1 + Kǫ)1/ǫKǫ2n = O(ǫn). ✔

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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SLIDE 65

Proof sketch

With high probability |M(i + 1)| = |M(i)| −

1 − iǫ + O ǫai r(xi)n + bi r(xi)n

  • |M(i)|

+O(√n log n + ǫ2n) = (1 − (i + 1)ǫ)2n ± ai + O(ǫai + bi + ǫ2n). ➾ (A1) for iteration i + 1 with ai+1 = (1 + Kǫ)ai + Kǫ2n. ✔ 1/ǫ iterations ➾ ai ≤ (1/ǫ)(1 + Kǫ)1/ǫKǫ2n = O(ǫn). ✔

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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SLIDE 66

Proof sketch

With high probability |M(i + 1)| = |M(i)| −

1 − iǫ + O ǫai r(xi)n + bi r(xi)n

  • |M(i)|

+O(√n log n + ǫ2n) = (1 − (i + 1)ǫ)2n ± ai + O(ǫai + bi + ǫ2n). ➾ (A1) for iteration i + 1 with ai+1 = (1 + Kǫ)ai + Kǫ2n. ✔ 1/ǫ iterations ➾ ai ≤ (1/ǫ)(1 + Kǫ)1/ǫKǫ2n = O(ǫn). ✔

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36

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SLIDE 67

Future directions

How to cope with multigraphs? Transversal in high dimensional Latin cubes.

Jane Gao Monash University On Aharoni-Berger’s conjecture of rainbow matchings Discrete Mathematics Seminar 2018 Joint work / 36