Ramanujan Graphs of Every Degree

Ramanujan Graphs of Every Degree

Ramanujan Graphs of Every Degree Adam Marcus (Crisply, Yale) Daniel Spielman (Yale) Nikhil Srivastava (MSR India) Expander Graphs Sparse, regular well-connected graphs with many properties of random graphs. Random walks mix quickly. Every set of vertices has many neighbors. Pseudo-random generators. Error-correcting codes. Sparse approximations of complete graphs. Spectral Expanders Let G be a graph and A be its adjacency matrix a 0 1 0 0 1 b 1 0 1 0 1 e 0 1 0 1 0 c 0 0 1 0 1 1 1 0 1 0 d Eigenvalues λ1 λ2 λn “trivial” ≥ ≥ ···≥ If d-regular (every vertex has d edges), λ1 = d Spectral Expanders If bipartite (all edges between two parts/colors) eigenvalues are symmetric about 0 If d-regular and bipartite, λ = d n − “trivial” a b 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 0 1 1 c d 1 1 0 0 0 0 0 1 1 0 0 0 e f 1 0 1 0 0 0 Spectral Expanders G is a good spectral expander if all non-trivial eigenvalues are small [ ] -d 0 d Bipartite Complete Graph Adjacency matrix has rank 2, so all non-trivial eigenvalues are 0 a b 0 0 0 1 1 1 0 0 0 1 1 1 0 0 0 1 1 1 c d 1 1 1 0 0 0 1 1 1 0 0 0 e f 1 1 1 0 0 0 Spectral Expanders G is a good spectral expander if all non-trivial eigenvalues are small [ ] -d 0 d Challenge: construct infinite families of fixed degree Spectral Expanders G is a good spectral expander if all non-trivial eigenvalues are small [ ] ( 0 ) -d 2pd 1 2pd 1 d − − − Challenge: construct infinite families of fixed degree Alon-Boppana ‘86: Cannot beat 2pd 1 − Ramanujan Graphs: 2pd 1 − G is a Ramanujan Graph if absolute value of non-trivial eigs 2pd 1 − [ ] ( 0 ) -d 2pd 1 2pd 1 d − − − Ramanujan Graphs: 2pd 1 − G is a Ramanujan Graph if absolute value of non-trivial eigs 2pd 1 − [ ] ( 0 ) -d 2pd 1 2pd 1 d − − − Margulis, Lubotzky-Phillips-Sarnak’88: Infinite sequences of Ramanujan graphs exist for d =prime+1 Ramanujan Graphs: 2pd 1 − G is a Ramanujan Graph if absolute value of non-trivial eigs 2pd 1 − [ ] ( 0 ) -d 2pd 1 2pd 1 d − − − Friedman’08: A random d-regular graph is almost Ramanujan : 2pd 1+✏ − Ramanujan Graphs of Every Degree Theorem: there are infinite families of bipartite Ramanujan graphs of every degree. Ramanujan Graphs of Every Degree Theorem: there are infinite families of bipartite Ramanujan graphs of every degree. And, are infinite families of (c,d)-biregular Ramanujan graphs, having non-trivial eigs bounded by pd 1+pc 1 − − Bilu-Linial ‘06 Approach Find an operation that doubles the size of a graph without creating large eigenvalues. [ ( ) ] 2pd 1 0 2pd 1 -d − − − d Bilu-Linial ‘06 Approach Find an operation that doubles the size of a graph without creating large eigenvalues. [ ( ) ] 2pd 1 0 2pd 1 -d − − − d 2-lifts of graphs a b e c d 2-lifts of graphs a a b b e e c c d d duplicate every vertex 2-lifts of graphs a0 a1 1 b0 b e0 e1 c0 c1 1 d0 d duplicate every vertex 2-lifts of graphs a0 a1 1 b0 b e0 e1 c0 c1 1 d0 d for every pair of edges: leave on either side (parallel), or make both cross 2-lifts of graphs a0 a1 1 b0 b e0 e1 c0 c1 1 d0 d for every pair of edges: leave on either side (parallel), or make both cross 2-lifts of graphs 0 1 0 0 1 1 0 1 0 1 0 1 0 1 0 0 0 1 0 1 1 1 0 1 0 2-lifts of graphs 0 1 0 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1 0 1 0 2-lifts of graphs 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 1 0 Eigenvalues of 2-lifts (Bilu-Linial) Given a 2-lift of G, create a signed adjacency matrix As with a -1 for crossing edges and a 1 for parallel edges 1 a0 a 0 -1 0 0 1 1 b0 b -1 0 1 0 1 1 0 1 0 -1 0 e0 e 1 0 0 -1 0 1 c0 c 1 1 0 1 0 1 d0 d Eigenvalues of 2-lifts (Bilu-Linial) Theorem: The eigenvalues of the 2-lift are the union of the eigenvalues of A (old) and the eigenvalues of As (new) 1 a0 a 0 -1 0 0 1 1 b0 b -1 0 1 0 1 1 0 1 0 -1 0 e0 e 1 0 0 -1 0 1 c0 c 1 1 0 1 0 1 d0 d Eigenvalues of 2-lifts (Bilu-Linial) Theorem: The eigenvalues of the 2-lift are the union of the eigenvalues of A (old) and the eigenvalues of As (new) Conjecture: Every d-regular graph has a 2-lift in which all the new eigenvalues have absolute value at most 2pd 1 − Eigenvalues of 2-lifts (Bilu-Linial) Conjecture: Every d-regular graph has a 2-lift in which all the new eigenvalues have absolute value at most 2pd 1 − Would give infinite families of Ramanujan Graphs: start with the complete graph, and keep lifting. Eigenvalues of 2-lifts (Bilu-Linial) Conjecture: Every d-regular graph has a 2-lift in which all the new eigenvalues have absolute value at most 2pd 1 − We prove this in the bipartite case. a 2-lift of a bipartite graph is bipartite Eigenvalues of 2-lifts (Bilu-Linial) Theorem: Every d-regular graph has a 2-lift in which all the new eigenvalues have absolute value at most 2pd 1 − Trick: eigenvalues of bipartite graphs are symmetric about 0, so only need to bound largest Eigenvalues of 2-lifts (Bilu-Linial) Theorem: Every d-regular bipartite graph has a 2-lift in which all the new eigenvalues have absolute value at most 2pd 1 − First idea: a random 2-lift m Specify a lift by s 1 2 {± } Pick s uniformly at random First idea: a random 2-lift m Specify a lift by s 1 2 {± } Pick s uniformly at random Are graphs for which this usually fails First idea: a random 2-lift m Specify a lift by s 1 2 {± } Pick s uniformly at random Are graphs for which this usually fails Bilu and Linial proved G almost Ramanujan, implies new eigenvalues usually small. Improved by Puder and Agarwal-Kolla-Madan The expected polynomial Consider E [ χAs (x)] s The expected polynomial Consider E [ χAs (x)] s p Prove max-root E [ χAs (x)] 2 d 1 s − ⇣ ⌘ Prove χ A s ( x ) is an interlacing family Conclude there is an s so that max-root (χ (x)) 2pd 1 As − The expected polynomial Theorem (Godsil-Gutman ‘81): E [ χAs (x)]=µG(x) s the matching polynomial of G The matching polynomial (Heilmann-Lieb ‘72) n 2i i µ (x)= x − ( 1) m G − i i 0 X≥ mi = the number of matchings with i edges µ (x)=x6 7x4 + 11x2 2 G − − µ (x)=x6 7x4 + 11x2 2 G − − one matching with 0 edges µ (x)=x6 7x4 + 11x2 2 G − − 7 matchings with 1 edge µ (x)=x6 7x4 + 11x2 2 G − − µ (x)=x6 7x4 + 11x2 2 G − − Proof that E [ χAs (x)]=µG(x) s Expand E [det( xI A s )] using permutations s − x ±1 0 0 ±1 ±1! ±1 x ±1 0 0 0! 0 ±1 x ±1 0 0! 0 0 ±1 x ±1 0! ±1 0 0 ±1 x ±1! ±1 0 0 0 ±1 x! Proof that E [ χAs (x)]=µG(x) s Expand E [det( xI A s )] using permutations s − same edge: x ±1 0 0 ±1 ±1! same value ±1 x ±1 0 0 0! 0 ±1 x ±1 0 0! 0 0 ±1 x ±1 0! ±1 0 0 ±1 x ±1! ±1 0 0 0 ±1 x! Proof that E [ χAs (x)]=µG(x) s Expand E [det( xI A s )] using permutations s − same edge: x ±1 0 0 ±1 ±1! same value ±1 x ±1 0 0 0! 0 ±1 x ±1 0 0! 0 0 ±1 x ±1 0! ±1 0 0 ±1 x ±1! ±1 0 0 0 ±1 x! Proof that E [ χAs (x)]=µG(x) s Expand E [det( xI A s )] using permutations s − x ±1 0 0 ±1 ±1! ±1 x ±1 0 0 0! 0 ±1 x ±1 0 0! 0 0 ±1 x ±1 0! ±1 0 0 ±1 x ±1! ±1 0 0 0 ±1 x! Get 0 if hit any 0s Proof that E [ χAs (x)]=µG(x) s Expand E [det( xI A s )] using permutations s − x ±1 0 0 ±1 ±1! ±1 x ±1 0 0 0! 0 ±1 x ±1 0 0! 0 0 ±1 x ±1 0! ±1 0 0 ±1 x ±1! ±1 0 0 0 ±1 x! Get 0 if take just one entry for any edge Proof that E [ χAs (x)]=µG(x) s Expand E [det( xI A s )] using permutations s − x ±1 0 0 ±1 ±1! ±1 x ±1 0 0 0! 0 ±1 x ±1 0 0! 0 0 ±1 x ±1 0! ±1 0 0 ±1 x ±1! ±1 0 0 0 ±1 x! Only permutations that count are involutions Proof that E [ χAs (x)]=µG(x) s Expand E [det( xI A s )] using permutations s − x ±1 0 0 ±1 ±1! ±1 x ±1 0 0 0! 0 ±1 x ±1 0 0! 0 0 ±1 x ±1 0! ±1 0 0 ±1 x ±1! ±1 0 0 0 ±1 x! Only permutations that count are involutions Proof that E [ χAs (x)]=µG(x) s Expand E [det( xI A s )] using permutations s − x ±1 0 0 ±1 ±1! ±1 x ±1 0 0 0! 0 ±1 x ±1 0 0! 0 0 ±1 x ±1 0! ±1 0 0 ±1 x ±1! ±1 0 0 0 ±1 x! Only permutations that count are involutions Correspond to matchings The matching polynomial (Heilmann-Lieb ‘72) n 2i i µ (x)= x − ( 1) m G − i i 0 X≥ Theorem (Heilmann-Lieb) all the roots are real The matching polynomial (Heilmann-Lieb ‘72) n 2i i µ (x)= x − ( 1) m G − i i 0 X≥ Theorem (Heilmann-Lieb) all the roots are real and have absolute value at most 2pd 1 − The matching polynomial (Heilmann-Lieb ‘72) n 2i i µ (x)= x − ( 1) m G − i i 0 X≥ Theorem (Heilmann-Lieb) all the roots are real and have absolute value at most 2pd 1 − p Implies max-root E [ χAs (x)] 2 d 1 s − ⇣ ⌘ Interlacing p(x)= d (x ↵ ) Polynomial i=1 − i d 1 interlaces q(x)=Q − (x βi) i=1 − Q if ↵1 β1 ↵2 ↵d 1 βd 1 ↵d ··· − − Common Interlacing p1 ( x ) and p 2 ( x ) have a common interlacing if can partition the line into intervals so that each interval contains one root from each poly β βd 1 2 − β1 β3 Common Interlacing p1 ( x ) and p 2 ( x ) have a common interlacing if can partition the line into intervals so that each interval contains one root from each poly β βd 1 ) ( ) 2( ) ( ) −( β1 β3 Common Interlacing If p1 and p2 have a common interlacing, max-root (pi) max-root (Ei [ pi ]) for some i.

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