Undirected ST-Connectivity In Log Space

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Undirected ST- Connectivity In Log Space Omer Reingold Slides by Sharon Bruckner

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Undirected ST-Connectivity In Log Space. Omer Reingold Slides by Sharon Bruckner. Today. Some history What are we adding to the mix? Connectivity in expanders Making expanders: powering it up and cutting it down Putting it together in Log-Space In conclusion. Some History. - PowerPoint PPT Presentation

Transcript of Undirected ST-Connectivity In Log Space

Page 1: Undirected ST-Connectivity In Log Space

Undirected ST-Connectivity In Log Space

Omer ReingoldSlides by Sharon Bruckner

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Today

• Some history

• What are we adding to the mix?– Connectivity in expanders– Making expanders: powering it up and

cutting it down– Putting it together in Log-Space

• In conclusion

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Some History

• What is ST-Connectivity?

• What do we know about it?

• What are we trying to accomplish?

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What is ST-Connectivity?

• Given a graph G and two vertices s and t:– Answer YES if there is a path from s to t

in G.– Answer NO if there is no such path

• Two flavors to the problem:– STCON where G is a directed graph– USTCON where G is undirected.

• Today we’ll talk about USTCON

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What do we know about it?• Solved easily with BFS

– But – polynomial space!

• USTCON is in NL (=NSPACE(log))– Just guess the path

• USTCON is in DSPACE(log2n) (Savitch)– If there’s a path from s to t, then exists z

such that there is a path from s to z and from z to t…

• USTCON is in RL– Random walk– Randomness is a resource!

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What are we trying to accomplish?

We would like an algorithm for USTCON which is deterministic and works in space logarithmic in the size of the graph

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What are we adding to the mix?

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Useful Notations

• The adjacency matrix of a graph G is a matrix with 1 in the (i,j) element if vertices i and j are connected, 0 otherwise.

• If the graph is D-regular, the sum of each row is equal.

• We will use the normalized adjancecy matrix, where we divide each value by D.

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Useful Notations

• The normalized adjacency matrix M is a stochastic matrix, and serves as the “random walk” matrix.

• The largest eigenvalue of M is 1, with the vector (1,1,1…,1)єRn

• Let G’s 2nd largest eigenvalue be λ(G).• A (N,D,λ) graph is a D regular graph

over N vertices with λ(G) <= λ

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Connectivity in Expanders

What would happen if each connected component of our graph was an expander?

We could decide USTCON in logspace!

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Expanders – a Reminder

Two equivalent definitions of expander• G = (N,D, λ) is an expander iff the

spectral gap 1- λ > 0• G = (N,D, λ) is an expander if there

exists ε>0 such that for any set S of at most half the vertices in G, at least (1+ ε)|S| vertices of G are connected to some vertex in S

Note that the adjacency matrix in this case in

normalized!

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Every expander has a O(log(N)) diameter

Theorem:For any s and t in an expander, there’s

a path from s to t of length O(log(N))

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Proof

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Logspace Algorithm for paths in an expander

For a (N,D, λ) expander there is a a space O(logD*logN) algorithm which decided USTCON for any s and t

Idea:From any vertex s there are Dl=O(logN) different paths. Simply enumerate them all and see if any of them reach t.

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How much does it cost?

•At each vertex we have a choice of D vertices, log(D) to represent 1…D.

•Each path is log(N) long.

• we need log(D) at each stage of a log(N) path, altogether O(logD*logN)

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So far

We now know that if our graph G was an expander graph, USTCON can be solved in Log-Space.

How can we turn G into a graph of expanders?

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Making expanders: powering it up and cutting it down

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What do we want from the expander graph G’?

1. There is a path from s to t in G if and only if there is a path from s’ to t’ in G’.

2. Each connected component is an expander, with constant expansion

3. Construction in Log-Space.

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The Plan

• New tools for our toolbox– Rotation Maps– Powering– Zig Zag products

• The actual construction• Why we got what we wanted• Why we got it in Log-Space

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• Series of powering by 8 and zig zag, one increases the spectral gap and the other one decresases it, but not by much.

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Rotation Maps

• This is the notation we’ll use in this algorithm

GRot : N D N D Let G be a D regular undirected graph. The rotation map

GRot v,i w, j

If the edge (v,w) exists and is the ith edge coming out of v and the jth edge coming out of w

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Rotation Map Example

• Here or on the board

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PoweringIf we had no limitations on the degree of the graph, we could make it into an expander graph by powering:

The k-th power of the D-regular graph G is the graph Gk where there is an edge (u,v) iff there is a path of length ≤ k between u and v in G.

In rotation map notation, this means that

k 0 1 k k k 1 i i G i 1 iGRot v , a ...a v , b ...b where v ,b Rot v ,a

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Zig Zag Product

If G is a D-regular graph with N vertices and H is a d-regular graph with D vertices and rotation map RotH, we replace each vertex v in G with a copy of H, Hv. Therefore, our new graph has [N]x[D] vertices.

H

Part of G

v is now Hv

v

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Zig-Zag ProductThe resulting graph is a

d2 regular graph, with edges as follows:

Hv

Hw

(v,a) (v,a’)

(w,b’) (w,b)

G

v

w

a’

b’

Rot ((v,a), (i,j)) =

zG H

zG H

H

G

H

w,b , j', i ' where

a ', i ' Rot a, i

w,b ' Rot v,a '

b, j' Rot b ', j

z

i i’

j j’

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Zig-Zag Product

Take my word for it (no proof):

If G is an (N,D,λ) graph and H is a (D,d,) graph, then

zG H

Therefore, the zig-zag product provides an expander with ample spectral gap!

211 (G Z H ) 1 1

2 G H

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The Actual Construction

Show a transformation that turns every connected component of a graph into an expander.

But!Not any graph, but a D16 regular graph.

We will see how to construct such a graph later

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Main Transformation

On input G and H, where G is a D16 regular graph on N vertices, and H is a D-regular graph on D16 vertices, the transformation outputs a graph Gl as follows:

• Set l to be the smallest integer s.t. If D is constant, then this number is O(logN).

•G0 = G,

l2

2

1 11

DN 2

8i i 1G G H z

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Why is this an expander?

Let G and H be inputs of above. If and G is connected and non-bipartite then

Which means that the output of is indeed an expander.

H 1/ 2

G,H 1/ 2

Non bipartite means that G cannot be split into two sets of

vertices where all the edges of G are between those two sets

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Proof

Recall G0=G, connected and non-bipartite. Therefore, (known fact) Since l = O(logN) is the smallest integer such that

it’s enough to see that We know that and because of the lemma from before we get that

20G 1 1/ DN

l2 N2 21 1/ DN 1 1/ DN 1/ 2

2

i i 1i 0 G max G ,1/ 2

H 1/ 2

i 1 i 1 i 1G H 1 3/8 1 G 1 1/ 3 1 G

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Proof Continued

Recall . Also, it’s a property of powering that if G is a (N,D,λ) graph then Gt is a (N,Dt,λt) graph. Therefore, we can bound λ(Gi) by

For each i, one of two cases occurs:

Otherwise,

8i i 1G G H

8

i 11 1/ 3 1 G

8

i 1 i

1 5 1G G

2 6 2

42

i i 1 i 1 i 1G G because it 's the square of 1 1/ 3 1 G G

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Connected Components

• We’ve seen a construction which takes a connected graph G and transforms it, using an appropriate H, to an expander.

• However, we still need to show that is well defined and can operate on graphs that are not connected – composed of connected components

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Connected Components

G and H as before, if Is a connected component of G then

S N

l16SS D

G | ,H G,H |

In plain English: The output of on a single connected component S of G is the same as taking on G and looking at the sub-graph induced by the transformation of S.

In plainer English: S is a connected component in G ↔ The transformation of S is a connected component in Gl.

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Proof

• Ask Oded

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What do we want from the expander graph G’?

1. There is a path from s to t in G if and only if there is a path from s’ to t’ in G’.

2. Each connected component is an expander.

3. Construction in Log-Space.

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Log Space Construction

Prove that for any D, can be calculated in space O(log(N)).

We describe an algorithm A which constructs the rotation map of (G,H) O(logN) space.

The input tape will contain G,H and the output tape will contain

Gv, a , Rot v, a

l16 16v N D , a D

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Proof

Idea:Evaluating RotGi+1 takes just a constant additional amount of memory over evaluating RotGi. And all recursions use the same space!

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Proof - Continued

A will allocate the variables:v in [N] (from the original G)a0, …, al in [D16] (vertex names in H)