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Undirected ST-Connectivity in Log-Space

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Vertex Expansion Properties give us that the Expander Graph will have Logarithmic Diameter. ... Solving USTCON given a Constant Degree Expander. ... – PowerPoint PPT presentation

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Title: Undirected ST-Connectivity in Log-Space


1
Undirected ST-Connectivity in Log-Space
  • By Omer Reingold (Weizmann Institute)
  • Year 2004
  • Presented by Maor Mishkin

2
ST-Connectivity Problem
  • Given an Undirected Graph and
  • given two Vertices in the Graph, s and t,
  • We need to return true if s and t are
    connected and to return false if they are not
    connected.

TRUE
FALSE
3
ST-Connectivity Problem
  • Is called USTCON or Maze Problem.
  • The STCON problem is on a Directed Graph.

Exit
t
Entrance
s
4
ST-Connectivity Problem
  • Related problem (Cook late 70s)- Universal
    Traversal Problem, where we need to also return
    the path, which connects s and t Not the focus
    of this lecture.

s
t
5
Basic Search Algorithms
  • Breadth First Search (BFS) and
  • Depth First Search (DFS)
  • solve the problem in directed graphs (denoted
    STCON), therefore will solve in Undirected also.
  • Let N be the input Graph size.
  • Time O(N) -gt this is also the lower Time bound
    for USTCON problem.
  • Space O(N).

6
Space vs. Time
  • Algorithms have central resources of computation,
    Space Time.
  • Space is the work memory not including Input
    memory.
  • Trade-Off example Given a bit array, calculate
    the parity bit (XOR over all the bits) in Time
    O(1).
  • Algorithm Pre-Calculation - Create an array in
    the size of 2N and put in place j the parity bit
    of the bit array representation of j.

Input101101 Output0
Input100101 Output1
7
Log-Space Algorithms
  • Definition of a Log-Space algorithm Given an
    input of size N, algorithms Space is O(logN).
  • Claim. If the algorithm is Log-Space
    Deterministic gt Time is polynomial.
  • Proof. Lets assume that it is not polynomial Time
    and is Log-Space, therefore will have
    different Space states. By
    looking on Space at time i (Si), we know that we
    will have Si Sj that Si Sj and ij (since
    Time is bigger than Space states)-gt a
    contradiction to algorithm finishing the
    calculation.
  • That is, class LOG-SPACE is contained in P.

8
Previous Related Work
  • STCON J. Savitch (70), Log2 Space a super
    polynomial Time.
  • USTCON R. Aleliunas (79), Randomized Log-Space.
    Use a pointer to current vertex and a counter.
    Randomly start finding a path from s to t, stop
    when counter hits a limit.
  • the Random walk has a one side error.

9
Previous Related Work
  • USTCON Massive work to solve the problem
    without Randomization, but still
    pseudo-randomized algorithms AKS87, BNS89,
    Nis92b, INW94 We will fully remove the
    Randomization factor.
  • Universal Traversal Sequence Noam Nisan 92b,
    quasi-polynomial Time in Space Log2.

10
Previous Related Work
  • USTCON NSW89 improved Savitch (70) to Space
    Log1.5, and not polynomial Time.
  • USTCON ATSWZ00 improved the previous one to
    Space Log1.333, but still not polynomial Time
    most Space efficient until this work.

11
Approach
  • To solve the connectivity problem between s t,
    improve the connectivity of every connected
    component in the Graph, that is
  • Transform the input Graph into a Graph, which
    has Logarithmic Diameter (with the same connected
    components). We also make it a Constant Degree
    one.

12
Approach
  • Since the Graph will have Logarithmic Diameter,
    we can build all Logarithmic length paths,
    starting from s, and to see if one visits t .
  • Since the Degree is Constant and does not depend
    on N, the number of such paths is
    (polynomial). We later explain how to execute
    this in Log-Space.

13
Open issues
  • How can we enumerate paths on a Graph that is
    Constant Degree Logarithmic Diameter Graph in
    Log-Space (relatively easy).
  • How can we Transform the input Graph into a
    Constant Degree Logarithmic Diameter Graph (the
    main issue).

14
Powering
  • Definition. the kth Power of G contains an edge
    between two vertices v w, iff there exists a
    path of length k from v to w in G.
  • Repeatedly squaring the graph logarithmic number
    of times will turn G into a Logarithmic Diameter
    Graph.
  • Powering increases the Degree of the Graph and
    will not maintain the Graph as a Constant Degree
    one.

15
Decreasing Degrees
  • Replacement Product - an operation with two
    Graphs, a D-regular Graph G with N vertices and a
    d-regular Graph H on D vertices (with dltltD).
  • Each vertex v of G is replaced with a copy Hv
    of H.
  • Each of the d vertices of Hv is connected to its
    neighbors in Hv and also to one vertex in Hw,
    where (v,w) is one of the D edges going out of v
    in G.
  • The Degree of the Product Graph is d1.

16
Expander Graphs
  • Definition. For a d-regular Graph G(V,E), VN.
  • , ,
  • Vertex Expansion Properties give us that the
    Expander Graph will have Logarithmic Diameter.

17
Expander Graphs
  • We can turn a Graph into an Expander by Squaring
    it Logarithmic Times.
  • Algebraic Expansion Properties will give us a way
    to measure the Graph Expansion Properties.
  • Introduced in the 1970s.
  • Widely used for De-Randomization, Error
    Correction, CS theory.

18
Not Damaging Logarithmic Diameter
  • It turns out that if H is a good enough
    Expander, the expansion properties of the
    Replacement Product are not worse by much than
    those of the original Graph.
  • Formal statements to this effect were proved by
    Reingold, Vadhan Wigderson RVW01 for the
    Replacement Product and for the Zig-Zag Product
    (to be described later).

19
Informal USTCON algorithm
  • 1. First turn the input Graph into a
    constant-degree, regular Graph with each
    connected component being non-bipartite (not
    Replacement Product).
  • 2. The main transformation turns each connected
    component of the Graph, in a logarithmic number
    of phases, into an Expander (a logarithmic
    diameter)
  • 2.1. Each phase starts by raising the current
    graph to some constant power and then reducing
    the degree back via a Replacement or Zig-Zag
    product, using a constant size Expander.

20
Informal USTCON algorithm
  • 3. Now solve USTCON on the resulting Graph that
    has Logarithmic Diameter Constant Degree.

21
Graph Representation
  • Adjacency Matrix - A way to represent a Graph
    G(V,E) not the input graph will be used for
    theoretic discussion only.
  • At entry (v,u) will have a non-negative integer
    that equals to the number of edges that go from
    vertex v to vertex u.
  • A Graph is undirected iff its adjacency matrix
    is symmetric.
  • A Graph is D-regular if the sum of entries in a
    row (and column) is D.

22
Graph Representation
  • Given a D-regular Graph, we can assume that for
    vertex v, the edges are labeled 1D, and we can
    talk about the ith neighbor of v.
  • When taking a step from v to w, it may be useful
    to keep track of the edges traversed to get to w
    (rather then just remembering that we are now at
    w).

23
Graph Representation
  • For a D-regular undirected graph G, let us define
    Rotation Map
  • RotG ND --gt ND is defined as
    RotG(v,i) (w,j) if the ith edge incident to v
    leads to w, and this is the jth edge incident to
    w.
  • Rotation map will be the input Graph
    representation at this work.

24
Measure of Graph Expansion
  • We would like to make sure that our iterations
    will give us a good Expander, therefore we
    would like to measure our Graph Expansion.
  • Expansion Properties can be calculated. we will
    look at the Normalized Adjacency Matrix MG of a
    D-regular Graph G, that is the Adjacency Matrix
    of G divided by D.
  • Formally -gt

25
Eigenvalues and Eigenvectors
  • Eigenvalue - The factor by which a linear
    transformation multiplies one of its
    Eigenvectors.
  • Eigenvector For matrix M, vector x is an
    Eigenvector with Eigenvalue ? iff Mx ?x.
  • All one Eignvalue

26
Graph Expansion Measurement
  • It turns out that the Eigenvalues of MG are at
    most 1.
  • We denote by ?(G) the second largest Eigenvalue
    of MG (in the absolute value)
  • It is known that ?(G) is a good measure of the
    Expansion property of G.alpha vs. lambda
  • We refer to a D-regular undirected Graph G with N
    vertices such that ?(G)lt ? as an (N,D,?)-graph.

27
Solving USTCON given a Constant Degree Expander.
  • USTCON in Constant Degree Expanders can be solved
    in Log-Space
  • Let ? lt1 be some constant, then there exists an
    O(logDlogN) Space algorithm A, such that when a
    D-regular undirected Graph G with N vertices is
    given to A as an input the following holds
  • If s t are in the same connected component
    this component is an (N,D, ?)-Graph then A
    outputs connected.
  • If A outputs connected then s t are indeed in
    the same connected component.

28
Solving USTCON given a Constant Degree Expander
(cont.)
  • The algorithm A simply enumerates all Dl paths
    of length lO(logN) from s, where the leading
    constant in the big-O notation depends on ?. The
    algorithm A outputs connected iff at least one
    of these paths encounter t.
  • Following any path from s with length l requires
    O(logN) Space.
  • Enumerating all Dl paths requires O(logDlogN)
    Space. When D is a constant we get O(logN) Space.

29
Solving USTCON given a Constant Degree Expander
(cont.)
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30
Powering Expansion Measure
  • Our main transformation will take a graph and
    transform each one of its connected components
    into a Constant Degree Expander. If we ignore the
    constant degree requirement, a simple way of
    amplifying the Graph is by Powering.
  • Let G be a D-regular multi-graph with N vertexes,
    given by rotation map RotG. The tth power of G
    is the Dt-regular Graph Gt whose rotation map
    is given by
  • Where these values are computed via the rule

31
Powering Expansion Measure
  • Lemma - If G is an (N,D,?)-graph then Gt is an
    (N,Dt, ?t)-graph.
  • Proof The normalized adjacency matrix MGt of
    Gt is the tth power of the Normalized Matrix MG
    of G, so all the Eigenvalues also get raised to
    the tth power.
  • MGtx MGt-1MGx MGt-1?x
  • ? MGt-1 x ?tx

32
Two Graph Products
  • Reminder - Replacement Product
  • Zig-Zag Product of G H correspond to a subset
    of the paths of length three in the Replacement
    Product of these Graphs.
  • The degree of the output graph is d2 (d2ltltD)

33
Zig-Zag Product
  • Definition. If G is a D-regular Graph with N
    vertexes with rotation map RotG H is a
    d-regular Graph with D vertexes with rotation map
    RotH, then their Zig-Zag Product G H is defined
    to be the d2-regular graph with ND vertexes
    whose rotation map RotG H is as follows
  • RotG H((v,a),(i,j))
  • 1. Let(a,i)RotH (a,i)
  • 2. Let(w,b)RotG(v,a)
  • 3. Let(b,j)RotH(b,j)
  • 4. Output((w,b),(j,i))

z
z
z
34
Expansion Properties of G H
z
  • Theorem. (RVW01) If G is an (N,D,?G)-graph H
    is a (D,d, ?H)-graph, then G H is a
  • (ND,d2,f(?G, ?H))-graph, where
  • We get, that if is a good Expander (?H -gt0)
    then f(?G, ?H)-gt ?G

z
35
Universal Traversal exploration sequence
  • The mentioned Algorithm also solves Universal
    Traversal
  • (i.e. finding the path from s to t if such a
    path exist).
  • Every edge in the logarithmic long path of the
    final G H Graph is a sequence in G (original
    input) can be followed by the Rotation Graph
    Labeling in the Zig-Zag Product.

z
36
Issues Summary
  • USTCON
  • Log-Space Polynomial Time
  • Powering
  • Replacement Product
  • Expander Graphs
  • Zig-Zag Product
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