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1 Hardness Result for MAX-3SAT This lecture is given by: Limor Ben Efraim
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2 3Sat CNF formula: a formula of n variables (x i ) given by m clauses (C j ), each clause contains exactly 3 literals. Max-3Sat: Given: 3Sat CNF formula. Goal: Find an assignment x that maximize the number of satisfied clauses. Hastard (1997), Khot(2002): For any constant > 0, it is NP Hard to distinguish whether a MAX-3SAT instance is satisfiable or there is no assignment that satisfies ⅞+ fraction of the clauses. Fact: Any random assignment satisfies 7/8 from the clauses.
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3 Max-3Lin-2: Given: a system of linear equations over Z 2, exactly 3 variables in each equation. Goal: Find an assignment that maximize the number of satisfied equations. We saw MAX-3Lin-2 Gap(½+ ,1- ) MAX-3Sat Gap(⅞+ ,1- ) 4 gadget
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4 Label Cover - Reminder Each vertex V is a set of u variables. Each vertex W is a set of u clauses When an assignment to LC satisfies the edge (V,W)? If satisfies W, and (V) is a restriction of (W). Bipartite graph … … Constraints Functions
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5 type-0 block A set of Tu clauses and u variables. type-1 block A set of (T+1)u clauses. 0 is the family of all type-0 blocks 1 is the family of all type-1 blocks Given W 2 1 (V 2 0 ): M W (M V ) – the set of all satisfying assignments to W (V). Given W 2 1 (V 2 0 ), how many satisfying assignments there are ? Answer: At most 7 (T+1)u (2 u 7 Tu ) values.
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6 When a type-0 block V is a sub block of type-1 block W ? V,W :M W ! M V is the operation of taking a sub assignment. If we can replace u clauses {c i | i=1,2,…u} in W by u variables {x i | i=1,2,…,u} in V such that the variable x i is in the clause c i for 1 · i · u.
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7 Label Cover + (V,W) 2 E(LG+) if V is a sub-block of W. Each vertex V is in 0 Each vertex W is in When an assignment to LC+ satisfies the edge (V,W)? If satisfies both V and W, and V,W ( (W))= (V). Bipartite graph … …
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8 Theorem: It is NP Hard to distinguish between the following two cases: YES: There is an assignment that satisfies every edge in the graph NO: No assignment can satisfies more that 2 - (u) of the edges
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9 Lemma: W 2 1. Let , ’ 2 M W. If V is a random sub-block of W then Pr V [ V,W ( )= V,W ( ’)] · 1/T Proof: , ’ differ at least on one clause. For a choice of a random sub-block V, one replaces at random u clauses out of (T+1)u clauses in W. With probability · 1/T each different clause is replaced. Corollary: W 2 1. Let 0 µ M W and 2 . If V is a random sub block of W then Pr V [ 8 ’ 2 , ’ , V,W ( ) V,W ( ’)] ¸ 1-| |/T
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10 The Smoothness Lemma: For any set 0 µ M W Proof:
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11 Label Cover + with smoothness property. 3Sat CNF formula Our Plan If there is a satisfiable assignment to the Label Cover+ The 3Sat CNF formula is satisfiable. If the Label Cover+ is 2 - (u) satisfiable The 3Sat CNF formula is · ⅞+ 8 satisfiable.
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12 Long Code F V is the set of all functions f:M V ! {-1,1}. F W is the set of all functions f:M W ! {-1,1}. Long code of an assignment x 2 M V is the mapping A:F V ! {-1,1} where A(f)=f(x). Size: 2 2 |V|
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13 Building… V W … … AWAW AVAV We will replace each vertex W (V) in a set of boolean variables, a variable for each bit of A W (A V ), the long code of W (V). (W,f) ! X W,f. (V,f) ! X V,f.
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14 Building - Continue What are the clauses ? To answer this, we define a test for each (W,V) 2 E(LC+) V is a sub block of W
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15 The test Pick a block W 2 1 Pick a random sub-block V of W. Let = V,W Let A,B be the supposed long codes of supposed satisfying assignment to the blocks V,W resp. Pick a function f:M V ! {-1,1} with the uniform probability. Pick a function g:M W ! {-1,1} with the uniform probability.
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16 Accept unless A(f)=B(g)=B(h)=1. Define a function h:M W ! {-1,1} independently 8 y 2 M W if f( (y))=1 then h(y)=-g(y) if f( (y)=-1 then: Equivalent: Accept if the clause X V,f Ç X W,g Ç X W,h is satisfiable {0,1} ! {1,-1} x)=(-1) x
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17 Completeness This test has perfect completeness. If f(y |V )=1, by definition one of g(y),h(y) will be -1 B(g)=-1 or B(h)=-1. If f(y |V )=-1, we have A(f)=-1. How many clauses we got ? Polynomially in n for constant u !!!
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18 Fourier Analysis Reminder: F V is the set of all functions f:M V ! {-1,1}. Orthonormal basis to F V is: (f)= x 2 f(x) 8 µ {-1,1} V. v=|V|. The inner product of 2 functions A,B is (A,B)=2 -2 v f 2 F V A(f)B(f)
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19 Fourier Analysis-Continue Lemma: For any f,g 2 F V and , µ {-1,1} V : (fg)= (f) (g) 2. (f) (f)= M (f). Lemma: 1. E f [ (f)]=0 8 µ {-1,1} V, ;. 2. E f [A(f)]=0 Parseval’s Formula:
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20 Soundness The acceptance criteria can be written as: E f,g,h [ 1-⅛ (1+A(f)) (1+B(g)) (1+B(h)) ] = ⅞ - ⅛ [ E g,h (B(g)B(h)) + E f,g,h ( A(f)B(g)B(h) ) ] We will show that each term · O( ) For the rest of the proof fix T= (f,g),(f,h) are independent
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21 E g,h, [B(g)B(h)]
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22 s x is the number of y 2 s.t. y |V =x
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23 Pr[s x =1] ¸ 1-
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24 e(x) · 1-
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25 E f,g,h, [A(f)B(g)B(h)]
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26 Lemma: For any , Proof: the left size is equal to
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28 Cauchy-Schwartz inequality E[X] 2 · E[X 2 ]
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29 Cauchy-Schwartz inequality Goal: to see that this is bounded by O( )
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30 Reminder Label Cover+ 3Sat CNF Formula Given assignment to the 3Sat-CNF formula We can find an assignment to the Label Cover+ Goal: to see that if the assignment satisfies ¸ ⅞+O( of the clauses Then we can find an assignment that satisfies ¸ 2 - (u) of the edges.
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31 The Folding Mechanism Goal: To make sure that A(f)=-A(-f) 8 f. Action: Given A: F U ! {-1,1}, define A’: for every pair (f,-f) selecting one of (f,-f). IF: f is selected (A’(f),A’(-f))=(A(f),-A(f)) IF: -f is selected (A’(f),A’(-f))=(-A(-f),A(-f))
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32 We will assume all our long codes are of the folding mechanism !!!
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33 We will create an assignment to Label Cover+ based on By the folding lemma , ;
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34 For the choice Previous theorem on Label Cover+
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35 Summary Label Cover + Gap(2 - (u),1) Long Code + Testing Max-3Sat Gap(⅞+ ,1) FIN
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