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# Low-End Uniform Hardness vs. Randomness Tradeoffs for Arthur-Merlin Games.

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1. Low-End Uniform Hardness vs. Randomness Tradeoffs for Arthur-Merlin Games. Ronen Shaltiel, University of Haifa Chris Umans, Caltech

2. coin tosses message Arthur-Merlin Games [B,GMR] • Interactive games in which the all-powerful prover Merlin attempts to prove some statement to a probabilistic poly-time verifier. “xL” Merlin Arthur toss coins I accept

3. coin tosses message Arthur-Merlin Games [B,GMR] • Completeness: If the statement is true then Arthur accepts. • Soundness: If the statement is false then Pr[Arthur accepts]<½. “xL” Merlin Arthur toss coins I accept

4. Arthur-Merlin Games [B,GMR] • Completeness: If the statement is true then Arthur accepts. • Soundness: If the statement is false then Pr[Arthur accepts]<½. • The class AM: All languages L which have an Arthur-Merlin protocol. • Contains many interesting problems not known to be in NP.

5. Efficient deterministic simulation of prob. algs. BPP=P BPPSUBEXP=DTIME(2no(1)) Efficient nondeterministic simulation of prob. protocols AM=NP AMNSUBEXP=NTIME(2no(1)) Derandomization goals: • We don’t know how to separate BPP from NEXP. • Such a separation implies certain circuit lower bounds [IKW01,KI02].

6. Hardness versus Randomness Initiated by [BM,Yao,Shamir,NW]. Assumption: hard functions exist. Conclusion: Derandomization. A lot of works: [BM82,Y82,HILL,NW88,BFNW93, I95,IW97,IW98,KvM99,STV99,ISW99,MV99, ISW00,SU01,U02,TV02,GST03,SU05,U05,…]

7. A quick survey of (nonuniform) hardness/randomness tradeoffs Assumption: There exists a function in E=DTIME(2O(l)) which is hard for “small” (size s(l)) circuits.

8. A quick survey of (uniform) hardness/randomness tradeoffs Assumption: There exists a function in E=DTIME(2O(l)) which is hard for “small” (time s(l)) algorithms/protocols. This paper* (*) The simulation only succeeds on “feasibly generated inputs”.

9. Jargon: Just like [IW98] paper but for AM instead of BPP A low-end gap theorem for AM. • Informal statement: • Either AM protocols are very strong. • Or, AM protocols are somewhat weak. • Formal statement: • Either E=DTIME(2O(l)) has Arthur-Merlin protocols running in time 2(log l)3. • Or, for every LAM there is a nondeterministic machineM that runs in subexponential time and agrees with L on “feasibly generated inputs”. • No polynomial time machine can produce inputs on which M fails. Should have been poly(l)

10. A uniform hardness vs. randomness tradeoff for AM • Informal statement: • Either AM protocols are very strong. • Or, AM protocols are somewhat weak. • Formal statement: For l<s(l)<2l. • Either E=DTIME(2O(l)) has Arthur-Merlin protocols running in time s(l). • Or, for every LAM there is a nondeterministic machineM that runs in time2O(l) and agrees with L on “feasibly generated inputs” of length n=s(l)1/(log(l)-loglog(s(l)))2. • No polynomial time machine can produce inputs on which M fails. Should have been Ω(1)

11. Motivation: weak unconditional derandomization • We believe that AM=NP (= Σ1). • We only know that AM is in Σ3. • Goal: Unconditional proof that AMΣ2 (or even AMΣ2-TIME(2no(1)). • Conditional => Unconditional ?? • Approach [GST03]: • Either AM is weak: AM=NP⇒ AM⊆Σ2. • Or AM is very strong: AM=E⇒ ??? • ⇒ AM=coAMΣ2. • Missing step: remove “feasibly generated inputs”.

12. A low-end gap theorem for AM∩coAM. • Informal statement: • Either AM∩coAM is very strong. • Or, AM∩coAM is somewhat weak. • Formal statement: • Either E=DTIME(2O(l)) has Arthur-Merlin protocols running in time 2(log l)3. • Or, for every LAM∩coAMthere is a nondeterministic machine M that runs in subexponential time and agrees with L on all inputs (not necessarily feasibly generated). Should have been poly(l)

13. Plan for rest of talk • Explain the overall approach of getting uniform hardness vs. randomness tradeoffs for AM (which is in [GST03]). • This approach uses a “hitting-set generator” construction by [MV99] which only works in the high end. • Main technical contribution of this paper is improving the [MV99] construction so that it works in the low-end. • Improvement uses “PCP tools” which were not used previously in this framework.

14. The high level approach (following [GST03])

15. Use nonuniform tradeoffs for AM. Derandomization fails => hard function f has small nondeterministic circuits. Want to show that: => f has small AM protocol. Observation [GST03]: The [MV99] tradeoff has an AM protocol in which Arthur verifies that the circuit obtained is single-valued (defines a function). C is supposed to define a function: For every y, C is supposed to have witnesses showing C(y)=0 or C(y)=1but not both! (single valued circuit) The uniform tradeoff of [GST03]: resilient AM protocols f(y)=? f(y)=b Merlin Arthur nonuniform advice Constructs nondet. Circuit C that is supposed to compute f AM protocol verifying that C=f. (exists as f is complete for E) Suppose Arthur could verify that this is indeed the case. witness showing C(y)=b

16. Use nonuniform tradeoffs for AM. Derandomization fails => hard function f has small nondeterministic circuits. Want to show that: => f has small AM protocol. Observation [GST03]: The [MV99] tradeoff has an AM protocol in which Arthur verifies that the circuit obtained is single-valued (defines a function). => AM protocol for f. Problem: The [MV99] generator only works in the “high end”. Our contribution: Modify [MV99] into a “low-end” generator. C is guaranteed to define a function: For every y, C is has witnesses showing C(y)=0 or C(y)=1 but not both! The uniform tradeoff of [GST03]: f(y)=? f(y)=b Merlin Arthur AM protocol in which Arthur receives a certified valid circuit C C is supposed to compute f AM protocol verifying that C=f. (exists as f is complete for E) witness showing C(y)=b

17. Commit-and-evaluate AM protocols for function f(y). Properties: Input y can be revealed to Merlin after commit phase. Conformity: Honest Merlin can make Arthur output f(y). Resiliency: Following commit phase Merlin is (w.h.p) committed to some function g(y) (may differ from f). Thm: If E has such AM protocols then E has standardAM protocols. Abstraction: commit-and-evaluate AM protocols and resiliency. Merlin Arthur Commit phase: AM protocol generating “advice string”. f(y)=? f(y)=b Evaluation phase: AM protocol that uses advice string and outputs a value v(y).

18. Following [GST03]: In the case of AM∩coAM we can trust Merlin to send a “good”x. No problem if we only care about inputs that can be “feasibly generated” by some efficient TM. Nondet machine M(x) (supposed to accept LAM) Use function f to construct small “hitting set” of “pseudorandom strings”. Run AM protocol on input x (using pseudorandom strings as random coins) and accept if all runs accept. Proof of correctness by reduction Suppose M fails on an input x. Construct an efficient commit-and-evaluate AM protocol that uses x and conforms resiliently with f. => f has a standard efficient AM protocol. This is where uniformity comes in: Protocols rather than circuits. The big picture: How to derandomize an AM protocol How can Arthur obtain x? From his point of view x is a nonuniformadvice string. Where do “feasibly generated inputs” come in?

19. Improving Miltersen-Vinodchandran hitting set generator (How to derandomize an AM language)

20. The MV hitting set generator {0,1}m deg 2l/2 polys truth table f:{0,1}l→{0,1} • Nondet. Machine M(x): derandomizes AM protocol with m coins • For every output string guess a response for Merlin and accept if Arthur accepts all of them. • x∊L ⇒ Merlin can answer any string ⇒ M accepts (no error). • x∉L ⇒ Merlin can answer ½ strings ⇒ M may err. Z p(x,y) deg. 2l/2 rows and columns A Hitting set small set (≈2m) extractor field size q=102l/2

21. {0,1}m truth table f:{0,1}l→{0,1} Z p(x,y) deg. 2l/2 rows and columns A very small set extractor field size q=102l/2 A commit-and-evaluate AM protocol for p.

22. {0,1}m truth table f:{0,1}l→{0,1} Z p(x,y) deg. 2l/2 rows and columns A small set (≈2m) extractor field size q=102l/2 A commit-and-evaluate AM protocol for p. p(x,y)=b p(x,y)=? deg 2l/2 polys Merlin Arthur • Conformity: v • Resiliency: v (RS code). • w.h.p. over S∀univariate poly g∊Z, g(S) is unique. • Efficiency: (on high end m=2Ω(l)). • Protocol runs in time poly(m). • Protocol requires passing polynomials of degree 2l/2. commit phase: S∊RField of size m p(S2) evaluation phase: • Both compute path to (x,y) • ∀ line on path: p|line andwitness w • Arthur checks: • small set: p|line∊Z using w. • consistency of p|line.

23. S2→Sd|Sd|=2Ω(l) no gain! {0,1}m truth table f:{0,1}l→{0,1} Z p(x,y) deg. 2l/2 rows and columns A very small set extractor field size q=102l/2 A commit-and-evaluate AM protocol for p. deg 2l/2 polys For low end (say m=lO(1)) we need to reduce degree Merlin Arthur • Conformity: v • Resiliency: v (RS code). • w.h.p. over S∀univariate poly g∊Z, g(S) is unique. • Efficiency: (on high end m=2Ω(l)). • Protocol runs in time poly(m). • Protocol requires passing polynomials of degree 2l/2. Can get deg=2l/dusing p(x1,..,xd) with d variables. commit phase: S∊RField of size m p(S2) p(x,y)=b p(x,y)=? evaluation phase: • Both compute path to (x,y) • ∀ line on path: p|line andwitness w • Arthur checks: • small set: p|line∊Z using w. • consistency of p|line.

24. Arthur can verify that he gets a low-degree polynomial by performing low-degree testing! {0,1}m truth table f:{0,1}l→{0,1} Z p(x,y) deg. 2l/2 rows and columns A very small set extractor field size q=102l/2 p|”line” has many coefficients The best of both worlds deg 2l/2 polys Merlin Arthur • Best of both worlds: • Use p(x1,..,xd) deg 2l/d. • Run MV as ifp=p(x,y). • Resiliency: v (RM code). • Size of box=|S|2 ≈ m2. doesn’t depend on d! • Sending p|”line” costs 2l/2 bits. commit phase: S∊RField of size m p(S2) p(x1,..,xd/2;xd/2+1,..,xd). p(x,y)=b p(x,y)=? evaluation phase: • p|”line” has small (non-det) circuit • p|”line” has commit-and-evaluate protocol • Suppose p|”line” could be sent more efficiently: • Both compute path to (x,y) • ∀ line on path: p|line andwitness w • Arthur checks: • small set: p|line∊Z using w. • consistency of p|line.

25. Need locally computable extractors! Requires running the extractor on p|line(t) for all qd inputs t to p|line. {0,1}m truth table f:{0,1}l→{0,1} Z p(x,y) deg. 2l/2 rows and columns A very small set extractor field size q=102l/2 Locally computable extractors deg 2l/2 polys Merlin Arthur Story so far: • Use polynomials p with many variables and pretend they are bivariate. • Assume that p|”line”can be sent efficiently. (Not yet justified). • Is the AM protocol efficient? commit phase: v S∊RField of size m v p(S2) Efficient AM protocol! p(x,y)=b p(x,y)=? evaluation phase: • Thm: [V] no locally computable extractors for low-entropy. • We know that inputs to extractors are low-degree polynomials! • Can use extractor construction [SU01] which is locally computable. • Both compute path to (x,y) v • ∀ line on path: v p|line andwitness w • Arthur checks: • small set: p|line∊Z using w. • consistency of p|line. X v v

26. {0,1}m truth table f:{0,1}l→{0,1} Z p(x,y) deg. 2l/2 rows and columns A very small set extractor field size q=102l/2 Intuition: If p|”line” doesn’t have an efficient commit-and-evaluate protocol then it’s better to use it as the hard function. (It is over less variables!) Recursive win-win analysis a-la [ISW99]. Win-win analysis deg 2l/2 polys Merlin Arthur Main ideas: • Use polynomials p with many variables and pretend they are bivariate. • Assume that p|”line”can be sent efficiently. (Not yet justified). • Use locally computable extractors (exist when inputs are low degree polynomials. commit phase: v S∊RField of size m v p(S2) Efficient AM protocol! p(x,y)=b p(x,y)=? evaluation phase: • Both compute path to (x,y) ???? v • ∀ line on path: v p|line andwitness w • Arthur checks: • small set: p|line∊Z using w. • consistency of p|line. v v

27. The recursive HSG truth table of f (2l bits) ALL rows and columns to extractor each row and column (2l/2 bits each ) …

28. Recursive commit-and-evaluate AM protocol truth table of f • Arthur: random m x m box • Merlin: commits to top board • ! (input revealed) • Arthur/ Merlin: commit to each line’s board • Arthur: random points for checking lines • Merlin: commits to lines… …

29. Parameters • Start with 2l bit truth table • <log l levels • # “lines”≈ 2O(l).v • Efficiency of AM protocol: • poly(m) blow-up at each level )poly(m)logl running time • convert O(log l) rounds to two rounds )poly(m)(log l)2 time for final AM protocol

30. Conclusions • Key ideas: • commit-and-evaluate protocols as abstraction. • operate implicitly on lines. • PCP tools: low-degree testing, self-correction. • “local extractor” when know in advance it will applied to low-degree polynomials. • “Recursive win-win analysis” allows large objects to have short descriptions. • Open problems: • improve poly(m)(log l)2 to poly(m)(“optimal”). • remove “feasibly generated inputs” from main theorem. • ⇒ Uncondtional proof that AM⊆Σ2(TIME(2no(1))).

31. That’s it…