finite monoids, regular languages, circuit complexity and logic pascal tesson laval university,...

Finite monoids, regular languages,

circuit complexity and logic

Pascal TessonLaval University, Quebec City, Canada

P.Tesson Dagstuhl Seminar on Circuits, Logic and Games 2

• Fact: Circuit complexity is difficult...• ... so it’s important to develop numerous

angles of attack on the central questions.

• Logic has been very helpful. (e.g. logical characterizations of AC0,

ACC0.)

• Algebra has been helpful: – Smolensky’s lower bounds.– Programs over finite monoids (Barrington,

Straubing, Thérien).

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Quick circuit reminder

• NC1: languages recognized by family of AND/OR circuits with fan-in 2 and depth O(log n).

• AC0: languages recognized by family of AND/OR circuits with arbitrary fan-in, depth O(1) and poly-size.

• ACC0: languages recognized by family of AND/OR/MODq circuits with arbitrary fan-in, depth O(1) and poly-size.

• CC0: languages recognized by family of MODq circuits with arbitrary fan-in, depth O(1) and poly-size.

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Regular languages

and finite monoids

In this talk...

• Finite monoids to understand regular languages.

• Finite monoids to characterize boolean circuit complexity classes.

• Finite monoids to understand the circuit complexity of regular languages.

Circuit complexityFirst order logic

over words

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Outline

I. Finite automata and finite monoids

II. Programs over finite monoidsIII. Some tools for lower boundsIV. Circuit complexity of regular

languagesV. Conclusion

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Finite monoids and automata

• Monoid: set + binary associative operation + identity element.

• Examples– * is a monoid under concatenation. Empty word

is the identity element.

– For every k, the set Tk of functions t:[k] [k] forms a monoid under composition.

– For a finite automaton A, each finite word induces a transformation on the set of states. The transition monoid of A is the submonoid of T|A|.

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Finite monoids = finite automata

• A finite monoid can be conveniently represented by a finite automaton– states: elements of the monoid.– alphabet: elements of the monoid.– transitions: (m,n) = mn

• Finite monoid finite automata: just two points of view.

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Def’n: A language L * is recognized by the finite monoid M if there exists homomorphism :* M and a subset F M such that

-1 (F) = L.

Theorem: L is regular iff it is recognized by some finite monoid M.

Def’n: The syntactic monoid of L is the transition monoid of its minimal automaton.

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Algebraic automata theory

Why use this algebraic point of view?

• Important classes of regular languages can be characterized by the algebraic properties of their syntactic monoids.

• Often gives algorithms to test membership in a given class of regular languages.

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Star-free languages

• A regular language is star-free if it can be defined by a regular expression using , ;, concatenation and boolean operations but without the Kleene star.

• Example: L = (ab)* is a star-free language since

L = ;cb Å a;c Å (;caa;c)c Å (;cbb;c)c

• But how does one decide whether a given regular language is star-free?

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Theorem: [Schützenberger] L is star-free iff its syntactic monoid is aperiodic, i.e. contains no non-trivial subgroup.

It can also be shown that M is aperiodic iff there exists n s.t. xn+1 = xn for all x 2 M.

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Logic over words

View finite words over as a linearly ordered -colored structure.

We construct first-order sentences using the following atomic formulas:

1. for each a 2 a unary predicate Qa

w ² Qax iff wx = a2. x < y (with the obvious semantics)

We can also augment the logic with modular counting quantifiers.

9i mod p x (x) (there exist i modulo p x’s s.t. holds)

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1. x y Qax ((y < x) Qby)

defines the language b*a*

2. To define (ab)* we can use the sentence:8x 8y (Qb x ! [9 z (z<x)]) Æ (Qax ! [9 z (x < z)]) Æ

[((x y) Æ Qax Æ Qay) Ç ((x y) Æ Qb x Æ Qby)]

! 9 z [(x <z<y) Ç (y <z<x)]

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Theorem: [McNaughton-Papert] L is star-free iff it is definable in FO[<] iff L’s syntactic monoid is aperiodic.

Theorem:L is definable in FO+MOD[<] iff its syntactic monoid is solvable.

Theorem:L is definable in MOD[<] iff its syntactic monoid is a solvable group.

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Outline

I. Finite automata and finite monoids

II. Programs over finite monoidsIII. Some tools for lower boundsIV. Circuit complexity of regular

languagesV. Conclusion

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From homomorphisms to programs

a1 a2 ... an-1 an

m1 m2 ... mn-1 mn

homomorphism

Multiply in M

result is m = (input)accept if m F

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From homomorphisms to programs

a1 a2 ... an-1 an

m1 m2 m3 ... ms-1 ms

program over M: each output element depends on a single input position

Multiply in M

result is m = (input)accept if m F

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Programs over monoids

An n-input program over M of length s is a sequence of instructions I1 I2 ... Is where each instruction is a pair: Ij = (fj, kj) where fj: M and 1 kj n.

The output of on input w = a1 ... an is the monoid element

w) = f1(ak1) f2(ak2

) ... fs(aks)

A language L n is recognized by a program over M if there exists F M such that w L iff (w) F.

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Programs over monoids

To recognize subsets of * we use a family {n}n 0 where each n processes inputs of length n. The length of such a family is then a function of n.

Often, we require that {n}n ¸ 0 is s.t. the nth program is constructible within some resource bound. ) uniformity restrictions. (not our problem today!)

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Bounded-width branching programs

• Programs over monoids: originally a point of view on bounded width branching programs.

x1 x7 x5 x1

On input x1x2 ... xn: the red arrows are followed when the queried bit is 0, the blue arrows are followed when the bit is 1. For example if x1 = 0, x7 = 1.

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Barrington’s theorem

Theorem: [Barrington]A language lies in NC1 iff it can be recognized by a polynomial length family of programs over a finite monoid. In fact, any simple non-Abelian group will do.

Recall: the commutator of two group elements [g,h] = g-1h-1gh.If G is simple and non-Abelian, then [G,G] = G.

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Barrington’s theorem (proof)

Easy direction: show that L recognized by a poly-length program over a finite monoid ) L 2 NC1. (more on this later)

Hard direction: suppose L 2 NC1 and G simple non-Abelian. Show by induction on depth d: if C is an AND/OR circuit with binary fan-in and g 2 G, there is a program C,g of length O(4d) whose output is g if C evaluates to 1 and 1G otherwise.

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Barrington theorem’s proof (cont’d)

Suppose for simplicity that g = [g1,g2] and assume the ouput of C is AND(C1,C2). By induction, exists C1,g1

and C2,g2 of length

O(4d-1).Define C,g = [C1,g1

,C2,g2]

If C1 = 0 then C1,g1 outputs 1G and so

[1G,C2,g2] = C2,g2

1 C2,g2 = 1G.

If C1 and C2 both evaluate to 1, the program C,g outputs [g1,g2] = g.

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• Alternative point of view: if L is a regular language whose syntactic monoid is non-solvable then L is NC1 complete under non-uniform projections.

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Algebraic characterizations in NC1

Theorem: K 2 AC0 iff K is recognized by a poly-length

program over a finite aperiodic monoid.K 2 CC0 iff K is recognized by a poly-length

program over a finite solvable group.K 2 ACC0 iff K is recognized by a poly-length

program over a finite solvable monoid.

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Contrast with:

Theorem: K 2 AC0 iff K is definable in FO[Arb], i.e. FO

extended with arbitrary numerical predicates.

K 2 CC0 iff K is definable in MOD[Arb].K 2 ACC0 iff K is definable in FO+MOD[Arb]

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So what?

Looks nice but how is that useful?

1. Provides some insight into the power and limitations of these circuit classes. Since AC0 corresponds to aperiodic monoids, it’s natural to see PARITY as the canonical example of a language that these circuits can’t compute.

2. Separation conjectures can be reformulated algebraically. Showing CC0 ACC0 translates into show AND cannot be computed by a poly-length program over a solvable group.

3. Roadmap: start with very simple classes of solvable groups and work your way up.

4. More generally, finer grain in the analysis: the power of the program depends both on length and on structure of underlying monoid.

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Some results

Theorem: [Barrington-Straubing]If L has a neutral letter and is recognized by a program of length o(n log log n) over some finite monoid M then L can be recognized via morphism by a direct product of M and its reverse Mr.

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Theorem [Barrington-Straubing-Thérien]Any program over a group G such that [G,G] is a p-group requires exponential length to compute AND.

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Outline

I. Finite automata and finite monoids

II. Programs over finite monoidsIII. One useful tool for lower

boundsIV. Circuit complexity of regular

languagesV. Conclusion

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Communication complexity

• k players collaborate to determine if an input string w = a1 a2 ... an belongs to a given language L.

• The player j sees each ai except those such that i j (mod k).

a1 a4 a7 ... a2 a5 a8 ... a3 a6 a9 ...

The k-party communication complexity of L is the least amount of bits that the parties need to exchange in the worst-case to determine if their input belongs to L.

One can similarly define the communication complexity of a monoid M as the complexity of evaluating the product m1m2 ... mn in M.

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A general framework for lower bounds

Theorem:If M has communication complexity O(f), then any language recognized by a program of length s over M has communication complexity at most O(f(s)).

The same holds for various variants of the communication complexity model.

This gives an algebraic point of view on these lower bound techniques and exposes their limits.

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Theorem: [T., Thérien]In the two-party model, a monoid M has communication complexity:

(1) iff M is commutative(log n) iff M is non commutative but

every subgroup of M is abelian and M satisfies (xy)n(yx)n(xy)n = (xy)n for some n. (we denote this class as DO Å H(Ab) )

(n) otherwise.

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Outline

I. Finite automata and finite monoids

II. Programs over finite monoidsIII. One useful tool for lower

boundsIV. Circuit complexity of regular

languagesV. Conclusion

P.Tesson Dagstuhl Seminar on Circuits, Logic and Games 35

• The classical result PARITY AC0 shows that understanding the circuit complexity of regular languages is central to progress in the field.

• By the algebraic characterizations of AC0, CC0 and ACC0 we already have good tools for a first, rough classification.

• How precise can we be about the circuit complexity of regular languages?

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Theorem: [Koucký, Pudlák, Thérien]A regular language (with a neutral letter) can

be computed by an ACC0 circuit using O(n) wires iff its syntactic monoid lies in DO Å H(Ab).

Theorem: [Chandra, Fortune, Lipton]Any regular language in ACC0 can be

computed by a circuit using only O(ng-1(n)) wires for any primitive recursive g.

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Some ideas of the proof

The upper bound relies on the combinatorial characterization of the regular languages with syntactic monoids in this class.

For the lower bound: deep results about superconcentrators are needed to show that if L is regular with 2-party communication complexity (n) then L requires a superlinear number of wires.

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Open problem

Question: What regular languages can be computed by an AC0, CC0 or ACC0 circuit using only linearly many gates?

Hint: These correspond exactly to FO2[Arb], MOD2[Arb] and FO+MOD2[Arb]. (see [Koucký,Lautemann,Thérien])

Conjectured answers:It is believed that the answer will have some algebraic form. In particular: show that AC0 circuits for (ab)* require a superlinear number of gates in the presence of a neutral letter.

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Conclusion

Open problems suggested by the algebraic point of view:– Show that AND cannot be computed by poly-

length program over S4.

– Show that AND cannot be computed by poly-length program over a super-solvable group.