1 Introduction. 2 Complexity of Norms. 3 Query Complexity. 4 Summary. Hugo Férée, Walid Gomaa, Mathieu Hoyrup. The Query Complexity of Real Functionals ...
Outline Introduction Complexity of Norms Query Complexity Summary
The Query Complexity of Real Functionals Hugo Férée, Walid Gomaa, Mathieu Hoyrup
School on Computation and Computability in Dynamics ICTP Trieste, July 29th, 2014 Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
1 2 3 4
Introduction
Complexity of Norms Query Complexity Summary
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
1 2 3 4
Introduction
Complexity of Norms Query Complexity Summary
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Computing with Real Numbers (qn )n∈N
x if ∀n, |x − qn | ≤ 2−n
Computation model: Oracle Turing Machines Finite-time computation
−→ finite number of queries −→ finite knowledge of the input
Bounding computation time
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
(1)
⇐⇒ bounding computational power ⇐⇒ bounding number of queries The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Computing with Real Numbers Cont’d f ∈ C[0, 1] ⇐⇒ ∃µ, fQ :
modulus of continuity : µ : N → N
|x − y | ≤ 2−µ(n) =⇒ |f (x) − f (y )| ≤ 2−n
approximation function: fQ : Q × N → Q
|fQ (q, n) − f (q)| ≤ 2−n
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Computing with Real Numbers Cont’d Theorem
f : [0, 1] → R is computable w.r.t. an oracle ⇐⇒ f is continuous. ⇓ Complexity version ⇓
Theorem f : [0, 1] → R is polynomial time computable w.r.t. to an oracle ⇐⇒ its modulus of continuity is bounded by a polynomial. Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Second-Order Complexity [Kawamura& Cook] Regular functions
Σ is a finite alphabet
Oracle machine M realizes a functional: (Σ∗ → Σ∗ ) → (Σ∗ → Σ∗ ) φ 7→ ψ φ M (u): φ : Σ ∗ → Σ∗ φ is regular: |u| ≤ |v | ⇒ |φ(u)| ≤ |φ(v )| (consistency condition for complexity) u ∈ Σ∗
Mφ (u) = ψ(u)
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Second-Order Complexity Regular functions cont’d
The size of φ:
|φ| : N → N
Pairing of regular φ, ψ:
|φ|(n) = |φ(0n )|
hφ, ψi (0u) = φ(u)10|ψ(u)|
hφ, ψi (1u) = ψ(u)10|φ(u)|
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Second-Order Complexity Second-order polynomial
every c ∈ N is a second-order polynomial
every first-order variable n is a second-order polynomial
if P, Q are second-order polynomials, then so are: P + Q, PQ, and X (P), where X is a second-order variable P(X ) = X (x) + X (X (x) · X (x)) + 4 X (x) = x 3
P(X )(n) = n3 + n18 − n2 + 4
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Representation of f ∈ C[0, 1]
Modulus µ : N → N ⇒ regular µ¯ : Σ∗ → Σ∗ : µ¯(u) = 0µ(|u|)
Approximation function fQ : Q × N → Q ⇒ regular ¯fQ : Σ∗ × Σ∗ → Σ∗ : ¯fQ (u, v ) = a0n 1w
( n + dw fQ (du , |v |) = −n − 1 + dw
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
a=0 a=1
The Query Complexity of Real Functionals
(2)
Outline Introduction Complexity of Norms Query Complexity Summary
Representation of f ∈ C[0, 1] Cont’d D E ¯f = µ¯, ¯fQ
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Second-Order Complexity Running in polynomial time
Mφ (u) runs in poly-time if:
There exists a second-order polynomial P(n, X ) such that for any regular function φ : Σ∗ → Σ∗ and u ∈ Σ∗ , Mφ (u) halts in at most P(|u|, |φ|) steps.
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
1 2 3 4
Introduction
Complexity of Norms Query Complexity Summary
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Polynomial-Time Computable Norms
F is poly-time computable: F is not complete and
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Dependence of a Norm on a Point A norm F and a point α ∈ [0, 1]: dF ,α (n) =
sup{l : ∃f ∈ Lip1 , Supp(f ) ⊆ N (α, 1/l) and F (f ) > 2−n } α
|{z}
1/l
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
f
The Query Complexity of Real Functionals
Example
Outline Introduction Complexity of Norms Query Complexity Summary
F = ||.||∞
F = ||.||1
=⇒
=⇒
dF ,α (n) ∼ 2n
dF ,α (n) ∼ 2 2 n
Let Q = {q0 , q1 , . . .} be a dense subset of [0, 1]: Then
F (f ) =
dF ,qi (n) ≥ 2n−i , dF ,α (n) ≤
X |f (qi )|
(n + 1)2 , ε
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
i
2i
n≥i
for almost all α
The Query Complexity of Real Functionals
(3) (4)
(5)
Relevant Points
Outline Introduction Complexity of Norms Query Complexity Summary
Norm of f depends on the values of f at points of high dependence (α ∈ [0, 1] : dF ,α is large) Definition
α is relevant if ∃c > 0, ∀n,
dF ,α (n) ≥ c · 2 2 n
Rk = {α : ∀n, dF ,α (n) ≥ 2n−k }, All relevant points:
R=
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
relevant up to constant k
[
Rk
k
The Query Complexity of Real Functionals
Relevant Points
Outline Introduction Complexity of Norms Query Complexity Summary
Examples
Example
For ||.||∞ and ||.||1 , R = [0, 1]. Example P F (f ) = i relevant.
|f (qi )| . 2i
The {qi } is a dense subset of [0, 1]. The qi ’s are
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Relevant Points Cont’d
A norm should look everywhere to separate different functions: Theorem R is dense.
F (f ) up to some precision depends only on Rµf (k ) , so the points of Rµf (k ) are relevant to evaluate the norm of a function up to precision k : Theorem
f = 0 on R2µf (k ) =⇒ F (f ) ≤ c.2−k . µf : modulus of f
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
R is Dense (Proof)
F (h0 ) ≥ 2−c Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
R is Dense (Proof)
F (h1 ) ≥ 2−c−2 Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
R is Dense (Proof)
F (h2 ) ≥ 2−c−4
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
R is Dense (Proof)
F (hn ) ≥ 2−c−2n
dF ,α (2n + c) ≥ 2n+p =⇒ α ∈ R Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
1 2 3 4
Introduction
Complexity of Norms Query Complexity Summary
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Complexity of Norms
Complexity Restriction =⇒
Bounding computation time (power) and bounding the number and size of queries
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Query Complexity
Definition Qn : oracle calls of F on x 7→ 0 with precision 2−n . Definition F has a polynomial query complexity if it is computable by a relativized OTM with |Qn | ≤ P(n). Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Query Complexity Cont’d
Theorem If F has polynomial query complexity, then 1 2
Almost every point has a polynomial dependency (dF ,α ∈ P for almost all α). The set of relevant points has Lebesgue measure 0.
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Query Complexity Cont’d Proposition
F has polynomial query complexity n =⇒ ∃α, dF2,α (n) is bounded by a polynomial.
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
Query Complexity Cont’d Open question
Can generalize to any F : C[0, 1] → R?
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
One Oracle Access Case
Theorem The following are equivalent:
F is computable by a polynomial time machine doing only one oracle query ∀f , F (f ) = φ(f (α)) where: α ∈ Poly (R) φ ∈ Poly (R → R) φ is uniformly continuous
Open question
Generalization to any finite number of queries? Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Outline Introduction Complexity of Norms Query Complexity Summary
1 2 3 4
Introduction
Complexity of Norms Query Complexity Summary
Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals
Summary
Outline Introduction Complexity of Norms Query Complexity Summary
Set-up: Oracle Turing machine + Second-order complexity [Kawamura& Cook]
Introduced notions of dependence function dF ,α and relevant point Norm depends on values of high dependence (relevant) such points are dense Polynomial query complexity ⇒ almost all points have polynomial dependency Poly-time norms depend on few number of points, but depends significantly on them Hugo Férée, Walid Gomaa, Mathieu Hoyrup
The Query Complexity of Real Functionals