Rodrigo Ba Purdue University Department of Mathematics West - - PowerPoint PPT Presentation

rodrigo ba
SMART_READER_LITE
LIVE PREVIEW

Rodrigo Ba Purdue University Department of Mathematics West - - PowerPoint PPT Presentation

Stability inequalities for martingales and Riesz transforms nuelos Rodrigo Ba Purdue University Department of Mathematics West Lafayette, IN. 47906 May 19, 2017 With Adam Ose kowski Partially supported by NSF R. Ba


slide-1
SLIDE 1

Stability inequalities for martingales and Riesz transforms∗

Rodrigo Ba˜ nuelos†

Purdue University Department of Mathematics West Lafayette, IN. 47906

May 19, 2017

∗With Adam Ose

¸kowski

†Partially supported by NSF

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-2
SLIDE 2

Stability (quantitative/deficit) sharp inequalities

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-3
SLIDE 3

Stability (quantitative/deficit) sharp inequalities

Optimal/sharp inequalities

Suppose you have two functionals E and F on some normed (real) linear space M satisfying the functional inequality E F in the sense that E(x) F(x), ∀x ∈ M. The functional inequality E F is sharp if for all λ < 1 there exist x ∈ M such that E(x) > λF(x) The subset M0 = {x ∈ M : E(x) = F(x)} is called the set of optimizers (extremals) of the inequality. When M0 = ∅, the inequality is said to be optimal. (Note: An optimal functional inequality is sharp but not vice–versa.)

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-4
SLIDE 4

Definition

Let d be a metric on M (not necessarily the norm metric) and Φ a “rate function.” The optimal functional inequality E F is (d, Φ)– stable if F(x) − E(x) Φ(d(x, M0)), ∀x ∈ M In various examples, Φ(t) = ct2 and d(x, y) = x − yM and F(x) − E(x) c inf

z∈M0 x − z2 M.

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-5
SLIDE 5

Definition

Let d be a metric on M (not necessarily the norm metric) and Φ a “rate function.” The optimal functional inequality E F is (d, Φ)– stable if F(x) − E(x) Φ(d(x, M0)), ∀x ∈ M In various examples, Φ(t) = ct2 and d(x, y) = x − yM and F(x) − E(x) c inf

z∈M0 x − z2 M.

Classical Sobolev in Rn (n 3). k2

n = n(n−2) 4

|Sn−1| k2

nf2

2n n−2 ∇f2

2,

∀f ∈ H1

0(Rn) = M,

M0 = {x → c(a + b|x − x0|2)−(n−2)/2, a, b > 0, x0 ∈ Rn, c ∈ R} Optimality: Aubin (1976), Talenti (1976). Stability: Biachi-Egnell (1990) ∇f2

2 − k2 nf2

2n n−2 C inf

g∈M0 ∇(f − g)2 2

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-6
SLIDE 6

More general Sobolev (0 < α < n/2). f

2n n−2α kn,α(−∆)α/2f2

Optimality: Lieb (1983), Stability: Cheng-Frank-Weth (2013) Hardy-Littlewood-Sobolev Optimality: Lieb (1983). Stability: Carlen (2016), Log-Sobolev Gross (1975), Stability Fathi-Indrei-Ledoux (2015), Nash Optimality: Carlen-Loss (1993). Stability: Carlen-Lieb (2017) Housdorff-Young inequality: Sharpness Beckner 1975 (Lieb 1990) Stability: Chris 2015. 1 p 2, q =

p p−1

ˆ fq (Ap)nfp Ap = p1/2pq−1/2q Ap is best contacts. Extremizers are general Gaussians: g(x) = ceQ(x)+x·v.

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-7
SLIDE 7

More general Sobolev (0 < α < n/2). f

2n n−2α kn,α(−∆)α/2f2

Optimality: Lieb (1983), Stability: Cheng-Frank-Weth (2013) Hardy-Littlewood-Sobolev Optimality: Lieb (1983). Stability: Carlen (2016), Log-Sobolev Gross (1975), Stability Fathi-Indrei-Ledoux (2015), Nash Optimality: Carlen-Loss (1993). Stability: Carlen-Lieb (2017) Housdorff-Young inequality: Sharpness Beckner 1975 (Lieb 1990) Stability: Chris 2015. 1 p 2, q =

p p−1

ˆ fq (Ap)nfp Ap = p1/2pq−1/2q Ap is best contacts. Extremizers are general Gaussians: g(x) = ceQ(x)+x·v. Brasco &De Philippis (2016). Torsional rigidity for Brownian motion.

  • D∗

Ez(τD∗)dz −

  • D

Ez(τD)dz CnA(D)2 (Fraenkel Asymmetry) A(D) := inf{|D△B| |D| : B is a ball with |B| = |D|}. Problem: Prove “it” for stable processes (any subordination of BM).

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-8
SLIDE 8

Martingales: Sharp (but not optimal, i.e., M0 = ∅)) inequalities. (Reference: A. Ose ¸kowski, “Sharp martingale and semimartingale inequalities”, Monografie Matematyczne 72, Birkh¨ auser, 2012.)

Doob

{fn} an Lp, 1 < p ∞ martingale. f ∗ = supn |fn| maximal function. f ∗p p p − 1fp Burkholder (1984), Wang (1991 for dyadic): Inequality is sharp. But M0 = ∅.

Burkholder (1966) S(f) = (

n(fn − fn−1)2)1/2

apfp S(f)p bpfp 1 < p < ∞ Many sharp versions of these exists but none are optimal i.e., M0 = ∅, outside of the trivial case of p = 2. (The first sharp case of these for Brownian martingales/stochastic integrals is due to B. Davis (1976).)

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-9
SLIDE 9

X, Y c´ adl´ ag (right continuous/left limits) martingales: Y is differentially subordinate to X (Y << X), if the process {[X, X]t − [Y, Y ]t}t0 is nonnegative and nondecreasing in t. They are orthogonal (Y ⊥ X) if [X, Y ] = 0. 1 < p < ∞ and . p∗ = max{p, p/(p − 1)}. Set ||X||p = supt0 ||Xt||p

Burkholder (1984) Y << X

||Y ||p (p∗ − 1)||X||p. The constant (p∗ − 1) is best possible. Furthermore, the inequality is always strict unless p = 2. That is, inequality is sharp and M0 = ∅ unless p = 2.

R.B. G. Wang (1995) Y << X and Y ⊥ X

||Y ||p cot π 2p∗

  • ||X||p.

The constant cot

  • π

2p∗

  • is the best possible. Furthermore, the inequality is always

strict unless p = 2 unless p = 2. That is, inequality is sharp and M0 = ∅ unless p = 2.

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-10
SLIDE 10

A careful analysis of proofs reveals that “almost” extremals used to proof sharpness are “almost” eigenfunctions. The dyadic maximal function in Rn (dyadic martingales). Md(f)(x) = sup{ 1 |Q|

  • Q

|f(y)|dy : x ∈ Q, Q ∈ [0, 1]n, dyadic cube} Doob (for inequality) Wang (1995) for sharpness: Md(f)p

p p−1fp,

1 < p ∞. (Here we may restrict to non-negative functions.)

  • A. Melas (2015): If you take a sequence {fn} of almost externals then

limn Md(fn) −

p p−1fnp = 0

Theorem (Melas 2015)

Fix 2 < p < ∞, ǫ > 0 (small enough). Suppose f 0 (in Lp) is such that Md(f)p

  • p

p − 1 − ε

  • fp.

Then Md(f) − p p − 1fp cpε1/pfp for some constant cp depending only on p.

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-11
SLIDE 11

Theorem (A.Ose ¸kowski & R.B. 2016: Y << X)

(i) Let 1 < p < 2 and ε > 0. ||Y ||p (

1 p−1 − ε)||X||p. Then

  • |Y∞| −

1 (p − 1)|X∞|

  • p cpε1/2||X||p.

O(ε1/2) as ε → 0 is sharp. cp = O((2 − p)−1/2) as p ↑ 2 and this is sharp. (ii) Let 2 < p < ∞ and ε > 0. ||Y ||p (p − 1 − ε)||X||p.

  • |Y∞| − (p − 1)|X∞|
  • p cpε1/p||X||p,

O(ε1/p) as ε → 0 is sharp. cp is O((p − 2)−1/p) as p ↓ 2 and O(p) as p → ∞. These orders are sharp. (iii) For p = 2, no c2 and κ exist such that ||Y ||2 (1 − ε)||X||2 implies

  • |Y∞| − |X∞|
  • 2 c2εκ||X||2. In fact, there exist martingales Y and X,

Y << X, such that Y 2 = X2, and |Y | − |X|2 X2 > 0 (independent of ε)

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-12
SLIDE 12

Theorem (A.Ose ¸kowski & R.B. 2016: Y << X and Y ⊥ X)

(i)

  • |Y∞| − tan

π 2p

  • |X∞|
  • p

cpε1/2||X||p, 1 < p < 2, if X and Y are such that ||Y ||p

  • tan

π 2p

  • − ε
  • ||X||p.

Orders in ε as ε → 0, and cp, as p ↑ 2, are best possible. (ii)

  • |Y∞| − cot

π 2p

  • |X∞|
  • p

cpε1/p||X||p, 2 < p < ∞, if ||Y ||p

  • cot π

2p − ε

  • ||X||p

(iii) As in previous theorem, no such estimate exists for p = 2.

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-13
SLIDE 13

Beurling-Ahlfors operator in complex plane C Bf(z) = − 1 π p.v.

  • C

f(w) (z − w)2 dw. It is a Calderón-Zygmund singular integral and Bfp Cpfp, 1 < p < ∞.

Conjecture T. Iwaniec 1984

The operator norm of B on Lp is p∗ − 1: Bp→p = (p∗ − 1), 1 < p < ∞

Known:

(p∗ − 1) Bp→p 1.575(p∗ − 1) Lower bound O. Lehto (1965) upper bound R.B and P. Janakiraman (2008). Lehto’s functions used to prove the lower bound have the property that |Bf(z)| ≈ (p∗ − 1)|f(z)|. That is, they are “near eigenfunctions.”

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-14
SLIDE 14
  • Bf(ξ)

= ξ ξ

  • f(ξ) = ξ

2

|ξ|2 ˆ f(ξ) = ξ2

1 − 2iξ1ξ2 − ξ2 2

|ξ|2 ˆ f(ξ) ⇒ B = R2

1 − R2 2 + 2iR1R2 = Re(B) + i Im(B)

where R1 and R2 are the Riesz transforms in R2.

1

  • R. B. Wang (1995): Both Re(B) and Im(B) have norm (p∗ − 1) (Proving

Bp 4(p∗ − 1))

2

Nazarov and Volberg (2004): R2

j − R2 kp→p (p∗ − 1)

2RjRkp→p (p∗ − 1) (Proving Bp,p 2(p∗ − 1))

3

Geiss, Montgomery-Smith and Saksman (2009): R2

j − R2 kp→p = (p∗ − 1),

2RjRkp→p = (p∗ − 1), j = k

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-15
SLIDE 15

Theorem (A.Ose

¸kowski & R.B. 2016) T either Re(B) or Im(B) or more generally, R2

j − R2 k or 2RjRk, j = k in Rn.

(i) Let 1 < p < 2, ε > 0. If f ∈ Lp(Rn) is such that ||Tf||p ((p − 1)−1 − ε)||f||p, then |Tf| − (p − 1)−1|f|p cpε1/2||f||p. The order O(ε1/2), as ε → 0, is best possible as is the order O((2 − p)−1/2), as p ↑ 2 for cp. (cp is explicit and independent of dimension) (ii) Let 2 < p < ∞, ε > 0. If f ∈ Lp(Rn) is such that ||Tf||p (p − 1 − ε)||f||p, then |Tf| − (p − 1)|f|p cpε1/pfp, (iii) For p = 2, there is no stability result of the above type. That is, there are no finite constants c2 and κ > 0 such that |Tf| − |f|p c2εκ||f||L2(Rd)

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-16
SLIDE 16

First order Riesz transforms Calderón-Zygmund singular integrals and also Fourier multipliers with

  • Rjf(ξ) = −iξj

|ξ| , j = 1, 2, . . . , n. For n = 1 this is just the Hilbert transform. n = 1: Pichorides (1972). n > 1: Iwaniec-Martin (1995) ||Rjf||Lp(p cot π 2p∗ ||f||p, j = 1, 2, . . . , n and this is sharp. R.B. Wang (1995) obtained it from Orthogonal martingales.

Theorem (A.Ose

¸kowski & R.B. 2016) Same type of stability results hold for Rj. (i) Let 1 < p < 2, ε > 0. ||Rjf||p

  • tan

π 2p

  • − ε
  • ||f||p ⇒ |Rjf| − tan

π 2p

  • |f|p cpε1/2||f||p,
  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-17
SLIDE 17

Burkholder’s inequality fn =

n

  • k=1

dk, g =

n

  • k=1

ek, |ek| |dk|, a.s. ∀k Burkholder’s inequality: considers the function V : R × R → R defined by Vp(x, y) = |y|p − (p∗ − 1)p|x|p. The goal is then to show that EV (fn, gn) 0. Burkholder then “introduces” the function Up(x, y) = βp (|y| − (p∗ − 1)|x|) (|x| + |y|)p−1 , where βp = p

  • 1 − 1

p∗ p−1 and proves that this function satisfies the following properties: Vp(x, y) U(x, y) for all x, y ∈ R and EUp(fn, gn) EU(fn−1, gn−1) · · · EU(f0, g0) = 0

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-18
SLIDE 18

Lemma (G. Wang (1995))

Let U : R × R → R which is ”smooth” (outside the origin with certain bounds, . . . ) and satisfying (for all h, k ∈ R) Uxx(x, y)|h|2 + 2Uxy(x, y)hk + Uyy(x, y)|k|2 −ci(x, y)(|h|2 − |k|2). Then if X, Y are two martingales such that Y << X, there is a nondecreasing sequence (τn)n1 of stopping times converging to infinity such that EU(Xτn∧t, Yτn∧t) EU(X0, Y0), n = 1, 2, . . . . Example satisfying Wang’s Lemma is Burkholder’s function: Up(x, y) = p

  • 1 − 1

p p−1 ((p − 1)|y| − |x|)(|x| + |y|)p−1, 1 < p < 2

Lemma

The function also has (1 < p < 2) Up(x, y) (p − 1)p|y|p − |x|p +

  • 1 − p
  • 1 − 1

p p−1 ((p − 1)|y| − |x|)2 (|x| + |y|)2−p

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-19
SLIDE 19
  • 1 − p
  • 1 − 1

p p−1 E((p − 1)|Y∞| − |X∞|)2 (|X∞| + |Y∞|)2−p ||X||p

p − (p − 1)p||Y ||p p

(1 − (1 − (p − 1)ε)p) ||X||p

p

p(p − 1)ε||X||p

p.

This, H¨

  • lder inequality, and Burkholder’s estimate yield

||(p − 1)|Y∞| − |X∞|||p

  • E

((p − 1)|Y∞| − |X∞|)2 (|X∞| + |Y∞|)2−p 1/2 |||X∞| + |Y∞|||

(2−p) 2

p

  p(p − 1)ε 1 − p

  • 1 − 1

p

p−1   

1/2

||X||p/2

p

·

  • p

p − 1||X||p (2−p)

2

.

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-20
SLIDE 20

2 < p < ∞ we consider Up(x, y) =        p

  • 1 − 1

p p−1 (|y| − (p − 1)|x|)(|x| + |y|)p−1 if |y| (p − 2)|x|, −(p − 1)2p−2 pp−2 |x|p if |y| < (p − 2)|x|.

Lemma (Up satisfies Wang’s Lemma and)

Up(x, y) |y|p − (p − 1)p|x|p + αp

  • |y| − (p − 1)|x|
  • p,

αp = p − 2 p − 1 1 2 − 1 e

  • .

αp

  • |Y∞| − (p − 1)|X∞|
  • p

p (p − 1)p||X||p p − ||Y ||p p

  • (p − 1)p − (p − 1 − ε)p

||X||p

p

p(p − 1)p−1ε||X||p

p.

  • R. Ba˜

nuelos (Purdue) May 19, 2017

slide-21
SLIDE 21

Thank You!

  • R. Ba˜

nuelos (Purdue) May 19, 2017