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Optimal order digital nets and sequences Takashi Goda University of - - PowerPoint PPT Presentation

Optimal order digital nets and sequences Takashi Goda University of Tokyo Joint work with Kosuke Suzuki and Takehito Yoshiki RICAM Discrepancy Workshop, November 2018 Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM


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Optimal order digital nets and sequences

Takashi Goda

University of Tokyo

Joint work with Kosuke Suzuki and Takehito Yoshiki RICAM Discrepancy Workshop, November 2018

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 1 / 36

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This talk is

NOT directly about discrepancy... BUT about how the idea from discrepancy problem can be used to

  • btain some results in numerical integration.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 2 / 36

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This talk is

NOT directly about discrepancy... BUT about how the idea from discrepancy problem can be used to

  • btain some results in numerical integration.

The following is a list of our papers which this talk is based on.

▶ TG, K. Suzuki, T. Yoshiki: Optimal order quadrature error bounds for

infinite-dimensional higher-order digital sequences, Found. Comput. Math. 18 (2018) 433–458.

▶ TG, K. Suzuki, T. Yoshiki: Optimal order quasi-Monte Carlo integration in

weighted Sobolev spaces of arbitrary smoothness, IMA J. Numer. Anal. 37 (2017), 505–518.

▶ TG, K. Suzuki, T. Yoshiki: An explicit construction of optimal order

quasi-Monte Carlo rules for smooth integrands, SIAM J. Numer. Anal. 54 (2016), 2664–2683.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 2 / 36

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Lp-discrepancy

Definition

For an N-element point set P ⊂ [0, 1]s, the Lp-discrepancy is defined by (Lp(P))p := ∫

[0,1]s

  • 1

N ∑

x∈P

1x∈[0,y) − λ([0, y))

  • p

dy, where λ denotes the Lebesgue measure in Rs.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 3 / 36

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Lp-discrepancy

Definition

For an N-element point set P ⊂ [0, 1]s, the Lp-discrepancy is defined by (Lp(P))p := ∫

[0,1]s

  • 1

N ∑

x∈P

1x∈[0,y) − λ([0, y))

  • p

dy, where λ denotes the Lebesgue measure in Rs. In case of p = 2, (L2(P))2 = 1 3s − 2 N ∑

x∈P s

j=1

1 − x2

j

2 + 1 N2 ∑

x,y∈P s

j=1

min(1 − xj, 1 − yj).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 3 / 36

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Quasi-Monte Carlo (QMC) integration

Problem

Approximate/Estimate I(f ) := ∫

[0,1]s f (x) dx,

where s ∈ N and f : [0, 1]s → R is integrable.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 4 / 36

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Quasi-Monte Carlo (QMC) integration

Problem

Approximate/Estimate I(f ) := ∫

[0,1]s f (x) dx,

where s ∈ N and f : [0, 1]s → R is integrable. Choose an N-element point set P ⊂ [0, 1]s. Approximate I(f ) by QP(f ) := 1 N ∑

x∈P

f (x). For an infinite sequence of points S = {xn | n ≥ 0}, the first N elements of S are used as P.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 4 / 36

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Worst-case error

Definition

For a function space V with norm ∥ · ∥V , ewor(V , P) := sup

∥f ∥V ≤1

|QP(f ) − I(f )|.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 5 / 36

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Worst-case error

Definition

For a function space V with norm ∥ · ∥V , ewor(V , P) := sup

∥f ∥V ≤1

|QP(f ) − I(f )|. We want to construct a good P depending on V . When V is an RKHS with kernel K, (ewor(V , P))2 = ∫

[0,1]s

[0,1]s K(x, y) dx dy

− 2 N ∑

x∈P

[0,1]s K(x, y) dy + 1

N2 ∑

x,y∈P

K(x, y).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 5 / 36

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L2-discrepancy (again)

Let us consider an RKHS with K ∗

1,s(x, y) = s

j=1

min(1 − xj, 1 − yj). The L2-discrepancy of P is same as the worst-case error in this RKHS.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 6 / 36

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L2-discrepancy (again)

Let us consider an RKHS with K ∗

1,s(x, y) = s

j=1

min(1 − xj, 1 − yj). The L2-discrepancy of P is same as the worst-case error in this RKHS. This RKHS is V = H∗

1,s = s

j=1

H∗

1

where H∗

1 =

{ f : [0, 1] → R | f (1) = 0, f (1) ∈ L2 } .

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 6 / 36

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Optimal order QMC for L2-discrepancy

QMC point sets, which achieve the optimal order worst-case error in this RKHS, also achieve the optimal order L2-discrepancy: L2(P) ≍ (log N)(s−1)/2 N .

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 7 / 36

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Optimal order QMC for L2-discrepancy

QMC point sets, which achieve the optimal order worst-case error in this RKHS, also achieve the optimal order L2-discrepancy: L2(P) ≍ (log N)(s−1)/2 N . For s = 1 and s = 2, there are many explicit constructions of such point sets. But for s ≥ 3, we only know the results from

1 Chen and Skriganov (2002), Skriganov (2006) 2 Dick and Pillichshammer (2014), Dick, Hinrichs, Markhasin and

Pillichshammer (2017): higher order digital nets/sequences

3 Levin (2018): Halton sequences Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 7 / 36

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Sobolev spaces of our interest

In this work we consider functions of higher smoothness: V = Hα,s =

s

j=1

Hα, where α ≥ 2 and Hα = { f : [0, 1] → R | f (r) : abs. conti. for 0 ≤ r ≤ α − 1, f (α) ∈ L2 } .

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 8 / 36

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Sobolev spaces of our interest

In this work we consider functions of higher smoothness: V = Hα,s =

s

j=1

Hα, where α ≥ 2 and Hα = { f : [0, 1] → R | f (r) : abs. conti. for 0 ≤ r ≤ α − 1, f (α) ∈ L2 } . Hα,s coincides with an RKHS with kernel Kα,s(x, y) =

s

j=1

[ α ∑

r=0

Br(xj)Br(yj) (r!)2 + (−1)α+1 B2α(|xj − yj|) (2α)! ] , where Br denotes the Bernoulli poly. of degree r (Wahba, 1990).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 8 / 36

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Higher order convergence

Known results (Dick, 2008; Baldeaux and Dick, 2009)

Higher order digital nets/sequences achieve ewor(Hα,s, P) ≪ (log N)c(α,s) Nα . c(α, s) = αs is obtained for order α digital nets. The best possible exponent of log N term is (s − 1)/2 (for linear quadrature algorithm).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 9 / 36

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Higher order convergence

Known results (Dick, 2008; Baldeaux and Dick, 2009)

Higher order digital nets/sequences achieve ewor(Hα,s, P) ≪ (log N)c(α,s) Nα . c(α, s) = αs is obtained for order α digital nets. The best possible exponent of log N term is (s − 1)/2 (for linear quadrature algorithm).

Aim of this talk

Prove that higher order digital nets/sequences achieve the optimal order of convergence ewor(Hα,s, P) ≪ (log N)(s−1)/2 Nα .

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 9 / 36

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Main result

Theorem (G., Suzuki and Yoshiki, 2018)

For α ≥ 2, order 2α + 1 digital nets/sequences in prime base b achieve ewor(Hα,s, P) ≍ (log N)(s−1)/2 Nα for N = bm with m ∈ N.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 10 / 36

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In the rest of this talk

I focus on

1 nets, and 2 an upper bound. (Remark: A lower bound follows from the “bumping

function” argument by Bakhvalov (1959).)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 11 / 36

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In the rest of this talk

I focus on

1 nets, and 2 an upper bound. (Remark: A lower bound follows from the “bumping

function” argument by Bakhvalov (1959).) I want to

1 introduce higher order digital nets, and 2 show a sketch of our proof for the main result by highlighting an

analogy to the proof by Dick and Pillichshammer (2014), who proved the optimal order L2-discrepancy bound for order 3 digital nets.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 11 / 36

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Digital nets

Definition (Niederreiter, 1992)

For prime b, Fb denotes the b-element field.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 12 / 36

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Digital nets

Definition (Niederreiter, 1992)

For prime b, Fb denotes the b-element field. For s, m, n ∈ N, let C1, . . . , Cs ∈ Fn×m

b

.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 12 / 36

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Digital nets

Definition (Niederreiter, 1992)

For prime b, Fb denotes the b-element field. For s, m, n ∈ N, let C1, . . . , Cs ∈ Fn×m

b

. For 0 ≤ h < bm, write h = η0 + η1b + · · · + ηm−1bm−1.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 12 / 36

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Digital nets

Definition (Niederreiter, 1992)

For prime b, Fb denotes the b-element field. For s, m, n ∈ N, let C1, . . . , Cs ∈ Fn×m

b

. For 0 ≤ h < bm, write h = η0 + η1b + · · · + ηm−1bm−1. For 1 ≤ j ≤ s, let xh,j = ξ1,h,j b + · · · + ξn,h,j bn ∈ [0, 1], where (ξ1,h,j, . . . , ξn,h,j)⊤ = Cj · (η0, . . . , ηm−1)⊤ ∈ Fn

b.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 12 / 36

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Digital nets

Definition (Niederreiter, 1992)

For prime b, Fb denotes the b-element field. For s, m, n ∈ N, let C1, . . . , Cs ∈ Fn×m

b

. For 0 ≤ h < bm, write h = η0 + η1b + · · · + ηm−1bm−1. For 1 ≤ j ≤ s, let xh,j = ξ1,h,j b + · · · + ξn,h,j bn ∈ [0, 1], where (ξ1,h,j, . . . , ξn,h,j)⊤ = Cj · (η0, . . . , ηm−1)⊤ ∈ Fn

b.

Set xh = (xh,1, . . . , xh,s) ∈ [0, 1]s.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 12 / 36

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Digital nets

Definition (Niederreiter, 1992)

For prime b, Fb denotes the b-element field. For s, m, n ∈ N, let C1, . . . , Cs ∈ Fn×m

b

. For 0 ≤ h < bm, write h = η0 + η1b + · · · + ηm−1bm−1. For 1 ≤ j ≤ s, let xh,j = ξ1,h,j b + · · · + ξn,h,j bn ∈ [0, 1], where (ξ1,h,j, . . . , ξn,h,j)⊤ = Cj · (η0, . . . , ηm−1)⊤ ∈ Fn

b.

Set xh = (xh,1, . . . , xh,s) ∈ [0, 1]s. We call P = {xh : 0 ≤ h < bm} a digital net over Fb with generating matrices C1, . . . , Cs.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 12 / 36

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Dual net

Definition

The dual net of P with C1, . . . , Cs is defined by P⊥ = { (k1, . . . , ks) ∈ Ns

0 : C ⊤ 1 ⃗

k1 ⊕ · · · ⊕ C ⊤

s ⃗

ks = 0 ∈ Fm

b

} , where we write ⃗ k = (κ0, . . . , κn−1) ∈ Fn

b

for k = κ0 + κ1b + · · · .

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 13 / 36

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NRT metric and (t, m, s)-nets

For k = κ1ba1−1 + · · · + κvbav−1 with κi ∈ {1, . . . , b − 1} and a1 > a2 > · · · , the NRT metric is µ1(k) = a1 and µ1(k1, . . . , ks) =

s

j=1

µ1(kj).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 14 / 36

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NRT metric and (t, m, s)-nets

For k = κ1ba1−1 + · · · + κvbav−1 with κi ∈ {1, . . . , b − 1} and a1 > a2 > · · · , the NRT metric is µ1(k) = a1 and µ1(k1, . . . , ks) =

s

j=1

µ1(kj).

Definition

We call P a digital (t, m, s)-net if µ1(P⊥) := min

k∈P⊥\{0} µ1(k) ≥ m − t + 1.

(Constructions: Sobol’, Faure, Niederreiter, Tezuka, Niederreiter-Xing, ...)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 14 / 36

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Dick metric and higher order nets

Let α ∈ N. For k = κ1ba1−1 + · · · + κvbav−1 with κi ∈ {1, . . . , b − 1} and a1 > a2 > · · · , the Dick metric is µα(k) = a1 + · · · + amin(v,α) and µα(k1, . . . , ks) =

s

j=1

µα(kj). α = 1: the NRT metric.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 15 / 36

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Dick metric and higher order nets

Let α ∈ N. For k = κ1ba1−1 + · · · + κvbav−1 with κi ∈ {1, . . . , b − 1} and a1 > a2 > · · · , the Dick metric is µα(k) = a1 + · · · + amin(v,α) and µα(k1, . . . , ks) =

s

j=1

µα(kj). α = 1: the NRT metric.

Definition

We call P an order α digital (t, m, s)-net if µα(P⊥) := min

k∈P⊥\{0} µα(k) ≥ αm − t + 1.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 15 / 36

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Explicit construction

Define Dα : [0, 1]α → [0, 1] by            x1 = (0.ξ1,1ξ2,1ξ3,1 . . .)b x2 = (0.ξ1,2ξ2,2ξ3,2 . . .)b . . . xα = (0.ξ1,αξ2,αξ3,α . . .)b. → (0. ξ1,1ξ1,2 . . . ξ1,α

  • α

ξ2,1ξ2,2 . . . ξ2,α

  • α

. . .)b. For x ∈ [0, 1]αs, we write Dα(x) = (Dα(x1, . . . , xα), . . . , Dα(xα(s−1)+1, . . . , xαs)) ∈ [0, 1]s.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 16 / 36

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Explicit construction

Define Dα : [0, 1]α → [0, 1] by            x1 = (0.ξ1,1ξ2,1ξ3,1 . . .)b x2 = (0.ξ1,2ξ2,2ξ3,2 . . .)b . . . xα = (0.ξ1,αξ2,αξ3,α . . .)b. → (0. ξ1,1ξ1,2 . . . ξ1,α

  • α

ξ2,1ξ2,2 . . . ξ2,α

  • α

. . .)b. For x ∈ [0, 1]αs, we write Dα(x) = (Dα(x1, . . . , xα), . . . , Dα(xα(s−1)+1, . . . , xαs)) ∈ [0, 1]s.

Theorem (Dick, 2007)

Let P be a digital (t, m, αs)-net. Then Dα(P) is an order α digital (tα, m, s)-net with tα ≤ α min {m, t + ⌊s(α − 1)/2⌋} .

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 16 / 36

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Another look at construction

Let P be a digital (t, m, αs)-net with C1, . . . , Cαs ∈ Fm×m

b

. We write C1 =    c1,1 . . . cm,1    , . . . , Cα =    c1,α . . . cm,α    , Cα+1 =    c1,α+1 . . . cm,α+1    . . . .

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 17 / 36

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Another look at construction

Let P be a digital (t, m, αs)-net with C1, . . . , Cαs ∈ Fm×m

b

. We write C1 =    c1,1 . . . cm,1    , . . . , Cα =    c1,α . . . cm,α    , Cα+1 =    c1,α+1 . . . cm,α+1    . . . . Dα(P) is a digital net with D1, . . . , Ds ∈ Fαm×m

b

where D1 =              c1,1 . . . c1,α . . . cm,1 . . . cm,α              , D2 =              c1,α+1 . . . c1,2α . . . cm,α+1 . . . cm,2α              , . . . .

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 17 / 36

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Toward the proof: Walsh functions

Definition

For k = κ0 + κ1b + · · · , the k-th Walsh function walk is defined by walk(x) := exp [2πi b (κ0ξ1 + κ1ξ2 + · · · ) ] , where x = ξ1/b + ξ2/b2 + · · · . For vectors k ∈ Ns

0, we define

walk(x) :=

s

j=1

walkj(xj).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 18 / 36

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ONB

The set {walk : k ∈ Ns

0} forms an ONB in L2([0, 1]s).

Therefore, in general, we have K(x, y) = ∑

k,l∈Ns

ˆ K(k, l)walk(x)wall(y), where ˆ K(k, l) is the (k, l)-th Walsh coefficient ˆ K(k, l) = ∫

[0,1]s

[0,1]s K(x, y)walk(x)wall(y) dx dy.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 19 / 36

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Character property

Lemma

Let P be a digital net with C1, . . . , Cs ∈ Fn×m

b

. We have ∑

x∈P

walk(x) = { bm = N if k ∈ P⊥,

  • therwise.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 20 / 36

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Worst-case error for digital nets

Lemma

For an RKHS V with kernel K and a digital net P, (ewor(V , P))2 = ∑

k,l∈P⊥\{0}

ˆ K(k, l).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 21 / 36

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Worst-case error for digital nets

Lemma

For an RKHS V with kernel K and a digital net P, (ewor(V , P))2 = ∑

k,l∈P⊥\{0}

ˆ K(k, l). Proof: Recall the following explicit formula (ewor(V , P))2 = ∫

[0,1]s

[0,1]s K(x, y) dx dy

− 2 N ∑

x∈P

[0,1]s K(x, y) dy + 1

N2 ∑

x,y∈P

K(x, y).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 21 / 36

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Worst-case error for digital nets (continued)

The first term is ∫

[0,1]s

[0,1]s K(x, y) dx dy = ˆ

K(0, 0).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 22 / 36

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Worst-case error for digital nets (continued)

The first term is ∫

[0,1]s

[0,1]s K(x, y) dx dy = ˆ

K(0, 0). The second term is 2 N ∑

x∈P

[0,1]s K(x, y) dy

= 1 N ∑

x∈P

[0,1]s K(x, y) dy + 1

N ∑

x∈P

[0,1]s K(y, x) dy

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 22 / 36

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Worst-case error for digital nets (continued)

The first term is ∫

[0,1]s

[0,1]s K(x, y) dx dy = ˆ

K(0, 0). The second term is 2 N ∑

x∈P

[0,1]s K(x, y) dy

= 1 N ∑

x∈P

[0,1]s K(x, y) dy + 1

N ∑

x∈P

[0,1]s K(y, x) dy

= 1 N ∑

x∈P

k∈Ns

ˆ K(k, 0)walk(x) + 1 N ∑

x∈P

l∈Ns

ˆ K(0, l)wall(x)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 22 / 36

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Worst-case error for digital nets (continued)

The first term is ∫

[0,1]s

[0,1]s K(x, y) dx dy = ˆ

K(0, 0). The second term is 2 N ∑

x∈P

[0,1]s K(x, y) dy

= 1 N ∑

x∈P

[0,1]s K(x, y) dy + 1

N ∑

x∈P

[0,1]s K(y, x) dy

= 1 N ∑

x∈P

k∈Ns

ˆ K(k, 0)walk(x) + 1 N ∑

x∈P

l∈Ns

ˆ K(0, l)wall(x) = ∑

k∈P⊥

ˆ K(k, 0) + ∑

l∈P⊥

ˆ K(0, l).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 22 / 36

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Worst-case error for digital nets (continued)

Finally, the third term is 1 N2 ∑

x,y∈P

K(x, y) = 1 N2 ∑

x,y∈P

k,l∈Ns

ˆ K(k, l)walk(x)wall(y)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 23 / 36

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Worst-case error for digital nets (continued)

Finally, the third term is 1 N2 ∑

x,y∈P

K(x, y) = 1 N2 ∑

x,y∈P

k,l∈Ns

ˆ K(k, l)walk(x)wall(y) = ∑

k,l∈Ns

ˆ K(k, l) 1 N ∑

x∈P

walk(x) 1 N ∑

y∈P

wall(y)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 23 / 36

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Worst-case error for digital nets (continued)

Finally, the third term is 1 N2 ∑

x,y∈P

K(x, y) = 1 N2 ∑

x,y∈P

k,l∈Ns

ˆ K(k, l)walk(x)wall(y) = ∑

k,l∈Ns

ˆ K(k, l) 1 N ∑

x∈P

walk(x) 1 N ∑

y∈P

wall(y) = ∑

k,l∈P⊥

ˆ K(k, l).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 23 / 36

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SLIDE 48

Worst-case error for digital nets (continued)

Finally, the third term is 1 N2 ∑

x,y∈P

K(x, y) = 1 N2 ∑

x,y∈P

k,l∈Ns

ˆ K(k, l)walk(x)wall(y) = ∑

k,l∈Ns

ˆ K(k, l) 1 N ∑

x∈P

walk(x) 1 N ∑

y∈P

wall(y) = ∑

k,l∈P⊥

ˆ K(k, l). Altogether we have (ewor(V , P))2 = ˆ K(0, 0) − ∑

k∈P⊥

ˆ K(k, 0) − ∑

l∈P⊥

ˆ K(0, l) + ∑

k,l∈P⊥

ˆ K(k, l) = ∑

k,l∈P⊥\{0}

ˆ K(k, l).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 23 / 36

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SLIDE 49

Learning from L2-discrepancy for digital nets

For a digital net P, (L2(P))2 = ∑

k,l∈P⊥\{0}

ˆ K ∗

1,s(k, l),

where K ∗

1,s(x, y) = s

j=1

min(1 − xj, 1 − yj). Constructions of digital nets with optimal order L2-discrepancy ✄ Chen and Skriganov (2002) ✄ Dick and Pillichshammer (2014): order 3 digital nets

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 24 / 36

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SLIDE 50

Learning from L2-discrepancy for digital nets

For a digital net P, (L2(P))2 = ∑

k,l∈P⊥\{0}

ˆ K ∗

1,s(k, l),

where K ∗

1,s(x, y) = s

j=1

min(1 − xj, 1 − yj). Constructions of digital nets with optimal order L2-discrepancy ✄ Chen and Skriganov (2002) ✄ Dick and Pillichshammer (2014): order 3 digital nets

Common idea

is to exploit the decay and the sparsity of ˆ K ∗

1,s.

Decay: ˆ K ∗

1,s(k, l) ≪ b−µ1(k)−µ1(l)

Sparsity: ˆ K ∗

1,s(k, l) = 0

for many (k, l)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 24 / 36

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SLIDE 51

Rough sketch: Optimal order L2-discrepancy bounds

P: an order 3 digital (t, m, s)-net (L2(P))2 = ∑

k,l∈P⊥\{0}

ˆ K ∗

1,s(k, l)

(Dick and Pillichshammer, 2014)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 25 / 36

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SLIDE 52

Rough sketch: Optimal order L2-discrepancy bounds

P: an order 3 digital (t, m, s)-net (L2(P))2 = ∑

k,l∈P⊥\{0}

ˆ K ∗

1,s(k, l) ≪

k,l∈P⊥\{0} ˆ K ∗

1,s(k,l)̸=0

b−µ1(k)−µ1(l) (Dick and Pillichshammer, 2014)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 25 / 36

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SLIDE 53

Rough sketch: Optimal order L2-discrepancy bounds

P: an order 3 digital (t, m, s)-net (L2(P))2 = ∑

k,l∈P⊥\{0}

ˆ K ∗

1,s(k, l) ≪

k,l∈P⊥\{0} ˆ K ∗

1,s(k,l)̸=0

b−µ1(k)−µ1(l) =

z=2µ1(P⊥)

b−z

  • {(k, l) ∈ (P⊥ \ {0})2 : µ1(k) + µ1(l) = z, ˆ

K ∗

1,s(k, l) ̸= 0}

  • (Dick and Pillichshammer, 2014)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 25 / 36

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SLIDE 54

Rough sketch: Optimal order L2-discrepancy bounds

P: an order 3 digital (t, m, s)-net (L2(P))2 = ∑

k,l∈P⊥\{0}

ˆ K ∗

1,s(k, l) ≪

k,l∈P⊥\{0} ˆ K ∗

1,s(k,l)̸=0

b−µ1(k)−µ1(l) =

z=2µ1(P⊥)

b−z

  • {(k, l) ∈ (P⊥ \ {0})2 : µ1(k) + µ1(l) = z, ˆ

K ∗

1,s(k, l) ̸= 0}

ms−1 b2µ1(P⊥) ≪ ms−1 b2m = (logb N)s−1 N2 . (Dick and Pillichshammer, 2014)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 25 / 36

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SLIDE 55

If only the decay of ˆ Kα,s is considered

(ewor(Hα,s, P))2 = ∑

k,l∈P⊥\{0}

ˆ Kα,s(k, l), where Kα,s(x, y) =

s

j=1

[ α ∑

r=0

Br(xj)Br(yj) (r!)2 + (−1)α+1 B2α(|xj − yj|) (2α)! ] .

Lemma (Baldeaux and Dick, 2009)

For k, l ∈ Ns

0,

ˆ Kα,s(k, l) ≪ b−µα(k)−µα(l).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 26 / 36

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SLIDE 56

Rough sketch: Nearly optimal order error bounds

P: an order α digital (t, m, s)-net (ewor(Hα,s, P))2 = ∑

k,l∈P⊥\{0}

ˆ Kα,s(k, l)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 27 / 36

slide-57
SLIDE 57

Rough sketch: Nearly optimal order error bounds

P: an order α digital (t, m, s)-net (ewor(Hα,s, P))2 = ∑

k,l∈P⊥\{0}

ˆ Kα,s(k, l) ≪ ∑

k,l∈P⊥\{0}

b−µα(k)−µα(l)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 27 / 36

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SLIDE 58

Rough sketch: Nearly optimal order error bounds

P: an order α digital (t, m, s)-net (ewor(Hα,s, P))2 = ∑

k,l∈P⊥\{0}

ˆ Kα,s(k, l) ≪ ∑

k,l∈P⊥\{0}

b−µα(k)−µα(l) =

z=2µα(P⊥)

b−z

  • {(k, l) ∈ (P⊥ \ {0})2 : µα(k) + µα(l) = z}
  • Takashi Goda (U. Tokyo)

Optimal order digital nets and sequences RICAM Workshop 27 / 36

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SLIDE 59

Rough sketch: Nearly optimal order error bounds

P: an order α digital (t, m, s)-net (ewor(Hα,s, P))2 = ∑

k,l∈P⊥\{0}

ˆ Kα,s(k, l) ≪ ∑

k,l∈P⊥\{0}

b−µα(k)−µα(l) =

z=2µα(P⊥)

b−z

  • {(k, l) ∈ (P⊥ \ {0})2 : µα(k) + µα(l) = z}

m2αs b2µα(P⊥) ≪ m2αs b2αm = (logb N)2αs N2α . The exponent of log N terms comes from the counting step with respect to µα-metric.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 27 / 36

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SLIDE 60

Effect of switching the metric

Counting along µα-metric gives

  • {k ∈ P⊥ \ {0} : µα(k) = z}
  • ≪ bz−αmmαs

for z ≥ µα(P⊥),

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 28 / 36

slide-61
SLIDE 61

Effect of switching the metric

Counting along µα-metric gives

  • {k ∈ P⊥ \ {0} : µα(k) = z}
  • ≪ bz−αmmαs

for z ≥ µα(P⊥), while counting along µ1-metric gives

  • {k ∈ P⊥ \ {0} : µ1(k) = z}
  • ≪ bz−mms−1

for z ≥ µ1(P⊥).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 28 / 36

slide-62
SLIDE 62

Effect of switching the metric

Counting along µα-metric gives

  • {k ∈ P⊥ \ {0} : µα(k) = z}
  • ≪ bz−αmmαs

for z ≥ µα(P⊥), while counting along µ1-metric gives

  • {k ∈ P⊥ \ {0} : µ1(k) = z}
  • ≪ bz−mms−1

for z ≥ µ1(P⊥). We want to

1 switch the metric from µα to µ1, and 2 exploit the sparsity of ˆ

Kα,s to deal with the double sum ∑

k,l∈P⊥\{0}.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 28 / 36

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SLIDE 63

Analogy to L2-discrepancy problem

(ewor(Hα,s, P))2 = ∑

k,l∈P⊥\{0}

ˆ Kα,s(k, l).

Exploit the decay and the sparsity of ˆ Kα,s

Decay: ˆ Kα,s(k, l) ≪ b−µα(k)−µα(l) (Baldeaux and Dick, 2009) Sparsity: ˆ Kα,s(k, l) = 0 for many (k, l) (G., Suzuki and Yoshiki, 2018)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 29 / 36

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SLIDE 64

Analogy to L2-discrepancy problem + ϵ

In order to switch the metric in the counting step, we need:

Additional tricks

Propagation: P: order 2α + 1 net ⇒ P: order 1 net (Dick, 2008) Interpolation: µα(k) ≥ Aµ2α+1(k) + Bµ1(k) where A = α − 1 2α and B = α + 1 2α (G., Suzuki and Yoshiki, 2017). The interpolation inequality on µα is nothing but Jensen’s inequality with respect to α.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 30 / 36

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SLIDE 65

Remark: how sparse is ˆ Kα,s?

Let k =

v

i=1

κibci−1 and l =

w

i=1

λibdi−1, such that c1 > c2 > · · · , d1 > d2 > · · · and κi, λi ∈ {1, . . . , b − 1}.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 31 / 36

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SLIDE 66

Remark: how sparse is ˆ Kα,s?

Let k =

v

i=1

κibci−1 and l =

w

i=1

λibdi−1, such that c1 > c2 > · · · , d1 > d2 > · · · and κi, λi ∈ {1, . . . , b − 1}. For p, q ∈ N0, we write k(p) =

v

i=p+1

κibci−1 and l(q) =

w

i=q+1

λibdi−1 where the empty sum is set to 0.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 31 / 36

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SLIDE 67

Remark: how sparse is ˆ Kα,s?

Let k =

v

i=1

κibci−1 and l =

w

i=1

λibdi−1, such that c1 > c2 > · · · , d1 > d2 > · · · and κi, λi ∈ {1, . . . , b − 1}. For p, q ∈ N0, we write k(p) =

v

i=p+1

κibci−1 and l(q) =

w

i=q+1

λibdi−1 where the empty sum is set to 0. We say “(k, l) is of type (p, q)” if k(p) = l(q) and κpbcp−1 ̸= λqbdq−1.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 31 / 36

slide-68
SLIDE 68

Remark: how sparse is ˆ Kα,s?

Let k =

v

i=1

κibci−1 and l =

w

i=1

λibdi−1, such that c1 > c2 > · · · , d1 > d2 > · · · and κi, λi ∈ {1, . . . , b − 1}. For p, q ∈ N0, we write k(p) =

v

i=p+1

κibci−1 and l(q) =

w

i=q+1

λibdi−1 where the empty sum is set to 0. We say “(k, l) is of type (p, q)” if k(p) = l(q) and κpbcp−1 ̸= λqbdq−1.

Lemma (G., Suzuki and Yoshiki, 2018)

If there exists one index j ∈ {1, . . . , s} such that (kj, lj) is of type (pj, qj) with pj + qj > 2α, then ˆ Kα,s(k, l) = 0.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 31 / 36

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SLIDE 69

Rough sketch: Optimal order error bounds

P: an order 2α + 1 digital (t, m, s)-net (ewor(Hα,s, P))2 = ∑

k,l∈P⊥\{0}

ˆ Kα,s(k, l)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 32 / 36

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SLIDE 70

Rough sketch: Optimal order error bounds

P: an order 2α + 1 digital (t, m, s)-net (ewor(Hα,s, P))2 = ∑

k,l∈P⊥\{0}

ˆ Kα,s(k, l) ≪ ∑

k,l∈P⊥\{0} ˆ Kα,s(k,l)̸=0

b−µα(k)−µα(l)

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 32 / 36

slide-71
SLIDE 71

Rough sketch: Optimal order error bounds

P: an order 2α + 1 digital (t, m, s)-net (ewor(Hα,s, P))2 = ∑

k,l∈P⊥\{0}

ˆ Kα,s(k, l) ≪ ∑

k,l∈P⊥\{0} ˆ Kα,s(k,l)̸=0

b−µα(k)−µα(l) ≤ b−2Aµ2α+1(P⊥) ∑

k,l∈P⊥\{0} ˆ Kα,s(k,l)̸=0

b−B(µ1(k)+µ1(l))

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 32 / 36

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SLIDE 72

Rough sketch: Optimal order error bounds

P: an order 2α + 1 digital (t, m, s)-net (ewor(Hα,s, P))2 = ∑

k,l∈P⊥\{0}

ˆ Kα,s(k, l) ≪ ∑

k,l∈P⊥\{0} ˆ Kα,s(k,l)̸=0

b−µα(k)−µα(l) ≤ b−2Aµ2α+1(P⊥) ∑

k,l∈P⊥\{0} ˆ Kα,s(k,l)̸=0

b−B(µ1(k)+µ1(l)) = b−2Aµ2α+1(P⊥)

z=2µ1(P⊥)

b−Bz ×

  • {(k, l) ∈ (P⊥ \ {0})2 : µ1(k) + µ1(l) = z, ˆ

Kα,s(k, l) ̸= 0}

  • Takashi Goda (U. Tokyo)

Optimal order digital nets and sequences RICAM Workshop 32 / 36

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SLIDE 73

Rough sketch: Optimal order error bounds

P: an order 2α + 1 digital (t, m, s)-net (ewor(Hα,s, P))2 = ∑

k,l∈P⊥\{0}

ˆ Kα,s(k, l) ≪ ∑

k,l∈P⊥\{0} ˆ Kα,s(k,l)̸=0

b−µα(k)−µα(l) ≤ b−2Aµ2α+1(P⊥) ∑

k,l∈P⊥\{0} ˆ Kα,s(k,l)̸=0

b−B(µ1(k)+µ1(l)) = b−2Aµ2α+1(P⊥)

z=2µ1(P⊥)

b−Bz ×

  • {(k, l) ∈ (P⊥ \ {0})2 : µ1(k) + µ1(l) = z, ˆ

Kα,s(k, l) ̸= 0}

ms−1 b2Aµ2α+1(P⊥)+2Bµ1(P⊥) ≪ ms−1 b2αm = (logb N)s−1 N2α .

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 32 / 36

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SLIDE 74

Some comments

Again I want to stress similarity of the proofs. In the proof of Dick and Pillichshammer (2014), we see

  • {(k, l) ∈ (P⊥ \ {0})2 : µ1(k) + µ1(l) = z, ˆ

K ∗

1,s(k, l) ̸= 0}

  • .

In our proof, we see

  • {(k, l) ∈ (P⊥ \ {0})2 : µ1(k) + µ1(l) = z, ˆ

Kα,s(k, l) ̸= 0}

  • .

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 33 / 36

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SLIDE 75

Some comments

Again I want to stress similarity of the proofs. In the proof of Dick and Pillichshammer (2014), we see

  • {(k, l) ∈ (P⊥ \ {0})2 : µ1(k) + µ1(l) = z, ˆ

K ∗

1,s(k, l) ̸= 0}

  • .

In our proof, we see

  • {(k, l) ∈ (P⊥ \ {0})2 : µ1(k) + µ1(l) = z, ˆ

Kα,s(k, l) ̸= 0}

  • .

On order 2α + 1 digital sequences: The optimal order error bound holds only for a geometric sequence of # of points N = b1, b2, . . .. This cannot be improved for any extensible QMC rule (Owen, 2016).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 33 / 36

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SLIDE 76

Summary

Order 2α + 1 digital nets/sequences achieve the optimal order of convergence for numerical integration in Hα,s = ⊗s

j=1 Hα.

Explicit construction of higher order digital nets and sequences is

  • possible. We obtain an optimal order quadrature rule which is

extensible both in the number of points and the dimension. The main idea of the proof comes from the L2-discrepancy problem together with some additional tricks (interpolation and propagation).

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 34 / 36

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SLIDE 77

“Deep” learning from L2-discrepancy problem?

After the work of Dick and Pillichshammer (2014), it has been proven that order 2 (instead of 3) digital sequences achieve the best possible

  • rder of Lp-discrepancy for all 1 < p < ∞ by

▶ Dick, Hinrichs, Markhasin and Pillichshammer (2017) Israel J. Math.

The proof is based on Haar functions instead of Walsh functions.

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 35 / 36

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SLIDE 78

“Deep” learning from L2-discrepancy problem?

After the work of Dick and Pillichshammer (2014), it has been proven that order 2 (instead of 3) digital sequences achieve the best possible

  • rder of Lp-discrepancy for all 1 < p < ∞ by

▶ Dick, Hinrichs, Markhasin and Pillichshammer (2017) Israel J. Math.

The proof is based on Haar functions instead of Walsh functions. Can we learn further from their result? Is order 2α + 1 best possible?? Does Haar analysis help us??? How about other function spaces (e.g., Besov and Triebel-Lizorkin)? For the case of smoothness less than 2, please refer to

▶ Hinrichs, Markhasin, Oettershagen and Ullrich (2016) Numer. Math.

We do not have any progress on these questions so far...

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 35 / 36

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SLIDE 79

Thank you for your attention!

Takashi Goda (U. Tokyo) Optimal order digital nets and sequences RICAM Workshop 36 / 36