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A randomised lattice rule algorithm with pre-determined generating vector and random number of points for Korobov spaces with $0 < α\le 1/2$

Dirk Nuyens, Laurence Wilkes

TL;DR

This work extends randomised lattice rules for Korobov spaces to the low-smoothness regime $0<\alpha\le 1/2$, where points are shifted to accommodate noncontinuous functions. It introduces a pre-determined generating vector alongside a random number of points (and random shifts for $\alpha\le1/2$) and proves the existence of a vector $\boldsymbol{z}$ that achieves near-optimal randomised error, with explicit bounds shrinking as $n$ grows. The key innovation is the construction of good sets $G_{n,\lambda}$ via primes in $\mathcal{P}_n$ and the Chinese Remainder Theorem, enabling rigorous control over the RMS error and yielding $e^{\text{rms}}=O(n^{-\alpha-1/2+\epsilon})$ for any $\epsilon>0$ by suitable parameter choices. A dimension-independent bound is obtained under a tractability-type condition on the weights, and lower bounds are provided to validate the near-optimality of the method. Overall, the paper generalises prior results for $\alpha>1/2$ to the challenging $0<\alpha\le 1/2$ regime, offering a practical path to improved randomised integration in high dimensions.

Abstract

In previous work (Kuo, Nuyens, Wilkes, 2023), we showed that a lattice rule with a pre-determined generating vector but random number of points can achieve the near optimal convergence of $O(n^{-α-1/2+ε})$, $ε> 0$, for the worst case expected error, commonly referred to as the randomised error, for numerical integration of high-dimensional functions in the Korobov space with smoothness $α> 1/2$. Compared to the optimal deterministic rate of $O(n^{-α+ε})$, $ε> 0$, such a randomised algorithm is capable of an extra half in the rate of convergence. In this paper, we show that a pre-determined generating vector also exists in the case of $0 < α\le 1/2$. Also here we obtain the near optimal convergence of $O(n^{-α-1/2+ε})$, $ε> 0$; or in more detail, we obtain $O(\sqrt{r} \, n^{-α-1/2+1/(2r)+ε'})$ which holds for any choices of $ε' > 0$ and $r \in \mathbb{N}$ with $r > 1/(2α)$.

A randomised lattice rule algorithm with pre-determined generating vector and random number of points for Korobov spaces with $0 < α\le 1/2$

TL;DR

This work extends randomised lattice rules for Korobov spaces to the low-smoothness regime , where points are shifted to accommodate noncontinuous functions. It introduces a pre-determined generating vector alongside a random number of points (and random shifts for ) and proves the existence of a vector that achieves near-optimal randomised error, with explicit bounds shrinking as grows. The key innovation is the construction of good sets via primes in and the Chinese Remainder Theorem, enabling rigorous control over the RMS error and yielding for any by suitable parameter choices. A dimension-independent bound is obtained under a tractability-type condition on the weights, and lower bounds are provided to validate the near-optimality of the method. Overall, the paper generalises prior results for to the challenging regime, offering a practical path to improved randomised integration in high dimensions.

Abstract

In previous work (Kuo, Nuyens, Wilkes, 2023), we showed that a lattice rule with a pre-determined generating vector but random number of points can achieve the near optimal convergence of , , for the worst case expected error, commonly referred to as the randomised error, for numerical integration of high-dimensional functions in the Korobov space with smoothness . Compared to the optimal deterministic rate of , , such a randomised algorithm is capable of an extra half in the rate of convergence. In this paper, we show that a pre-determined generating vector also exists in the case of . Also here we obtain the near optimal convergence of , ; or in more detail, we obtain which holds for any choices of and with .
Paper Structure (5 sections, 5 theorems, 63 equations)

This paper contains 5 sections, 5 theorems, 63 equations.

Key Result

Lemma 1

For $\lambda \in (0,\alpha)$ and prime $p$, the set $G_\lambda^{(p)}$ satisfies the condition

Theorems & Definitions (10)

  • Lemma 1
  • proof
  • Lemma 2
  • proof
  • Lemma 3
  • proof
  • Theorem 1
  • proof
  • Theorem 2
  • proof