Ryuichi Ohori

Matsumoto Makoto, Ryuichi Ohori, Takehito Yoshiki

In this paper, we consider Quasi-Monte Carlo (QMC) worst case error of weighted smooth function classes in $C^\infty[0,1]^s$ by a digital net over $\mathbb F_2$. We show that the ratio of the worst case error to the QMC integration error of an exponential function is bounded above and below by constants. This result provides us with a simple interpretation that a digital net with small QMC integration error for an exponential function also gives the small integration error for any function in this function space.

Makoto Matsumoto, Ryuichi Ohori

Fix an integer $s$. Let $f:[0,1)^s \to \mathbb R$ be an integrable function. Let $P\subset [0,1]^s$ be a finite point set. Quasi-Monte Carlo integration of $f$ by $P$ is the average value of $f$ over $P$ that approximates the integration of $f$ over the $s$-dimensional cube. Koksma-Hlawka inequality tells that, by a smart choice of $P$, one may expect that the error decreases roughly $O(N^{-1}(\log N)^s)$. For any $α\geq 1$, J.\ Dick gave a construction of point sets such that for $α$-smooth $f$, convergence rate $O(N^{-α}(\log N)^{sα})$ is assured. As a coarse version of his theory, M-Saito-Matoba introduced Walsh figure of Merit (WAFOM), which gives the convergence rate $O(N^{-C\log N/s})$. WAFOM is efficiently computable. By a brute-force search of low WAFOM point sets, we observe a convergence rate of order $N^{-α}$ with $α>1$, for several test integrands for $s=4$ and $8$.

Takashi Goda, Ryuichi Ohori, Kosuke Suzuki et al.

In this paper, we study randomized quasi-Monte Carlo (QMC) integration using digitally shifted digital nets. We express the mean square QMC error of the $n$-th discrete approximation $f_n$ of a function $f\colon[0,1)^s\to \mathbb{R}$ for digitally shifted digital nets in terms of the Walsh coefficients of $f$. We then apply a bound on the Walsh coefficients for sufficiently smooth integrands to obtain a quality measure called Walsh figure of merit for root mean square error, which satisfies a Koksma-Hlawka type inequality on the root mean square error. Through two types of experiments, we confirm that our quality measure is of use for finding digital nets which show good convergence behaviors of the root mean square error for smooth integrands.