Researcher Database

HARAMOTO, Hiroshi

FacultyFaculty of Education Mathematics Education
PositionAssociate Professor
Last Updated :2020/05/31

Researcher Profile and Settings

Profile and Settings

Name

  • Name

    HARAMOTO, Hiroshi

Education, Etc.

Education

  • 2008, Hiroshima University

その他基本情報

Committee Memberships

  • 2019/04 - Today

Academic & Professional Experience

  • 2011/04 - Today, Faculty of Education, Ehime University
  • 2008/10 - 2011/03, Faculty of Natural Sciences, Kure National College of Technology
  • 2008/04 - 2008/09, Hiroshima University

Research Activities

Research Areas, Etc.

Research Areas

  • Natural sciences, Applied mathematics and statistics
  • Natural sciences, Basic mathematics

Research Interests

  • Random Number Generation

Book, papers, etc

Published Papers

  • Study on properties of the sum of integer sequences in "Seiyo Sanpo", Transactions of mathematical education for colleges and universities, Transactions of mathematical education for colleges and universities, 2020/03, [Refereed]
  • Checking the quality of approximation of p-values in statistical tests for random number generators by using a three-level test., Hiroshi Haramoto, Makoto Matsumoto, Mathematics and Computers in Simulation, Mathematics and Computers in Simulation, 2019, [Refereed], 0378-4754, 10.1016/j.matcom.2018.08.005
  • A Method to Compute an Appropriate Sample Size of a Two-Level Test for the NIST Test Suite, Hiroshi Haramoto, Makoto Matsumoto, Monte Carlo and quasi-Monte Carlo Methods 2016, Monte Carlo and quasi-Monte Carlo Methods 2016, 2018/08, [Refereed], 2194-1009
  • A non-empirical test on the second to the sixth least significant bits of pseudorandom number generators, Haramoto Hiroshi, Makoto Matsumoto, Takuji Nishimura, Yuki Otsuka, Monte Carlo and quasi-Monte Carlo methods 2012, Monte Carlo and quasi-Monte Carlo methods 2012, 2013, [Refereed], 2194-1009, 10.1007/978-3-642-41095-6_19
  • 2009/03, [Refereed], 0377-0427, 10.1016/j.cam.2008.07.044
  • 2009, [Refereed], 10.1007/978-3-642-04107-5_26
  • A Fast Jump Ahead Algorithm for Linear Recurrences in a Polynomial Space, H. Haramoto, M. Matsumoto, P. L'Ecuyer, Sequences ant Their Applications (LNCS 5203), Sequences ant Their Applications (LNCS 5203), 2008, [Refereed], 0302-9743, 10.1007/978-3-540-85912-3_26
  • Efficient jump ahead for F(2)-linear random number generators, Haramoto Hiroshi, Matsumoto Makoto, Nishimura Takuji, Panneton Francois, L'Ecuyer Pierre, INFORMS JOURNAL ON COMPUTING, INFORMS JOURNAL ON COMPUTING, 2008, [Refereed], 1091-9856, 10.1287/ijoc.1070.0251
  • Computing conditional probabilities for $F2$-linear pseudorandom bit generator by splitting Mac-Williams identity, H. Haramoto, M. Matsumoto, T. Nishimura, International Journal of Pure and Applied Mathematics, International Journal of Pure and Applied Mathematics, 2007, [Refereed], 1311-8080
  • 2006, [Refereed], 0948-695X, 10.3217/jucs-012-06-0672

Books etc

  • 2015, 9784864810340
  • 2015, 9784864810333
  • 2014, 9784864810227
  • 2014, 9784864810210
  • 2013, 9784864810043
  • 2013, 9784864810036
  • 2012, 9784901683975
  • 2012, 9784901683968

Conference Activities & Talks

  • 2019/10
  • 2019/09
  • A visible flaw of xorshift128+ generators, Hiroshi Hatamoto, Makoto Matsumoto, Mutsuo Saito, 12th International Conference on Monte Carlo Methods and Applications, 2019/07
  • Large sample sizes may result in erroneous rejection in statistical tests on randomness: a computational solution, Hiroshi Haramoto, 12th International Conference on Monte Carlo Methods and Applications, 2019/07
  • 2019/01
  • 2018/12
  • 2018/09
  • Testing the Reliability of Statistical Tests for Pseudorandom Number Generators, Hiroshi Haramoto, 13th International Conference in Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing (MCQMC2018), 2018/07
  • 2017/09
  • Testing soundness of statistical tests for random number generators by using a three-level test, Hiroshi Haramoto, 11th International Conference on Monte Carlo Methods and Applications (MCM 2017), 2017/07
  • 2016/09
  • A Method to Compute an Appropriate Sample Size of the Two-Level Test of NIST Test Suite for Frequency and Binary Matrix Rank Test, Hiroshi Haramoto, Twelveth International conference on Monte Carlo and quasi-Monte Carlo methods in scientific computing (MCQMC2016), 2016/08
  • 2016/06
  • 2015/09
  • A method to check soundness of statistical tests on randomness, Hiroshi Haramoto, 10th IMACS Seminar on Monte Carlo Methods (MCM2015), 2015/07
  • 2015/04, 招待有り
  • An approximation of the weight distribution of the n-th bits of pseudorandom number generators, Hiroshi Haramoto, Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing (MCQMC2014), 2014/04
  • 2012/09
  • 2012/09
  • A non-empirical test on the second to the sixth lowest bits of pseudorandom number generators, Hiroshi Haramoto, Workshop for Quasi-Monte Carlo and Pseudo Random Number Generation, 2012/06, 招待有り
  • A non-empirical test on the second to the sixth lowest bits of pseudorandom number generators, Hiroshi Haramoto, Tenth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing (MCQMC 2012), 2012/02
  • A Fast Jump Ahead Algorithm for $\mathbb{F}_2$ Linear Recurrences in a Polynomial Space, Hiroshi Haramoto, Makoto Matsumoto, Pierre L'Ecuyer, The fifth Interna- tional Conference on Sequences and Their Applications, 2008/09
  • Automatization of Statistical Tests on Random- ness to Obtain Clearer Conclusion, Hiroshi Haramoto, Makoto Matsumoto, 8th International Confer- ence on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, 2008/07
  • A jumping method for linear pseu- dorandom number generator with huge state over the two-element field, H.Haramoto, F.Panneton, T.Nishimura, 7th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, 2006/08
  • Pulmonary Mersenne Twister pseudorandom number generator, M.Matsumoto, M.Saito, H.Haramoto, F.Panneton, T.Nishimura, 7th In- ternational Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, 2006/08
  • Hearty Twister: a new random number generator, H.Haramoto, M.Matsumoto, 5th IMACS Seminar on Monte Carlo Methods, 2005/05

Misc

Other Research Activities

Research Grants & Projects

  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Challenging Exploratory Research, Research on number theory in vew of finite symmetric spaces and the associated graph spectrum, HIRANO Miki, We have developed a study of spectral distribution problems of Cayley graphs in view of Number Theory. In particular, we give a result on boundary problem of Ramanujancy for some families of Cayley graphs on non-commutative finite groups, which is similar to the case of a family of circulant graphs. Our results suggest an interesting (unknown) relation between theory of graph spectrum and analytic number theory.
  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Challenging Exploratory Research, Higher order hyper uniform point sets and higher order quasi-Monte Carlo method, Matsumoto Makoto, HAGITA Mariko, NISHIMURA Takuji, HARAMOTO Hiroshi, HARASE Shin, Let f be an integrand function defined on an s-dimensional hyper cube. Quasi-Monte Carlo method is to choose a point set P of size N in this hyper cube, and obtain numerical approximation of the integral of f by the mean value of f over P. When P is chosen uniformly randomly, the integration error is known to converge with order N's power to -1/2. Classical Quasi-Monte Carlo tries to design a good P with order nearly 1/N. Our research focuses on an index called parameterized Walsh Figure of Merit. By searching for P with small value of this index, we find P with smaller error than previously proposed point sets. In particular, for low dimensions s<5, our method shows remarkable improvements.
  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Challenging Exploratory Research, New figure of merits for quasi-Monte Carlo point set, Matsumoto Makoto, Nishimura Takuji, Hagita Mariko, Haramoto Hiroshi, Numerical integration over a high dimensional space appears in many area in sciences. A major algorithm is Monte Carlo method, but the order of the estimated error, inverse of square root of N, where N is the size of point sets, is relatively large. Quasi-Monte Carlo method is to choose a "good" point set to make the error much smaller. In this research, as a criterion on the hyper uniformity of point sets, Walsh figure of merit is introduced. It directly bounds the integration error, and it is efficiently computable. More over, we introduced "derivation sensitivity parameter", which makes the point set effective for higher dimensions. The point set is available from a homepage. We conducted several numerical experiments, which show advantages of the proposed point sets over existing ones.
  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (A), New developments in number theoretic geometry, topology, and algorithm, Matsumoto Makoto, TAMAGAWA AKIO, Mochizuki Shinichi, Hoshi Yuichiro, Tsuzuki Nobuo, Terasoma Tomohide, Saito Shuji, Tsuji Takeshi, Shiho Atsushi, Morita Shigeyuki, Shimada Ichiro, Kimura Shun-ichi, Kamada Seiichi, Sakuma Makoto, Ishii Akira, Takahashi Nobuyoshi, Hiranouchi Toshiro, Haramoto Hiroshi, Kaneko Masanobu, Taguchi Yuichiro, Furusho Hidekazu, Nishimura Takuji, Hagita Mariko, Yamauchi Takuya, Asakura Masanori, Mizusawa Yasushi, We studied pure mathematics such as number theory, algebra, geometry, in an interdisciplinary manner. In addition, we studied there application in other branch of science and engineering. In pure mathematics side, we constructed a mixed elliptic motif obtained from universal family of elliptic curves. Also, given an l-adic linear representation of arithmetic fundamental group of an algebraic curve, we compared the image of the representation and the image of the Galois group of k-rational point of curves. As for applicational research, we developped a fast numerical integration algorithm based on quasi-Monte Carlo. The method depends on a point set (called Niederreiter-Xing point sets) whose basis is in the theory of rational points of algebraic curves). We introduced a new criteria for uniformity of point set named WAFOM, and our algorithm uses point sets obtained by scrambling Niederreiter-Xing point sets whose WAFOM value is small. Its effectiveness is empirically confirmed.
  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Young Scientists (B), Improvement of pseudorandom number generators from viewpoint of algebra and statistics, HARAMOTO Hiroshi, (1) We proposes an adaptive modification of statistical tests, in particular TestU01. This procedure automatically increases the sample size, and tests the PRNG again. It stops when the p-value falls in a clearly rejectable range. (2) We have implemented the codes of the jumping-ahead for MT19937 and WELL19937, in C and C++ languages. These are distributed from a homepage. (3) we report a method to compute the weight distribution of the second to the sixth lowest bits of several PRNGs by using MacWilliams identity.
  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Challenging Exploratory Research, Low Discrepancy Sequence, SAITO Mutsuo, MATSUMOTO Makoto, NISHIMURA Takuji, HARAMOTO Hiroshi, We have developed a new figure of merit of Low Discrepancy Sequence(LDS), called Walsh Figure Of Merit(WAFOM). WFOM is a function that takes point set in a unit hypercube in S-dimensional space and gives a real number as figure of merit of the point set. WAFOM can be used to evaluate the upper bound of the error of numerical integration. We gave a proof that the order of calculation of WAFOM is O(nSN) by using discrete Fourier inverse transformation, where n is number of bits below radix point of binary form, S is number of dimension and N is number of points in the LDS. WAFOM makes finding new LDS easy because of faster calculation speed compared to existing method to calculate figure of merit of LDS.
  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Challenging Exploratory Research, High performance random number generator for new generation, MATSUMOTO Makoto, HAGITA Mariko, NISHIMURA Takuji, SAITOU Mutsuo, HARAMOTO Hiroshi, Mutsuo Saito and Matsumoto designed MTGP random number generators which specialize for the architecture of Graphic Processing Units, and its dynamic parameter generator MTGPDC. Also, TinyMT generators with small size of memory are developed. These are open source from our homepage. Haramoto et. al. gave methods to compute the distribution of lower bits of random numbers using generalized Mac Williams identity.
  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (A), New developments in number theory and geometry : arithmetic topology, categorical arithmetic geometry, algorithm, MATSUMOTO Makoto, TAMAGAWA Akio, MOCHIZUKI Shinichi, TSUZUKI Nobuo, KIMURA Shunichi, TERASOMA Tomohide, MORITA Shigeyuki, HIROSE Susumu, MORITA Takehiko, YOSHINO Masafumi, NAGAI Yoshitaka, SUGAWA Toshiyuki, TAKAHASHI Nobuyoshi, KANEKO Masanobu, TAGUCHI Yuichirou, ITO Hiroyuki, NISHIMURA Takuji, SAITO Shuji, TSUJI Takeshi, MORITA Yoshiyuki, SHIMADA Ichirou, ISHII Akira, YAMAUCHI Takuya, SHIHO Atsushi, SAITO Mutsuo, HARAMOTO Hiroshi, By using methods of geometric topology in arithmetic geometry, knowledges on topology (such as the cohomology of the mapping class groups) are utilized in researches on arithmetic geometry (such as outer Galois representations).(2)We developped a frame work to detect objects in arithmetic geometry by means of its combinatorial and categorical data.(3)We developped algebraic and geometric alogrithm for applications such as evaluation of pseudorandom number generators.

Activity track record

Educational activities

Course in charge

  • 2019, the first semester, under graduate, 新入生セミナーB
  • 2019, the first semester, under graduate, 数学科教育法Ⅲ
  • 2019, the first semester, under graduate, 数学科教育法3
  • 2019, the first semester, under graduate, 数学概論
  • 2019, the first semester, under graduate, 代数学Ⅰ
  • 2019, the first semester, under graduate, 代数学1
  • 2019, the first semester, under graduate, 数学・情報研究
  • 2019, the first semester, under graduate, 数学科教育法3


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