Standard

Efficient Algorithms for Computer Simulation of Gaussian Distribution. / Voytishek, A. V.; Ivanova, Yu A.; Seitmuratov, U. P.

In: Computational Mathematics and Mathematical Physics, Vol. 66, No. 3, 01.05.2026, p. 383-395.

Research output: Contribution to journal › Article › peer-review

Harvard

Voytishek, AV, Ivanova, YA & Seitmuratov, UP 2026, 'Efficient Algorithms for Computer Simulation of Gaussian Distribution', Computational Mathematics and Mathematical Physics, vol. 66, no. 3, pp. 383-395. https://doi.org/10.1134/S0965542525702008

APA

Voytishek, A. V., Ivanova, Y. A., & Seitmuratov, U. P. (2026). Efficient Algorithms for Computer Simulation of Gaussian Distribution. Computational Mathematics and Mathematical Physics, 66(3), 383-395. https://doi.org/10.1134/S0965542525702008

Vancouver

Voytishek AV, Ivanova YA, Seitmuratov UP. Efficient Algorithms for Computer Simulation of Gaussian Distribution. Computational Mathematics and Mathematical Physics. 2026 May 1;66(3):383-395. doi: 10.1134/S0965542525702008

Author

Voytishek, A. V. ; Ivanova, Yu A. ; Seitmuratov, U. P. / Efficient Algorithms for Computer Simulation of Gaussian Distribution. In: Computational Mathematics and Mathematical Physics. 2026 ; Vol. 66, No. 3. pp. 383-395.

BibTeX

@article{27243a1166b744cbbb75a4577c144624,
title = "Efficient Algorithms for Computer Simulation of Gaussian Distribution",
abstract = "The paper compares new efficient versions of the double-sided rejection algorithms with piecewise constant majorant and minorant and the modified ziggurat algorithm applied to computer modeling of the widely used Gaussian distribution. It is shown that these algorithms are significantly more cost-efficient than all known algorithms for modeling the Gaussian distribution (including the Box–M{\"u}ller formulas, which are considered the most efficient).",
keywords = "Box–M{\"u}ller formulas, Gaussian distribution, complexity of computer simulation, double-sided rejection algorithm with piecewise constant majorant and minorant and probability equalization, modified ziggurat algorithm, Гауссовское распределение, формулы Бокса — Мюллера, двусторонний алгоритм отбора (rejection sampling) с кусочно-постоянными мажорантой и минорантой и выравниванием вероятностей, модифицированный алгоритм «зиккурат», сложность компьютерного моделирования",
author = "Voytishek, {A. V.} and Ivanova, {Yu A.} and Seitmuratov, {U. P.}",
note = "Voytishek, A. V. Efficient Algorithms for Computer Simulation of Gaussian Distribution / A. V. Voytishek, Yu. A. Ivanova, U. P. Seitmuratov // Computational Mathematics and Mathematical Physics. – 2026. – Vol. 66, No. 3. – P. 383-395. – DOI 10.1134/S0965542525702008. – EDN OPCSAC. This work was performed within the state assignment of the Institute of Computational Mathematics and Mathematical Geophysics of the Siberian Branch of the Russian Academy of Science, FWNM-2025-0002.",
year = "2026",
month = may,
day = "1",
doi = "10.1134/S0965542525702008",
language = "English",
volume = "66",
pages = "383--395",
journal = "Computational Mathematics and Mathematical Physics",
issn = "0965-5425",
publisher = "Pleiades Publishing",
number = "3",

}

RIS

TY - JOUR

T1 - Efficient Algorithms for Computer Simulation of Gaussian Distribution

AU - Voytishek, A. V.

AU - Ivanova, Yu A.

AU - Seitmuratov, U. P.

N1 - Voytishek, A. V. Efficient Algorithms for Computer Simulation of Gaussian Distribution / A. V. Voytishek, Yu. A. Ivanova, U. P. Seitmuratov // Computational Mathematics and Mathematical Physics. – 2026. – Vol. 66, No. 3. – P. 383-395. – DOI 10.1134/S0965542525702008. – EDN OPCSAC. This work was performed within the state assignment of the Institute of Computational Mathematics and Mathematical Geophysics of the Siberian Branch of the Russian Academy of Science, FWNM-2025-0002.

PY - 2026/5/1

Y1 - 2026/5/1

N2 - The paper compares new efficient versions of the double-sided rejection algorithms with piecewise constant majorant and minorant and the modified ziggurat algorithm applied to computer modeling of the widely used Gaussian distribution. It is shown that these algorithms are significantly more cost-efficient than all known algorithms for modeling the Gaussian distribution (including the Box–Müller formulas, which are considered the most efficient).

AB - The paper compares new efficient versions of the double-sided rejection algorithms with piecewise constant majorant and minorant and the modified ziggurat algorithm applied to computer modeling of the widely used Gaussian distribution. It is shown that these algorithms are significantly more cost-efficient than all known algorithms for modeling the Gaussian distribution (including the Box–Müller formulas, which are considered the most efficient).

KW - Box–Müller formulas

KW - Gaussian distribution

KW - complexity of computer simulation

KW - double-sided rejection algorithm with piecewise constant majorant and minorant and probability equalization

KW - modified ziggurat algorithm

KW - Гауссовское распределение

KW - формулы Бокса — Мюллера

KW - двусторонний алгоритм отбора (rejection sampling) с кусочно-постоянными мажорантой и минорантой и выравниванием вероятностей

KW - модифицированный алгоритм «зиккурат»

KW - сложность компьютерного моделирования

UR - https://www.mendeley.com/catalogue/e3850035-b738-3969-b2b8-8c1ce51e69f8/

UR - https://www.scopus.com/pages/publications/105038032561

UR - https://elibrary.ru/item.asp?id=90808745

U2 - 10.1134/S0965542525702008

DO - 10.1134/S0965542525702008

M3 - Article

VL - 66

SP - 383

EP - 395

JO - Computational Mathematics and Mathematical Physics

JF - Computational Mathematics and Mathematical Physics

SN - 0965-5425

IS - 3

ER -

ID: 85120139