RUS  ENG
Full version
PEOPLE

Mikhailov Guennady Alekseevich

Publications in Math-Net.Ru

  1. Study of the bias of $N$-particle estimates of the Monte Carlo method in problems with particle interaction

    Dokl. RAN. Math. Inf. Proc. Upr., 519 (2024),  33–38
  2. Efficiently realized approximate models of random functions in stochastic problems of the theory of particle transfer

    Sib. Zh. Vychisl. Mat., 27:2 (2024),  189–209
  3. Optimization of a numerical-statistical algorithm for estimating the mean particle flow in a bounded random medium with multiplication

    Zh. Vychisl. Mat. Mat. Fiz., 64:11 (2024),  2194–2204
  4. Study and optimization of $N$-particle numerical statistical algorithm for solving the Boltzmann equation

    Zh. Vychisl. Mat. Mat. Fiz., 64:5 (2024),  842–851
  5. New computer efficient approximations of random functions for solving stochastic transport problems

    Zh. Vychisl. Mat. Mat. Fiz., 64:2 (2024),  337–349
  6. Numerical-statistical investigation of superexponential growth of the mean particle flux with multiplication in a homogeneous random medium

    Dokl. RAN. Math. Inf. Proc. Upr., 514:1 (2023),  112–117
  7. Investigation of the overexponential growth of the mean particles flux with multiplication in a random medium

    Sib. Zh. Vychisl. Mat., 26:4 (2023),  401–413
  8. Study of superexponential growth of the mean partile flux by Monte Carlo method

    Sib. Zh. Vychisl. Mat., 26:3 (2023),  277–285
  9. Construction of effective randomized projective estimates for solutions of integral equations based on Legendre polynomials

    Dokl. RAN. Math. Inf. Proc. Upr., 507 (2022),  81–85
  10. Comparative analysis of various numerically statistical projection algorithms for the solving the transfer theory problems

    Dokl. RAN. Math. Inf. Proc. Upr., 502 (2022),  42–45
  11. New correlative randomized algorithm for estimating the influence of the medium stochasticity on particle transport

    Dokl. RAN. Math. Inf. Proc. Upr., 498 (2021),  55–58
  12. Numerical-statistical and analytical study of asymptotics for the average multiplication particle flow in a random medium

    Zh. Vychisl. Mat. Mat. Fiz., 61:8 (2021),  1353–1362
  13. New statistical kernel-projection estimator in the Monte Carlo method

    Dokl. RAN. Math. Inf. Proc. Upr., 493 (2020),  62–67
  14. Monte Carlo algorithms for estimating time asymptotics of multiplication particle flow in a random medium

    Dokl. RAN. Math. Inf. Proc. Upr., 490 (2020),  47–50
  15. Randomized algorithms of Monte Carlo method for problems with random parameters (“double randomization” method)

    Sib. Zh. Vychisl. Mat., 22:2 (2019),  187–200
  16. Improvement of multidimensional randomized Monte Carlo algorithms with “splitting”

    Zh. Vychisl. Mat. Mat. Fiz., 59:5 (2019),  822–828
  17. Estimation by Monte Carlo method of functional characteristics of the radiation intensity field passing throw a random medium

    Sib. Zh. Vychisl. Mat., 21:4 (2018),  349–365
  18. Monte Carlo methods for estimating the probability distributions of criticality parameters of particle transport in a randomly perturbed medium

    Zh. Vychisl. Mat. Mat. Fiz., 58:11 (2018),  1900–1910
  19. Randomized projection method for estimating angular distributions of polarized radiation based on numerical statistical modeling

    Zh. Vychisl. Mat. Mat. Fiz., 56:9 (2016),  1560–1570
  20. Effective averaging of stochastic radiative models based on Monte Carlo simulation

    Zh. Vychisl. Mat. Mat. Fiz., 56:5 (2016),  896–908
  21. Investigation and improvement of biased Monte-Carlo estimates

    Zh. Vychisl. Mat. Mat. Fiz., 55:1 (2015),  10–21
  22. About efficient algorithms of numerically-statistical simulation

    Sib. Zh. Vychisl. Mat., 17:2 (2014),  177–190
  23. Parametric weighted minimax estimates in Monte-Carlo methods

    Zh. Vychisl. Mat. Mat. Fiz., 53:9 (2013),  1503–1516
  24. “Poisson” models of random fields with applications in transport theory

    Zh. Vychisl. Mat. Mat. Fiz., 52:1 (2012),  144–152
  25. Vector estimators of the Monte Carlo method: dual representation and optimization

    Sib. Zh. Vychisl. Mat., 13:4 (2010),  423–438
  26. Algorithms for the exact and approximate statistical modeling of Poisson ensembles

    Zh. Vychisl. Mat. Mat. Fiz., 50:6 (2010),  1005–1016
  27. Estimation of the criticality parameters of branching processes by the Monte Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 50:2 (2010),  362–374
  28. Improvement of weight computational statistical modeling via the transition to a subcritical Galton–Watson process

    Dokl. Akad. Nauk, 424:3 (2009),  311–314
  29. Modification of two-step Monte Carlo algorithms based on the symmetry of the first step

    Zh. Vychisl. Mat. Mat. Fiz., 49:11 (2009),  2010–2019
  30. Study of weighted Monte Carlo algorithms with branching

    Zh. Vychisl. Mat. Mat. Fiz., 49:3 (2009),  441–452
  31. Moments of the critical parameters of the transport of particles in a random medium

    Zh. Vychisl. Mat. Mat. Fiz., 48:12 (2008),  2225–2236
  32. Distributed computing by the Monte Carlo method

    Avtomat. i Telemekh., 2007, no. 5,  157–170
  33. Modifications of weighted Monte Carlo algorithms for nonlinear kinetic equations

    Zh. Vychisl. Mat. Mat. Fiz., 47:12 (2007),  2110–2121
  34. Monte Carlo study of time asymptotics of the polarized radiation intensity

    Zh. Vychisl. Mat. Mat. Fiz., 47:7 (2007),  1264–1275
  35. Variance of a standard vector Monte Carlo estimate in the theory of polarized radiative transfer

    Zh. Vychisl. Mat. Mat. Fiz., 46:11 (2006),  2099–2113
  36. Investigation and reduction of variance of a weighted estimate in numerical statistical simulation

    Zh. Vychisl. Mat. Mat. Fiz., 46:8 (2006),  1519–1536
  37. Weighted Monte Carlo method for an approximate solution of the nonlinear coagulation equation

    Zh. Vychisl. Mat. Mat. Fiz., 46:4 (2006),  715–726
  38. Global weighted Monte Carlo method for the nonlinear Boltzmann equation

    Zh. Vychisl. Mat. Mat. Fiz., 45:10 (2005),  1860–1870
  39. Monte Carlo methods for solving the first boundary value problem for a polyharmonic equation

    Zh. Vychisl. Mat. Mat. Fiz., 45:3 (2005),  495–508
  40. Optimization of weighted Monte Carlo methods with respect to auxiliary variables

    Sibirsk. Mat. Zh., 45:2 (2004),  399–409
  41. Probability models, integral equations, and weighted Monte Carlo methods

    Zh. Vychisl. Mat. Mat. Fiz., 44:1 (2004),  30–37
  42. Corrections to the article “Weighted Monte Carlo methods for approximate solution of a nonlinear Boltzmann equation”

    Sibirsk. Mat. Zh., 44:2 (2003),  473–474
  43. Monte Carlo method of calculation the derivatives of solution to stationary diffusion equation

    Zh. Vychisl. Mat. Mat. Fiz., 43:10 (2003),  1517–1529
  44. Weighted algorithms for the statistical modeling of diffusion processes

    Zh. Vychisl. Mat. Mat. Fiz., 43:4 (2003),  571–584
  45. Weighted Monte Carlo methods for approximate solution of a nonlinear Boltzmann equation

    Sibirsk. Mat. Zh., 43:3 (2002),  620–628
  46. New Monte Carlo methods for estimating time dependences in radiative transfer processes

    Zh. Vychisl. Mat. Mat. Fiz., 42:4 (2002),  569–579
  47. Solving the multidimensional difference biharmonic equation by the Monte Carlo method

    Sibirsk. Mat. Zh., 42:5 (2001),  1125–1135
  48. A new monte carlo method for solving a stationary diffusion equation

    Sibirsk. Mat. Zh., 41:5 (2000),  1098–1105
  49. New Monte Carlo methods for solving boundary value problems

    Sib. Zh. Vychisl. Mat., 1:1 (1998),  67–76
  50. Parametric differentiation and estimates for eigenvalues by the Monte–Carlo method

    Sibirsk. Mat. Zh., 39:4 (1998),  931–941
  51. New weighted “path estimates” in the Monte Carlo method

    Sibirsk. Mat. Zh., 39:2 (1998),  396–404
  52. Solution of the Dirichlet difference problem for the multidimensional Helmholtz equation by the Monte Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 38:1 (1998),  99–106
  53. Solution of boundary value problems by the “random walk on spheres” method with reflection from the boundary

    Dokl. Akad. Nauk, 353:6 (1997),  720–722
  54. Solution of boundary value problem(s) of the second and third kind by Monte Carlo methods

    Sibirsk. Mat. Zh., 38:3 (1997),  603–614
  55. Solution of the Helmholtz equation with a complex parameter and the realization of the Fourier transform by the Monte Carlo method

    Dokl. Akad. Nauk, 349:1 (1996),  17–19
  56. Estimates for the nonuniformity of the distributions of congruent sums of random variables

    Dokl. Akad. Nauk, 347:1 (1996),  23–26
  57. Solving boundary value problems with complex parameters by the Monte Carlo method

    Sibirsk. Mat. Zh., 37:4 (1996),  881–888
  58. Unbiasedness and variance of the standard estimate of the Monte Carlo method

    Dokl. Akad. Nauk, 343:3 (1995),  306–308
  59. The Monte Carlo methods for solving the vector and Stochastic Helmholtz equations

    Sibirsk. Mat. Zh., 36:3 (1995),  602–610
  60. To the theory of the estimators of the Monte Carlo method which are connected with a “random walk by spheres”

    Sibirsk. Mat. Zh., 36:3 (1995),  543–550
  61. A new Monte Carlo method for calculating the covariance function of the solution of the general harmonic equation

    Dokl. Akad. Nauk, 338:5 (1994),  601–603
  62. A “path” estimate for the solution of linear and nonlinear radiation transport equations in the large

    Dokl. Akad. Nauk, 337:2 (1994),  162–164
  63. Solution of the Dirichlet problem for elliptic systems with variable parameters by the Monte Carlo method

    Dokl. Akad. Nauk, 336:6 (1994),  737–740
  64. Convergence of computational models of random fields associated with Palm point flows

    Dokl. Akad. Nauk, 335:3 (1994),  291–294
  65. Solving the Dirichlet problem for nonlinear elliptic equations by the Monte Carlo method

    Sibirsk. Mat. Zh., 35:5 (1994),  1085–1093
  66. New Monte Carlo methods for computing the critical value of the parameters of the particle transport equation

    Dokl. Akad. Nauk, 332:1 (1993),  21–23
  67. Solution of the equation $\Delta u+u^n=0$ by the Monte Carlo method

    Dokl. Akad. Nauk, 331:6 (1993),  681–683
  68. Monte Carlo methods for solving metaharmonic equations of the form $\Delta^{p+1}u+cu=(-1)^{p+1}g$

    Dokl. Akad. Nauk, 331:1 (1993),  20–23
  69. New algorithms of the Monte Carlo method for solving the Helmholtz equation

    Dokl. Akad. Nauk, 326:6 (1992),  943–947
  70. Minimax solutions of equations that determine the variances of weight estimates of the Monte Carlo method

    Dokl. Akad. Nauk SSSR, 307:5 (1989),  1050–1054
  71. Minimax Monte-Carlo methods for solving integral equations of the second kind

    Zh. Vychisl. Mat. Mat. Fiz., 29:11 (1989),  1650–1661
  72. Uniform optimization of weighted estimates of the Monte Carlo method

    Dokl. Akad. Nauk SSSR, 303:2 (1988),  290–293
  73. A new approach to the calculation of derivatives with respect to parameters by the Monte Carlo method

    Dokl. Akad. Nauk SSSR, 295:1 (1987),  34–37
  74. Vector Monte Carlo methods for computing perturbations and derivatives with respect to parameters

    Zh. Vychisl. Mat. Mat. Fiz., 27:9 (1987),  1311–1319
  75. Vector Monte Carlo methods for calculating iterations of integral operator resolvents

    Zh. Vychisl. Mat. Mat. Fiz., 26:8 (1986),  1141–1149
  76. Vector representations of bilinear estimates of the Monte Carlo method and realization of special iteration processes

    Dokl. Akad. Nauk SSSR, 285:4 (1985),  803–807
  77. Investigation and reduction of variance of weight vector algorithms of the Monte Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 25:11 (1985),  1614–1627
  78. A criterion for uniform optimality of Monte Carlo weight methods and its applications

    Dokl. Akad. Nauk SSSR, 279:6 (1984),  1318–1322
  79. Error of the Monte Carlo method in solving the transfer vector equation

    Dokl. Akad. Nauk SSSR, 279:5 (1984),  1046–1049
  80. Minimax theory of Monte Carlo weight methods

    Zh. Vychisl. Mat. Mat. Fiz., 24:9 (1984),  1294–1302
  81. Uniform optimization of Monte Carlo weight methods. A minimax approach

    Dokl. Akad. Nauk SSSR, 270:5 (1983),  1054–1058
  82. Approximate models of random processes and fields

    Zh. Vychisl. Mat. Mat. Fiz., 23:3 (1983),  558–566
  83. Simulation of random processes and fields on the basis of Palm point flows

    Dokl. Akad. Nauk SSSR, 262:3 (1982),  531–535
  84. Optimization of vector algorithms in the Monte-Carlo method

    Dokl. Akad. Nauk SSSR, 260:1 (1981),  26–31
  85. Nonlinear theory of optimization of statistical modeling for solving integral equations of the second kind

    Zh. Vychisl. Mat. Mat. Fiz., 21:6 (1981),  1435–1444
  86. Algorithms for calculations of a complex reactor cell by the Monte Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 21:2 (1981),  432–440
  87. The variance of vector algorithms in the Monte Carlo method

    Dokl. Akad. Nauk SSSR, 253:5 (1980),  1047–1050
  88. Nonlinear equations connected with optimization of Monte Carlo methods for solving integral equations of the second kind

    Dokl. Akad. Nauk SSSR, 252:4 (1980),  792–796
  89. The development and application of the method of numerical statistic modeling for solving one-dimensional problems in radiative transport theory

    Sibirsk. Mat. Zh., 20:3 (1979),  682–687
  90. Estimation of the difficulty of simulating the process of “random walk on spheres” for some types of regions

    Zh. Vychisl. Mat. Mat. Fiz., 19:2 (1979),  510–515
  91. Numerical construction of a random field with a given spectral density

    Dokl. Akad. Nauk SSSR, 238:4 (1978),  793–795
  92. Efficient algorithms of the Monte-Carlo method for computing the correlation characteristics of conditional mathematical expectations

    Zh. Vychisl. Mat. Mat. Fiz., 17:1 (1977),  246–249
  93. Monte Carlo methods for estimating the correlation function of strong fluctuations of light in a turbulent medium

    Zh. Vychisl. Mat. Mat. Fiz., 16:5 (1976),  1264–1275
  94. On the “reproduction” method for simulation of random vectors and processes (randomization of correlation matrices

    Teor. Veroyatnost. i Primenen., 19:4 (1974),  873–878
  95. Use of the fundamental solutions of elliptic equations for constructing Monte Carlo algorithms

    Zh. Vychisl. Mat. Mat. Fiz., 14:3 (1974),  728–736
  96. A “walk on spheres” algorithm for the equation $\Delta u-cu=-g$

    Dokl. Akad. Nauk SSSR, 212:1 (1973),  15–18
  97. Modification of the local estimation of particle flux by the Monte Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 13:3 (1973),  574–582
  98. Two remarks on the simulation of random variables

    Zh. Vychisl. Mat. Mat. Fiz., 12:5 (1972),  1350–1352
  99. An investigation of the effectiveness of the use of asymptotic solutions in computations by the Monte Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 12:1 (1972),  150–158
  100. A combination of the finite-sum and Monte Carlo methods for the solution of integral equations of the second kind

    Mat. Zametki, 9:4 (1971),  425–434
  101. A new algorithm of the Monte Carlo method for estimation of the maximal eigenvalue of an integral operator

    Dokl. Akad. Nauk SSSR, 191:5 (1970),  993–996
  102. On a¨class of Monte Carlo estimators

    Teor. Veroyatnost. i Primenen., 15:1 (1970),  142–144
  103. Optimization of the estimate of functional dependencies by the Monte Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 10:3 (1970),  734–740
  104. A use of the approximate solutions of the adjoint problem for the improvement of the algorithms of a Monte Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 9:5 (1969),  1145–1152
  105. Solution of the dirichlet problem for the equation $\Delta u-cu=-q$ by a model of “walks on spheres”

    Zh. Vychisl. Mat. Mat. Fiz., 9:3 (1969),  647–654
  106. A principle for optimizing calculations by the Monte-Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 8:5 (1968),  1085–1093
  107. A certain “direct” method of simulation of random variables

    Zh. Vychisl. Mat. Mat. Fiz., 8:4 (1968),  928–929
  108. Estimation of certain nonlinear functionals and approximate calculation of the group constants of transfer theory by a Monte Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 8:3 (1968),  590–599
  109. Monte-Carlo calculation of derivatives of functionals from the solution of the transfer equation according to the parameters of the system

    Zh. Vychisl. Mat. Mat. Fiz., 7:4 (1967),  915–919
  110. Construction of economic algorithms for simulating random variables

    Zh. Vychisl. Mat. Mat. Fiz., 6:6 (1966),  1134–1136
  111. On calculations of perturbations of nuclear reactors by Monte-Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 6:2 (1966),  380–384
  112. Calculations of parameters of critical systems by the Monte-Carlo method

    Zh. Vychisl. Mat. Mat. Fiz., 6:1 (1966),  71–80
  113. On modelling random variables for one class of distributions

    Teor. Veroyatnost. i Primenen., 10:4 (1965),  749–751

  114. Gurii Ivanovich Marchuk (on the occasion of his 75th birthday)

    Sib. Zh. Vychisl. Mat., 3:2 (2000),  89–95
  115. On the anniversary of Anatoly Semenovich Alekseev

    Sib. Zh. Vychisl. Mat., 1:4 (1998),  299–300
  116. Gurii Ivanovich Marchuk (on the occasion of his seventieth birthday)

    Sibirsk. Mat. Zh., 36:3 (1995),  483–487
  117. Scientific information on the fourth all-union conference on the use of Monte Carlo methods in computational mathematics and mathematical physics

    Zh. Vychisl. Mat. Mat. Fiz., 14:6 (1974),  1616–1617
  118. The third all-union conference on Monte Carlo methods

    Zh. Vychisl. Mat. Mat. Fiz., 12:2 (1972),  557–558
  119. The second all-union conference on Monte Carlo methods (Sukhumi, 20–25 October 1969)

    Zh. Vychisl. Mat. Mat. Fiz., 10:3 (1970),  798–799
  120. The first all-union conference on monte carlo methods: Novosibirsk, 17–21 November 1966

    Zh. Vychisl. Mat. Mat. Fiz., 7:3 (1967),  714–716

© Steklov Math. Inst. of RAS, 2026