Dr. Venera Khoromskaia

  1. Book
    Venera Khoromskaia and Boris. N. Khoromskij.
    Tensor Numerical Methods in Quantum Chemistry.
    De Gruyter, Berlin, 2018.

    Papers on tensor numerical methods, since 2006

  2. B. N. Khoromskij and V. Khoromskaia.
    Editorial: Tensor numerical methods and their application in scientific computing and data science. (Open access).
    Numer. Lin. Algebra Appl., doi/10.1002/nla.2493, 2023.

  3. B. N. Khoromskij and V. Khoromskaia.
    Fast solution of three-dimensional elliptic equations with randomly generated jumping
    coefficients by using tensor-structured preconditioners. (Open access).
    Numer. Lin. Algebra Appl., e2477, 2022.

  4. V. Khoromskaia and B. N. Khoromskij.
    Ubiquitous Nature of the Reduced Higher Order SVD in Tensor-Based Scientific Computing. (Open access).
    Frontiers in Applied Mathematics and Statistics,
    Special Issue: "High-Performance Tensor Computations in Scientific Computing and Data Science" (8), pp.144-164, 2022.

  5. B. Schmitt, B. N. Khoromskij, V. Khoromskaia, V. Schulz.
    Tensor method for optimal control problems constrained by fractional three-dimensional
    elliptic operator with variable coefficients. (Open access).
    Numer. Lin. Algebra Appl. , e2404, 2022.
    E-Preprint arXiv:2006.09314, 2020.

  6. C. Kweyu, V. Khoromskaia and B. N. Khoromskij, M. Stein, P. Benner.
    Solution decomposition for the nonlinear Poisson-Boltzmann equation using the range-separated tensor format.
    E-preprint arXiv:2109.14073, 2021.

  7. V. Khoromskaia and B. N. Khoromskij.
    Prospects of tensor-based numerical modeling of the collective electrostatic potential in many-particle systems. (Abstract).
    E-Preprint arXiv:2001.11393, 2020.
    Comput. Math. Math. Physics, 61 (5), 864-886, 2021.

  8. P. Benner, V. Khoromskaia, B. N. Khoromskij, C. Kweyu and M. Stein.
    Regularization of Poisson-Boltzmann type equations with singular source terms using the range-separated tensor format. (Abstract).
    SIAM J. Sci. Comput., 43 (1), A415-A445, 2021.

  9. V. Khoromskaia and B. N. Khoromskij.
    Tensor-based techniques for fast discretization and solution of 3D elliptic equations with random coefficients.
    E-Preprint arXiv:2007.06524, 2020.

  10. P. Benner, V. Khoromskaia, B. N. Khoromskij, C. Kweyu and M. Stein.
    Computing Electrostatic Potentials of Biomolecules using Regularization based on the Range-separated Tensor Format
    E-Preprint arXiv:1901.09864, 2019.

  11. V. Khoromskaia, B. N. Khoromskij and F. Otto.
    Numerical study in stochastic homogenization for elliptic partial differential equations: Convergence rate in the size of representative volume elements.
    E-preprint arXiv:1901.09864, 2019.
    Numer. Linear Algebra Appl., 27(3) 2020, e2296 (Open access).

  12. G. Heidel, V. Khoromskaia, B. N. Khoromskij and V. Schulz.
    Tensor Approach to Optimal Control Problems with Fractional Multidimensional Elliptic Operator in Constraints. (Abstract).
    E-Preprint arXiv:1809.01971v1, 2018.
    J. Comput. Phys., 424, 109865, 2021.

  13. P. Benner, V. Khoromskaia and B. N. Khoromskij.
    Range-Separated Tensor Format for Many-particle Modeling.
    SIAM J. Sci. Comput., 40 (2), A1034-A1062, 2018.

  14. P. Benner, V. Khoromskaia, B. N. Khoromskij and C. Yang.
    Computing the Density of States for Optical Spectra of Molecules by Low-rank and QTT Tensor Approximation. (Abstract)
    E-preprint 2018, arXiv:1801.03852.
    J. Comput. Phys., 382 (2019), pp. 221-239.

  15. A. Litvinenko, D. Keyes, V. Khoromskaia, B. N. Khoromskij and H. G. Matthies
    Tucker tensor analysis of Matern functions in spatial statistics.
    Preprint, 2017, arXiv:1711.06874.
    Comput. Methods Appl. Math., 2019, 19(1) pp.101-122.

  16. V. Khoromskaia, B. N. Khoromskij and F. Otto.
    A Numerical Primer in 2D Stochastic Homogenization: CLT scaling in the Representative Volume Element.
    Preprint 47/2017 , Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2017.

  17. P. Benner, V. Khoromskaia and B. N. Khoromskij.
    Range-separated Tensor Formats for Numerical Modeling of Many-particle Interaction Potentials.
    Preprint 39/2016, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2016.
    E-preprint, arXiv:1606.09218, (39p.), 2016.

  18. P. Benner, S. Dolgov, V. Khoromskaia and B. N. Khoromskij.
    Fast Iterative Solution of the Bethe-Salpeter Eigenvalue Problem Using Low-rank and QTT Tensor Approximation.
    Preprint 14/2016, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2016, (arXiv:1602.02646, 2016).
    J. Comput. Phys., 334, 2017 pp. 221-239.

  19. V. Khoromskaia and B. N. Khoromskij.
    Block circulant and Toeplitz structures in the linearized Hartree-Fock equation on finite lattices: tensor approach.
    Preprint 12/2017 , Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2017.
    Comput. Methods Appl. Math. , 17 (3), 431-455, 2017.

  20. V. Khoromskaia and B. N. Khoromskij.
    Fast Tensor Method for Summation of Long-Range Potentials on 3D Lattices with Defects.
    Preprint 65/2015 , Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2015.
    Numer. Linear Algebra Appl., 23, 2016, pp. 249-271.

  21. V. Khoromskaia and B. N. Khoromskij.
    Tensor Numerical Methods in Quantum Chemistry: from Hartree-Fock to Excitation Energies.
    arXiv:1504.06289v1, 2015
    Phys. Chemistry Chem. Physics, 2015, 17, 31491 - 31509.

  22. P. Benner, V. Khoromskaia and B. N. Khoromskij.
    A Reduced Basis Approach for Calculation of the Bethe-Salpeter Excitation Energies using Low-Rank Tensor Factorizations.
    arXiv:1505.02696, 2015.
    Molecular Physics, 114 (7-8) 2016.

  23. V. Khoromskaia and B. N. Khoromskij.
    Tucker tensor method for fast grid-based summation of long-range potentials on 3D lattices with defects.
    Preprint 88/2014 , Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2014.
    arXiv:14.1994v2, 2014

  24. V. Khoromskaia and B. N. Khoromskij.
    Grid-based Lattice Summation of Electrostatic Potentials by Assembled Rank-structured Tensor Approximation.
    arXiv:1405.2270v2 , 2014.
    Comput. Phys. Communications, 185 (2014), pp. 3162-3174.

  25. V. Khoromskaia and B. N. Khoromskij.
    Tensor Approach to Linearized Hartree-Fock Equation for Lattice-type and Periodic Systems.
    Preprint 62/2014 , Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2014.
    arXiv:1408.3839v1, 2014.

  26. V. Khoromskaia and B. N. Khoromskij.
    Lattice Summation of Electrostatic Potentials by Low-rank Tensor Approximation.
    Preprint 116/2013, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2013.

  27. V. Khoromskaia.
    Black-Box Hartree-Fock Solver by Tensor Numerical Methods.
    Preprint 90/2013, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2013.
    Comput. Methods Appl. Math., Vol. 14 (2014) No.1, pp. 89-111.

  28. V. Khoromskaia, B. N. Khoromskij.
    Moller-Plesset (MP2) Energy Correction using Tensor Factorization of the Grid-Based Two-Electron Integrals.
    Preprint 26/2013, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2013.
    Comput. Phys. Communications, 185 (2014) pp. 2-10.

  29. V. Khoromskaia, B. N. Khoromskij and R. Schneider.
    Tensor-structured Factorized Calculation of Two-electron Integrals in a General Basis.
    Preprint 29/2012, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2012.
    SIAM J. Sci. Comput. , Vol. 35, no. 2, A987-A1010, 2013.

  30. V. Khoromskaia, D. Andrae and B. N. Khoromskij.
    Fast and Accurate Tensor Calculation of the Fock Operator in a General Basis.
    Preprint 4/2012, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2012.
    Comput. Phys. Communications , 183 (2012) 2392-2404.

  31. V. Khoromskaia, B. N. Khoromskij and R. Schneider.
    QTT Representation of the Hartree and Exchange Operators in Electronic Structure Calculations.
    Preprint 37/2011, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2011.
    Comput. Methods Appl. Math. , v.11, No.3, pp. 327-41, 2011.

  32. T. Blesgen, V. Gavini and V. Khoromskaia.
    Approximation of the Electron Density of Aluminium Clusters in Tensor-Product Format.
    Preprint 66/2009, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2009.
    J. Comput. Phys. , 231 (2012), 2551-2564.

  33. B. N. Khoromskij, V. Khoromskaia, and H.-J. Flad.
    Numerical Solution of the Hartree-Fock Equation in Multilevel Tensor-structured Format.
    Preprint 44/2009, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2009.
    SIAM J. Sci. Comput., v. 33, No.1, pp. 45-65, 2011.

  34. V. Khoromskaia.
    Numerical Solution of the Hartree-Fock Equation by Multilevel Tensor-structured methods.
    Dissertation (pdf, English), TU Berlin, 2010, pp. 1-157.
    TU Berlin OPUS entry: (pdf, English) https://depositonce.tu-berlin.de/bitstream/11303/3016/1/Dokument_34.pdf

  35. V. Khoromskaia.
    Computation of the Hartree-Fock Exchange by the Tensor-Structured Methods.
    Preprint 25/2009, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2009.
    Comput. Methods in Appl. Math., vol. 10, No 2, pp.204-218, 2010.

  36. B. N. Khoromskij and V. Khoromskaia.
    Multigrid Accelerated Tensor Approximation of Function Related Multi-dimensional Arrays.
    Preprint 40/2008, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2008.
    SIAM J. Sci. Comput., vol. 31, No. 4, pp. 3002-3026, 2009.

  37. B. N. Khoromskij, V. Khoromskaia, S.R. Chinnamsetty, and H.-J. Flad.
    Tensor Decomposition in Electronic Structure Calculations on 3D Cartesian Grids.
    Preprint 65/2007, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2007.
    J. Comput. Phys. , 228(2009), pp. 5749-5762, 2009.

  38. B. N. Khoromskij and V. Khoromskaia.
    Low Rank Tucker-Type Tensor Approximation to Classical Potentials.
    Preprint 105/2006, Max-Planck Institute for Mathematics in the Sciences, Leipzig, 2006.
    Central European Journ. Math. v.5, N.3, pp.523-550, 2007.


    Papers in computer science, since 1975

  39. V. Kh. Khoromskaia.
    Petri Nets Based Modelling of Control Flow for Memory-aid Interactive Programs in Telemedicine.
    Preprint JINR E-11-2004-81, Dubna, Moscow region, 2004;
    Bulletin of PF University of Russia, Moscow, Series Applied and Computer Mathematics, 2004, Vol.3, No.1, pp.74-84.

  40. Jaenicke, h., Khoromskaia, V., Tittgemeyer, M. and Kruggel, F.
    Fast affine scaling of the 3D MR images with lesions.
    Max-Planck-Institute for Cognitive Neuroscience, Annual Report 2002,2.7.4, Leipzig.

  41. V.Kh. Khoromskaya, B.N. Khoromskij.
    On the Computing Complexity of Iterative Substructuring Algorithms in Nonlinear Magnetostatic Problems.
    Preprint JINR E2-92-450, Joint Institute for Nuclear Research, Dubna, Moscow region, 1992.

  42. E.D. Lapchik, V. F. Rubtzov, A. V. Trifonov, V.Kh. Khoromskaya, V.N. Shkudenkov.
    Programs for Controlling the AELT-2/160 Automatic Film Scanning Device On-line with the SM-4 Computer.
    Communications of the Joint Institute for Nuclear Research, 10-85-7, Dubna, Moscow region, 1985.

  43. M.K. Baranchuk,.., V.Kh. Khoromskaya, V.N. Shkudenkov.
    Scanning control of the AELT-2/160 Automatic Film Scanning System On-line with the SM-4 Computer.
    Communications of the Joint Institute for Nuclear Research, 10-83-538, Dubna, Moscow region, 1983.

  44. V.F. Rubtsov, V.N. Smirnov, V.Kh. Khoromskaya.
    Test programs for developing the scanning control hardware for the AELT-2/160 Automatic Film
    Scanning System with the On-line SM-4 Computer.
    JINR DP B1-10-83-631, Dubna, Moscow region, 1983 .

  45. V.F. Rubtsov, V.N. Smirnov, V.Kh. Khoromskaya.
    FIFO Memory Block for Data Buffering in the AELT-2/160 Automatic Film Scanning System
    with the On-line SM-4 Computer.
    Communications of the Joint Institute for Nuclear Research, 10-83-408, Dubna, Moscow region, 1983.

  46. V.A. Vagov, D. Rubin, V.Kh. Khoromskaya.
    Logic Analysers. Data Selection (survey).
    Communications of the Joint Institute for Nuclear Research, 11-82-645, Dubna, Moscow region, 1982.

  47. V.A. Vagov, D. Rubin, V.Kh. Khoromskaya.
    Logic Analysers. Block Diagram.
    Communications of the Joint Institute for Nuclear Research, 11-82-644, Dubna, Moscow region, 1982.

  48. Ya. Ruzhichka, M.R. Har'yuzov, V.Kh. Khoromskaya.
    Using the Networking Interface of Two Processors CDC-1604A for Controlling the Scanning Process
    at the HPD by the Graphic Display.
    Communications of the Joint Institute for Nuclear Research, 10-11214, Dubna, Moscow region, 1978.

  49. B.A. Bezrukov, A.I. Efimova, F. Kotorobaj, V.I. Moroz, V.Kh. Khoromskaya.
    Interface for Connecting VT-340 with the Computer CDC-1604A.
    Communications of the Joint Institute for Nuclear Research, 11-10425, Dubna, Moscow region, 1977.

  50. B.A. Bezrukov, A.F. Vinogradov, A. I. Efimova, F. Kotorobaj, V.I. Moroz, V.I.Pervushov, V.N. Samojlov, Yu.V. Stolyarskij,
    V.Kh. Khoromskaya, N.I.Chulkov, S.A Tschelev.
    Basic Principles of Using NML EC-5012 for the Computer CDC-1604A.
    Communications of the Joint Institute for Nuclear Research, 11-9188, Dubna, Moscow region, 1975.

  51. B.A. Bezrukov, A.F. Vinogradov, A. I. Efimova, F. Kotorobaj, V.I. Moroz, V.I.Pervushov, V.N. Samojlov, Yu.V. Stolyarskij,
    V.Kh. Khoromskaya, N.I.Chulkov, S.A Tschelev.
    Interface for Networking Two Computers CDC-1604A.
    Communications of the Joint Institute for Nuclear Research, 10-9191, Dubna, Moscow region, 1975.

Unpublished

  1. V. Khoromskaia.
    Multilevel Tucker Approximation of 3D Tensors,
    2007-2009.

  2. V. Khoromskaia and E. Twerdowski.
    Wavelet Data Compression for Ultrasonic Full Transient Analysis.
    2004, manuscript.

  3. V. Khoromskaia.
    Fast affine scaling of the 3D MRT brain images with lesions.
    Max-Planck-Institute for Cognitive Neuroscience.
    2002, manuscript.
last modified 22.02.2023 by V.Khoromskaia.