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Journal Article (6)

  1. 1.
    Benner, P.; Khoromskaia, V.; Khoromskij, B. N.: Range-Separated Tensor Format for Many-Particle Modeling. SIAM Journal on Scientific Computing 40 (2), pp. A1034 - A1062 (2018)
  2. 2.
    Litvinenko, A.; Keyes, D.; Khoromskaia, V.; Khoromskij, B. N.; Matthies, H. G.: Tucker Tensor Analysis of Matérn Functions in Spatial Statistics. Computational Methods in Applied Mathematics (accepted)
  3. 3.
    Benner, P.; Dolgov, S.; Khoromskaia, V.; Khoromskij, B. N.: Fast Iterative Solution of the Bethe–Salpeter Eigenvalue Problem Using Low-Rank and QTT Tensor Approximation. Journal of Computational Physics 334, pp. 221 - 239 (2017)
  4. 4.
    Khoromskaia, V.; Khoromskij, B. N.: Block Circulant and Toeplitz Structures in the Linearized Hartree–Fock Equation on Finite Lattices: Tensor Approach. Computational Methods in Applied Mathematics 17 (3), pp. 431 - 455 (2017)
  5. 5.
    Benner, P.; Khoromskaia, V.; Khoromskij, B. N.: A Reduced Basis Approach for Calculation of the Bethe-Salpeter Excitation Energies by using Low-Rank Tensor Factorisations. Molecular Physics 114 (7-8), pp. 1148 - 1161 (2016)
  6. 6.
    Khoromskaia, V.; Khoromskij, B. N.: Tensor numerical methods in quantum chemistry: from Hartree–Fock to excitation energies. Physical Chemistry Chemical Physics 17 (47), pp. 31491 - 31509 (2015)

Working Paper (1)

  1. 7.
    Benner, P.; Khoromskaia, V.; Khoromskij, B. N.; Yang, C.: Computing the Density of States for Optical Spectra by Low-Rank and QTT Tensor Approximation. (2018)
 
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