Tensor product approximation with optimal rank in quantum chemistry.
By Sambasiva Rao Chinnamsetty, M. Espig, Boris N. Khoromskij, Wolfgang Hackbusch, Heinz-Jürgen Flad. 2007
61 citations recorded by the source corpus.
Subfields: Computational Mathematics, Spectroscopy, Statistical and Nonlinear Physics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mathematics
- Boris N. Khoromskij
- Wolfgang Hackbusch
- André Uschmajew
- Reinhold Schneider
- Ivan V. Oseledets
- Heinz-Jürgen Flad
- Lars Grasedyck
- Christine Tobler
In Spectroscopy
- Wolfgang Hackbusch
- Heinz-Jürgen Flad
- Sambasiva Rao Chinnamsetty
- Boris N. Khoromskij
- M. Espig
- André Uschmajew
- Reinhold Schneider
- Lars Grasedyck
In Statistical and Nonlinear Physics
- Wolfgang Hackbusch
- M. Espig
- Boris N. Khoromskij
- Heinz-Jürgen Flad
- André Uschmajew
- Alexander Litvinenko
- Sambasiva Rao Chinnamsetty
- Elmar Zander
Citations in the corpus
- A literature survey of low‐rank tensor approximation techniques (2013, neutral): “…convolution [152]; • computational tasks in electronic structure calculations, e.g., based on Hartree-Fock or DFT models [23,24,31,44,45,47,87,141–146,150,156–159]; • the solution of stochastic and parametric PDEs [68,69,76,77,161,165,171,189,202]; • approximation of Green’s…”
- Efficient Analysis of High Dimensional Data in Tensor Formats (2012, background): “The similar splitting work, but in application in another context was done in [12, 13, 10, 11, 5].”
- Efficient multi-scale computation of products of orbitals in electronic structure calculations (2010, methodology): “Within the present work, we focus on an alternative approach for the computation of two-electron integrals [11,12,31] which is based on the best fixed-rank tensor product approximation of orbitals.”
- Concepts of Data-Sparse Tensor-Product Approximation in Many-Particle Modelling (2008, methodology): “Similar results for wavelets are presented in [14].”
- Black Box Low Tensor-Rank Approximation Using Fiber-Crosses (2009, background): “Nonetheless, available state-of-the-art methods are quite efficient and have proven to be reliable in many practical cases [2, 4, 7].”
- Use of tensor formats in elliptic eigenvalue problems (2012, unknown): “…E. Tyrtyshnikov 3 1Max-Planck-Institut für Mathematik in den Naturwissenschaften, D-04103, Leipzig, Germany 2Universität Zürich, Switzerland 3Institute of Numerical Mathematics, Russian Academy of Sciences, Gubkina 8, 119333 Moscow, Russia SUMMARY We investigate approximations to eigenfunctions…”
- Alternating Minimal Energy Methods for Linear Systems in Higher Dimensions (2013, unknown): “For ALS there is also a lack of convergence estimates both in the classical papers [16, 4], and in the recent ones, where ALS was applied to the Tucker model [5, 33], tensor trains [29], hierarchical Tucker format [25] and high–dimensional interpolation [34].”
- Adaptive low rank wavelet methods and applications to two-electron Schrödinger equations (2012, background): “, in density fitting schemes in quantum chemistry – the combination of separable expansions with wavelet approximation of lower-dimensional factors has been considered in [25, 26, 24, 27].”
- Regularity of Tensor Product Approximations to Square Integrable Functions (2011, background): “We ask the following question: Which regularity can we expect the factors uk of a best approximation to have in comparison to the regularity of f ? This question is important for instance in quantum chemistry [2,3,5, 9,10], where tensor products are used to approximate wave functions of atoms and mo”
- A regularized Newton method for the efficient approximation of tensors represented in the canonical tensor format (2012, methodology): “In [4,5] we made the same observation as for the model problem.”
- The tensor product approximation to single-electron systems (2009, methodology): “More details have already been discussed in our previous article [5] and also in [6].”