Abstract
The main goal of this paper is to extend the so-called Dirac–Frenkel variational principle in the framework of tensor Banach spaces. To this end we observe that a tensor product of normed spaces can be described as a union of disjoint connected components. Then we show that each of these connected components, composed by tensors in Tucker format with a fixed rank, is a Banach manifold modelled in a particular Banach space, for which we provide local charts. The description of the local charts of these manifolds is crucial for an algorithmic treatment of high-dimensional partial differential equations and minimisation problems. In order to describe the relationship between these manifolds and the natural ambient space, we prove under natural conditions that each connected component can be immersed in a particular ambient Banach space. This fact allows us to finally extend the Dirac–Frenkel variational principle in the framework of topological tensor spaces.
Similar content being viewed by others
Notes
The condition of an open covering is not needed, see [25].
It suffices to have in (3.2) the terms \(n=0\) and \(n=N.\) The derivatives are to be understood as weak derivatives.
\(\mathbf {v}_{0}\) can be chosen as the best approximation of \(\mathbf { u}_{0}\) in \(\mathfrak {M}_{\mathfrak {r}}(\mathbf {V}_D)\) because a best approximation exists [11].
Observe that the derivative at t of a map \(\mathbf {v}:I \rightarrow \mathfrak {M}_{(1,\ldots ,1)}(\mathbf {V})\) considered as a morphism between manifolds is given by a linear map \(\mathrm {T}_t \mathbf {v}:\mathbb {R} \rightarrow \mathbb {T}_{\mathbf {v}(t)}(\mathfrak {M}_{(1,\ldots ,1)}(\mathbf {V}))\) which is characterised by the fact that \(\mathrm {T}_t \mathbf {v}(\dot{\mu }) = \dot{\mu } \mathrm {T}_t \mathbf {v}(1)\) holds for all \(\dot{\mu } \in \mathbb {R}.\) It allows us to identify the linear map \(\mathrm {T}_t \mathbf {v}\) with the vector \(\mathrm {T}_t \mathbf {v}(1),\) that represents the derivative of the curve \(\mathbf {v}(t)\) by using local coordinates which is usually written as \(\dot{\mathbf {v}}(t)\) by abuse of notation.
References
P. A. Absil, R. Mahoni, and R. Sepulchre, Optimization Algorithms on Matrix Manifolds, Princeton University Press, Princeton, 2008.
Y. I. Alber, James orthogonality and orthogonal decompositions of Banach spaces. J. Math. Anal. Appl. 312 (2005), 330–342.
A. Arnold and T. Jahnke, On the approximation of high-dimensional differential equations in the hierarchical Tucker format. BIT Numer. Math. 54 (2014), 305–341.
C. Bardos, I .Catto, N. Mauser and S. Trabelsi, Setting and Analysis of the multiconfiguration time-dependent Hartree-Fock equations, Arch. Rational Mech. Anal. 198 Issue 1 (2010), 273–330.
M. S. Berger, Nonlinearity and Functional Analysis. Lectures on Nonlinear Problems in Mathematical Analysis. Academic Press, Cambridge, 1997.
D. Belita, Smooth homogeneous structures in operator theory. Chapman & Hall/CRC Press, Boca Raton, 2006.
I. Cioranescu, Geometry of Banach Spaces, Duality Mappings and Nonlinear Problems. Springer-Verlag, 1990.
G. Dirr, V. Rakocevic, and H. K. Wimmer, Estimates for projections in Banach spaces and existence of direct complements. Studia Math., 170:2 (2005), 211–216.
A. Douady, Le problème des modules pour les sous–espaces analytiques compacts d’un espace analytique donné. Annales de l’Institut Fourier, 16 (1) (1966), 1–95.
M. Fabian, P. Habala, P. Hajek, and V. Montesinos, Banach Space Theory. Springer-Verlag, 2011.
A. Falcó and W. Hackbusch, Minimal subspaces in tensor representations. Found. Comput. Math. 12 (2012), 765–803.
A. Falcó and A. Nouy, Proper generalized decomposition for nonlinear convex problems in tensor Banach spaces. Numer. Math. 121 (2012), 503–530.
K. Floret, Weakly compact sets, Lect. Notes Math., vol.119. Springer-Verlag, 1980.
W. H. Greub, Linear Algebra, Graduate Text in Mathematics, 4th ed., Springer-Verlag, 1981.
A. Grothendieck, Résumé de la th éorie métrique des produit tensoriels topologiques. Bol. Soc. Mat. S ão Paulo 8 (1953/56), 1–79.
E. Hairer, C. Lubich, and G. Wanner, Geometrical Numerical Integration: Structure-Preserving Algo-rithms for Ordinary Differential Equations, 2nd ed., Springer-Verlag, 2006.
J. Haegeman, M. Mariën, T. J. Osborne, and F. Verstraete, Geometry of matrix product states: Metric, parallel transport, and curvature. Journal of Mathematical Physics 55, 021902 (2014).
W. Hackbusch and S. Kühn, A new scheme for the tensor representation. J. Fourier Anal. Appl. 15 (2009), 706–722.
W. Hackbusch, Tensor spaces and numerical tensor calculus. Springer-Verlag, 2012.
P. Hájek and M. Johanis, Smooth analysis in Banach spaces. Series in Non-linear analysis and applications 19, Walter de Gruyter, 2014.
D. R. Hartree, The calculation of atomic structures. Chapman & Hall, 1957.
S. Holtz, Th. Rohwedder, and R. Schneider, On manifold of tensors of fixed TT rank. Numer. Math. 121 (2012), 701–731.
S. Kamimura and W. Takahashi, Strong convergence of a proximal–type algorithm in a Banach space. SIAM J. Optim. 13 (2003), 938–945.
O. Koch and C. Lubich, Dynamical tensor approximation. SIAM J. Matrix Anal. Appl. 31 (2010), 2360-2375.
S. Lang, Differential and Riemannian Manifolds. Graduate Texts in Mathematics 160. Springer–Verlag, 1995.
W. A. Light and E. W. Cheney, Approximation theory in tensor product spaces. Lect. Notes Math. 1169, Springer–Verlag, 1985.
C. Lubich, From Quantum to Classical Molecular Dynamics: Reduced Models and Numerical Analysis. European Mathematical Society, 2008.
J. E. Marsden, T. Ratiu, and R. Abraham, Manifolds, Tensor Analysis, and Applications. Springer-Verlag, 1988.
B. Simon, Uniform crossnorms. Pacific J. Math. 46 (1973), 555–560.
I. V. Oseledets, A new tensor decomposition. Doklady Math. 80 (2009), 495–496.
I. V. Oseledets, Tensor-train decomposition. SIAM J. Sci. Comput. 33 (2011), 2295–2317.
I. V. Oseledets and E. E. Tyrtyshnikov, TT-cross approximation for multidimensional arrays. Linear Algebra Appl. 432 (2010), 70-88.
E. Schmidt, Zur Theorie der linearen und nichtlinearen Integralgleichungen I, Math. Ann. 63 (1906), 433-476.
H. Upmeier, Symmetric Banach manifolds and Jordan \( C^*\) Algebras. North–Holland, 1985.
A. Uschmajew and B. Vandereycken, The geometry of algorithms using hierarchical tensors. Linear Algebra and its Applications, Volume 439, Issue 1, (2013) 133-166.
F. Verstraete and J. I. Cirac, Matrix product states represent ground states faithfully. Phys. Rev. B - Condens. Matter Mater. Phys. 73, 094423 (2006).
G. Vidal, Efficient classical simulation of slightly entangled quantum computations. Phys. Rev. Lett. 91 (14), 147902 (2003).
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Joseph M. Landsberg.
Rights and permissions
About this article
Cite this article
Falcó, A., Hackbusch, W. & Nouy, A. On the Dirac–Frenkel Variational Principle on Tensor Banach Spaces. Found Comput Math 19, 159–204 (2019). https://doi.org/10.1007/s10208-018-9381-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10208-018-9381-4