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Learning Relevant Features of Data with Multi-scale Tensor Networks
E. M. Stoudenmire
Inspired by coarse-graining approaches used in physics, we show how similar algorithms can be adapted for data. The resulting algorithms are based on layered tree tensor networks a…
Matrix product state techniques for two-dimensional systems at finite temperature
Benedikt Bruognolo, Zhenyue Zhu, Steven R. White +1
The density matrix renormalization group is one of the most powerful numerical methods for computing ground-state properties of two-dimensional (2D) quantum lattice systems. Here w…
Towards the solution of the many-electron problem in real materials: equation of state of the hydrogen chain with state-of-the-art many-body methods
Mario Motta, David M. Ceperley, Garnet Kin-Lic Chan +18
We present numerical results for the equation of state of an infinite chain of hydrogen atoms. A variety of modern many-body methods are employed, with exhaustive cross-checks and…
Sliced Basis Density Matrix Renormalization Group for Electronic Structure
E. Miles Stoudenmire, Steven R. White
We introduce a hybrid approach to applying the density matrix renormalization group (DMRG) to continuous systems, combining a grid approximation along one direction with a finite G…