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Document type:
Bachelorarbeit
Author(s):
Zekai Li
Title:
Decomposition Methods for Tensor Networks
Translated title:
Zerlegunsgmethoden für Tensornetzwerke
Abstract:
We introduce and evaluate a modified Time Evolution Block Decimation (TEBD) algorithm employing a truncation method based on QR decomposition instead of Singular Value Decomposition (SVD). This modification significantly reduces the computational complexity from d^3 to d&2 , where d represents the dimension of the physical Hilbert space. In a benchmark study involving a global quench simulation in a d-state quantum clock model, we found that compared to the SVD-based TEBD algorithm, the approach based on QR decomposition provides a considerable speedup.
Supervisor:
Christian B. Mendl
Advisor:
Philipp Seitz
Year:
2024
Quarter:
1. Quartal
Year / month:
2024-03
Month:
Mar
Language:
en
University:
Technical University of Munich
Faculty:
TUM School of Computation, Information and Technology
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