Alternating and Gaussian fermionic Isometric Tensor Network States
Yantao Wu, Zhehao Dai, Sajant Anand, Sheng-Hsuan Lin, Qi Yang, Lei Wang, Frank Pollmann, Michael P. Zaletel

TL;DR
This paper introduces an improved alternating isometric tensor network state (isoTNS) for 2D quantum systems and a Gaussian fermionic extension, demonstrating superior entanglement mediation and ground state approximation capabilities.
Contribution
The paper presents an alternating isoTNS variant and a Gaussian fermionic tensor network framework, enhancing the representation of quantum many-body states and their entanglement structure.
Findings
Alternating isoTNS better captures ground states than original isoTNS.
Alternating isoTNS mediates entanglement more efficiently.
Numerical results show improved energy and bond-dimension scaling for fermionic models.
Abstract
Isometric tensor networks in two dimensions enable efficient and accurate study of quantum many-body states, yet the effect of the isometric restriction on the represented quantum states is not fully understood. We address this question in two main contributions. First, we introduce an improved variant of isometric network states (isoTNS) in two dimensions, where the isometric arrows on the columns of the network alternate between pointing upward and downward, hence the name alternating isometric tensor network states. Second, we introduce a numerical tool -- isometric Gaussian fermionic TNS (isoGfTNS) -- that incorporates isometric constraints into the framework of Gaussian fermionic tensor network states. We demonstrate in numerous ways that alternating isoTNS represent many-body ground states of two-dimensional quantum systems significantly better than the original isoTNS. First, we…
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Taxonomy
TopicsQuantum many-body systems · Computational Physics and Python Applications · Quantum, superfluid, helium dynamics
