Fermionic Partial Transpose in the Overlap Matrix Framework for Entanglement Negativity

• URL: http://arxiv.org/abs/2503.07742v2
• Date: Wed, 12 Mar 2025 06:08:37 GMT
• Title: Fermionic Partial Transpose in the Overlap Matrix Framework for Entanglement Negativity
• Authors: Jun Qi Fang, Xiao Yan Xu,
• Abstract summary: We introduce the fermionic partial transpose into the overlap matrix approach.<n>We derive an explicit formula for calculating entanglement negativity in bipartite systems.<n>We numerically compute the logarithmic negativity of two lattice models to verify the Gioev-Klich-Widom scaling law.
• Score: 0.4209374775815558
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Over the past two decades, the overlap matrix approach has been developed to compute quantum entanglement in free-fermion systems, particularly to calculate entanglement entropy and entanglement negativity. This method involves the use of partial trace and partial transpose operations within the overlap matrix framework. However, previous studies have only considered the conventional partial transpose in fermionic systems, which does not account for fermionic anticommutation relations. Although the concept of a fermionic partial transpose was introduced in \cite{Shapourian2017prb}, it has not yet been systematically incorporated into the overlap matrix framework. In this paper, we introduce the fermionic partial transpose into the overlap matrix approach, provide a systematic analysis of the validity of partial trace and partial transpose operations, and derive an explicit formula for calculating entanglement negativity in bipartite systems. Additionally, we numerically compute the logarithmic negativity of two lattice models to verify the Gioev-Klich-Widom scaling law. For tripartite geometries, we uncover limitations of the overlap matrix method and demonstrate that the previously reported logarithmic negativity result for a homogeneous one-dimensional chain in a disjoint interval geometry exceeds its theoretical upper bound. Our findings contribute to a deeper understanding of partial trace and partial transpose operations in different representations.

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