Entanglement of weighted graphs uncovers transitions in variable-range interacting models
Debkanta Ghosh, Keshav Das Agarwal, Pritam Halder, Aditi Sen De

TL;DR
This paper investigates how the entanglement patterns in variable-range interacting Ising models, measured by GGM, reveal phase transitions and intrinsic properties of the Hamiltonian, with implications for quantum computation and state reduction.
Contribution
It introduces a method to detect interaction range transitions via GGM dynamics and proposes a local measurement strategy for state reduction in weighted graph states.
Findings
GGM dynamics detect transition points in interaction ranges.
Time-derivative and time-averaged GGM identify different regimes.
Local measurement strategy reduces system size while preserving entanglement properties.
Abstract
The cluster state acquired by evolving the nearest-neighbor (NN) Ising model from a completely separable state is the resource for measurement-based quantum computation. Instead of an NN system, a variable-range power law interacting Ising model can generate a genuine multipartite entangled (GME) weighted graph state (WGS) that may reveal intrinsic characteristics of the evolving Hamiltonian. We establish that the pattern of generalized geometric measure (GGM) in the evolved state with an arbitrary number of qubits is sensitive to fall-off rates and the range of interactions of the evolving Hamiltonian. We report that the time-derivative and time-averaged GGM at a particular time can detect the transition points present in the fall-off rates of the interaction strength, separating different regions, namely long-range, quasi-local and local ones in one- and two-dimensional lattices with…
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Taxonomy
TopicsQuantum many-body systems · Theoretical and Computational Physics · Complex Network Analysis Techniques
