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[10]Connectivity Engineering: Inverse Reconstruction of Discrete Bulk Topology from Entanglement Fingerprints

Wenjun Luo

Published Oct 25, 2026• 0 citations
Publisher

Abstract

In the framework of connectivity engineering, this paper proposes a method to inversely reconstruct the internal discrete topological connectivity from the boundary entanglement entropy spectrum. Based on a one-dimensional spin-1/2 network, we extract a three-dimensional entanglement fingerprint characterizing the internal connectivity: the mutual information peak, the peak position, and the late-time residual fidelity. Numerical diagnostics show that when the connectivity reaches k=3, the mutual information peak reaches 1.49 times that of the baseline network, and the system enters the topological saturation regime; at this point, the fingerprint vectors for k=3 and k=4 are indistinguishable within numerical precision. We prove that this degeneracy originates from the joint mechanism of graph-theoretic topology and dynamical decay, and further increasing k does not yield substantial cross-region entanglement channels. Even in the presence of numerical noise, the significant gap in late-time fidelity between k=2 and the saturation regime ensures the high robustness of the inverse mapping. This result establishes the effectiveness of the "entanglement fingerprint distance" as an inverse diagnostic operator, providing an operational benchmark for discrete bulk geometry reconstruction using purely boundary observables.

DOI
10.5281/zenodo.23643056

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In the framework of connectivity engineering, this paper proposes a method to inversely reconstruct the internal discrete topological connectivity from the boundary entanglement entropy spectrum. Based on a one-dimensional spin-1/2 network, we extract a three-dimensional entanglement fingerprint characterizing the internal connectivity: the mutual information peak, the peak position, and the late-time residual fidelity. Numerical diagnostics show that when the connectivity reaches k=3, the mutual information peak reaches 1.49 times that of the baseline network, and the system enters the topological saturation regime; at this point, the fingerprint vectors for k=3 and k=4 are indistinguishable within numerical precision. We prove that this degeneracy originates from the joint mechanism of graph-theoretic topology and dynamical decay, and further increasing k does not yield substantial cross-region entanglement channels. Even in the presence of numerical noise, the significant gap in late-time fidelity between k=2 and the saturation regime ensures the high robustness of the inverse mapping. This result establishes the effectiveness of the "entanglement fingerprint distance" as an inverse diagnostic operator, providing an operational benchmark for discrete bulk geometry reconstruction using purely boundary observables.
The contradiction between the thermodynamic arrow of time and microscopic dynamical reversibility is a core problem in statistical physics. Within the framework of connectivity engineering, this paper proposes a new mechanism: irreversible accumulation of subsystem entropy caused by topological quenching. We numerically simulate the cyclic switching of a one-dimensional spin network between topological steps k=1 and k=4. Results show that each switch from the highly connected state to the frustrated state leads to an irreversible "fall" of information into the local entanglement space; when switched back to the initial topology, the subsystem entanglement entropy cannot recover to its initial value, but instead surges from 0 to approximately 2.96 and remains in the saturation regime, exhibiting a unidirectional entropy accumulation. Since the theoretical maximum entropy of this subsystem is 3.0, this irreversible saturation directly reveals the limit of information coarse-graining. The above results prove that the microscopic origin of the arrow of time is precisely the information scrambling caused by the irreversibility of underlying geometric topological reconstruction.
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There is a huge discrepancy between the divergent vacuum zero-point energy in quantum field theory and the macroscopic cosmological constant. Within the framework of connectivity engineering, this paper explores the regulatory mechanism of underlying graph topology on the ground state energy of finite systems. By introducing a truncated step k in a one-dimensional XXZ spin network, numerical results show that the absolute value of the system's ground state energy does not decline trivially and linearly with the reduction of interaction bonds, but rather exhibits strong non-trivial topological frustration. The normal network (k=1), due to strong local entanglement, exhibits a lower bare ground state energy density; while after introducing long-range geometric decoupling, the parity matching of sub-chain lengths and boundary reconstruction lead to a non-monotonic evolution of the ground state energy density, reaching a maximum at k=4 due to odd-lattice frustration. This topology-induced energy renormalization conceptually provides a minimal discrete sandbox for the "geometric truncation" of vacuum energy, and implies that the residual energy of macroscopic spacetime (dark energy) may correspond to the geometric frustration tension of the underlying discrete network that has not been fully canceled after topological saturation.
Topological order represents a profound state of matter characterized by exotic properties robust against local perturbations, such as fractionalized excitations and ground state degeneracy dependent on system topology. While extensively studied in closed quantum systems, the detection and characterization of topological order in open quantum systems, which inevitably interact with their environment, remain a significant challenge. Environmental coupling typically introduces decoherence and dissipation, potentially obscuring or even destroying fragile quantum correlations. This paper investigates the concept of "entropic fingerprints" as a robust diagnostic tool for identifying topological order in systems subjected to environmental influences. We explore how various entanglement measures, particularly the topological entanglement entropy and related information-theoretic quantities, can be adapted and reinterpreted in the context of non-equilibrium steady states or dynamically evolving open systems. Through a theoretical framework employing Lindblad master equations and tensor network methods, we demonstrate that universal signatures of topological order, though potentially modified, can persist in the steady-state entanglement properties of open systems. Our findings suggest that specific patterns in the bipartite entanglement entropy, conditional entropies, and mutual information, robust against a finite range of environmental parameters, can serve as reliable indicators of underlying topological phases. This research not only offers a pathway for experimentally probing topological materials in realistic, noisy environments but also deepens our fundamental understanding of how quantum information is preserved or degraded under open system dynamics.