Connectivity--Interference Competition in Coherent Transport on Percolated Hierarchical Small-World Networks
- URL: http://arxiv.org/abs/2608.19130v1
- Date: Wed, 19 Aug 2026 17:26:32 GMT
- Title: Connectivity--Interference Competition in Coherent Transport on Percolated Hierarchical Small-World Networks
- Abstract summary: Adding links generally improves classical transport by increasing the number of available paths.<n>We show that coherent quantum transport can display the opposite behavior.<n>Results provide a design principle for coherent transport in disordered photonic and quantum-network architectures.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Adding links generally improves classical transport by increasing the number of available paths. We show that coherent quantum transport can display the opposite behavior. Using continuous-time quantum walks on a percolated hierarchical small-world network, we identify a coherent overconnectivity penalty: root-to-boundary transport is maximized at intermediate bond probability and decreases as the network approaches full connectivity. The effect is quantified by the final-layer limiting probability $χ_N$ and by the penalty $P_Q=1-χ_N(p=1)/\max_pχ_N(p)$, which measures the loss caused by making the architecture fully connected. The optimum results from a competition between shortcut-assisted spreading and interference-induced intra-layer recirculation. Spectral analysis shows that bond dilution creates motif-induced degeneracies and reorganizes the eigenstates connecting the root to the outermost layer. A comparison with dephased and classical transport shows that the non-monotonic landscape is not a purely geometrical percolation effect, but a coherent architecture-dependent phenomenon. These results provide a design principle for coherent transport in disordered photonic and quantum-network architectures.
Related papers
- From Self-Attention to Connection Laplacian: A Unified Operator View of Transformers [53.505136935517925]
Self-attention is a ubiquitous primitive in modern sequence models, yet its operator-level geometry is only partially understood.<n>We prove that single-head attention (SHA) is exactly a connection propagation step with constant transport.<n>We find that trained Transformers across scales (from 124M to 8B) and structures (encoder/decoder) exhibit geometric structure consistent with our theory.
arXiv Detail & Related papers (2026-07-12T09:44:54Z) - Quantum percolation theory for dynamic propagation connectivity of transport networks [2.519906683279153]
Connectivity degradation in transport networks under structural disturbance is a central problem in network resilience research.<n>Existing methods rely mainly on percolation theory and topological connectivity measures.<n>This paper introduces quantum percolation theory into transport network connectivity analysis.
arXiv Detail & Related papers (2026-06-29T12:32:23Z) - Interplay of Electrode Coupling Engineering, Quasiperiodicity, and Magnetic Flux in Quantum Transport through a Su-Schrieffer-Heeger Ring [20.955595307205247]
We show that engineering electrode-coupling configurations can reshape coherent transport phenomena in quasiperiodic quantum systems.<n>We analyze charge and heat transport, as well as current fluctuations, in a quasiperiodic Su-Schefferri-Heeger ring with both symmetric and asymmetric multi-site reservoir couplings.
arXiv Detail & Related papers (2026-06-27T10:15:04Z) - Asymptotic Limits of Entanglement Distribution [43.748379918040854]
We investigate the limits of entanglement distribution across quantum networks utilizing intermediate stations and local operations.<n>We establish a strict dichotomy: the preservation of entanglement over arbitrarily long distances is possible if the underlying quantum channel admits a correctable subspace.<n>We derive a fundamental lower bound on the physical resource requirements, proving that for channels without a correctable subspace, the number of parallel channels per link must scale at least logarithmically with the number of intermediate stations to sustain a non-zero amount of entanglement.
arXiv Detail & Related papers (2026-05-22T09:56:38Z) - Parrondo-type enhancement of quantum-state transfer in spin chains [1.9078991171384019]
We investigate the transfer of single-qubit and Bell states in finite $XX$ spin chains under periodic switching.<n>We show that periodic driving can outperform static configurations and achieve higher transfer fidelities.
arXiv Detail & Related papers (2026-03-15T18:20:59Z) - The Inductive Bias of Convolutional Neural Networks: Locality and Weight Sharing Reshape Implicit Regularization [57.37943479039033]
We study how architectural inductive bias reshapes the implicit regularization induced by the edge-of-stability phenomenon in gradient descent.<n>We show that locality and weight sharing fundamentally change this picture.
arXiv Detail & Related papers (2026-03-05T04:50:51Z) - ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks [71.02216400133858]
Physics-informed neural networks (PINNs) have earned high expectations in solving partial differential equations (PDEs)<n>Previous research observed the propagation failure phenomenon of PINNs.<n>This paper provides a formal and in-depth study of propagation failure and its root cause.
arXiv Detail & Related papers (2025-02-02T13:56:38Z) - Unveiling the Importance of Nonshortest Paths in Quantum Networks [1.2920416805641026]
We apply a statistical physics model -- concurrence percolation -- to uncover the origin of stronger connectivity on scale-free networks.<n>Our findings highlight a crucial principle for QN design: when non-shortest paths are abundant, they notably enhance QN connectivity beyond what is achievable with classical percolation.
arXiv Detail & Related papers (2024-02-23T17:45:00Z) - Engineering Transport via Collisional Noise: a Toolbox for Biology
Systems [44.99833362998488]
We study a generalised XXZ model in the presence of collision noise, which allows to describe environments beyond the standard Markovian formulation.
Results constitute an example of the essential building blocks for the understanding of quantum transport in noisy and warm disordered environments.
arXiv Detail & Related papers (2023-11-15T12:55:28Z) - Deep Architecture Connectivity Matters for Its Convergence: A
Fine-Grained Analysis [94.64007376939735]
We theoretically characterize the impact of connectivity patterns on the convergence of deep neural networks (DNNs) under gradient descent training.
We show that by a simple filtration on "unpromising" connectivity patterns, we can trim down the number of models to evaluate.
arXiv Detail & Related papers (2022-05-11T17:43:54Z) - Rethinking Skip Connection with Layer Normalization in Transformers and
ResNets [49.87919454950763]
Skip connection is a widely-used technique to improve the performance of deep neural networks.
In this work, we investigate how the scale factors in the effectiveness of the skip connection.
arXiv Detail & Related papers (2021-05-15T11:44:49Z) - Concurrence Percolation in Quantum Networks [3.52359746858894]
We introduce a new statistical theory, concurrence percolation theory (ConPT)
We find that the entanglement transmission threshold predicted by ConPT is lower than the known classical-percolation-based results.
ConPT also shows a percolation-like universal critical behavior derived by finite-size analysis on the Bethe lattice.
arXiv Detail & Related papers (2021-03-25T17:14:48Z) - Optimizing Mode Connectivity via Neuron Alignment [84.26606622400423]
Empirically, the local minima of loss functions can be connected by a learned curve in model space along which the loss remains nearly constant.
We propose a more general framework to investigate effect of symmetry on landscape connectivity by accounting for the weight permutations of networks being connected.
arXiv Detail & Related papers (2020-09-05T02:25:23Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.