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At least 901 records · Page 50

Implementability of two-qubit unitary operations over the butterfly network and the ladder network with free classical communication

We investigate distributed implementation of two-qubit unitary operations over two primitive networks, the butterfly network and the ladder network, as a first step to apply network coding for quantum computation. By classifying two-qubit unitary operations in terms of the Kraus-Cirac number, the number of non-zero parameters describing the global part of two-qubit unitary operations, we analyze which class of two-qubit unitary operations is implementable over these networks with free classical communication. For the butterfly network, we show that two classes of two-qubit unitary operations, which contain all Clifford, controlled-unitary and matchgate operations, are implementable over the network. For the ladder network, we show that two-qubit unitary operations are implementable over the network if and only if their Kraus-Cirac number do not exceed the number of the bridges of the ladder.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Implementing controlled-unitary operations over the butterfly network

We introduce a multiparty quantum computation task over a network in a situation where the capacities of both the quantum and classical communication channels of the network are limited and a bottleneck occurs. Using a resource setting introduced by Hayashi [1], we present an efficient protocol for performing controlled-unitary operations between two input nodes and two output nodes over the butterfly network, one of the most fundamental networks exhibiting the bottleneck problem. This result opens the possibility of developing a theory of quantum network coding for multiparty quantum computation, whereas the conventional network coding only treats multiparty quantum communication.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Phase multistability in a dynamical small world network

The effect of phase multistability is explored in a small world network of periodic oscillators with diffusive couplings. The structure of the network represents a ring with additional non-local links, which spontaneously arise and vanish between arbitrary nodes. The dynamics of random couplings is modeled by “birth” and “death” stochastic processes by means of the cellular automate approach. The evolution of the network under gradual increasing of the number of random couplings goes through stages of phases fluctuations and spatial cluster formation. Finally, in the presence of non-local couplings the phase multistability “dies” and only the in-phase regime survives.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stochastic approximation methods-Powerful tools for simulation and optimization: A survey of some recent work on multi-agent systems and cyber-physical systems

Stochastic approximation methods have found extensive and diversified applications. Recent emergence of networked systems and cyber-physical systems has generated renewed interest in advancing stochastic approximation into a general framework to support algorithm development for information processing and decisions in such systems. This paper presents a survey on some recent developments in stochastic approximation methods and their applications. Using connected vehicles in platoon formation and coordination as a platform, we highlight some traditional and new methodologies of stochastic approximation algorithms and explain how they can be used to capture essential features in networked systems. Distinct features of networked systems with randomly switching topologies, dynamically evolving parameters, and unknown delays are presented, and control strategies are provided.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Recovering network topologies via Taylor expansion and compressive sensing

Gaining knowledge of the intrinsic topology of a complex dynamical network is the precondition to understand its evolutionary mechanisms and to control its dynamical and functional behaviors. In this article, a general framework is developed to recover topologies of complex networks with completely unknown node dynamics based on Taylor expansion and compressive sensing. Numerical simulations illustrate the feasibility and effectiveness of the proposed method. Moreover, this method is found to have good robustness to weak stochastic perturbations. Finally, the impact of two major factors on the topology identification performance is evaluated. This method provides a natural and direct point to reconstruct network topologies from measurable data, which is likely to have potential applicability in a wide range of fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Coarse-grained model of water diffusion and proton conductivity in hydrated polyelectrolyte membrane

Using dissipative particle dynamics (DPD), we simulate nanoscale segregation, water diffusion, and proton conductivity in hydrated sulfonated polystyrene (sPS). We employ a novel model [Lee et al. J. Chem. Theory Comput. 11(9), 4395-4403 (2015)] that incorporates protonation/deprotonation equilibria into DPD simulations. The polymer and water are modeled by coarse-grained beads interacting via short-range soft repulsion and smeared charge electrostatic potentials. The proton is introduced as a separate charged bead that forms dissociable Morse bonds with the base beads representing water and sulfonate anions. Morse bond formation and breakup artificially mimics the Grotthuss mechanism of proton hopping between the bases. The DPD model is parameterized by matching the proton mobility in bulk water, dissociation constant of benzenesulfonic acid, and liquid-liquid equilibrium of water-ethylbenzene solutions. The DPD simulations semi-quantitatively predict nanoscale segregation in the hydrated sPS into hydrophobic and hydrophilic subphases, water self-diffusion, and proton mobility. As the hydration level increases, the hydrophilic subphase exhibits a percolation transition from isolated water clusters to a 3D network. The analysis of hydrophilic subphase connectivity and water diffusion demonstrates the importance of the dynamic percolation effect of formation and breakup of temporary junctions between water clusters. The proposed DPD model qualitatively predicts the ratio of proton to water self-diffusion and its dependence on the hydration level that is in reasonable agreement with experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design and verification of distributed logic controllers with application of Petri nets

The paper deals with the designing and verification of distributed logic controllers. The control system is initially modelled with Petri nets and formally verified against structural and behavioral properties with the application of the temporal logic and model checking technique. After that it is decomposed into separate sequential automata that are working concurrently. Each of them is re-verified and if the validation is successful, the system can be finally implemented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stochastic averaging and sensitivity analysis for two scale reaction networks

In the presence of multiscale dynamics in a reaction network, direct simulation methods become inefficient as they can only advance the system on the smallest scale. This work presents stochastic averaging techniques to accelerate computations for obtaining estimates of expected values and sensitivities with respect to the steady state distribution. A two-time-scale formulation is used to establish bounds on the bias induced by the averaging method. Further, this formulation provides a framework to create an accelerated “averaged” version of most single-scale sensitivity estimation methods. In particular, we propose the use of a centered ergodic likelihood ratio method for steady state estimation and show how one can adapt it to accelerated simulations of multiscale systems. Lastly, we develop an adaptive “batch-means” stopping rule for determining when to terminate the micro-equilibration process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Self-consistent hopping theory of activated relaxation and diffusion of dilute penetrants in dense crosslinked polymer networks

We generalize a microscopic statistical mechanical theory of the activated dynamics of dilute spherical penetrants in glass-forming liquids to study the influence of crosslinking in polymer networks on the penetrant relaxation time and diffusivity over a wide range of temperature and crosslink fraction (f n ). Our calculations are relevant to recent experimental studies of a nm-sized molecule diffusing in poly-(n-butyl methacrylate) networks. The theory predicts the penetrant relaxation time increases exponentially with the glass transition temperature, T g (f n ), which grows roughly linearly with the square root of fn due to the coupling of local hopping to longer-range collective elasticity. Moreover, T g is also found to be proportional to a geometric confinement parameter defined as the ratio of the penetrant diameter to the mean network mesh size. The decoupling ratio of the penetrant and Kuhn segment alpha times displays a complex non-monotonic dependence on f n and temperature that is well collapsed based on the variable T g (f n )/T. A model for the penetrant diffusion constant that combines activated relaxation and entropic mesh confinement is proposed, which results in a significantly stronger suppression of mass transport with degree of effective supercooling than predicted for the penetrant alpha time. Furthermore, this behavior corresponds to a new network-based type of “decoupling” of diffusion and relaxation. In contrast to the diffusion of larger nanoparticles in high temperature rubbery networks, our analysis in the supercooled regime suggests that for the penetrants studied the mesh confinement effects are of secondary importance relative to the consequences of crosslink-induced slowing down of activated hopping of glassy physics origin.

Chemistry↗

Stabilization of a locally minimal forest

The method of partial stabilization of locally minimal networks, which was invented by Ivanov and Tuzhilin to construct examples of shortest trees with given topology, is developed. According to this method, boundary vertices of degree 2 are not added to all edges of the original locally minimal tree, but only to some of them. The problem of partial stabilization of locally minimal trees in a finite-dimensional Euclidean space is solved completely in the paper, that is, without any restrictions imposed on the number of edges remaining free of subdivision. A criterion for the realizability of such stabilization is established. In addition, the general problem of searching for the shortest forest connecting a finite family of boundary compact sets in an arbitrary metric space is formalized; it is shown that such forests exist for any family of compact sets if and only if for any finite subset of the ambient space there exists a shortest tree connecting it. The theory developed here allows us to establish further generalizations of the stabilization theorem both for arbitrary metric spaces and for metric spaces with some special properties. Bibliography: 10 titles.

97 MATHEMATICS AND COMPUTING↗

Seasonal dynamics of core fungi in the switchgrass phyllosphere, and co-occurrence with leaf bacteria

Plant leaves harbor complex microbial communities that influence plant health and productivity. Nevertheless, a detailed understanding of phyllosphere community assembly and drivers is needed, particularly for phyllosphere fungi. Here, we investigated seasonal dynamics of epiphytic phyllosphere fungal communities in switchgrass ( Panicum virgatum L.), a focal bioenergy crop. We also leverage previously published data on switchgrass phyllosphere bacterial communities from the same experimental plants, allowing us to compare fungal and bacterial dynamics and explore inter-Domain network associations in the switchgrass phyllosphere. Overall, we found a strong impact of sampling date on fungal community composition, with multiple taxonomic levels exhibiting clear temporal patterns in relative abundance. In addition, leaf nitrogen concentration, leaf dry matter content, plant height, and minimum daily air temperature explained significant variation in phyllosphere fungal communities, likely due to their correlation with sampling date. Finally, among the core taxa, fungal-bacterial network associations were much more common than bacteria-bacteria associations, suggesting the importance of inter-Domain phylogenetic diversity in microbiome assembly. Although our findings highlight the complexity of phyllosphere microbiome assembly, the clear temporal patterns in lineage-specific fungal abundances give promise to the potential for accurately predicting shifts in fungal phyllosphere communities throughout the growing season, a key research priority for sustainable agriculture.

16S rRNA↗

Structural motifs and bonding in two families of boron structures predicted at megabar pressures

The complex crystal chemistry of elemental boron has led to numerous proposed structures with distinctive motifs as well as contradictory findings. Herein, evolutionary structure searches performed at 100 GPa have uncovered a series of metastable phases of boron, and bonding analyses were carried out to elucidate their electronic structure. These polymorphs, dynamically stable at 100 GPa, were grouped into two families. Here, the first was derived from the thermodynamic minimum at these conditions, α-Ga, whereas channels comprised the second. Two additional intergrowth structures were uncovered, and it was shown they could be constructed by stacking layers of α-Ga-like and channel-like allotropes on top of each other. A detailed bonding analysis revealed networks of four-center σ-bonding functions linked by two-center B-B bonds in the α-Ga based structures, and networks that were largely composed of three-center σ-bonding functions in the channel-based structures. Seven of these high-pressure phases were found to be metastable at atmospheric conditions, and their Vickers hardnesses were estimated to ≈ 36 GPa.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Differentially Private Generation of Social Networks via Exponential Random Graph Models

Many social networks contain sensitive relational information. One approach to protect the sensitive relational information while offering flexibility for social network research and analysis is to release synthetic social networks at a pre-specified privacy risk level, given the original observed network. In this work, we propose the DP-ERGM procedure that synthesizes networks that satisfy the differential privacy (DP) via the exponential random graph model (EGRM). We apply DP-ERGM to a college student friendship network and compare its original network information preservation in the generated private networks with two other approaches: differentially private DyadWise Randomized Response (DWRR) and Sanitization of the Conditional probability of Edge given Attribute classes (SCEA). The results suggest that DP-EGRM preserves the original information significantly better than DWRR and SCEA in both network statistics and inferences from ERGMs and latent space models. In addition, DP-ERGM satisfies the node DP, a stronger notion of privacy than the edge DP that DWRR and SCEA satisfy.

97 MATHEMATICS AND COMPUTING↗

Fungal-Bacterial Cooccurrence Patterns Differ between Arbuscular Mycorrhizal Fungi and Nonmycorrhizal Fungi across Soil Niches

Soil bacteria and fungi are known to form niche-specific communities that differ between actively growing and decaying roots. Yet almost nothing is known about the cross-kingdom interactions that frame these communities and the environmental filtering that defines these potentially friendly or competing neighbors. We explored the temporal and spatial patterns of soil fungal (mycorrhizal and nonmycorrhizal) and bacterial cooccurrence near roots of wild oat grass, Avena fatua, growing in its naturalized soil in a greenhouse experiment. Amplicon sequences of the fungal internal transcribed spacer (ITS) and bacterial 16S rRNA genes from rhizosphere and bulk soils collected at multiple plant growth stages were used to construct covariation-based networks as a step toward identifying fungal-bacterial associations. Corresponding stable-isotope-enabled metagenome-assembled genomes (MAGs) of bacteria identified in cooccurrence networks were used to inform potential mechanisms underlying the observed links. Bacterial-fungal networks were significantly different in rhizosphere versus bulk soils and between arbuscular mycorrhizal fungi (AMF) and nonmycorrhizal fungi. Over 12 weeks of plant growth, nonmycorrhizal fungi formed increasingly complex networks with bacteria in rhizosphere soils, while AMF more frequently formed networks with bacteria in bulk soils. Analysis of network-associated bacterial MAGs suggests that some of the fungal-bacterial links that we identified are potential indicators of bacterial breakdown and consumption of fungal biomass, while others intimate shared ecological niches.

54 ENVIRONMENTAL SCIENCES↗

Hypernetwork science via high-order hypergraph walks

We propose high-order hypergraph walks as a framework to generalize graph-based network science techniques to hypergraphs. Edge incidence in hypergraphs is quantitative, yielding hypergraph walks with both length and width. Graph methods which then generalize to hypergraphs include connected component analyses, graph distance-based metrics such as closeness centrality, and motif-based measures such as clustering coefficients. We apply high-order analogs of these methods to real world hypernetworks, and show they reveal nuanced and interpretable structure that cannot be detected by graph-based methods. Lastly, we apply three generative models to the data and find that basic hypergraph properties, such as density and degree distributions, do not necessarily control these new structural measurements. Our work demonstrates how analyses of hypergraph-structured data are richer when utilizing tools tailored to capture hypergraph-native phenomena, and suggests one possible avenue towards that end.

97 MATHEMATICS AND COMPUTING↗

Malcolm

Malcolm is a powerful, easily deployable network traffic analysis tool suite for full packet capture artifacts (PCAP files) and Zeek logs.

Grover, SethD↗