Constructive spherical codes on layers of flat tori

A new class of spherical codes is constructed by selecting a finite subset of flat tori from a foliation of the unit sphere S^{2L-1} of R^{2L} and designing a structured codebook on each torus layer. The resulting spherical code can be the image of a lattice restricted to a specific hyperbox in R^L in each layer. Group structure and homogeneity, useful for efficient storage and decoding, are inherited from the underlying lattice codebook. A systematic method for constructing such codes are presented and, as an example, the Leech lattice is used to construct a spherical code in R^{48}. Upper and lower bounds on the performance, the asymptotic packing density and a method for decoding are derived.Comment: 9 pages, 5 figures, submitted to IEEE Transactions on Information Theor

Exploring the high-pressure materials genome

A thorough in situ characterization of materials at extreme conditions is challenging, and computational tools such as crystal structural search methods in combination with ab initio calculations are widely used to guide experiments by predicting the composition, structure, and properties of high-pressure compounds. However, such techniques are usually computationally expensive and not suitable for large-scale combinatorial exploration. On the other hand, data-driven computational approaches using large materials databases are useful for the analysis of energetics and stability of hundreds of thousands of compounds, but their utility for materials discovery is largely limited to idealized conditions of zero temperature and pressure. Here, we present a novel framework combining the two computational approaches, using a simple linear approximation to the enthalpy of a compound in conjunction with ambient-conditions data currently available in high-throughput databases of calculated materials properties. We demonstrate its utility by explaining the occurrence of phases in nature that are not ground states at ambient conditions and estimating the pressures at which such ambient-metastable phases become thermodynamically accessible, as well as guiding the exploration of ambient-immiscible binary systems via sophisticated structural search methods to discover new stable high-pressure phases.Comment: 14 pages, 6 figure

ACCESS POINT NAME (APN)/DATA NETWORK NAME (DNN) BASED AUTO-ANCHORING OF FIFTH GENERATION/NEXT GENERATION TRAFFIC IN WI-FI

Private Third Generation Partnership Project (3GPP) Fifth Generation/next Generation (5G/nG) network environments will have a mix of access technologies, such as Wi-Fi6 and 5G/nG Radio Access Network (RAN) technologies. Techniques presented herein provide for the capability to transport and intelligently anchor 5G/nG data using a Wi-Fi system, which may allow for private 5G/nG onboarding utilizing the Wi-Fi system

PROACTIVE EXCHANGE OF DATA BETWEEN CLOUD PROVIDERS VIA CONTROLLER COORDINATION AND TRIGGER DYNAMIC WORKFLOWS

A multi-cloud Software Defined Network (SDN) controller proactively learns insights about subscribers, such as enterprise users, end users, and/or other cloud providers. Based on the learned insights, the multi-SDN controller applies dynamic policies on other cloud provides to which those subscribers are attached to. The multi-cloud SDN controller co-ordinates with various cloud providers, enterprise network controllers, and Internet Service Providers (ISPs) to proactively notify other cloud providers with information about affected users so that those providers can install additional resources at cloud edge/core on the fly. Additionally, the multi-cloud SDN controller facilitates a warm hand off from one cloud region to another cloud region. When the multi-cloud SDN controller learns about an enterprise outage, it proactively notifies other cloud providers of the outage event and the other cloud providers can use this for a warm hand off of session to the region(s) through which the users will be reconnected. The likely regions are derived based on telemetry obtained from multi-cloud SDN controller. The multi-cloud SDN controller also triggers a proactive cleanup of user context of the cloud provider side. The cloud provider cleans up after the connection reset event based on information from the multi-cloud SDN controller, rather than wait on a timeout of the connection

Viscoelastic Properties of Dynamically Asymmetric Binary Fluids Under Shear Flow

We study theoretically the viscoelastic properties of sheared binary fluids that have strong dynamical asymmetry between the two components. The dynamical asymmetry arises due to asymmetry between the viscoelastic stresses, particularly the bulk stress. Our calculations are based on the two-fluid model that incorporates the asymmetric stress distribution. We simulate the phase separation process under an externally imposed shear and compare the asymmetric case with the usual phase separation under a shear flow without viscoelastic effects. We also simulate the behavior of phase separated stable morphologies under applied shear and compute the stress relaxation.Comment: 10 pages text, 9 figure

The Phase Diagram of all Inorganic Materials

Understanding how the arrangement of atoms and their interactions determine material behavior has been the dominant paradigm in materials science. A complementary approach is studying the organizational structure of networks of materials, defined on the basis of interactions between materials themselves. In this work, we present the "phase diagram of all known inorganic materials", an extremely-dense complex network of nearly $2.1 \times 10^4$ stable inorganic materials (nodes) connected with $41 \times 10^6$ tie-lines (edges) defining their two-phase equilibria, as computed via high-throughput density functional theory. We show that the degree distribution of this network follows a lognormal form, with each material connected to on average 18% of the other materials in the network via tie-lines. Analyzing the structure and topology of this network has potential to uncover new materials knowledge inaccessible from the traditional bottom-up (atoms to materials) approaches. As an example, we derive a data-driven metric for the reactivity of a material as characterized by its connectedness in the network, and quantitatively identify the noblest materials in nature

DYNAMIC TELEMETRY PROFILE ENFORCEMENT IN A CONTROLLER NETWORK

Because telemetry processing can involve high resource usage, such processing is typically provided via a cloud infrastructure. However, there are drawbacks to current implementations involving such cloud infrastructure processing. For example, such processing typically follows standard processing patterns. Yet, with the increasing complexity of different network use cases, there are scenarios that would benefit from dynamic telemetry processing. Presented herein are techniques through which multiple device telemetry profiles can allow a cloud controller to dynamically match a telemetry profile to specific conditions for a tenant network. Each telemetry profile may include selections for data processing through priority and secured queues. Additionally, the cloud controller may have reverse telemetry policies to push reverse telemetry to the customer edge when original usage telemetry data is retrieved, processed, and/or transferred