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Traditionally power distribution networks are either not observable or only partially observable. This complicates development and implementation of new smart grid technologies, such as those related to demand response, outage detection and…

Optimization and Control · Mathematics 2015-03-02 Deepjyoti Deka , Scott Backhaus , Michael Chertkov

Quantum networks constitute a major part of quantum technologies. They will boost distributed quantum computing drastically by providing a scalable modular architecture of quantum chips, or by establishing an infrastructure for measurement…

Quantum Physics · Physics 2023-05-05 Seid Koudia

In Functional Analysis, certain conclusions apply to sequences, but they cannot be carried over when we consider nets. In fact, some nets, including sequences, can behave unexpectedly. In this paper we are interested in exploring the…

Functional Analysis · Mathematics 2024-01-17 Sheldon Dantas , Daniel L. Rodríguez-Vidanes

Fog computing allows computationally-heavy problems with tight time constraints to be solved even if end devices have limited computational resources and latency induced by cloud computing is too high. How can energy consumed by fog…

Systems and Control · Electrical Eng. & Systems 2023-03-24 Hanna Bogucka , Bartosz Kopras , Filip Idzikowski , Bartosz Bossy , Paweł Kryszkiewicz

In this article, a discrete analogue of continuous Teissier distribution is presented. Its several important distributional characteristics have been derived. The estimation of the unknown parameter has been done using the method of maximum…

Methodology · Statistics 2021-10-22 Bhupendra Singh , Varun Agiwal , Ravindra Pratap Singh , Abhishek Tyagi

In this short paper, we introduce the Ridgeline model, an extension of the Roofline model [4] for distributed systems. The Roofline model targets shared memory systems, bounding the performance of a kernel based on its operational…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-18 Fabio Checconi , Jesmin Jahan Tithi , Fabrizio Petrini

Hierarchical statistical models are widely employed in information science and data engineering. The models consist of two types of variables: observable variables that represent the given data and latent variables for the unobservable…

Machine Learning · Statistics 2014-02-21 Keisuke Yamazaki

This paper proposes two nonlinear dynamics to solve constrained distributed optimization problem for resource allocation over a multi-agent network. In this setup, coupling constraint refers to resource-demand balance which is preserved at…

Systems and Control · Electrical Eng. & Systems 2023-10-30 Mohammadreza Doostmohammadian , Alireza Aghasi , Maria Vrakopoulou , Hamid R. Rabiee , Usman A. Khan , Themistoklis Charalambou

Distributed ledgers, including blockchain and other decentralized databases, are designed to store information online where all trusted network members can update the data with transparency. The dynamics of ledger's development can be…

Probability · Mathematics 2026-03-10 Jiewei Feng , Christopher King

Quantum computing offers the potential to solve certain complex problems, yet, scaling monolithic processors remains a major challenge. Modular and distributed architectures are proposed to build large-scale quantum systems while bringing…

We propose a novel structure, the data-sharing graph, for characterizing sharing patterns in large-scale data distribution systems. We analyze this structure in two such systems and uncover small-world patterns for data-sharing…

Networking and Internet Architecture · Computer Science 2007-05-23 Adriana Iamnitchi , Matei Ripeanu , Ian Foster

These lecture notes cover basic automata-theoretic concepts and logical formalisms for the modeling and verification of concurrent and distributed systems. Many of these concepts naturally extend the classical automata and logics over…

Logic in Computer Science · Computer Science 2021-10-19 Benedikt Bollig , Paul Gastin

Turbulence is characterized by the non-linear cascades of energy and other inviscid invariants across a huge range of scales, from where they are injected to where they are dissipated. Recently, new experimental, numerical and theoretical…

Fluid Dynamics · Physics 2018-10-10 A. Alexakis , L. Biferale

In this paper we investigate the ability of a neural network to approximate algebraic properties associated to lattice simplices. In particular we attempt to predict the distribution of Hilbert basis elements in the fundamental…

Combinatorics · Mathematics 2018-07-24 Brian Davis

In recent decades, it has been emphasized that the evolving structure of networks may be shaped by interaction principles that yield sparse graphs with a vertex degree distribution exhibiting an algebraic tail, and other structural traits…

Statistical Mechanics · Physics 2025-07-01 Dario Borrelli

In this work we present a model for computation of random processes in digital computers which solves the problem of periodic sequences and hidden errors produced by correlations. We show that systems with non-invertible non-linearities can…

Statistical Mechanics · Physics 2007-05-23 Monica A. Garcia-Nustes , Leonardo Trujillo , Jorge A. Gonzalez

In this chapter we will argue that studying such multi-scale multi-science systems gives rise to inherently hybrid models containing many different algorithms best serviced by different types of computing environments (ranging from…

Astrophysics · Physics 2007-05-23 A. G. Hoekstra , S. F. Portegies Zwart , M. Bubak , P. M. A. Sloot

In this paper we consider the question whether a distributed network of sensors and data processors can form "perceptions" based on the sensory data. Because sensory data can have exponentially many explanations, the use of a central data…

adap-org · Physics 2007-05-23 George Chapline

Analyzing the underlying structure of multiple time-sequences provides insights into the understanding of social networks and human activities. In this work, we present the \emph{Bayesian nonparametric Poisson process allocation} (BaNPPA),…

Machine Learning · Statistics 2018-04-04 Hongyi Ding , Mohammad Emtiyaz Khan , Issei Sato , Masashi Sugiyama

Coded computing is a distributed paradigm that uses coding theory to introduce \textit{redundancy} and overcome bottlenecks in large-scale systems. In the same vein, randomized numerical linear algebra employs probabilistic methods to…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-19 Neophytos Charalambides , Arya Mazumdar