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The incorporation of particle inertia into the usual mean field theory for particle aggregation and fragmentation in fluid flows is still an unsolved problem. We therefore suggest an alternative approach that is based on the dynamics of…

Fluid Dynamics · Physics 2011-03-08 Jens C. Zahnow , Joeran Maerz , Ulrike Feudel

Graph partitioning is a key fundamental problem in the area of big graph computation. Previous works do not consider the practical requirements when optimizing the big data analysis in real applications. In this paper, motivated by…

Databases · Computer Science 2024-04-10 Baoling Ning , Jianzhong Li

We employ the macroscopic fluctuation theory to study fluctuations of integrated current in one-dimensional lattice gases with a step-like initial density profile. We analytically determine the variance of the current fluctuations for a…

Statistical Mechanics · Physics 2015-06-05 P. L. Krapivsky , Baruch Meerson

We consider the class of exchangeable fragmentation-coagulation (EFC) processes where coagulations are multiple and not simultaneous, as in a $\Lambda$-coalescent, and fragmentation dislocates at finite rate an individual block into…

Probability · Mathematics 2021-04-30 Clément Foucart

The influence of the initial fluctuations on the onset of scaling in the quench to zero temperature of a two dimensional system with conserved order parameter, is analyzed in detail with and without topological defects. We find that the…

Condensed Matter · Physics 2009-10-28 Claudio Castellano , Marco Zannetti

We develop here a simple yet versatile model for nuclear fragmentation in heavy ion collisions. The model allows us to calculate thermodynamic properties such as phase transitions as well as the distribution of fragments at disassembly. In…

Nuclear Theory · Physics 2016-09-08 Jicai Pan , Subal Das Gupta

Assessing where and how information is stored in biological networks (such as neuronal and genetic networks) is a central task both in neuroscience and in molecular genetics, but most available tools focus on the network's structure as…

Information Theory · Computer Science 2023-02-24 Clifford Bohm , Douglas Kirkpatrick , Victoria Cao , Christoph Adami

We consider a self-similar fragmentation process in which the generic particle of size $x$ is replaced at probability rate $x^\alpha$, by its offspring made of smaller particles, where $\alpha$ is some positive parameter. The total of…

Probability · Mathematics 2007-05-23 Jean Bertoin , Alexander Gnedin

An investigation of the spatial fluctuations and their manifestations in the vicinity of the quantum critical point within the framework of the renormalized $\phi^{4}$ theory is proposed. Relevant features are reported through the…

This paper studies chance-constrained stochastic optimization problems with finite support. It presents an iterative method that solves reduced-size chance-constrained models obtained by partitioning the scenario set. Each reduced problem…

Optimization and Control · Mathematics 2024-11-26 Marius Roland , Alexandre Forel , Thibaut Vidal

Quantum computing allows for the manipulation of highly correlated states whose properties quickly go beyond the capacity of any classical method to calculate. Thus one natural problem which could lend itself to quantum advantage is the…

Quantum Physics · Physics 2024-12-19 Kevin Lively , Tim Bode , Jochen Szangolies , Jian-Xin Zhu , Benedikt Fauseweh

We derive the fluctuation theorem for quantum-state statistics that can be obtained when we initially measure the total energy of a quantum system at thermal equilibrium, let the system evolve unitarily, and record the quantum-state data…

Statistical Mechanics · Physics 2018-08-01 Naoto Tsuji , Masahito Ueda

We study a point process describing the asymptotic behavior of sizes of the largest components of the random graph G(n,p) in the critical window p=n^{-1}+lambda n^{-4/3}. In particular, we show that this point process has a surprising…

Probability · Mathematics 2007-05-23 Svante Janson , Joel Spencer

Fragmentation can be observed in nature and in everyday life on a wide range of length scales and for all kinds of technical applications. Most studies on dynamic failure focus on the behaviour of bulk systems in one, two and three…

Soft Condensed Matter · Physics 2015-10-02 Falk K. Wittel , Ferenc Kun , Hans J. Herrmann , Bernd H. Kröplin

We discuss the role and the treatment of polarization effects in many-body systems of charged conducting clusters and apply this to the statistical fragmentation of Na-clusters. We see a first order microcanonical phase transition in the…

Condensed Matter · Physics 2016-08-15 O. Schapiro , P. J. Kuntz , K. Möhring , P. A. Hervieux , D. H. E. Gross , M. E. Madjet

We use a model whose rules were inspired by population genetics, the random capability growth model, to describe the statistical details observed in experiments of fragmentation of brittle platelike objects, and in particular the existence…

Statistical Mechanics · Physics 2016-12-21 M. A. F. Gomes , Viviane M. de Oliveira

We study the nonequilibrium phase transition in a model of aggregation of masses allowing for diffusion, aggregation on contact and fragmentation. The model undergoes a dynamical phase transition in all dimensions. The steady state mass…

Statistical Mechanics · Physics 2015-06-25 Satya N. Majumdar , Supriya Krishnamurthy , Mustansir Barma

We show how to apply the macroscopic fluctuation theory (MFT) of Bertini, De Sole, Gabrielli, Jona-Lasinio, and Landim to study the current fluctuations of diffusive systems with a step initial condition. We argue that one has to…

Statistical Mechanics · Physics 2015-05-13 B. Derrida , A. Gerschenfeld

The fractal character of some quantum properties has been shown for systems described by continuous variables. Here, a definition of quantum fractal states is given that suits the discrete systems used in quantum information processing,…

Quantum Physics · Physics 2007-08-03 Gregg Jaeger

Partitioning a set of elements into an unknown number of mutually exclusive subsets is essential in many machine learning problems. However, assigning elements, such as samples in a dataset or neurons in a network layer, to an unknown and…

Machine Learning · Computer Science 2023-11-10 Thomas M. Sutter , Alain Ryser , Joram Liebeskind , Julia E. Vogt
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