Category: Paper Announcement
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Condensation of degrees emerging through a first-order phase transition in classical random graphs
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When steam condenses from vapour into liquid, the water molecules move closely together and the system, from a mathematical point of view, comes to reside in an extremely small portion of the conceptually available phase space.
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Effective bandwidth of non-Markovian packet traffic
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Telecommunications engineers and operations researchers aim to manage complex and fluctuating traffic flows through extended networks. Among other techniques, they have exploited results from the theory of large deviations to estimate the likelihood that a demand in service will overflow the available […]
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Thermodynamic uncertainty for run-and-tumble type processes
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Systems out of equilibrium typically carry macroscopic currents of particles, mass or energy. Thermodynamic uncertainty relations offer universal bounds linking such currents and their statistical fluctuations to other system properties, especially entropy production.
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Comment on D. Bernoulli (1738)
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Probability theory emerged in the second half of the 17th century as a way to think about monetary gambles, and how to choose wisely when facing uncertainty. Early thinking suggested that people would act so as to maximise the expected change in […]
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Detection and replenishment of missing data in marked point processes
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Point processes offer a convenient mathematical representation of earthquakes, volcanic eruptions, crimes and many other processes which occur at random times and locations. The data available in these fields has exploded with modern recording technology, and yet many data sets suffer from […]
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Can Signal Delay Be Functional? Including Delay In Evolved Robot Controllers
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Signals travel at finite speeds within the nerves of living organisms, between satellites and the Earth, or in computers and other technological devices. As a result, they incur delays in moving from one point to another, which engineers, roboticists, control-theorists and neuroscientists […]
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Anomalous Diffusion in Random Dynamical Systems
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Brownian motion has long been the standard paradigm for modelling random, diffusive motion, such as the haphazard movement of a dust particle floating in a fluid. This is considered to be “normal” diffusion, in which the mean square particle displacement – calculated […]
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Noisy network attractor models for transitions between EEG microstates
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Electroencephalography (EEG) provides a direct measure of neuronal activity as reflected in the scalp electrical field. Empirically, global measures of EEG topography remain stable in so-called EEG microstates for brief periods (50–100 ms) before switching to another quasi-stable state.
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Normal and Anomalous Diffusion in Soft Lorentz Gases
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Engineered nanoscale structures known as artificial graphene exhibit the properties of real graphene but in a setup where it is easy to tune features such as the electronic density, lattice constant, geometry or coupling with the environment.
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On reversals in 2D turbulent Rayleigh-Bénard convection: Insights from embedding theory and comparison with proper orthogonal decomposition analysis
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In the 1980s, most researchers approached empirical analysis of low-dimensional dynamical systems through the famous Takens embedding theorem, which guarantees that the attractor of any dynamical system can be reconstructed from samples of the values of key variables.