scholarly journals Investigations of Sizes and Dynamical Motions of Solar Photospheric Granules by a Novel Granular Segmenting Algorithm

2021 ◽  
Vol 923 (2) ◽  
pp. 133
Author(s):  
Liu Yanxiao ◽  
Jiang Chaowei ◽  
Yuan Ding ◽  
Zuo Pingbing ◽  
Wang Yi ◽  
...  
Keyword(s):  
Power Law ◽  
Convective Instability ◽  
Solar Photosphere ◽  
Dynamical Process ◽  
Cascade Process ◽  
Solar Telescope ◽  
Power Law Distribution ◽  
Gauss Function ◽  
Power Law Function ◽  
Convective Motions

Abstract Granules observed in the solar photosphere are believed to be convective and turbulent, but the physical picture of the granular dynamical process remains unclear. Here we performed an investigation of granular dynamical motions of full length scales based on data obtained by the 1 m New Vacuum Solar Telescope and the 1.6 m Goode Solar Telescope. We developed a new granule segmenting method, which can detect both small faint and large bright granules. A large number of granules were detected, and two critical sizes, 265 and 1420 km, were found to separate the granules into three length ranges. The granules with sizes above 1420 km follow Gaussian distribution, and demonstrate flat in flatness function, which shows that they are non-intermittent and thus are dominated by convective motions. Small granules with sizes between 265 and 1420 km are fitted by a combination of power-law function and Gauss function, and exhibit nonlinearity in flatness function, which reveals that they are in the mixing motions of convection and turbulence. Mini granules with sizes below 265 km follow the power-law distribution and demonstrate linearity in flatness function, indicating that they are intermittent and strongly turbulent. These results suggest that a cascade process occurs: large granules break down due to convective instability, which transports energy into small ones; then turbulence is induced and grows, which competes with convection and further causes the small granules to continuously split. Eventually, the motions in even smaller scales enter in a turbulence-dominated regime.

Dynamical process of complex systems and fractional differential equations

Open Physics ◽  
2013 ◽  
Vol 11 (10) ◽  
Author(s):  
Hiroaki Hara ◽  
Yoshiyasu Tamura
Keyword(s):  
Complex Systems ◽  
External Force ◽  
Power Law ◽  
Slow Relaxation ◽  
Activation Process ◽  
Dynamical Process ◽  
Power Law Distribution ◽  
Scale Free ◽  
Internal States ◽  
Fractional Differential

AbstractBehavior of dynamical process of complex systems is investigated. Specifically we analyse two types of ideal complex systems. For analysing the ideal complex systems, we define the response functions describing the internal states to an external force. The internal states are obtained as a relaxation process showing a “power law” distribution, such as scale free behaviors observed in actual measurements. By introducing a hybrid system, the logarithmic time, and double logarithmic time, we show how the “slow relaxation” (SR) process and “super slow relaxation” (SSR) process occur. Regarding the irregular variations of the internal states as an activation process, we calculate the response function to the external force. The behaviors are classified into “power”, “exponential”, and “stretched exponential” type. Finally we construct a fractional differential equation (FDE) describing the time evolution of these complex systems. In our theory, the exponent of the FDE or that of the power law distribution is expressed in terms of the parameters characterizing the structure of the system.

scholarly journals The structure of co-publications multilayer network

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ghislain Romaric Meleu ◽  
Paulin Yonta Melatagia
Keyword(s):  
Power Law ◽  
Degree Distribution ◽  
Preferential Attachment ◽  
Small World ◽  
Generation Model ◽  
Small World Network ◽  
Power Law Distribution ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Scientific Papers

AbstractUsing the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks built from data extracted from the HAL archives and found that the network at each layer is a small-world network with power law distribution. In order to simulate such co-publication network, we propose a multilayer network generation model based on the formation of cliques at each layer and the affiliation of each new node to the higher layers. The clique is built from new and existing nodes selected using preferential attachment. We also show that, the degree distribution of generated layers follows a power law. From the simulations of our model, we show that the generated multilayer networks reproduce the studied properties of co-publication networks.

scholarly journals Power-law behavior of transcription factor dynamics at the single-molecule level implies a continuum affinity model

2021 ◽  
Author(s):  
David A Garcia ◽  
Gregory Fettweis ◽  
Diego M Presman ◽  
Ville Paakinaho ◽  
Christopher Jarzynski ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Single Molecule ◽  
Power Law ◽  
Dwell Time ◽  
Specific Binding ◽  
Power Law Distribution ◽  
Single Molecule Level ◽  
Binding Behavior ◽  
Chromatin Template ◽  
Nuclear Domains

Abstract Single-molecule tracking (SMT) allows the study of transcription factor (TF) dynamics in the nucleus, giving important information regarding the diffusion and binding behavior of these proteins in the nuclear environment. Dwell time distributions obtained by SMT for most TFs appear to follow bi-exponential behavior. This has been ascribed to two discrete populations of TFs—one non-specifically bound to chromatin and another specifically bound to target sites, as implied by decades of biochemical studies. However, emerging studies suggest alternate models for dwell-time distributions, indicating the existence of more than two populations of TFs (multi-exponential distribution), or even the absence of discrete states altogether (power-law distribution). Here, we present an analytical pipeline to evaluate which model best explains SMT data. We find that a broad spectrum of TFs (including glucocorticoid receptor, oestrogen receptor, FOXA1, CTCF) follow a power-law distribution of dwell-times, blurring the temporal line between non-specific and specific binding, suggesting that productive binding may involve longer binding events than previously believed. From these observations, we propose a continuum of affinities model to explain TF dynamics, that is consistent with complex interactions of TFs with multiple nuclear domains as well as binding and searching on the chromatin template.

scholarly journals Explaining the power-law distribution of human mobility through transportationmodality decomposition

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Kai Zhao ◽  
Mirco Musolesi ◽  
Pan Hui ◽  
Weixiong Rao ◽  
Sasu Tarkoma
Keyword(s):  
Power Law ◽  
Human Mobility ◽  
Power Law Distribution

Turbulent convective flows in the solar photospheric plasma

2015 ◽  
Vol 81 (5) ◽  
Author(s):  
A. Caroli ◽  
F. Giannattasio ◽  
M. Fanfoni ◽  
D. Del Moro ◽  
G. Consolini ◽  
...  
Keyword(s):  
Mean Square Displacement ◽  
Small Scale ◽  
Solar Photosphere ◽  
Distribution Analysis ◽  
Pixel Resolution ◽  
Convective Flows ◽  
Magnetic Elements ◽  
Highly Nonlinear ◽  
Convective Motions ◽  
Short Time

The origin of the 22-year solar magnetic cycle lies below the photosphere where multiscale plasma motions, due to turbulent convection, produce magnetic fields. The most powerful intensity and velocity signals are associated with convection cells, called granules, with a scale of typically 1 Mm and a lifetime of a few minutes. Small-scale magnetic elements (SMEs), ubiquitous on the solar photosphere, are passively transported by associated plasma flows. This advection makes their traces very suitable for defining the convective regime of the photosphere. Therefore the solar photosphere offers an exceptional opportunity to investigate convective motions, associated with compressible, stratified, magnetic, rotating and large Rayleigh number stellar plasmas. The magnetograms used here come from a Hinode/SOT uninterrupted 25-hour sequence of spectropolarimetric images. The mean-square displacement of SMEs has been modelled with a power law with spectral index ${\it\gamma}$. We found ${\it\gamma}=1.34\pm 0.02$ for times up to ${\sim}2000~\text{s}$ and ${\it\gamma}=1.20\pm 0.05$ for times up to ${\sim}10\,000~\text{s}$. An alternative way to investigate the advective–diffusive motion of SMEs is to look at the evolution of the two-dimensional probability distribution function (PDF) for the displacements. Although at very short time scales the PDFs are affected by pixel resolution, for times shorter than ${\sim}2000~\text{s}$ the PDFs seem to broaden symmetrically with time. In contrast, at longer times a multi-peaked feature of the PDFs emerges, which suggests the non-trivial nature of the diffusion–advection process of magnetic elements. A Voronoi distribution analysis shows that the observed small-scale distribution of SMEs involves the complex details of highly nonlinear small-scale interactions of turbulent convective flows detected in solar photospheric plasma.

MASS FUNCTION OF HALOS: A NEW ANALYTICAL APPROACH

2004 ◽  
Vol 13 (07) ◽  
pp. 1345-1349 ◽  
Author(s):  
JOSÉ A. S. LIMA ◽  
LUCIO MARASSI
Keyword(s):  
Power Law ◽  
Free Parameter ◽  
Analytical Approach ◽  
Mass Function ◽  
New Method ◽  
Power Law Distribution ◽  
The Press ◽  
The Universe ◽  
Special Case

A generalization of the Press–Schechter (PS) formalism yielding the mass function of bound structures in the Universe is given. The extended formula is based on a power law distribution which encompasses the Gaussian PS formula as a special case. The new method keeps the original analytical simplicity of the PS approach and also solves naturally its main difficult (the missing factor 2) for a given value of the free parameter.

scholarly journals Assessing the power law distribution of TGFs

2011 ◽  
Vol 116 (A10) ◽  
pp. n/a-n/a ◽  
Author(s):  
Andrew B. Collier ◽  
Thomas Gjesteland ◽  
Nikolai Østgaard
Keyword(s):  
Power Law ◽  
Power Law Distribution

scholarly journals Predicting observational signatures of coronal heating by Alfvén waves and nanoflares

2007 ◽  
Vol 3 (S247) ◽  
pp. 279-287
Author(s):  
Patrick Antolin ◽  
Kazunari Shibata ◽  
Takahiro Kudoh ◽  
Daiko Shiota ◽  
David Brooks
Keyword(s):  
Power Law ◽  
Alfven Waves ◽  
Alfvén Waves ◽  
Power Law Distribution ◽  
Longitudinal Modes ◽  
Heating Mechanism ◽  
Set Up ◽  
Power Law Index ◽  
Power Law Distributions ◽  
Release Processes

AbstractAlfvén waves can dissipate their energy by means of nonlinear mechanisms, and constitute good candidates to heat and maintain the solar corona to the observed few million degrees. Another appealing candidate is the nanoflare-reconnection heating, in which energy is released through many small magnetic reconnection events. Distinguishing the observational features of each mechanism is an extremely difficult task. On the other hand, observations have shown that energy release processes in the corona follow a power law distribution in frequency whose index may tell us whether small heating events contribute substantially to the heating or not. In this work we show a link between the power law index and the operating heating mechanism in a loop. We set up two coronal loop models: in the first model Alfvén waves created by footpoint shuffling nonlinearly convert to longitudinal modes which dissipate their energy through shocks; in the second model numerous heating events with nanoflare-like energies are input randomly along the loop, either distributed uniformly or concentrated at the footpoints. Both models are based on a 1.5-D MHD code. The obtained coronae differ in many aspects, for instance, in the simulated intensity profile that Hinode/XRT would observe. The intensity histograms display power law distributions whose indexes differ considerably. This number is found to be related to the distribution of the shocks along the loop. We thus test the observational signatures of the power law index as a diagnostic tool for the above heating mechanisms and the influence of the location of nanoflares.

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