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Register a new userSelf-organized Criticality in Multi-pulse Gamma-Ray Bursts
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The variability in multi-pulse gamma-ray bursts (GRBs) may help to reveal the mechanism of underlying processes from the central engine. To investigate whether the self-organized criticality (SOC) phenomena exist in the prompt phase of GRBs, we statistically study the properties of GRBs with more than 3 pulses in each burst by fitting the distributions of several observed physical variables with a Markov Chain Monte Carlo approach, including the isotropic energy $E_{rm iso}$, the duration time $T$ and the peak count rate $P$ of each pulse. Our sample consists of 454 pulses in 93 GRBs observed by the CGRO/BATSE satellite. The best-fitting values and uncertainties for these power-law indices of the differential frequency distributions are: $alpha^d_{E}=1.54 pm 0.09$, $alpha^d_{T}=1.82_{-0.15}^{+0.14}$ and $alpha^d_{P}=2.09_{-0.19}^{+0.18}$, while the power-law indices in the cumulative frequency distributions are: $alpha^c_{E}=1.44_{-0.10}^{+0.08}$, $alpha^c_{T}=1.75_{-0.13}^{+0.11}$ and $alpha^c_{P}=1.99_{-0.19}^{+0.16}$. We find that these distributions are roughly consistent with the physical framework of a Fractal-Diffusive, Self-Organized Criticality (FD-SOC) system with the spatial dimension $S=3$ and the classical diffusion $beta$=1. Our results support that the jet responsible for the GRBs should be magnetically dominated and magnetic instabilities (e.g., kink model, or tearing-model instability) lead the GRB emission region into the SOC state.
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A new cellular automaton (CA) model is presented for the self-organized criticality (SOC) in recurrent bursts of soft gamma repeaters (SGRs), which are interpreted as avalanches of reconnection in the magnetosphere of neutron stars. The nodes of a regular dodecahedron and a truncated icosahedron are adopted as spherically closed grids enclosing a neutron star. It is found that the system enters the SOC state if there are sites where the expectation value of the added perturbation is nonzero. The energy distributions of SOC avalanches in CA simulations are described by a power law with a cutoff, which is consistent with the observations of SGR 1806-20 and SGR 1900+14. The power-law index is not universal and depends on the amplitude of the perturbation. This result shows that the SOC of SGRs can be illustrated not only by the crust quake model but also by the magnetic reconnection model.
The complete Swift Burst Alert Telescope and X-Ray Telescope light curves of 118 gamma-ray bursts (GRBs) with known redshifts were fitted using the physical model of GRB pulses by Willingale et al. to produce a total of 607 pulses. We compute the pulse luminosity function utilizing three GRB formation rate models: a progenitor that traces the cosmic star formation rate density (CSFRD) with either a single population of GRBs, coupled to various evolutionary parameters, or a bimodal population of high- and low-luminosity GRBs, and a direct fit to the GRB formation rate excluding any a priori assumptions. We find that a single population of GRB pulses with an evolving luminosity function is preferred over all other univariate evolving GRB models, or bimodal luminosity functions in reproducing the observed GRB pulse L-z distribution and that the magnitude of the evolution in brightness is consistent with studies that utilize only the brightest GRB pulses. We determine that the appearance of a GRB formation rate density evolution component is an artifact of poor parametrization of the CSFRD at high redshifts rather than indicating evolution in the formation rate of early epoch GRBs. We conclude that the single brightest region of a GRB light curve holds no special property, by incorporating pulse data from the totality of GRB emission we boost the GRB population statistics by a factor of 5, rule out some models utilized to explain deficiencies in GRB formation rate modelling, and constrain more tightly some of the observed parameters of GRB behaviour.
Power law size distributions are the hallmarks of nonlinear energy dissipation processes governed by self-organized criticality. Here we analyze 75 data sets of stellar flare size distributions, mostly obtained from the {sl Extreme Ultra-Violet Explorer (EUVE)} and the {sl Kepler} mission. We aim to answer the following questions for size distributions of stellar flares: (i) What are the values and uncertainties of power law slopes? (ii) Do power law slopes vary with time ? (iii) Do power law slopes depend on the stellar spectral type? (iv) Are they compatible with solar flares? (v) Are they consistent with self-organized criticality (SOC) models? We find that the observed size distributions of stellar flare fluences (or energies) exhibit power law slopes of $alpha_E=2.09pm0.24$ for optical data sets observed with Kepler. The observed power law slopes do not show much time variability and do not depend on the stellar spectral type (M, K, G, F, A, Giants). In solar flares we find that background subtraction lowers the uncorrected value of $alpha_E=2.20pm0.22$ to $alpha_E=1.57pm0.19$. Furthermore, most of the stellar flares are temporally not resolved in low-cadence (30 min) Kepler data, which causes an additional bias. Taking these two biases into account, the stellar flare data sets are consistent with the theoretical prediction $N(x) propto x^{-alpha_x}$ of self-organized criticality models, i.e., $alpha_E=1.5$. Thus, accurate power law fits require automated detection of the inertial range and background subtraction, which can be modeled with the generalized Pareto distribution, finite-system size effects, and extreme event outliers.
Self-organized criticality (SOC) refers to the ability of complex systems to evolve towards a 2nd-order phase transition at which interactions between system components lead to scale-invariant events beneficial for system performance. For the last two decades, considerable experimental evidence accumulated that the mammalian cortex with its diversity in cell types and connections might exhibit SOC. Here we review experimental findings of isolated, layered cortex preparations to self-organize towards four dynamical motifs identified in the cortex in vivo: up-states, oscillations, neuronal avalanches, and coherence potentials. During up-states, the synchronization observed for nested theta/gamma-oscillations embeds scale-invariant neuronal avalanches that exhibit robust power law scaling in size with a slope of -3/2 and a critical branching parameter of 1. This dynamical coordination, tracked in the local field potential (nLFP) and pyramidal neuron activity using 2-photon imaging, emerges autonomously in superficial layers of organotypic cortex cultures and acute cortex slices, is homeostatically regulated, displays separation of time scales, and reveals unique size vs. quiet time dependencies. A threshold operation identifies coherence potentials; avalanches that in addition maintain the precise time course of propagated synchrony. Avalanches emerge under conditions of external driving. Control parameters are established by the balance of excitation and inhibition (E/I) and the neuromodulator dopamine. This rich dynamical repertoire is not observed in dissociated cortex cultures, which lack cortical layers and exhibit dynamics similar to a 1st-order phase transition. The precise interactions between up-states, nested oscillations, avalanches, and coherence potentials in superficial cortical layers provide compelling evidence for SOC in the brain.
The shape of clouds has proven to be essential for classifying them. Our analysis of images from fair weather cumulus clouds reveals that, besides by turbulence they are driven by self-organized criticality (SOC). Our observations yield exponents that support the fact the clouds, when projected to two dimensions (2D), exhibit conformal symmetry compatible with $c=-2$ conformal field theory (CFT), in contrast to 2D turbulence which has $c=0$ CFT. By using a combination of the Navier-Stokes equation, diffusion equations and a coupled map lattice (CML) we successfully simulated cloud formation, and obtained the same exponents.
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