Realistic Oscillation Research Articles

Thermo‐Mechanical Numerical Modeling of the South American Subduction Zone: A Multi‐Parametric Investigation

AbstractThe South American subduction zone is enigmatic due to its fast subducting plate consumption, strong oscillation in subducting plate velocity, and deep mantle subduction. A key to help understand these subduction zone characteristics is through studying its dynamics with buoyancy‐driven numerical modeling that uses independent variables to best approximate the dynamics of the real subduction system. We conduct a parametric investigation on the effect of upper mantle rheology, subduction interface yield stress and slab thermal weakening. To constrain those model variables, we attempt to find best‐fits by comparing our model outcomes with the present‐day slab geometry and estimates of Cenozoic velocities in the center of the South American subduction zone. Key ingredients that need to be reproduced are low slab dip angles close to the surface, steeper lower mantle dip angles, strong oscillation of the fast Farallon‐Nazca subducting plate velocity and a progressive decrease in trench retreat rate during long‐term subduction. We include these ingredients to define a model fitting score using 10 criteria. Our best fitting models involve a weak subduction zone interface (yield stress of ∼20 MPa) and significant slab thermal weakening to attain the fast Farallon‐Nazca subducting plate velocity and to better reproduce the subduction partitioning since 48 Ma due to reduced shear stresses resisting downdip slab sinking and reduced slab bending resistance. Furthermore, a non‐Newtonian upper mantle promotes slab folding and realistic oscillation of the subducting plate velocity. Whether and how this slab folding process induces temporal variations in Andean deformation remains an open question.

Fast oscillations, collisionless relaxation, and spurious evolution of supernova neutrino flavor

Mounting evidence indicates that neutrinos likely undergo fast flavor conversion (FFC) in at least some core-collapse supernovae. Outcomes of FFC, however, remain highly uncertain. Here we study the cascade of flavor-field power from large angular scales in momentum space down to small ones, showing that FFC enhances this process and thereby hastens relaxation. Cascade also poses a computational challenge, which is present even if the flavor field is stable: When power reaches the smallest angular scale of the calculation, error from truncating the angular-moment expansion propagates back to larger scales, to disastrous effect on the overall evolution. Essentially the same issue has prompted extensive work in the context of plasma kinetics. This link suggests new approaches to averting spurious evolution, a problem that presently puts severe limitations on the feasibility of realistic oscillation calculations.

Development of a displacement-reactivity feedback model for dynamic behavior simulation in fast burst reactor

In this study, a displacement-reactivity feedback model, which can directly represent the inherent “thermal expansion extinction effect” of fast burst reactors (FBRs), was developed with the aid of the static neutron transport component of the FBR-MPC code. Dynamic behaviors of bursts in the Godiva I reactor were simulated by coupling the simplified multiphysics models consisting of the point kinetic equations for neutronics, adiabatic equation for temperature, and thermoelastic equations for displacement/stress with the developed model. The results were compared with the corresponding experimental data and those obtained using the traditional fission yield (temperature rise)-reactivity feedback models. It was found that the developed model can provide good results for the bursts with no or a small inertia effect. For the bursts with a prominent inertia effect, the smaller burst width and asymmetric distribution of the fission rate curve, noticed in the experiments but not evident using the traditional models, can be reproduced. In addition, the realistic oscillations in reactivity and fission rate caused by the core vibration, as well as the deeper sub-prompt criticality in the plateau following the burst, can be observed. Therefore, the developed displacement-reactivity feedback model can be expected to be an effective tool for calculating the dynamic behaviors of bursts.

Self-sustained oscillations in excitable tree networks

Many practical systems, such as heart and neural systems, are described by excitable media or networks. Various oscillations of coupled excitable units are typical system states, determining some important functions in realistic processes. Excitable units do not oscillate individually, while oscillations of coupled excitable cells can appear after the self-organizations of collective motions via mutual interactions. Therefore, different mechanisms underlying oscillations turn to be very crucial issues under investigation. So far, all mechanisms of the oscillations of excitable networks rely, with no exception, on the existence of the oscillation sources formed by successive excited units on loops. Here, we explore a novel oscillation mechanism in diffusively coupled excitable networks where loop existence is no longer required, and oscillations can be sustained due to the excitation propagations between two hubs linked by a chain of low-degree nodes. Some necessary conditions for the sustained oscillations on hub size, chain length and coupling strength are analyzed in detail. And the possible application and significance of the explored mechanism for realistic oscillations of practical excitable networks are briefly discussed.

Renormalization-group equations of neutrino masses and flavor mixing parameters in matter

We borrow the general idea of renormalization-group equations (RGEs) to understand how neutrino masses and flavor mixing parameters evolve when neutrinos propagate in a medium, highlighting a meaningful possibility that the genuine flavor quantities in vacuum can be extrapolated from their matter-corrected counterparts to be measured in some realistic neutrino oscillation experiments. Taking the matter parameter aequiv 2sqrt{2}kern0.5em {G}_{mathrm{F}}{N}_eE to be an arbitrary scale-like variable with Ne being the net electron number density and E being the neutrino beam energy, we derive a complete set of differential equations for the effective neutrino mixing matrix V and the effective neutrino masses {tilde{m}}_i (for i = 1, 2, 3). Given the standard parametrization of V , the RGEs for left{{tilde{theta}}_{12},kern0.5em {tilde{theta}}_{13},kern0.5em {tilde{theta}}_{23},kern0.5em tilde{delta}right} in matter are formulated for the first time. We demonstrate some useful differential invariants which retain the same form from vacuum to matter, including the well-known Naumov and Toshev relations. The RGEs of the partial μ-τ asymmetries, the off-diagonal asymmetries and the sides of unitarity triangles of V are also obtained as a by-product.

Flow–topography interactions in shallow-water turbulence

Topography and external time-varying flows such as tides can have a profound influence on atmospheric and oceanic fluid motion. The effects of topography on turbulence have been little studied, and until recently those of tides have been overlooked. Our lack of understanding of these effects is a serious impediment to predicting flows both in the atmosphere and in the oceans. As a first step toward modelling realistic tidal oscillations, this study focuses on how an initially balanced flow containing a distribution of potential vorticity anomalies develops and becomes unbalanced (by emitting gravity waves) as a result of interactions with topography in the presence of an oscillating flow, here in the form of pure inertial oscillations (at the Coriolis frequency). We investigate a large parameter space spanned by the Burger number, the maximum amplitude of topography, and the amplitude of the flow oscillations. Comparisons are made with a time-independent and spatially-homogeneous steady flow in order to better understand the role played by flow oscillations. The most persistent large-amplitude gravity wave activity occurs for large-amplitude flow oscillations and for large topography. The latter produces large potential vorticity and depth anomalies which remain locked to the topography, thereby allowing gravity waves to be continually generated. By contrast, for a steady flow, large potential vorticity and depth anomalies are advected away from topographic features and so gravity waves are only generated at early times.

Biophysical modeling of excitability and membrane integration at the single cell and network levels

Ion channels facilitate the diffusion of specific ions across neuronal membranes. If large enough, this movement of charge creates currents that may change the membrane potential. Biophysical models of membrane potential assume the trans-membrane currents flow within an “equivalent electrical circuit” in which ion channels are represented by resistors arranged in parallel. The functions representing the trans-membrane currents mediated by channels are typically written using Ohm’s law. It is possible to describe channel-mediated currents by taking diffusion into consideration [1], but such formulations are not widely used in the literature. Here we present a model of membrane potential in which channel gating and current density are derived from first principles of thermodynamics, assuming that currents are produced by electrodiffusion. These models display properties that cannot be observed in conductance-based models, such as rectification of membrane currents. Guidelines for parameter estimation, and specific rules to adjust the model against experimental data, are presented along with examples of parameter regimes that yield representations of specific electrophysiological signatures with a biophysically sound baseline. Bifurcation analysis is used to describe transitions between qualitatively different behaviors of the model and link them to functionally relevant properties observable in neurons of different types. Network extensions are constructed using realistic synaptic input and local field potential oscillations to illustrate how networks may display potentially different responses to afferent input depending on the intrinsic properties of the participating neurons. The electrodiffusion formulation presented here constitutes a theoretical improvement over conductance-based models that may advance our current understanding of dynamical behavior in single cells and networks.

The Membrane Potential Waveform of Bursting Pacemaker Neurons Is a Predictor of Their Preferred Frequency and the Network Cycle Frequency

Many oscillatory networks involve neurons that exhibit intrinsic rhythmicity but possess a large variety of voltage-gated currents that interact in a complex fashion, making it difficult to determine which factors control frequency. Yet these neurons often have preferred (resonance) frequencies that can be close to the network frequency. Because the preferred frequency results from the dynamics of ionic currents, it can be assumed to depend on parameters that determine the neuron's oscillatory waveform shape. The pyloric network frequency in the crab Cancer borealis is correlated with the preferred frequency of its bursting pacemaker neurons anterior burster and pyloric dilator (PD). We measured the preferred frequency of the PD neuron in voltage clamp, which allows control of the oscillation voltage range and waveforms (sine waves and realistic oscillation waveforms), and showed that (1) the preferred frequency depends on the voltage range of the oscillating voltage waveform; (2) the slope of the waveform near its peak has a strongly negative correlation with the preferred frequency; and (3) correlations between parameters of the PD neuron oscillation waveform and its preferred frequency can be used to predict shifts in the network frequency. As predicted by these results, dynamic clamp shifts of the upper or lower voltage limits of the PD neuron waveform during ongoing oscillations changed the network frequency, consistent with the predictions from the preferred frequency. These results show that the voltage waveform of oscillatory neurons can be predictive of their preferred frequency and thus the network oscillation frequency.

Extracting Number-Selective Responses from Coherent Oscillations in a Computer Model

Cortical neurons selective for numerosity may underlie an innate number sense in both animals and humans. We hypothesize that the number- selective responses of cortical neurons may in part be extracted from coherent, object-specific oscillations . Here, indirect evidence for this hypothesis is obtained by analyzing the numerosity information encoded by coherent oscillations in artificially generated spikes trains. Several experiments report that gamma-band oscillations evoked by the same object remain coherent, whereas oscillations evoked by separate objects are uncorrelated. Because the oscillations arising from separate objects would add in random phase to the total power summed across all stimulated neurons, we postulated that the total gamma activity, normalized by the number of spikes, should fall roughly as the square root of the number of objects in the scene, thereby implicitly encoding numerosity. To test the hypothesis, we examined the normalized gamma activity in multiunit spike trains, 50 to 1000 msec in duration, produced by a model feedback circuit previously shown to generate realistic coherent oscillations. In response to images containing different numbers of objects, regardless of their shape, size, or shading, the normalized gamma activity followed a square-root-of-n rule as long as the separation between objects was sufficiently large and their relative size and contrast differences were not too great. Arrays of winner-take-all numerosity detectors, each responding to normalized gamma activity within a particular band, exhibited tuning curves consistent with behavioral data. We conclude that coherent oscillations in principle could contribute to the number-selective responses of cortical neurons, although many critical issues await experimental resolution.

Nonlinear oscillations of semigeostrophic Eady waves in the presence of diffusivity

Analyses are performed to examine the physical processes involved in nonlinear oscillations of Eady baroclinic waves obtained from viscous semigeostrophic models with two types of boundary conditions (freeslip and non-slip). By comparing with previous studies for the case of the free-slip boundary condition, it is shown that the nonlinear oscillations are produced mainly by the interaction between the baroclinic wave and zonal-mean state (total zonal-mean flow velocity and buoyancy stratification) but the timescale of the nonlinear oscillations is largely controlled by the diffusivity. When the boundary condition is non-slip, the nonlinear oscillations are further damped and slowed by the diffusive process. Since the free-slip (non-slip) boundary condition is the zero drag (infinite drag) limit of the more realistic drag boundary condition, the nonlinear oscillations obtained with the two types of boundary conditions are two extremes for more realistic nonlinear oscillations.

Realistic semiannual oscillation simulated in a middle atmosphere general circulation model

Although several general circulation modelling studies have presented simulations containing a tropical middle atmosphere semiannual oscillation (6 month period), none so far have been able to reproduce the observed amplitude and vertical structure extending into the mesosphere. Here we present simulations with the Canadian Middle Atmosphere Model which utilize a nonlinear broad‐spectrum gravity‐wave parameterization [Medvedev and Klaassen, 1995, 2000] and exhibit a semiannual oscillation in good agreement with observations.

Impacts of shortwave radiation forcing on ENSO: a study with a coupled tropical ocean-atmosphere model

We describe a coupled tropical ocean-atmosphere model that represents a new class of models that fill the gap between anomaly coupled models and fully coupled general circulation models. Both the atmosphere and ocean are described by two and half layer primitive equation models, which emphasize the physical processes in the oceanic mixed layer and atmospheric boundary layer. Ocean and atmosphere are coupled through both momentum and heat flux exchanges without explicit flux correction. The coupled model, driven by solar radiation, reproduces a realistic annual cycle and El Nino-Southern Oscillation (ENSO). In the presence of annual mean shortwave radiation forcing, the model exhibits an intrinsic mode of ENSO. The oscillation period depends on the mean forcing that determines the coupled mean state. A perpetual April (October) mean forcing prolongs (shortens) the oscillation period through weakening (enhancing) the mean upwelling and mean vertical temperature gradients. The annual cycle of the solar forcing is shown to have fundamental impacts on the behavior of ENSO cycles through establishing a coupled annual cycle that interacts with the ENSO mode. Due to the annual cycle solar forcing, the single spectral peak of the intrinsic ENSO mode becomes a double peak with a quasi-biennial and a low-frequency (4–5 years) component; the evolution of ENSO becomes phase-locked to the annual cycle; and the amplitude and frequency of ENSO become variable on an interdecadal time scale due to interactions of the mean state and the two ENSO components. The western Pacific monsoon (the annual shortwave radiation forcing in the western Pacific) is primarily responsible for the generation of the two ENSO components. The annual march of the eastern Pacific ITCZ tends to lock ENSO phases to the annual cycle. The model's deficiencies, limitations, and future work are also discussed.

Assimilating ocean tide determined data into global tidal models

A data assimilation procedure, which has successfully been applied to fictive and realistic scenarios, is applied to a 1 °-model making use of an effective iterative method for the solution of the minimization problem. Two sets of ocean tide determined data are used for the purpose of assimilation, the more extensive one mainly comprising pelagic together with some coastal sea surface elevation data, and the other one consisting of loading gravity data. The computed O1 and M2 global tidal oscillation systems, namely the fields of tidal elevation and loading gravity, are compared with numerous additional pelagic and coastal elevation data and with a selected number of proper gravity data, respectively. The assimilation of the two sets of data leads to an enormous reduction of the errors of the model results in all oceans. Assimilating this altogether still restricted number of data, allows studying the generation of realistic tidal oscillation phenomena by individual data and comparing these data effects with those having been obtained by previous data assimilation experiments using a model with coarser grid spacing. The field of dynamical residuals resulting from data assimilation reflects the far reaching influence of the data, and it is shown that the spatially integrated work done by the residuals contributes to the in all reduced rate of dissipation in the tidal power balance.