Velocity Distribution Associated With EUV Disturbances Caused by Eruptive MFR

Extreme ultraviolet (EUV) disturbances are ubiquitous during eruptive phenomena like solar flare and Coronal Mass Ejection (CME). In this work, we have performed a three-dimensional (3D) magnetohydrodynamic numerical simulation of CME with an analytic magnetic fluxrope (MFR) to study the complex velocity distribution associated with EUV disturbances. When the MFR erupts upward, a fast shock (FS) appears as a 3D dome, followed by outward moving plasma. In the center of the eruptive source region, an expanding CME bubble and a current sheet continuously grow, both of which are filled by inward moving plasma. At the flanks of the CME bubble, a complex velocity distribution forms because of the dynamical interaction between inward and outward plasma, leading to the formation of slow shock (SS) and velocity separatrix (VS). We note two types of vortices near the VS, not mentioned in the preceding EUV disturbance simulations. In first type of vortex, the plasma converges toward the vortex center, and in the second type, the plasma spreads out from the center. The forward modeling method has been used to create the synthetic SDO/AIA images, in which the eruptive MFR and the FS appear as bright structures. Furthermore, we also deduce the plasma velocity field by utilizing the Fourier local correlation tracking method on the synthetic images. However, we do not observe the VS, the SS, and the two types of vortices in this deduced velocity field.

Frequency-Domain Common Image Gathers for Quickly Checking the Accuracy of Migration Velocity

The common image gather (CIG) method enables qualitative and quantitative evaluation of the velocity model through the image. The most common such methods are offset-domain common image gather (ODCIG) and angle-domain common image gather (ADCIG). The challenge is that it requires a great deal of additional computation besides migration. We, therefore, introduce a new CIG method that has low computational cost: frequency-domain common image gather (FDCIG). FDCIG simply rearranges data using a gradient (partial image) calculated in the process of obtaining a migration image to represent it in the frequency-depth domain. We apply the FDCIG method to the layered model to show how FDCIGs behave when the velocity model is inaccurate. We also introduced the 3-D SEG/EAGE salt model to show how to apply the FDCIG method in the hybrid domain. Last, we applied 2-D real data. These sample field data also indicate that even in a complex velocity model, deviant behavior by FDCIG appears intuitively if the background velocity is inaccurate.

Love Waves in a Viscoelastic Stratum: Explicit Expression for Complex Velocity as a Function of Frequency

ABSTRACT Propagation of Love wave is considered in a two-layered stratum of isotropic viscoelastic solids. The complex dispersion equation for this wave is solved through a complex analysis technique. This gets an analytical expression for complex velocity, as a function of real frequency rather than the complex wavenumber. This complex (phase) velocity is used further to calculate the (complex) group velocity. Numerical example is solved to analyze the dispersion in speed and attenuation of the viscoelastic Love waves.

Accessing tens-to-hundreds femtoseconds nuclear state lifetimes with low-energy binary heavy-ion reactions

A novel Monte Carlo technique has been developed to determine lifetimes of excited states in the tens-to-hundreds femtoseconds range in products of low-energy heavy-ion binary reactions, with complex velocity distributions. The method is based on a detailed study of Doppler-broadened $$\gamma $$ γ -ray lineshapes. Its relevance is demonstrated in connection with the $$^{18}\text {O}(7.0\, \text {MeV/u})+\,^{181}\text {Ta}$$ 18 O ( 7.0 MeV/u ) + 181 Ta experiment, performed at GANIL with the AGATA+VAMOS+PARIS setup, to study neutron-rich O, C, N, ... nuclei. Excited states in $$^{17}\text {O}$$ 17 O and $$^{19}\text {O}$$ 19 O , with known lifetimes, are used to validate the method over the $$\sim 20{-}400\,\text {fs}$$ ∼ 20 - 400 fs lifetime-sensitivity range. Emphasis is given to the unprecedented position resolution provided by $$\gamma $$ γ -tracking arrays, which turns out to be essential for reaching the required accuracy in Doppler-shift correction. The technique is anticipated to be an important tool for lifetime investigations in exotic neutron-rich nuclei, produced with intense ISOL-type beams.

The impact of heterogeneous salt velocity models on the gross rock volume estimation: an example from the Santos Basin pre-salt, Brazil

The thick and heterogeneous salt section in the Santos Basin, offshore Brazil, imposes great challenges to access the pre-salt hydrocarbon reservoirs, especially in relation to seismic imaging, signal quality, and depth positioning. Some problems arise from the current velocity models for the salt section, which for the majority, assume the salt is a homogeneous halite layer. In the Santos Basin, the commonly assumed salt - halite - only makes up to 80% of the mineral in this section. The inclusion of other salts as stratification in the velocity models, based on seismic attributes, has achieved good results in the last decade, especially for depth resolution. In this work, we analyze the benefits of different velocity models, considering presence/absence of salt stratification, and comparing the gross rock volume above the oil-water contact. The results show a significant effect on depth resolution of the events, as well as on volume estimation, indicating that more reliability captured by the complex velocity models will ensure the more confident the resulting volumetric information is.

HypoSVI: Hypocenter inversion with Stein Variational Inference and Physics Informed Neural Networks

<p>High resolution earthquake hypocentral locations are of critical importance for understanding the regional context driving seismicity. We introduce a scheme to reliably approximate a hypocenter posterior in a continuous domain that relies on recent advances in deep learning.</p><p>Our method relies on a differentiable forward model in the form of a deep neural network, which is trained to solve the Eikonal equation (EikoNet). EikoNet can rapidly determine the travel-time between any source-receiver pair for a non-gridded solution. We demonstrate the robustness of these travel-time solutions are for a series of complex velocity models.</p><p>For the inverse problem, we utilize Stein Variational Inference, which is a recent approximate inference procedure that iteratively updates a configuration of particles to approximate a target posterior by minimizing the so-called Stein discrepancy. The gradients of this objective function can be rapidly calculated due to the differentiability of the EikoNet. The particle locations are updated until convergence, after which we utilize clustering techniques and kernel density methods to determine the optimal hypocenter and its uncertainty.</p><p>The inversion procedure outlined in this work is validated using a series of synthetic tests to determine the parameter optimisation and the validity for large observational datasets, which can locate earthquakes in 439s per event for 2039 observations. In addition, we apply this technique to a case study of seismicity in the Southern California region for earthquakes from 2019.</p>

The ThreeHundred: the structure and properties of cosmic filaments in the outskirts of galaxy clusters

Galaxy cluster outskirts are described by complex velocity fields induced by diffuse material collapsing towards filaments, gas and galaxies falling into clusters, and gas shock processes triggered by substructures. A simple scenario that describes the large-scale tidal fields of the cosmic web is not able to fully account for this variety, nor for the differences between gas and collisionless dark matter. We have studied the filamentary structure in zoom-in resimulations centred on 324 clusters from The ThreeHundred project, focusing on differences between dark and baryonic matter. This paper describes the properties of filaments around clusters out to five R200, based on the diffuse filament medium where haloes had been removed. For this, we stack the remaining particles of all simulated volumes to calculate the average profiles of dark matter and gas filaments. We find that filaments increase their thickness closer to nodes and detect signatures of gas turbulence at a distance of $\sim 2 \rm {{{~h^{-1}{\rm Mpc}}}}$ from the cluster. These are absent in dark matter. Both gas and dark matter collapse towards filament spines at a rate of $\sim 200 \rm {km ~ s^{-1} h^{-1}}$. We see that gas preferentially enters the cluster as part of filaments, and leaves the cluster centre outside filaments. We further see evidence for an accretion shock just outside the cluster. For dark matter, this preference is less obvious. We argue that this difference is related to the turbulent environment. This indicates that filaments act as highways to fuel the inner regions of clusters with gas and galaxies.