scholarly journals Improved Cauchy-characteristic evolution system for high-precision numerical relativity waveforms

2020 ◽  
Vol 102 (4) ◽  
Author(s):  
Jordan Moxon ◽  
Mark A. Scheel ◽  
Saul A. Teukolsky
Keyword(s):  
High Precision ◽  
Numerical Relativity ◽  
Evolution System ◽  
Characteristic Evolution

scholarly journals Hyperbolic evolution system for numerical relativity

1992 ◽  
Vol 68 (8) ◽  
pp. 1097-1099 ◽  
Author(s):  
C. Bona ◽  
J. Massó
Keyword(s):  
Numerical Relativity ◽  
Evolution System

NUMERICAL RELATIVITY: EVOLVING SPACETIME

1993 ◽  
Vol 04 (04) ◽  
pp. 883-907 ◽  
Author(s):  
C. BONA ◽  
J. MASSÓ
Keyword(s):  
Ad Hoc ◽  
Numerical Solutions ◽  
Numerical Relativity ◽  
Historical Review ◽  
Evolution System ◽  
Field Equations ◽  
Metric Tensor ◽  
New Family ◽  
Mandatory Use ◽  
Evolution Systems

The construction of numerical solutions of Einstein's General Relativity equations is formulated as an initial-value problem. The space-plus-time (3 + 1) decomposition of the spacetime metric tensor is used to discuss the structure of the field equations. The resulting evolution system is shown to depend in a crucial way on the coordinate gauge. The mandatory use of singularity avoiding coordinate conditions (like maximal slicing or similar gauges) is explained. A brief historical review of Numerical Relativity is included, showing the enormous effort in constructing codes based in these gauges, which lead to non-hyperbolic evolution systems, using "ad hoc" numerical techniques. A new family of first order hyperbolic evolution systems for the vacuum Einstein field equations in the harmonic slicing gauge is presented. This family depends on a symmetric 3 × 3 array of parameters which can be used to scale the dynamical variables in future numerical applications.

scholarly journals Robust evolution system for numerical relativity

1999 ◽  
Vol 60 (10) ◽  
Author(s):  
A. Arbona ◽  
C. Bona ◽  
J. Massó ◽  
J. Stela
Keyword(s):  
Numerical Relativity ◽  
Evolution System

scholarly journals THE BSSN FORMULATION IS A PARTIALLY CONSTRAINED EVOLUTION SYSTEM

2010 ◽  
Vol 19 (02) ◽  
pp. 153-158
Author(s):  
ADRIAN P. GENTLE
Keyword(s):  
Numerical Relativity ◽  
Einstein Equations ◽  
Evolution System ◽  
Connection Coefficients ◽  
Constrained Evolution ◽  
Conformal Connection

It is shown that the BSSN formulation of the Einstein equations, which forms the basis of most simulations in numerical relativity, explicitly uses the momentum constraints to evolve the conformal connection coefficients.

scholarly journals Coalescence of black hole–neutron star binaries

2021 ◽  
Vol 24 (1) ◽  
Author(s):  
Koutarou Kyutoku ◽  
Masaru Shibata ◽  
Keisuke Taniguchi
Keyword(s):  
Black Hole ◽  
Neutron Star ◽  
Gravitational Wave ◽  
High Precision ◽  
Numerical Relativity ◽  
Current Status ◽  
Wave Spectra ◽  
Tidal Disruption ◽  
Merger Process ◽  
General Relativistic

AbstractWe review the current status of general relativistic studies for coalescences of black hole–neutron star binaries. First, high-precision computations of black hole–neutron star binaries in quasiequilibrium circular orbits are summarized, focusing on the quasiequilibrium sequences and the mass-shedding limit. Next, the current status of numerical-relativity simulations for the merger of black hole–neutron star binaries is described. We summarize our understanding for the merger process, tidal disruption and its criterion, properties of the merger remnant and ejected material, gravitational waveforms, and gravitational-wave spectra. We also discuss expected electromagnetic counterparts to black hole–neutron star coalescences.

MULTI-PUNCTURE INITIAL DATA IN NUMERICAL RELATIVITY

2012 ◽  
Vol 07 ◽  
pp. 247-258
Author(s):  
CHUN-YU LIN ◽  
ZHOUJIAN CAO ◽  
HWEI-JANG YO
Keyword(s):  
Black Holes ◽  
Initial Data ◽  
High Precision ◽  
Local Convergence ◽  
Numerical Relativity ◽  
Linear Momentum ◽  
Computational Resource ◽  
Convergence Test

We present a spectral multi-puncture initial data solver based on the LORENE library http://www.lorene.obspm.fr/ . The solver generates multi black holes initial data with arbitrary linear momentum and spin within a moderate computational resource. The local convergence test shows that the solution rapidly converged to a high precision.

Automatic measurement of SAED patterns from asbestos minerals

1988 ◽  
Vol 46 ◽  
pp. 846-847
Author(s):  
J. C. Russ ◽  
T. Taguchi ◽  
P. M. Peters ◽  
E. Chatfield ◽  
J. C. Russ ◽  
...  
Keyword(s):  
Diffraction Pattern ◽  
High Precision ◽  
Diffraction Data ◽  
Automatic Measurement ◽  
Automatic Method ◽  
Important Method ◽  
X Ray ◽  
Integrated Intensity ◽  
Asbestiform Minerals ◽  
True Center

Conventional SAD patterns as obtained in the TEM present difficulties for identification of materials such as asbestiform minerals, although diffraction data is considered to be an important method for making this purpose. The preferred orientation of the fibers and the spotty patterns that are obtained do not readily lend themselves to measurement of the integrated intensity values for each d-spacing, and even the d-spacings may be hard to determine precisely because the true center location for the broken rings requires estimation. We have implemented an automatic method for diffraction pattern measurement to overcome these problems. It automatically locates the center of patterns with high precision, measures the radius of each ring of spots in the pattern, and integrates the density of spots in that ring. The resulting spectrum of intensity vs. radius is then used just as a conventional X-ray diffractometer scan would be, to locate peaks and produce a list of d,I values suitable for search/match comparison to known or expected phases.

On effects of non-systematic reflections on weak-beam images of partial dislocations

1991 ◽  
Vol 49 ◽  
pp. 688-689
Author(s):  
K. Z. Botros ◽  
S. S. Sheinin
Keyword(s):  
High Precision ◽  
Stacking Fault ◽  
Important Application ◽  
Stacking Fault Energy ◽  
Sharp Peak ◽  
Weak Beam ◽  
Partial Dislocations ◽  
Deviation Parameter ◽  
Beam Diffraction

The main features of weak beam images of dislocations were first described by Cockayne et al. using calculations of intensity profiles based on the kinematical and two beam dynamical theories. The feature of weak beam images which is of particular interest in this investigation is that intensity profiles exhibit a sharp peak located at a position very close to the position of the dislocation in the crystal. This property of weak beam images of dislocations has an important application in the determination of stacking fault energy of crystals. This can easily be done since the separation of the partial dislocations bounding a stacking fault ribbon can be measured with high precision, assuming of course that the weak beam relationship between the positions of the image and the dislocation is valid. In order to carry out measurements such as these in practice the specimen must be tilted to "good" weak beam diffraction conditions, which implies utilizing high values of the deviation parameter Sg.

Digital differential hysteresis iimage processing displays what the microscope acquires but the eye can't see

1995 ◽  
Vol 53 ◽  
pp. 642-643
Author(s):  
Klaus-Ruediger Peters
Keyword(s):  
Image Processing ◽  
Visual System ◽  
High Precision ◽  
Image Data ◽  
Processing Technology ◽  
Output Data ◽  
Contrast Resolution ◽  
Pixel Intensity ◽  
Data Reading ◽  
Hysteresis Properties

Differential hysteresis processing is a new image processing technology that provides a tool for the display of image data information at any level of differential contrast resolution. This includes the maximum contrast resolution of the acquisition system which may be 1,000-times higher than that of the visual system (16 bit versus 6 bit). All microscopes acquire high precision contrasts at a level of <0.01-25% of the acquisition range in 16-bit - 8-bit data, but these contrasts are mostly invisible or only partially visible even in conventionally enhanced images. The processing principle of the differential hysteresis tool is based on hysteresis properties of intensity variations within an image.Differential hysteresis image processing moves a cursor of selected intensity range (hysteresis range) along lines through the image data reading each successive pixel intensity. The midpoint of the cursor provides the output data. If the intensity value of the following pixel falls outside of the actual cursor endpoint values, then the cursor follows the data either with its top or with its bottom, but if the pixels' intensity value falls within the cursor range, then the cursor maintains its intensity value.

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