51 research outputs found
Intermediate behavior of Kerr tails
The numerical investigation of wave propagation in the asymptotic domain of
Kerr spacetime has only recently been possible thanks to the construction of
suitable hyperboloidal coordinates. The asymptotics revealed an apparent puzzle
in the decay rates of scalar fields: the late-time rates seemed to depend on
whether finite distance observers are in the strong field domain or far away
from the rotating black hole, an apparent phenomenon dubbed "splitting". We
discuss far-field "splitting" in the full field and near-horizon "splitting" in
certain projected modes using horizon-penetrating, hyperboloidal coordinates.
For either case we propose an explanation to the cause of the "splitting"
behavior, and we determine uniquely decay rates that previous studies found to
be ambiguous or immeasurable. The far-field "splitting" is explained by
competition between projected modes. The near-horizon "splitting" is due to
excitation of lower multipole modes that back excite the multipole mode for
which "splitting" is observed. In both cases "splitting" is an intermediate
effect, such that asymptotically in time strong field rates are valid at all
finite distances. At any finite time, however, there are three domains with
different decay rates whose boundaries move outwards during evolution. We then
propose a formula for the decay rate of tails that takes into account the
inter--mode excitation effect that we study.Comment: 16 page
Characteristic Evolution and Matching
I review the development of numerical evolution codes for general relativity
based upon the characteristic initial value problem. Progress in characteristic
evolution is traced from the early stage of 1D feasibility studies to 2D
axisymmetric codes that accurately simulate the oscillations and gravitational
collapse of relativistic stars and to current 3D codes that provide pieces of a
binary black hole spacetime. Cauchy codes have now been successful at
simulating all aspects of the binary black hole problem inside an artificially
constructed outer boundary. A prime application of characteristic evolution is
to extend such simulations to null infinity where the waveform from the binary
inspiral and merger can be unambiguously computed. This has now been
accomplished by Cauchy-characteristic extraction, where data for the
characteristic evolution is supplied by Cauchy data on an extraction worldtube
inside the artificial outer boundary. The ultimate application of
characteristic evolution is to eliminate the role of this outer boundary by
constructing a global solution via Cauchy-characteristic matching. Progress in
this direction is discussed.Comment: New version to appear in Living Reviews 2012. arXiv admin note:
updated version of arXiv:gr-qc/050809
Identification of Plasmodium vivax Proteins with Potential Role in Invasion Using Sequence Redundancy Reduction and Profile Hidden Markov Models
BACKGROUND: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. RESULTS: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. CONCLUSIONS: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria
Self-force: Computational Strategies
Building on substantial foundational progress in understanding the effect of
a small body's self-field on its own motion, the past 15 years has seen the
emergence of several strategies for explicitly computing self-field corrections
to the equations of motion of a small, point-like charge. These approaches
broadly fall into three categories: (i) mode-sum regularization, (ii) effective
source approaches and (iii) worldline convolution methods. This paper reviews
the various approaches and gives details of how each one is implemented in
practice, highlighting some of the key features in each case.Comment: Synchronized with final published version. Review to appear in
"Equations of Motion in Relativistic Gravity", published as part of the
Springer "Fundamental Theories of Physics" series. D. Puetzfeld et al.
(eds.), Equations of Motion in Relativistic Gravity, Fundamental Theories of
Physics 179, Springer, 201
Longitudinal Molecular Trajectories of Diffuse Glioma in Adults
The evolutionary processes that drive universal therapeutic resistance in adult patients with diffuse glioma remain unclear ¹² . Here we analysed temporally separated DNA-sequencing data and matched clinical annotation from 222 adult patients with glioma. By analysing mutations and copy numbers across the three major subtypes of difuse glioma, we found that driver genes detected at the initial stage of disease were retained at recurrence, whereas there was little evidence of recurrence-specifc gene alterations. Treatment with alkylating agents resulted in a hypermutator phenotype at diferent rates across the glioma subtypes, and hypermutation was not associated with diferences in overall survival. Acquired aneuploidy was frequently detected in recurrent gliomas and was characterized by IDH mutation but without co-deletion of chromosome arms 1p/19q, and further converged with acquired alterations in the cell cycle and poor outcomes. The clonal architecture of each tumour remained similar over time, but the presence of subclonal selection was associated with decreased survival. Finally, there were no differences in the levels of immunoediting between initial and recurrent gliomas. Collectively, our results suggest that the strongest selective pressures occur during early glioma development and that current therapies shape this evolution in a largely stochastic manner
Charged particles in higher dimensional homogeneous gravitational field: self-energy and self-force
Characteristic Evolution and Matching
I review the development of numerical evolution codes for general relativity
based upon the characteristic initial value problem. Progress is traced from
the early stage of 1D feasibility studies to 2D axisymmetric codes that
accurately simulate the oscillations and gravitational collapse of relativistic
stars and to current 3D codes that provide pieces of a binary black spacetime.
A prime application of characteristic evolution is to compute waveforms via
Cauchy-characteristic matching, which is also reviewed.Comment: Published version http://www.livingreviews.org/lrr-2005-1
Exploring new physics frontiers through numerical relativity
The demand to obtain answers to highly complex problems within strong-field gravity has been met with significant progress in the numerical solution of Einstein's equations - along with some spectacular results - in various setups. We review techniques for solving Einstein's equations in generic spacetimes, focusing on fully nonlinear evolutions but also on how to benchmark those results with perturbative approaches. The results address problems in high-energy physics, holography, mathematical physics, fundamental physics, astrophysics and cosmology
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