ترغب بنشر مسار تعليمي؟ اضغط هنا

Tidal torques. A critical review of some techniques

173   0   0.0 ( 0 )
 نشر من قبل Michael Efroimsky
 تاريخ النشر 2012
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

We point out that the MacDonald formula for body-tide torques is valid only in the zeroth order of e/Q, while its time-average is valid in the first order. So the formula cannot be used for analysis in higher orders of e/Q. This necessitates corrections in the theory of tidal despinning and libration damping. We prove that when the inclination is low and phase lags are linear in frequency, the Kaula series is equivalent to a corrected version of the MacDonald method. The correction to MacDonalds approach would be to set the phase lag of the integral bulge proportional to the instantaneous frequency. The equivalence of descriptions gets violated by a nonlinear frequency-dependence of the lag. We explain that both the MacDonald- and Darwin-torque-based derivations of the popular formula for the tidal despinning rate are limited to low inclinations and to the phase lags being linear in frequency. The Darwin-torque-based derivation, though, is general enough to accommodate both a finite inclination and the actual rheology. Although rheologies with Q scaling as the frequency to a positive power make the torque diverge at a zero frequency, this reveals not the impossible nature of the rheology, but a flaw in mathematics, i.e., a common misassumption that damping merely provides lags to the terms of the Fourier series for the tidal potential. A hydrodynamical treatment (Darwin 1879) had demonstrated that the magnitudes of the terms, too, get changed. Reinstating of this detail tames the infinities and rehabilitates the impossible scaling law (which happens to be the actual law the terrestrial planets obey at low frequencies).

قيم البحث

اقرأ أيضاً

421 - Michael Efroimsky 2012
In geophysics and seismology, it is a common knowledge that the quality factors Q of the mantle and crust materials scale as the tidal frequency to a positive fractional power (Karato 2007, Efroimsky and Lainey 2007). In astronomy, there exists an eq ually common belief that such rheological models introduce discontinuities into the equations and thus are unrealistic at low frequencies. We demonstrate that, while such models indeed make the conventional expressions for the tidal torque diverge for vanishing frequencies, the emerging infinities reveal not the impossible nature of one or another rheology, but a subtle flaw in the underlying mathematical model of friction. Flawed is the common misassumption that the tidal force and torque are inversely proportional to the quality factor. In reality, they are proportional to the sine of the tidal phase lag, while the inverse quality factor is commonly identified with the tangent of the lag. The sine and tangent of the lag are close everywhere {it{except in the vicinity of the zero frequency}}. Reinstating of this detail tames the fake infinities and rehabilitates the impossible scaling law (which happens to be the actual law the mantles obey). This preprint is a pilot paper. A more comprehensive treatise on tidal torques is to be published (Efroimsky and Williams 2009).
84 - C. T. J. Dodson 2012
Even linear operators on infinite-dimensional spaces can display interesting dynamical properties and yield important links among functional analysis, differential and global geometry and dynamical systems, with a wide range of applications. In parti cular, hypercyclicity is an essentially infinite-dimensional property, when iterations of the operator generate a dense subspace. A Frechet space admits a hypercyclic operator if and only if it is separable and infinite-dimensional. However, by considering the semigroups generated by multiples of operators, it is possible to obtain hypercyclic behaviour on finite dimensional spaces. This article gives a brief review of some recent work on hypercyclicity of operators on Banach, Hilbert and Frechet spaces.
120 - Fredrik Eriksen 2018
By means of digital image correlation, we experimentally characterize the deformation of a dry granular medium confined inside a Hele-Shaw cell due to air injection at a constant overpressure high enough to deform it (from 50 to 250 kPa). Air injecti on at these overpressures leads to the formation of so called pneumatic fractures, i.e. channels empty of beads, and we discuss the typical deformations of the medium surrounding these structures. In addition we simulate the diffusion of the fluid overpressure into the medium, comparing it with the Laplacian solution over time, and relating pressure gradients with corresponding granular displacements. In the compacting medium we show that the diffusing pressure field becomes similar to the Laplace solution on the order of a characteristic time given by properties of the pore fluid, granular medium and the system size. However, before the diffusing pressure approaches the Laplace solution on system scale, we find that it resembles the Laplacian field near the channels, with the highest pressure gradients on the most advanced channel tips and a screened pressure gradient behind them. We show that the granular displacements more or less always move in the direction against the local pressure gradients, and when comparing granular velocities with pressure gradients in the zone ahead of channels, we observe a Bingham type of rheology for the granular paste (the mix of air and beads), with an effective viscosity $mu_B$ and displacement thresholds $ abla P_c$ evolving during mobilization and compaction of the medium. Such a rheology, with disorder in the displacement thresholds, could be responsible for placing the pattern growth at moderate injection pressures in a universality class like the Dielectric Breakdown Model with $eta=2$, where fractal dimensions are found between 1.5 and 1.6 for the patterns.
We currently know about 30 magnetars: seemingly isolated neutron stars whose properties can be (in part) comprehended only acknowledging that they are endowed with magnetic fields of complex morphology and exceptional intensity-at least in some compo nents of the field structure. Although magnetars represent only a small percentage of the known isolated neutron stars, there are almost certainly many more of them, since most magnetars were discovered in transitory phases called outbursts, during which they are particularly noticeable. In outburst, in fact, a magnetar can be brighter in X-rays by orders of magnitude and usually emit powerful bursts of hard-X/soft-gamma-ray photons that can be detected almost everywhere in the Galaxy with all-sky monitors such as those on board the Fermi satellite or the Neil Gehrels Swift Observatory. Magnetars command great attention because the large progress that has been made in their understanding is proving fundamental to fathom the whole population of isolated neutron stars, and because, due to their extreme properties, they are relevant for a vast range of different astrophysical topics, from the study of gamma-ray bursts and superluminous supernovae, to ultraluminous X-ray sources, fast radio bursts, and even to sources of gravitational waves. Several excellent reviews with different focuses were published on magnetars in the last few years: among others, Israel and DallOsso (2011); Rea and Esposito (2011); Turolla and Esposito (2013); Mereghetti et al. (2015); Turolla et al. (2015); Kaspi and Beloborodov (2017). Here, we quickly recall the history of these sources and travel through the main observational facts, trying to touch some recent and sometimes little-discussed ramifications of magnetars.
The ability to predict, anticipate and reason about future outcomes is a key component of intelligent decision-making systems. In light of the success of deep learning in computer vision, deep-learning-based video prediction emerged as a promising re search direction. Defined as a self-supervised learning task, video prediction represents a suitable framework for representation learning, as it demonstrated potential capabilities for extracting meaningful representations of the underlying patterns in natural videos. Motivated by the increasing interest in this task, we provide a review on the deep learning methods for prediction in video sequences. We firstly define the video prediction fundamentals, as well as mandatory background concepts and the most used datasets. Next, we carefully analyze existing video prediction models organized according to a proposed taxonomy, highlighting their contributions and their significance in the field. The summary of the datasets and methods is accompanied with experimental results that facilitate the assessment of the state of the art on a quantitative basis. The paper is summarized by drawing some general conclusions, identifying open research challenges and by pointing out future research directions.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا