4,182 research outputs found
Spin-Orbit Misalignment of Merging Black-Hole Binaries with Tertiary Companions
We study the effect of external companion on the orbital and spin evolution
of merging black-hole (BH) binaries. An sufficiently close by and inclined
companion can excite Lidov-Kozai (LK) eccentricity oscillations in the binary,
thereby shortening its merger time. During such LK-enhanced orbital decay, the
spin axis of the BH generally exhibits chaotic evolution, leading to a wide
range (-) of final spin-orbit misalignment angle from an
initially aligned configuration. For systems that do not experience
eccentricity excitation, only modest () spin-orbit
misalignment can be produced, and we derive an analytic expression for the
final misalignment using the principle of adiabatic invariance. The spin-orbit
misalignment directly impacts the gravitational waveform, and can be used to
constrain the formation scenarios of BH binaries and dynamical influences of
external companions.Comment: Published in ApJ
Suppression of extreme orbital evolution in triple systems with short range forces
The Lidov-Kozai (LK) mechanism plays an important role in the secular
evolution of many hierarchical triple systems. The standard LK mechanism
consists of large-amplitude oscillations in eccentricity and inclination of a
binary subject to the quadrupole potential from an outer perturber. Recent work
has shown that when the octupole terms are included in the potential, the inner
binary can reach more extreme eccentricities as well as undergo orientation
flips. It is known that pericenter precessions due to short-range effects, such
as General Relativity and tidal and rotational distortions, can limit the
growth of eccentricity and even suppress standard (quadrupolar) LK
oscillations, but their effect on the octupole-level LK mechanism has not been
fully explored. In this paper, we systematically study how these short-range
forces affect the extreme orbital behaviour found in octupole LK cycles. In
general, the influence of the octupole potential is confined to a range of
initial mutual inclinations Itot centered around 90deg (when the inner binary
mass ratio is <<1), with this range expanding with increasing octupole
strength. We find that, while the short-range forces do not change the width
and location of this "window of influence", they impose a strict upper limit on
the maximum achievable eccentricity. This limiting eccentricity can be
calculated analytically, and its value holds even for strong octupole potential
and for the general case of three comparable masses. Short-range forces also
affect orbital flips, progressively reducing the range of Itot within which
flips are possible as the intensity of these forces increases.Comment: 20 pages,15 figures, updated to match version published on MNRA
Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution
Convolutional neural networks have recently demonstrated high-quality
reconstruction for single-image super-resolution. In this paper, we propose the
Laplacian Pyramid Super-Resolution Network (LapSRN) to progressively
reconstruct the sub-band residuals of high-resolution images. At each pyramid
level, our model takes coarse-resolution feature maps as input, predicts the
high-frequency residuals, and uses transposed convolutions for upsampling to
the finer level. Our method does not require the bicubic interpolation as the
pre-processing step and thus dramatically reduces the computational complexity.
We train the proposed LapSRN with deep supervision using a robust Charbonnier
loss function and achieve high-quality reconstruction. Furthermore, our network
generates multi-scale predictions in one feed-forward pass through the
progressive reconstruction, thereby facilitates resource-aware applications.
Extensive quantitative and qualitative evaluations on benchmark datasets show
that the proposed algorithm performs favorably against the state-of-the-art
methods in terms of speed and accuracy.Comment: This work is accepted in CVPR 2017. The code and datasets are
available on http://vllab.ucmerced.edu/wlai24/LapSRN
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