5,912 research outputs found
Plasmonic metamaterial enhanced axionic magnetoelectric effect
Axionic electrodynamics predicts many peculiar magnetoelectric-based
properties. Hitherto, simple structures such as one-dimensional multilayers
were employed to explore these axionic magnetoelectric responses, and
Fabry-P\'{e}rot interference mechanism was frequently applied to augment these
effects. In this Letter, we propose a new mechanism, metamaterial-enhanced
axionic magnetoelectric response, by taking advantage of intense enhancement of
localized electromagnetic fields associated with plasmonic resonances. Through
numerical simulations, we show that plasmonic metamaterial can enhance axionic
magnetoelectric effect by two orders of magnitude
Markov chain-based stability analysis of growing networks
From the perspective of probability, the stability of growing network is
studied in the present paper. Using the DMS model as an example, we establish a
relation between the growing network and Markov process. Based on the concept
and technique of first-passage probability in Markov theory, we provide a
rigorous proof for existence of the steady-state degree distribution,
mathematically re-deriving the exact formula of the distribution. The approach
based on Markov chain theory is universal and performs well in a large class of
growing networks.Comment: 11 page
Intrinsic left-handed electromagnetic properties in anisotropic superconductors
Left-handed materials usually are realized in artificial subwavelength
structures. Here we show that some anisotropic superconductors, such as
, and
, are intrinsic left-handed materials. The
condition is that the plasma frequency in the axis, , and in the
plane, , and the operating frequency, , satisfy
. In addition should be smaller than the
superconducting energy gap to sustain superconductivity. We study the
reflection and transmission of electromagnetic waves, and reveal negative
refraction and backward wave with phase velocity opposite to the direction of
energy flux propagation. We also discuss possible approaches of improvement,
making these properties feasible for experimental validation. Being intrinsic
left-hand materials, the anisotropic superconductors are promising for
applications in novel electromagnetic devices in the terahertz frequency band.Comment: 5 pages and 2 figure
A review of metasurfaces: physics and applications
Metamaterials are composed of periodic subwavelength metal/dielectric
structures that resonantly couple to the electric and/or magnetic components of
the incident electromagnetic fields, exhibiting properties that are not found
in nature. Planar metamaterials with subwavelength thickness, or metasurfaces,
consisting of single-layer or few-layer stacks of planar structures, can be
readily fabricated using lithography and nanoprinting methods, and the
ultrathin thickness in the wave propagation direction can greatly suppress the
undesirable losses. Metasurfaces enable a spatially varying optical response,
mold optical wavefronts into shapes that can be designed at will, and
facilitate the integration of functional materials to accomplish active control
and greatly enhanced nonlinear response. This paper reviews recent progress in
the physics of metasurfaces operating at wavelengths ranging from microwave to
visible. We provide an overview of key metasurface concepts such as anomalous
reflection and refraction, and introduce metasurfaces based on the
Pancharatnam-Berry phase and Huygens' metasurfaces, as well as their use in
wavefront shaping and beam forming applications, followed by a discussion of
polarization conversion in few-layer metasurfaces and their related properties.
An overview of dielectric metasurfaces reveals their ability to realize unique
functionalities coupled with Mie resonances and their low ohmic losses. We also
describe metasurfaces for wave guidance and radiation control, as well as
active and nonlinear metasurfaces. Finally, we conclude by providing our
opinions of opportunities and challenges in this rapidly developing research
field.Comment: 44 pages, 32 figures, 258 referemces This is an author-created,
un-copyedited version of an article accepted for publication in Reports on
Progress in Physics. IOP Publishing Ltd is not responsible for any errors or
omissions in this version of the manuscript or any version derived from it.
The Version of Record will be updated and available onlin
A reinterpretation of the metamaterial perfect absorber
We develop a simple treatment of a metamaterial perfect absorber (MPA) based
on grating theory. We analytically prove that the condition of MPA requires the
existence of two currents, which are nearly out of phase and have almost
identical amplitude, akin to a magnetic dipole. Furthermore, we show that
non-zero-order Bragg modes within the MPA may consume electromagnetic energy
significantly.Comment: 7 pages, 2 figures. It is an updated version with new titl
Jet Luminosity of Gamma-ray Bursts: Blandford-Znajek Mechanism v.s. Neutrino Annihilation Process
A neutrino-dominated accretion flow (NDAF) around a rotating stellar-mass
black hole (BH) is one of the plausible candidates for the central engine of
gamma-ray bursts (GRBs). Two mechanisms, i.e., Blandford-Znajek (BZ) mechanism
and neutrino annihilation process, are generally considered to power GRBs.
Using the analytic solutions from Xue et al. (2013) and ignoring the effects of
the magnetic field configuration, we estimate the BZ and neutrino annihilation
luminosities as the functions of the disk masses and BH spin parameters to
contrast the observational jet luminosities of GRBs. The results show that,
although the neutrino annihilation processes could account for most of GRBs,
the BZ mechanism is more effective, especially for long-duration GRBs.
Actually, if the energy of afterglows and flares of GRBs is included, the
distinction between these two mechanisms is more significant. Furthermore,
massive disk mass and high BH spin are beneficial to power high luminosities of
GRBs. Finally, we discuss possible physical mechanisms to enhance the disk mass
or the neutrino emission rate of NDAFs and relevant difference between these
two mechanisms.Comment: 20 pages, 3 tables, 2 figures, accepted for publication in ApJ
Can black-hole neutrino-cooled disks power short gamma-ray bursts?
Stellar-mass black holes (BHs) surrounded by neutrino-dominated accretion
flows (NDAFs) are the plausible candidates to power gamma-ray bursts (GRBs) via
neutrinos emission and their annihilation. The progenitors of short-duration
GRBs (SGRBs) are generally considered to be compact binaries mergers. According
to the simulation results, the disk mass of the NDAF has been limited after
merger events. We can estimate such disk mass by using the current SGRB
observational data and fireball model. The results show that the disk mass of a
certain SGRB mainly depends on its output energy, jet opening angle, and
central BH characteristics. Even for the extreme BH parameters, some SGRBs
require massive disks, which approach or exceed the limits in simulations. We
suggest that there may exist alternative magnetohydrodynamic processes or some
mechanisms increasing the neutrino emission to produce SGRBs with the
reasonable BH parameters and disk mass.Comment: 17 pages, 1 table, 2 figures, accepted for publication in Ap
From Sylvester's determinant identity to Cramer's rule
The object of this paper is to introduce a new and fascinating method of
solving large linear equations, based on Cramer's rule or Gaussian elimination
but employing Sylvester's determinant identity in its computation process. In
addition, a scheme suitable for parallel computing is presented for this kind
of generalized Chi\`{o}'s determinant condensation processes, which makes this
new method have a property of natural parallelism. Finally, some numerical
experiments also confirm our theoretical analysis.Comment: 15 pages, 4 figure
Hierarchical equations of motion for impurity solver in dynamical mean-field theory
A nonperturbative quantum impurity solver is proposed based on a formally
exact hierarchical equations of motion (HEOM) formalism for open quantum
systems. It leads to quantitatively accurate evaluation of physical properties
of strongly correlated electronic systems, in the framework of dynamical
mean-field theory (DMFT). The HEOM method is also numerically convenient to
achieve the same level of accuracy as that using the state-of-the-art numerical
renormalization group impurity solver at finite temperatures. The practicality
of the novel HEOM+DMFT method is demonstrated by its applications to the
Hubbard models with Bethe and hypercubic lattice structures. We investigate the
metal-insulator transition phenomena, and address the effects of temperature on
the properties of strongly correlated lattice systems.Comment: 14 pages, 11 figures, updated version accepted to be published in PR
Self-learning how to swim at low Reynolds number
Synthetic microswimmers show great promise in biomedical applications such as
drug delivery and microsurgery. Their locomotion, however, is subject to
stringent constraints due to the dominance of viscous over inertial forces at
low Reynolds number (Re) in the microscopic world. Furthermore, locomotory
gaits designed for one medium may become ineffective in a different medium.
Successful biomedical applications of synthetic microswimmers rely on their
ability to traverse biological environments with vastly different properties.
Here we leverage the prowess of machine learning to present an alternative
approach to designing low Re swimmers. Instead of specifying any locomotory
gaits \textit{a priori}, here a swimmer develops its own propulsion strategy
based on its interactions with the surrounding medium via reinforcement
learning. This self-learning capability enables the swimmer to modify its
propulsion strategy in response to different environments. We illustrate this
new approach using a minimal example that integrates a standard reinforcement
learning algorithm (-learning) into the locomotion of a swimmer consisting
of an assembly of spheres connected by extensible rods. We showcase
theoretically that this first self-learning swimmer can recover a previously
known propulsion strategy without prior knowledge in low Re locomotion,
identify more effective locomotory gaits when the number of spheres increases,
and adapt its locomotory gaits in different media. These results represent
initial steps towards the design of a new class of self-learning, adaptive (or
"smart") swimmers with robust locomotive capabilities to traverse complex
biological environments
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