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 $\mathrm{Bi_2Sr_2CaCu_2O_{8+\delta}}$, $\mathrm{YBa_2Cu_xO_y}$ and $\mathrm{La_{2-x}Sr_xCuO_4}$, are intrinsic left-handed materials. The condition is that the plasma frequency in the $c$ axis, $\omega_c$, and in the $ab$ plane, $\omega_{ab}$, and the operating frequency, $\omega$, satisfy $\omega_c<\omega<\omega_{ab}$. In addition $\omega$ 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 ($Q$-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