We report on-chip structures based on ordered dielectric nano-particle chain which can be used to steer and tune optical beams. With different elaborately designed structures, the optical beam can transmit in a negative direction, or totally reflected beyond the normal incidence with a subwavelength nanorod chain. The mechanism of the phenomenon is believed to be due to the symmetry of resonant modes in the dielectric nanoparticles. With the low-loss feature and the ultra-compact characteristic, this structure may find applications in photonic circuits.
We have studied the influence of underlayer thickness on the static and dynamic magnetic properties in perpendicular exchange-biased (PEB) [Pd/CoFeB] 4 /MnIr multilayers for both Pd and Cu cases. The PEB field [Formula: see text] decreases and the coercivity field [Formula: see text] increases with increasing thickness of Cu and Pd underlayers. The dynamic results demonstrate that the Gilbert damping constant [Formula: see text] increases with increasing the underlayer thickness in both cases. We attribute the enhancement in [Formula: see text] to the increased interfacial spin disordering due to the higher roughness. The increasing of spin disordering in the dead layer enhances the interfacial spin scattering or spin dephasing which makes an additional contribution to the damping constant [Formula: see text]. In addition, we find that the intrinsic damping constant becomes larger when exchange bias effect is established, because the introduction of anti-ferromagnetic (AFM) layer adds another transfer channel of angular momentum of ferromagnetic (FM) layer.
The wide application of machine learning (ML) techniques in statistics physics has presented new avenues for research in this field. In this paper, we introduce a semi-supervised learning method based on Siamese Neural Networks (SNN), trying to explore the potential of neural network (NN) in the study of critical behaviors beyond the approaches of supervised and unsupervised learning. By focusing on the (1+1) dimensional bond directed percolation (DP) model of nonequilibrium phase transition, we use the SNN to predict the critical values and critical exponents of the system. Different from traditional ML methods, the input of SNN is a set of configuration data pairs and the output prediction is similarity, which prompts to find an anchor point of data for pair comparison during the test. In our study, during test we set different bond probability $p$ as anchors, and discuss the impact of the configurations at this anchors on predictions. More, we use an iterative method to find the optimal training interval to make the algorithm more efficient, and the prediction results are comparable to other ML methods.
Recently the superconductivity has been discovered in the rock-salt structured binary lanthanum monoxide LaO through the state-of-the-art oxide thin-film epitaxy. This work reveals the normal state of superconducting LaO to be a $Z_2$ nontrivial topological metal that the Dirac point protected by the crystal symmetry is located at around the Fermi energy. By analysing the orbital characteristics, the nature of topological band structure of LaO originates from the intra-atomic transition in energy from outer shell La 5$d$ to inner shell 4$f$ orbitals driven by the strong octahedral crystal-field. Furthermore, the appearance of novel surface states unambiguously demonstrates the topological signature of LaO. Our theoretical findings not only shed light into the understanding of exotic quantum behaviors in LaO superconductor with intimate correlation between 4$f$ and 5$d$ orbitals in La, but also provide an exciting platform to explore the interplay of intriguing nontrivial topology and superconductivity.
Strongly correlated electrons can display intriguing spontaneous broken symmetries in the ground state. Understanding these symmetry breaking states is fundamental to elucidating the various exotic quantum phases in condensed matter physics. Here, we report a pronounced spontaneous rotational symmetry breaking of the superconductivity at the interface of YAlO$_3$/KTaO$_3$ with superconducting transition temperature of 1.86 K and the thickness of superconducting layer as thin as 4.5 nm. Both the magnetoresistance and upper critical field under an applied in-plane magnetic field manifest striking asymmetric twofold oscillations deep inside the superconducting state, whereas the anisotropy vanishes in the normal state, demonstrating that it is an intrinsic property of the superconducting phase. We attribute this behavior to the mixed-parity superconducting state with a mixture of $s$-wave and $p$-wave pairing components induced by strong electron correlation and spin-orbit coupling inherent to the inversion symmetry breaking at the interface of YAlO$_3$/KTaO$_3$. Our work demonstrates the unconventional character of the pairing interaction in the KTaO$_3$ interface superconductor and sheds new light on the pairing mechanism of unconventional superconductivity with inversion symmetry breaking.
Narrowband emitters or absorbers based on LSPRs (Localized Surface Plasmon Resonances) in MIM structures have drawn increasing attention because of their filter-free character, small volume and low power consumption. However, the plasmonics community has slowly come to the consensus that the ohmic losses of the metals are simply too high to realize ultra-narrowband resonance. Recently, parallel coupling between the LSPR and the lattice diffraction has also been present in the metallic particle array, which shows greater tolerance to inhomogeneous environment and has greater potential in the far field emission applications. In this paper, the delocalized parallel coupling with ultra-narrowband is stimulated in the Coating-MIM structure, at mid-infrared. Besides, coating with hundreds of nanometers is employed to modulate the coupled efficiency. By inducing this ultra-narrowband resonance, MIM structures may extend their application area into ultra-high performance.
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