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We investigated the magnon-photon coupling in an open cavity magnonic system, which leads to two different nonreciprocal singularities dominated by the dissipative coupling. One type of singularity is the exceptional point, which is just on the exceptional surface in parameter space. The other type of singularity is the bound state in the continuum discovered in the level-attraction-like coupling, which is above the exceptional surface. In experiment, we realized the two different singularities with nonreciprocity and selectivity in an open cavity magnonic system with suitable dissipation rating. Our results can be understood well with the pseudo-Hermitian theory of magnon-polariton system.

The inevitable Gilbert damping in magnetization dynamics is usually regarded as detrimental to spin transport. Here we apply a general feature of chiral non-Hermitian dynamics to a ferromagnetic-insulator--normal-metal heterostructure to show that the strong momentum dependence and chirality of the eddy-current-induced damping also causes beneficial scattering properties: A potential barrier that reflects magnon wave packets becomes unidirectionally transparent in the presence of a metallic cap layer. Passive magnon gates that turn presumably harmful dissipation into useful functionalities should be useful for future quantum magnonic devices., Comment: 7 pages, 3 figures

We present an experimental study of Rayleigh-B\'enard convection using liquid metal alloy gallium-indium-tin as the working fluid with a Prandtl number of $Pr=0.029$. The flow state and the heat transport were measured in a Rayleigh number range of $1.2\times10^{4} \le Ra \le 1.3\times10^{7}$. The temperature fluctuation at the cell centre is used as a proxy for the flow state. It is found that, as $Ra$ increases from the lower end of the parameter range, the flow evolves from a convection state to an oscillation state, a chaotic state, and finally a turbulent state for $Ra>10^5$. The study suggests that the large-scale circulation in the turbulent state is a residual of the cell structures near the onset of convection, which is in contrast with the case of $Pr\sim1$, where the cell structure is replaced by high-order flow modes transiently before the emergence of the large-scale circulation in the turbulent state. The evolution of the flow state is also reflected by the heat transport characterised by the Nusselt number $Nu$ and the probability density function (PDF) of the temperature fluctuation at the cell centre. It is found that the effective local heat transport scaling exponent $\gamma$, i.e., $Nu\sim Ra^{\gamma}$, changes continuously from $\gamma=0.49$ at $Ra\sim 10^4$ to $\gamma=0.25$ for $Ra>10^6$. Meanwhile, the PDF at the cell centre gradually evolves from a Gaussian-like shape before the transition to turbulence to an exponential-like shape in the turbulent state. For $Ra>10^6$, the flow shows self-similar behaviour, which is revealed by the universal shape of the PDF of the temperature fluctuation at the cell centre and a $Nu=0.19Ra^{0.25}$ scaling for the heat transport., Comment: 12 pages, 5 figures; Accepted for publication in the Journal of Fluid Mechanics

We report a study on low-temperature heat transport of Kitaev magnet Na$_2$Co$_2$TeO$_6$, with the heat current and magnetic fields along the honeycomb spin layer (the $ab$ plane). The zero-field thermal conductivity of $\kappa^a_{xx}$ and $\kappa^{a*}_{xx}$ display similar temperature dependence and small difference in their magnitudes; whereas, their magnetic field (parallel to the heat current) dependence are quite different and are related to the field-induced magnetic transitions. The $\kappa^a_{xx}(B)$ data for $B \parallel a$ at very low temperatures have an anomaly at 10.25--10.5 T, which reveals an unexplored magnetic transition. The planar thermal Hall conductivity $\kappa^a_{xy}$ and $\kappa^{a*}_{xy}$ show very weak signals at low fields and rather large values with sign change at high fields. This may point to a possible magnetic structure transition or the change of the magnon band topology that induces a radical change of magnon Berry curvature distribution before entering the spin polarized state. These results put clear constraints on the high-field phase and the theoretical models for Na$_2$Co$_2$TeO$_6$., Comment: 7 pages, 4 figures

Dissipation in mechanics, optics, acoustics, and electronic circuits is nowadays recognized to be not always detrimental but can be exploited to achieve non-Hermitian topological phases or properties with functionalities for potential device applications. As elementary excitations of ordered magnetic moments that exist in various magnetic materials, magnons are the information carriers in magnonic devices with low-energy consumption for reprogrammable logic, non-reciprocal communication, and non-volatile memory functionalities. Non-Hermitian topological magnonics deals with the engineering of dissipation and/or gain for non-Hermitian topological phases or properties in magnets that are not achievable in the conventional Hermitian scenario, with associated functionalities cross-fertilized with their electronic, acoustic, optic, and mechanic counterparts, such as giant enhancement of magnonic frequency combs, magnon amplification, (quantum) sensing of the magnetic field with unprecedented sensitivity, magnon accumulation, and perfect absorption of microwaves. In this review article, we address the unified approach in constructing magnonic non-Hermitian Hamiltonian, introduce the basic non-Hermitian topological physics, and provide a comprehensive overview of the recent theoretical and experimental progress towards achieving distinct non-Hermitian topological phases or properties in magnonic devices, including exceptional points, exceptional nodal phases, non-Hermitian magnonic SSH model, and non-Hermitian skin effect. We emphasize the non-Hermitian Hamiltonian approach based on the Lindbladian or self-energy of the magnonic subsystem but address the physics beyond it as well, such as the crucial quantum jump effect in the quantum regime and non-Markovian dynamics. We provide a perspective for future opportunities and challenges before concluding this article., Comment: 101 pages, 35 figures

We investigate the spatial distribution and dynamics of the vortices in rotating Rayleigh-B\'enard convection in a reduced Rayleigh-number range $1.3{\le}Ra/Ra_{c}{\le}166$. Under slow rotations ($Ra{\gtrsim}10Ra_{c}$), the vortices are randomly distributed. The size-distribution of the Voronoi cells of the vortex centers is well described by the standard $\Gamma$ distribution. In this flow regime the vortices exhibit Brownian-type horizontal motion. The probability density functions of the vortex displacements are, however, non-Gaussian at short time scales. At modest rotating rates ($4Ra_{c}{\le}Ra{\lesssim}10Ra_{c}$) the centrifugal force leads to radial vortex motions, i.e., warm cyclones (cold anticyclones) moving towards (outward from) the rotation axis. The mean-square-displacements of the vortices increase faster than linearly at large time. This super-diffusive behavior can be satisfactorily explained by a Langevin model incorporating the centrifugal force. In the rapidly rotating regime ($1.6Ra_{c}{\le}Ra{\le}4Ra_{c}$) the vortices are densely distributed, with the size-distribution of their Voronoi cells differing significantly from the standard $\Gamma$ distribution. The hydrodynamic interaction of neighboring vortices results in formation of vortex clusters. Inside clusters the correlation of the vortex velocity fluctuations is scale free, with the correlation length being approximately $30\%$ of the cluster length. We examine the influence of cluster forming on the dynamics of individual vortex. Within clusters, cyclones exhibit inverse-centrifugal motion as they submit to the motion of strong anticyclones, while the velocity for outward motion of the anticyclones is increased. Our analysis show that the mobility of isolated vortices, scaled by their vorticity strength, is a simple power function of the Froude number.

We have reported on the hysteresis and training effect of spin current in Pt/Y3Fe5O12 heterostructures during subsequent cycles of ionic liquid gate voltage Vg. The inverse spin Hall effect voltage in spin pumping and spin Hall magnetoresistance exhibit diode-like behaviors in the first half cycle of Vg andalsoshowhysteresisinthe first cycle of Vg. Both the diode-like behavior and the hysteresis become weak and even vanish in the second cycle of Vg due to the training effect. The above experimental results can be well explained by the screening charge doping model, in which the charge and the local magnetic moment are asymmetrically distributed in the Pt layer. The applicability of this model is further confirmed by measurements of anisotropic magnetoresistance and ferromagnetic resonance. The diode-like behavior is attributed to interplay between the asymmetrically distributed local magnetic moment and the spin current relaxation in the Pt layer. The hysteresis and the training effect arise from the incompletely reversible process between oxidation and reduction of Pt atoms and the evolution of the surface morphology at the ionic liquid/Pt interface under electric gating. This work provides new insights to improve the functional performance of electrically controlled spin current devices.

A neural network is a powerful tool that can uncover hidden laws beyond human intuition. However, it often appears as a black box due to its complicated nonlinear structures. By drawing upon the Gutzwiller mean-field theory, we can showcase a principle of sign rules for ordered states in qubit lattice models. We introduce a shallow feed-forward neural network with a single hidden neuron to present these sign rules. We conduct systematical benchmarks in various models, including the generalized Ising, spin-$1/2$ XY, (frustrated) Heisenberg rings, triangular XY antiferromagnet on a torus, and the Fermi-Hubbard ring at an arbitrary filling. These benchmarks show that all the leading-order sign rule characteristics can be visualized in classical forms, such as pitch angles. Besides, quantum fluctuations can result in an imperfect accuracy rate quantitatively., Comment: 12 pages, 11 figures

In this paper, we investigate how to deploy computational intelligence and deep learning (DL) in edge-enabled industrial IoT networks. In this system, the IoT devices can collaboratively train a shared model without compromising data privacy. However, due to limited resources in the industrial IoT networks, including computational power, bandwidth, and channel state, it is challenging for many devices to accomplish local training and upload weights to the edge server in time. To address this issue, we propose a novel multi-exit-based federated edge learning (ME-FEEL) framework, where the deep model can be divided into several sub-models with different depths and output prediction from the exit in the corresponding sub-model. In this way, the devices with insufficient computational power can choose the earlier exits and avoid training the complete model, which can help reduce computational latency and enable devices to participate into aggregation as much as possible within a latency threshold. Moreover, we propose a greedy approach-based exit selection and bandwidth allocation algorithm to maximize the total number of exits in each communication round. Simulation experiments are conducted on the classical Fashion-MNIST dataset under a non-independent and identically distributed (non-IID) setting, and it shows that the proposed strategy outperforms the conventional FL. In particular, the proposed ME-FEEL can achieve an accuracy gain up to 32.7% in the industrial IoT networks with the severely limited resources., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version will be superseded

We theoretically propose a method to realize optical nonreciprocity in rotating nano-diamond with a nitrogen-vacancy (NV) center. Because of the relative motion of the NV center with respect to the propagating fields, the frequencies of the fields are shifted due to the Doppler effect. When the control and probe fields are incident to the NV center from the same direction, the two-photon resonance still holds as the Doppler shifts of the two fields are the same. Thus, due to the electromagnetically-induced transparency (EIT), the probe light can pass through the NV center nearly without absorption. However, when the two fields propagate in opposite directions, the probe light can not effectively pass through the NV center as a result of the breakdown of two-photon resonance., Comment: 7 pages, 4 figures

Magnon cat state represents a macroscopic quantum superposition of collective magnetic excitations of large number spins that not only provides fundamental tests of macroscopic quantum effects but also finds applications in quantum metrology and quantum computation. In particular, remote generation and manipulation of Schr\"{o}dinger cat states are particularly interesting for the development of long-distance and large-scale quantum information processing. Here, we propose an approach to remotely prepare magnon even/odd cat states by performing local non-Gaussian operations on the optical mode that is entangled with magnon mode through pulsed optomagnonic interaction. By evaluating key properties of the resulting cat states, we show that for experimentally feasible parameters they are generated with both high fidelity and nonclassicality, and with a size large enough to be useful for quantum technologies. Furthermore, the effects of experimental imperfections such as the error of projective measurements and dark count when performing single-photon operations have been discussed, where the lifetime of the created magnon cat states is expected to be $t\sim1\,\mu$s., Comment: 14 pages, 10 figures

The spontaneous Hall effect is usually governed by three conventional mechanisms, such as the Berry curvature, skew scattering and side jump, which widely exist in ferromagnetic or antiferromagnetic materials. However, in this work, based on first principle calculations, we predict a giant crystal Hall effect (CHE) in the antiferromagnetic $\gamma$-FeMn, which can not be understood by the previous three conventional mechanisms and the Hall angle therein can be as large as 18.4% at low temperature. Furthermore, with Boltzmann transport equation and a tight-binding model, we conclude that, the asymmetric group velocities on Fermi surface is the origin of this CHE in $\gamma$-FeMn. And with a systematic symmetry argument, we show that, this unusual effect is not dependent on specific materials but universal in any crystals with similar symmetry even without local magnetization.

Based on the exact muffin-tin orbitals (EMTOs), we developed a first-principles method to calculate the current operators and investigated the anomalous Hall effect in bcc Fe as an example, with which we successfully separated the skew scattering contribution from the side jump and intrinsic contributions by fitting the scaling law with the introduction of sparse impurities. By investigating the temperature dependence of the anomalous Hall effect in bulk Fe, we predicted a fluctuated anomalous Hall angle as a function of temperature when considering only phonons, which, in the future, can be measured in experiments by suppressing magnon excitation, e.g., by applying a high external magnetic field.

The ability to recognize dynamical phenomena (e.g., dynamical phases) and dynamical processes in physical events from videos, then to abstract physical concepts and reveal physical laws, lies at the core of human intelligence. The main purposes of this paper are to use neural networks for classifying the dynamical phases of some videos and to demonstrate that neural networks can learn physical concepts from them. To this end, we employ multiple neural networks to recognize the static phases (image format) and dynamical phases (video format) of a particle-based skyrmion model. Our results show that neural networks, without any prior knowledge, can not only correctly classify these phases, but also predict the phase boundaries which agree with those obtained by simulation. We further propose a parameter visualization scheme to interpret what neural networks have learned. We show that neural networks can learn two order parameters from videos of dynamical phases and predict the critical values of two order parameters. Finally, we demonstrate that only two order parameters are needed to identify videos of skyrmion dynamical phases. It shows that this parameter visualization scheme can be used to determine how many order parameters are needed to fully recognize the input phases. Our work sheds light on the future use of neural networks in discovering new physical concepts and revealing unknown yet physical laws from videos., Comment: 15 pages, 15 figures

We study magnon hybridization in a ferrimagnetic heterostructure consisting of ultrathin gadolinium iron garnet and yttrium iron garnet layers and show the localized and extended spatial profiles of the magnon modes with different polarizations. These modes are expected to have distinct thermal excitation properties in the presence of a temperature gradient across the heterostructure. From a quantitative analysis of their consequences on longitudinal spin Seebeck effect, we predict an observable shift of the sign-changing temperature with respect to the one previously observed in gadolinium iron garnet. Moreover, the sign-changing point of spin Seebeck signal is found to be tunable by YIG thickness. Our results suggest the necessity of taking into account the temperature difference between the magnon modes in ferrimagnetic heterostructures., Comment: 9 pages, 5 figures

Strong coupling between cavity photons and various excitations in condensed matters boosts the field of light-matter interaction and generates several exciting sub-fields, such as cavity optomechanics and cavity magnon polariton. Axion quasiparticles, emerging in topological insulators, were predicted to strongly couple with the light and generate the so-called axion polariton. Here, we demonstrate that there arises a gapless level attraction in cavity axion polariton of antiferromagnetic topological insulators, which originates from a nonlinear interaction between axion and the odd-order resonance of cavity. Such a novel level attraction is essentially different from conventional level attractions with the mechanism of either a linear coupling or a dissipation-mediated interaction, and also different from the level repulsion induced by the strong coupling in common polaritons. Our results reveal a new mechanism of level attractions, and open up new roads for exploring the axion polariton with cavity technologies. They have potential applications for quantum information and dark matter research.

When a fluid system is subject to strong rotation, centrifugal fluid motion is expected, i.e., denser (lighter) fluid moves outward (inward) from (toward) the axis of rotation. Here we demonstrate, both experimentally and numerically, the existence of an unexpected outward motion of warm and lighter vortices in rotating turbulent convection. This anomalous vortex motion occurs under rapid rotations when the centrifugal buoyancy is sufficiently strong to induce a symmetry-breaking in the vorticity field, i.e., the vorticity of the cold anticyclones overrides that of the warm cyclones. We show that through hydrodynamic interactions the densely populated vortices can self-aggregate into coherent clusters and exhibit collective motion in this flow regime. Interestingly, the correlation of the vortex velocity fluctuations within a cluster is scale-free, with the correlation length being about 30% of the cluster length. Such long-range correlation leads to the collective outward motion of cyclones. Our study provides new understanding of vortex dynamics that are widely present in nature.

We present high-precision experimental and numerical studies of the Nusselt number $Nu$ as functions of the Rayleigh number $Ra$ in geostrophic rotating convection with domain aspect ratio ${\Gamma}$ varying from 0.4 to 3.8 and the Ekman number Ek from $2.0{\times}10^{-7}$ to $2.7{\times}10^{-5}$. The heat-transport data $Nu(Ra)$ reveal a gradual transition from buoyancy-dominated to geostrophic convection at large $Ek$, whereas the transition becomes sharp with decreasing $Ek$. We determine the power-law scaling of $Nu{\sim}Ra^{\gamma}$, and show that the boundary flows give rise to pronounced enhancement of $Nu$ in a broad range of the geostrophic regime, leading to reduction of the scaling exponent ${\gamma}$ in small ${\Gamma}$ cells. The present work provides new insight into the heat-transport scaling in geostrophic convection and may explain the discrepancies observed in previous studies., Comment: 5 pages, 4 figures, 1 table

Non-Hermitian physics has recently attracted much attention in optics and photonics. Less explored is non-Hermitian magnonics that provides opportunities to take advantage of the inevitable dissipation of magnons or spin waves in magnetic systems. Here we demonstrate non-Hermitian coherent coupling of two distant nanomagnets by fast spin waves with sub-50 nm wavelengths. Magnons in two nanomagnets are unidirectionally phase-locked with phase shifts controlled by magnon spin torque and spin-wave propagation. Our results are attractive for analog neuromorphic computing that requires unidirectional information transmission.

Real-time tracking of high-speed objects in cognitive tasks is challenging in the present artificial intelligence techniques because the data processing and computation are time-consuming resulting in impeditive time delays. A brain-inspired continuous attractor neural network (CANN) can be used to track quickly moving targets, where the time delays are intrinsically compensated if the dynamical synapses in the network have the short-term plasticity. Here, we show that synapses with short-term depression can be realized by a magnetic tunnel junction, which perfectly reproduces the dynamics of the synaptic weight in a widely applied mathematical model. Then, these dynamical synapses are incorporated into one-dimensional and two-dimensional CANNs, which are demonstrated to have the ability to predict a moving object via micromagnetic simulations. This portable spintronics-based hardware for neuromorphic computing needs no training and is therefore very promising for the tracking technology for moving targets., Comment: 9 pages, 6 figures

We propose a quantum state readout mechanism of a weakly coupled qubit in dispersive regime. The hybrid system consists of ferromagnetic insulator and a superconducting qubit in a microwave cavity. The enhancement of the measurement sensitivity is achieved by exerting torque on the ferromagnetic insulator magnetization, which compensates the damping of the system leading to an exceptional point. The proposed machanism allows to measure the qubit state either via the transmission of the cavity or the FMR signal of the magnetic material.

Artificial intelligence based on artificial neural networks, which are originally inspired by the biological architectures of human brain, has mostly been realized using software but executed on conventional von Neumann computers, where the so-called von Neumann bottleneck essentially limits the executive efficiency due to the separate computing and storage units. Therefore, a suitable hardware platform that can exploit all the advantages of brain-inspired computing is highly desirable. Based upon micromagnetic simulation of the magnetization dynamics, we demonstrate theoretically and numerically that recurrent neural networks consisting of as few as 40 magnetic tunnel junctions can generate and recognize periodic time series after they are trained with an efficient machine-learning algorithm. With ultrahigh operating speed, nonvolatile memory and high endurance and reproducibility, spintronic devices are promising hardware candidates for neuromorphic computing., Comment: 5 pages, 4 figures

The ability to tailor the damping factor is essential for spintronic and spin-torque applications. Here, we report an approach to manipulate the damping factor of FeGa/MgO(001) films by oblique deposition. Owing to the defects at the surface or interface in thin films, two-magnon scattering (TMS) acts as a non-Gilbert damping mechanism in magnetization relaxation. In this work, the contribution of TMS was characterized by in-plane angular dependent ferromagnetic resonance (FMR). It is demonstrated that the intrinsic Gilbert damping is isotropic and invariant, while the extrinsic mechanism related to TMS is anisotropic and can be tuned by oblique deposition. Furthermore, the two and fourfold TMS related to the uniaxial magnetic anisotropy (UMA) and magnetocrystalline anisotropy were discussed. Our results open an avenue to manipulate magnetization relaxation in spintronic devices., Comment: 20 pages,4 figures

In spintronics applications, ultrafast spin dynamics have to be controlled at femtosecond (fs) timescales via fs-laser radiation. At such ultrafast timescales, the effect of the Gilbert damping factor {\alpha} on ultrafast demagnetization time should be considered. In previous explorations for the relationship between these two parameters, it was found that the theoretical calculations based on the local spin-flip scattering model do not agree with the experimental results. Here, we find that in Fe81Ga19(FeGa)/Ir20Mn80(IrMn) bilayers, the unconventional IrMn thickness dependence of {\alpha} results from the competition between spin currents pumped from the ferromagnetic (FM) FeGa layer to the antiferromagnetic (AFM) IrMn layer and those pumped from the AFM layer to the FM layer. More importantly, we establish a proportional relationship between the change of the ultrafast demagnetization rate and the enhancement of Gilbert damping induced by the spin currents via interfacial spin chemical potential . Our work builds a bridge to connect the ultrafast demagnetization time and Gilbert damping in ultrafast photo-induced spin currents dominated systems, which not only explains the disagreement between experimental and theoretical results in the relation of {\tau}_M with {\alpha}, but provides further insight into ultrafast spin dynamics as well.