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Abstract High-temperature superconductivity was discovered in the pressurized nickelate La3Ni2O7 which has a unique bilayer structure and mixed valence state of nickel. The properties at ambient pressure contain crucial information of the fundamental interactions and bosons mediating superconducting pairing. Here, using X-ray absorption spectroscopy and resonant inelastic X-ray scattering, we identified that Ni 3 $${d}_{{x}^{2}-{y}^{2}}$$ d x 2 − y 2 , Ni 3 $${d}_{{z}^{2}}$$ d z 2 , and ligand oxygen 2p orbitals dominate the low-energy physics with a small charge-transfer energy. Well-defined optical-like magnetic excitations soften into quasi-static spin-density-wave ordering, evidencing the strong electronic correlation and rich magnetic properties. Based on an effective Heisenberg spin model, we extract a much stronger inter-layer effective magnetic superexchange than the intra-layer ones and propose two viable magnetic structures. Our findings emphasize that the Ni 3 $${d}_{{z}^{2}}$$ d z 2 orbital bonding within the bilayer induces novel electronic and magnetic excitations, setting the stage for further exploration of La3Ni2O7 superconductor.

Abstract Edge states in topological systems have attracted great interest due to their robustness and linear dispersions. Here a superconducting-proximitized edge interferometer is engineered on a topological insulator Ta2Pd3Te5 with asymmetric edges to realize the interfering Josephson diode effect (JDE), which hosts many advantages, such as the high efficiency as much as 73% at tiny applied magnetic fields with an ultra-low switching power around picowatt. As an important element to induce such JDE, the second-order harmonic in the current-phase relation is also experimentally confirmed by half-integer Shapiro steps. The interfering JDE is also accompanied by the antisymmetric second harmonic transport, which indicates the corresponding asymmetry in the interferometer, as well as the polarity of JDE. This edge interferometer offers an effective method to enhance the performance of JDE, and boosts great potential applications for future superconducting quantum devices.

Abstract We present a new scheme for Majorana modes in systems with nonsymmorphic-symmetry-protected band degeneracy. We reveal that when the gapless fermionic excitations are encoded with conventional superconductivity and magnetism, which can be intrinsic or induced by proximity effect, topological superconductivity and Majorana modes can be obtained. We illustrate this outcome in a system which respects the space group P4/n m m and features a fourfold-degenerate fermionic mode at (π, π) in the Brillouin zone. We show that in the presence of conventional superconductivity, different types of topological superconductivity, i.e., first-order and second-order topological superconductivity, with coexisting fragile Wannier obstruction in the latter case, can be generated in accordance with the different types of magnetic orders; Majorana modes are shown to exist on the boundary, at the corner and in the vortices. To further demonstrate the effectiveness of our approach, another example related to the space group P4/n c c based on this scheme is also provided. Our study offers insights into constructing topological superconductors based on bulk energy bands and conventional superconductivity and helps to find new material candidates and design new platforms for realizing Majorana modes.

Abstract Strongly correlated materials respond sensitively to external perturbations such as strain, pressure, and doping. In the recently discovered superconducting infinite-layer nickelates, the superconducting transition temperature can be enhanced via only ~ 1% compressive strain-tuning with the root of such enhancement still being elusive. Using resonant inelastic x-ray scattering (RIXS), we investigate the magnetic excitations in infinite-layer PrNiO2 thin films grown on two different substrates, namely SrTiO3 (STO) and (LaAlO3)0.3(Sr2TaAlO6)0.7 (LSAT) enforcing different strain on the nickelates films. The magnon bandwidth of PrNiO2 shows only marginal response to strain-tuning, in sharp contrast to the enhancement of the superconducting transition temperature T c in the doped superconducting samples. These results suggest the bandwidth of spin excitations of the parent compounds is similar under strain while T c in the doped ones is not, and thus provide important empirics for the understanding of superconductivity in infinite-layer nickelates.

Abstract This paper studies the problem of differentially private bipartite output consensus in continuous-time heterogeneous multi-agent systems (MASs) characterized by antagonistic interactions. A novel hybrid privacy-preserving event-triggered impulsive consensus protocol is introduced to protect the agent’s initial information from disclosure, which involves a discrete-time information transmission based on an event-triggering mechanism. Using stochastic Lyapunov method, sufficient conditions have been obtained to achieve mean square bipartite output consensus with a guaranteed level of privacy. Furthermore, the differential privacy of competitive agent pairs is exclusively secured by the proposed control scheme by injecting Laplace noise. The protocol also effectively prevents Zeno behavior by imposing a lower bound for impulsive intervals under all event-triggered conditions. A simulation example is provided to validate the effectiveness of the theoretical result.

Abstract The mechanism of unconventional superconductivity in correlated materials remains a great challenge in condensed matter physics. The recent discovery of superconductivity in infinite-layer nickelates, as an analog to high-T c cuprates, has opened a new route to tackle this challenge. By growing 8 nm Pr0.8Sr0.2NiO2 films on the (LaAlO3)0.3(Sr2AlTaO6)0.7 substrate, we successfully raise the superconducting onset transition temperature T c in the widely studied SrTiO3-substrated nickelates from 9 K into 15 K, which indicates compressive strain is an efficient protocol to further enhance superconductivity in infinite-layer nickelates. Additionally, the x-ray absorption spectroscopy, combined with the first-principles and many-body simulations, suggest a crucial role of the hybridization between Ni and O orbitals in the unconventional pairing. These results also suggest the increase of T c be driven by the change of charge-transfer nature that would narrow the origin of general unconventional superconductivity in correlated materials to the covalence of transition metals and ligands.

Abstract The realization of Majorana zero modes in condensed matter have been attracting enormous interests from fundamental science such as topological quantum computation. Recently iron based superconductors were identified as a high-temperature platform for realizing topological superconductivity and Majorana modes. As unconventional superconductors, one of the most important characteristics of them is that they are in the vicinity of magnetic states due to the strong Hund’s coupling in iron atoms. Here we propose that the line defects with missing Te/Se anions in Fe(Se, Te) superconductors provide the realization of intrinsic antiferromagnetic (AFM) chains with Rashba spin-orbit coupling. Against conventional wisdom, Majorana zero modes (MZMs) can be robustly generated at these AFM chain ends. These results can consistently explain the recent experimental observation of zero-energy end states in line defects of monolayer Fe(Te, Se)/SrTiO3 by scanning tunneling microscopy (STM) measurements. Our research not only demonstrates an unprecedented interplay among native line defect, emergent magnetism and topological superconductivity but also explores a high-temperature platform for Majorana fermions.

This paper addresses the problem of target tracking and circumnavigation control for a bearing-only multi-Unmanned Aerial Vehicle (UAV) system. First, using the bearing measurements, an adaptive algorithm in the form of a Proportional Integral (PI) controller is developed to estimate the target state. Subsequently, a distributed circumnavigation control protocol is established to evenly encircle the target. Then, we use the local information from each UAV in the network to calculate the relative position of the target, and further enhance the accuracy of estimation and circumnavigation algorithms by employing a Kalman filter. Finally, numerical simulation experiments are conducted to validate the effectiveness of the proposed tracking control algorithm.

Abstract Determining the pairing symmetry of single-layer FeSe on SrTiO3 is the key to understanding the enhanced pairing mechanism. It also guides the search for superconductors with high transition temperatures. Despite considerable efforts, it remains controversial whether the symmetry is the sign-preserving s- or the sign-changing s ±-wave. Here, we investigate the pairing symmetry of single-layer FeSe from a topological point of view. Using low-temperature scanning tunneling microscopy/spectroscopy, we systematically characterize the superconducting states at edges and corners of single-layer FeSe. The tunneling spectra collected at edges and corners show a full energy gap and a substantial dip, respectively, suggesting the absence of topologically non-trivial edge and corner modes. According to our theoretical calculations, these spectroscopic features can be considered as strong evidence for the sign-preserving s-wave pairing in single-layer FeSe.

Summary Coordination control of multiple autonomous underwater vehicles (AUVs) has attracted considerable attention owing to its widespread applications in deep‐sea exploration, marine environment monitoring, regional searches, and detector recovery. In addition, finite‐time control theory is applied to ensure that the system achieves its control goal as soon as possible. To the authors' knowledge, few studies have systematically summarized the finite‐time coordination control of multiple AUV systems. Thus this review aims to systematically and completely introduce the research progress into the coordination control methods for multi‐AUV systems and their combination with finite‐time theory. The primary areas of focus are the research significance, present state, and prospects of coordination control and finite‐time control theory in multiple AUV systems, as well as their applications.

Abstract The recently discovered kagome metals AV3Sb5 (A = Cs, Rb, K) exhibit a variety of intriguing phenomena, such as a charge density wave (CDW) with time-reversal symmetry breaking and possible unconventional superconductivity. Here, we report a rare non-monotonic evolution of the CDW temperature (T CDW) with the reduction of flake thickness approaching the atomic limit, and the superconducting transition temperature (T c) features an inverse variation with T CDW. T CDW initially decreases to a minimum value of 72 K at 27 layers and then increases abruptly, reaching a record-high value of 120 K at 5 layers. Raman scattering measurements reveal a weakened electron-phonon coupling with the reduction of sample thickness, suggesting that a crossover from electron-phonon coupling to dominantly electronic interactions could account for the non-monotonic thickness dependence of T CDW. Our work demonstrates the novel effects of dimension reduction and carrier doping on quantum states in thin flakes and provides crucial insights into the complex mechanism of the CDW order in the family of AV3Sb5 kagome metals.

This paper presents an adaptive learning structure based on neural networks (NNs) to solve the optimal robust control problem for nonlinear continuous-time systems with unknown dynamics and disturbances. First, a system identifier is introduced to approximate the unknown system matrices and disturbances with the help of NNs and parameter estimation techniques. To obtain the optimal solution of the optimal robust control problem, a critic learning control structure is proposed to compute the approximate controller. Unlike existing identifier-critic NNs learning control methods, novel adaptive tuning laws based on Kreisselmeier’s regressor extension and mixing technique are designed to estimate the unknown parameters of the two NNs under relaxed persistence of excitation conditions. Furthermore, theoretical analysis is also given to prove the significant relaxation of the proposed convergence conditions. Finally, effectiveness of the proposed learning approach is demonstrated via a simulation study.

This article investigates the differential privacy of the initial state for nabla discrete fractional-order dynamic systems. A novel differentially private Gaussian mechanism is developed which enhances the system’s security by injecting random noise into the output state. Since the existence of random noise gives rise to the difficulty of analyzing the nabla discrete fractional-order systems, to cope with this challenge, the observability of nabla discrete fractional-order systems is introduced, establishing a connection between observability and differential privacy of initial values. Based on it, the noise magnitude required for ensuring differential privacy is determined by utilizing the observability Gramian matrix of systems. Furthermore, an optimal Gaussian noise distribution that maximizes algorithmic performance while simultaneously ensuring differential privacy is formulated. Finally, a numerical simulation is provided to validate the effectiveness of the theoretical analysis.

This paper proposes an adaptive distributed hybrid control approach to investigate the output containment tracking problem of heterogeneous wide-area networks with intermittent communication. First, a clustered network is modeled for a wide-area scenario. An aperiodic intermittent communication mechanism is exerted on the clusters such that clusters only communicate through leaders. Second, in order to remove the assumption that each follower must know the system matrix of the leaders and achieve output containment, a distributed adaptive hybrid control strategy is proposed for each agent under the internal model and adaptive estimation mechanism. Third, sufficient conditions based on average dwell-time are provided for the output containment achievement using a Lyapunov function method, from which the exponential stability of the closed-loop system is analyzed. Finally, simulation results are presented to demonstrate the effectiveness of the proposed adaptive distributed intermittent control strategy.

This paper provides a survey of recent research progress in mathematical modeling and distributed control of wide-area networks. Firstly, the modeling is introduced for two types of wide-area networks, i.e., coopetitive networks and cooperative networks, with the help of algebraic graph theory. Particularly, bipartite network topologies and cluster network topologies are introduced for coopetitive networks. With respect to cooperative networks, an intermittent clustered network modeling is presented. Then, some classical distributed control strategies are reviewed for wide-area networks to ensure some desired collective behaviors, such as consensus (or synchronization), bipartite consensus (or polarization), and cluster consensus (or fragmentation). Finally, some conclusions and future directions are summarized.

The impact of the charge density wave (CDW) state to the electronic structure in the Kagome superconductors AV3Sb5 remains unclear. Here, the authors observe CDW-induced Fermi surface reconstruction with a strongly anisotropic CDW gap and signatures of the electron-phonon coupling for all V-derived bands.

The evolution of superconductivity in LiFeAs with respect to pressure or strain remains elusive. Here, the authors observe different response of superconducting states due to different orientations of local wrinkles on the surface of LiFeAs.

The series elastic actuator (SEA) is generally used as the torque source of the exoskeleton robot for human–robot interaction (HRI). In this paper, an impedance control method for lower limb exoskeleton robots driven by SEA is presented. First, considering the low-frequency vibrations generated by the lower limb exoskeleton robot during walking, the displacement generated by the robot is regarded as an external disturbance to the SEA motor. An SEA structure with negative stiffness structure (NSS) is designed to achieve vibration isolation in the low-frequency excitation region. Second, the dynamics model of the SEA-driven exoskeleton robot system is proposed, and the impedance control strategy is integrated into the proposed system. In addition, the numerical responses of the vibration-isolation system in both time and frequency domains are given, and the designed NSS is designed to achieve vibration isolation. The amplitude-frequency responses of the system are obtained. The harmonic balance (HB) method is used to give the analytical solution of the designed negative-stiffness isolation system, and the effects of different characteristic parameters on the isolation system are analyzed. Moreover, the stability of the SEA-driven exoskeleton impedance control system is demonstrated using the Lyapunov method. Finally, numerical simulations are carried out in order to show the effectiveness of the control method.

CAPTCHA, or Completely Automated Public Turing Tests to Tell Computers and Humans Apart, is a common mechanism used to protect commercial accounts from malicious computer bots, and the most widely used scheme is text-based CAPTCHA. In recent years, newly emerged deep learning techniques have achieved high accuracy and speed in attacking text-based CAPTCHAs. However, most of the existing attacks have various disadvantages, the attack process made high complexity or manually collecting and labeling a large number of samples to train a deep learning recognition model is time-consuming and expensive. In this paper, we propose a transfer learning-based approach that greatly reduces the attack complexity and the cost of labeling samples, specifically, by pre-training the model with randomly generated samples and fine-tuning the pre-trained model with a small number of real-world samples. To evaluate our attack, we tested 25 online CAPTCHAs achieving success rates ranging from 36.3% to 96.9%. To further explore the effect of the training sample characteristics on the attack accuracy, we elaborately imitate some samples and apply a generative adversarial network to refine the samples, sequentially we use these two kinds of generated samples to pre-train the models, respectively. The experimental results demonstrate that the similarity between randomly generated samples and elaborately imitated samples has a negligible impact on the attack accuracy. Instead, transfer learning is the key factor; it reduces the cost of data preparation while preserving the model's attack accuracy.

Maximizing network coverage is very important for heterogeneous directional sensor networks (HDSNs). HDSNs consist of directional sensor nodes with different parameters in terms of the sensing radius, the communication radius and the angle of view. After the initial deployment of the HDSNs, coverage problems occur, such as overlapped areas and holes in the coverage, which are not covered by any one of the sensor nodes. To solve these coverage problems, motility and mobility are often utilized. Motility means the ability to adjust the working direction of the nodes, while mobility presents the physical movement of the nodes. The coverage problem that we solved in this paper is characterized by the heterogeneity of the directional sensor nodes in terms of the sensing radius, the field of angle, the motility, the mobility, and the communication radius. A two-phase algorithm was proposed to solve the coverage optimization problem of the HDSNs. In the first phase of the proposed algorithm, a stepwise method was used to adjust the working direction of the nodes; in the second phase of the proposed algorithm, a virtual force-directed self-adaptive differential evolution algorithm was proposed to achieve a tradeoff between the coverage and the energy consumption. Extensive simulation experiments were performed to demonstrate the effectiveness of our proposed algorithm over alternative algorithms in terms of the coverage rate and energy consumption.

This paper reviews recent progress in model identification-based learning and optimal control and its applications to multi-agent systems (MASs). First, a class of learning-based optimal control method, namely adaptive dynamic programming (ADP), is introduced, and the existing results using ADP methods to solve optimal control problems are reviewed. Then, this paper investigates various kinds of model identification methods and analyzes the feasibility of combining the model identification method with the ADP method to solve optimal control of unknown systems. In addition, this paper expounds the current applications of model identification-based ADP methods in the fields of single-agent systems (SASs) and MASs. Finally, some conclusions and some future directions are presented.

Motivated by recent progress in the superconductivity nonreciprocal phenomena, we study the general theory of Josephson diodes. The central ingredient for Josephson diodes is the asymmetric proximity process inside the tunneling barrier. From the symmetry breaking point of view, there are two types of Josephson diodes: inversion breaking and time-reversal breaking. For the inversion breaking case, applying voltage bias could effectively tune the proximity process like the voltage-dependent Rashba coupling or electric polarization giving rise to I_{c}(V)≠I_{c}(-V) and I_{r+}≠I_{r-}. For the time-reversal breaking case, the current flow could adjust the internal time-reversal breaking field like magnetism or time-reversal breaking electron-electron pairing, which leads to I_{c+}≠I_{c-}. All these results provide a complete understanding and the general principles of realizing Josephson diodes, especially the recently found NbSe_{2}/Nb_{3}Br_{8}/NbSe_{2} Josephson diodes.

Summary: A significant manifestation of interplay of superconductivity and charge density wave, spin density wave, or magnetism is a dome-like superconducting critical temperature (Tc) in cuprate, iron-based, and heavy Fermion superconductors. Pesudogap, quantum critical point, and strange metals emerge in different doping ranges. Exploring dome-like Tc in new superconductors is of interest to detect emergent effects. Here we report the superconductivity in a new layered Cu-based compound RE2Cu5As3O2 (RE = La, Pr, Nd), in which the Tc exhibits dome-like variation with a maximum Tc of 2.5, 1.2, and 1.0 K with substitution of Cu by large amount of Ni ions. Simultaneously, the structural parameters like As-As bond length and c/a ratio exhibit unusual variations as the Ni-doping level goes through the optimal value. The robustness of superconductivity, up to 60% of Ni doping, reveals the unexpected impurity effect on inducing and enhancing superconductivity in these novel layered materials. : Phase Transitions; Superconductivity; Structural Property of Condensed Matter Subject Areas: Phase Transitions, Superconductivity, Structural Property of Condensed Matter

Recently, the alternating direction method of multipliers (ADMM) has been used effectively to solve the multi-agent unconstrained optimization problems, where the objective function is the sum of privately known local objective functions of agents. In this paper, first, with the help of the edge-node incidence matrix, an unconstrained optimization problem is transformed into an equivalent optimization problem with only equality constraint and, thus, can be dealt with the ADMM conveniently. Second, a novel distributed inexact consensus ADMM is proposed to enable the agents to reach consensus on the optimal solution of the optimization problem. At the same time, the analysis of the linear convergence of the proposed algorithm is also provided under some mild conditions. Finally, some simulation results are presented to demonstrate the better effectiveness of the proposed algorithm than the standard consensus-based ADMM algorithm.

More recently, lower limb exoskeletons (LLE) have gained considerable interests in strength augmentation, rehabilitation, and walking assistance scenarios. For walking assistance, the LLE is expected to control the affected leg to track the unaffected leg's motion naturally. A critical issue in this scenario is that the exoskeleton system needs to deal with unpredictable disturbance from the patient, and the controller has the ability to adapt to different wearers. To this end, a novel data-driven optimal control (DDOC) strategy is proposed to adapt different hemiplegic patients with unpredictable disturbances. The interaction relation between two lower limbs of LLE and the leg of patient's unaffected side are modeled in the context of leader-follower framework. Then, the walking assistance control problem is transformed into an optimal control problem. A policy iteration (PI) algorithm is utilized to obtain the optimal controller. To improve the online adaptation to different patients, an actor-critic neural network (AC/NN) structure of the reinforcement learning (RL) is employed to learn the optimal controller on the basis of PI algorithm. Finally, experiments both on a simulation environment and a real LLE system are conducted to verify the effectiveness of the proposed walking assistance control method.

In the presence of both space and time reversal symmetries, an s-wave A_{1g} superconducting state is usually topologically trivial. Here, we demonstrate that an exception can take place in a type of nonsymmorphic lattice structure. We specify the demonstration in a time reversal invariant system with a centrosymmetric space group P4/nmm, the symmetry that governs iron-based superconductors, by showing the existence of a second-order topological state protected by a mirror symmetry. The topological superconductivity is featured by 2Z degenerate Dirac cones on the (10) edge and Z pairs of Majorana modes at the intersection between the (11) and (11[over ¯]) edges. The topological invariance and Fermi surface criterion for the topological state are provided. Moreover, we point out that the previously proposed s-wave state in iron-based superconductors, which features a sign-changed superconducting order parameter between two electron pockets, is such a topological state. Thus, these results not only open a new route to pursue topological superconductivity, but also establish a measurable quantity to settle one long-lasting debate on the pairing nature of iron-based superconductors.

In this paper, we present a distributed algorithm based on an alternating direction method of multipliers (ADMM), which is applied to solve economic dispatch problems (EDPs). First, with the help of two indicator functions, an EDP is transformed to an equivalent optimization problem with only equality constraint and thus can be dealt with ADMM. Second, a centralized algorithm is proposed to solve the transformed EDP, and furthermore, a distributed algorithm is designed with the help of finite-time average-consensus control strategy. Compared with the existing algorithms for EDP, the distributed algorithm can solve the economic dispatch problem on directed graphs. Moreover, the proposed algorithms can ensure that the generator constraints are satisfied during the whole computation process. Finally, some simulation results are also provided to demonstrate the effectiveness of the proposed algorithms.

Nontrivial topology and unconventional pairing are two central guiding principles in the contemporary search for and analysis of superconducting materials and heterostructure compounds. Previously, a topological superconductor has been predominantly conceived to result from a topologically nontrivial band subject to an intrinsic or external superconducting proximity effect. Here, we propose a new class of topological superconductors that are uniquely induced by unconventional pairing. They exhibit a boundary-obstructed higher-order topological character and, depending on their dimensionality, feature unprecedently robust Majorana bound states or hinge modes protected by chiral symmetry. We predict the 112 family of iron pnictides, such as Ca_{1-x}La_{x}FeAs_{2}, to be highly suited material candidates for our proposal, which can be tested by edge spectroscopy. Because of the boundary obstruction, the topologically nontrivial feature of the 112 pnictides does not reveal itself for a bulk-only torus band analysis without boundaries, and as such, it had evaded previous investigations. Our proposal not only opens a new arena for highly stable Majorana modes in high-temperature superconductors but also provides the smoking gun for extended s-wave order in the iron pnictides.

The iron-based superconductor FeSe has attracted much recent attention because of its simple crystal structure, distinct electronic structure, and rich physics exhibited by itself and its derivatives. Determination of its intrinsic electronic structure is crucial to understanding its physical properties and superconductivity mechanism. Both theoretical and experimental studies so far have provided a picture that FeSe consists of one holelike Fermi surface around the Brillouin zone center in its nematic state. Here we report direct observation of two holelike Fermi surface sheets around the Brillouin zone center, and the splitting of the associated bands, in the nematic state of FeSe by taking high-resolution laser-based angle-resolved photoemission measurements. These results indicate that, in addition to nematic order and spin-orbit coupling, there is an additional order in FeSe that breaks either inversion or time-reversal symmetries. The new Fermi surface topology asks for reexamination of the existing theoretical and experimental understanding of FeSe and stimulates further efforts to identify the origin of the hidden order in its nematic state.

The iron-based superconductors are characterized by multiple-orbital physics where all the five Fe 3d orbitals get involved. The multiple-orbital nature gives rise to various novel phenomena like orbital-selective Mott transition, nematicity, and orbital fluctuation that provide a new route for realizing superconductivity. The complexity of multiple-orbital physics also requires us to disentangle the relationship between orbital, spin, and nematicity, and to identify dominant orbital ingredients that dictate superconductivity. The bulk FeSe superconductor provides an ideal platform to address these issues because of its simple crystal structure and unique coexistence of superconductivity and nematicity. However, the orbital nature of the low-energy electronic excitations and its relation to the superconducting gap remain controversial. Here, we report direct observation of the highly anisotropic Fermi surface and extremely anisotropic superconducting gap in the nematic state of the FeSe superconductor by high-resolution laser-based angle-resolved photoemission measurements. We find that the low-energy excitations of the entire hole pocket at the Brillouin zone center are dominated by the single d_{xz} orbital. The superconducting gap exhibits an anticorrelation relation with the d_{xz} spectral weight near the Fermi level; i.e., the gap size minimum (maximum) corresponds to the maximum (minimum) of the d_{xz} spectral weight along the Fermi surface. These observations provide new insights in understanding the orbital origin of the extremely anisotropic superconducting gap in the FeSe superconductor and the relation between nematicity and superconductivity in the iron-based superconductors.

Cooperation and competition are two typical interactional relationships in natural and engineering networked systems. Some complex behaviors can emerge through local interactions within the networked systems. This paper focuses on the coexistence of competition and cooperation (i.e., coopetition) at the network level and, simultaneously, the collective dynamics on such coopetition networks. The coopetition network is represented by a directed signed graph. The collective dynamics on the coopetition network is described by a multiagent system. We investigate two bipartite consensus strategies for multiagent systems such that all the agents converge to a final state characterized by identical modulus but opposite sign. Under a weak connectivity assumption that the coopetition network has a spanning tree, some sufficient conditions are derived for bipartite consensus of multiagent systems with the help of a structural balance theory. Finally, simulation results are provided to demonstrate the bipartite consensus formation.

Event-driven control scheduling strategies for multiagent systems play a key role in future use of embedded microprocessors of limited resources that gather information and actuate the agent control updates. In this paper, a distributed event-driven consensus problem is considered for a multi-agent system with second-order dynamics. Firstly, two kinds of event-driven control laws are, respectively, designed for both leaderless and leader-follower systems. Then, the input-to-state stability of the closed-loop multi-agent system with the proposed event-driven consensus control is analyzed and the bound of the inter-event times is ensured. Finally, some numerical examples are presented to validate the proposed event-driven consensus control.

Cuprates and iron-based superconductors are two classes of unconventional high-T_{c} superconductors based on 3d transition elements. Recently, two principles, the correspondence principle and the magnetic selective pairing rule, have emerged to unify their high-T_{c} superconducting mechanisms. These principles strongly regulate electronic structures that can host high-T_{c} superconductivity. Guided by these principles, here, we propose high-T_{c} superconducting candidates that are formed by cation-anion trigonal bipyramidal complexes with a d^{7} filling configuration on the cation ions. Their superconducting states are expected to be dominated by the d_{xy}±id_{x^{2}−y^{2}} pairing symmetry.

We show that topological states are often developed in two-dimensional semimetals with quadratic band crossing points (BCPs) by electron–electron interactions. To illustrate this, we construct a concrete model with the BCP on an extended Lieb lattice and investigate the interaction-driven topological instabilities. We find that the BCP is marginally unstable against infinitesimal repulsions. Depending on the interaction strengths, topological quantum anomalous/spin Hall, charge nematic, and nematic-spin-nematic phases develop separately. Possible physical realizations of quadratic BCPs are provided.

A distinct electronic structure was observed in the single-layer FeSe which shows surprisingly high-temperature superconductivity over 65 K. Here, we demonstrate that the electronic structure can be explained by the effective strain effect due to substrates. More importantly, we find that this electronic structure can be tuned into robust topological phases from a topologically trivial metallic phase by the spin-orbital interaction and couplings to substrates. The topological phase is robust against any perturbations that preserve the time-reversal symmetry. Our study suggests that nontrivial topology and high-T_{c} superconductivity can be intertwined in the single FeSe layer to search novel physics.

Parity is a fundamental quantum number used to classify a state of matter. Materials rarely possess ground states with odd parity. We show that the superconducting state in iron-based superconductors is classified as an odd-parity s-wave spin-singlet pairing state in a single trilayer FeAs/Se, the building block of the materials. In a low-energy effective model constructed on the Fe square bipartite lattice, the superconducting order parameter in this state is a combination of an s-wave normal pairing between two sublattices and an s-wave η pairing within the sublattices. The state has a fingerprint with a real-space sign inversion between the top and bottom As/Se layers. The results suggest that iron-based superconductors are a new quantum state of matter, and the measurement of the odd parity can help to establish high-temperature superconducting mechanisms.

Although iron-based superconductors are multiorbital systems with complicated band structures, we demonstrate that the low-energy physics which is responsible for their high-T_{c} superconductivity is essentially governed by an effective two-orbital Hamiltonian near half filling. This underlying electronic structure is protected by the S_{4} symmetry. With repulsive or strong next-nearest-neighbor antiferromagnetic exchange interactions, the model results in a robust A_{1g} s-wave pairing which can be mapped exactly to the d-wave pairing observed in cuprates. The classification of the superconducting (SC) states according to the S_{4} symmetry leads to a natural prediction of the existence of two different phases, named the A and B phases. In the B phase, the superconducting order has an overall sign change along the c axis between the top and bottom As (or Se) planes in a single Fe-As (or Fe-Se) trilayer structure, the common building block of iron-based superconductors. The sign change is analogous to the sign change in the d-wave superconducting state of cuprates upon 90° rotation. Our derivation provides a unified understanding of iron pnictides and iron chalcogenides, and suggests that cuprates and iron-based superconductors share an identical high-T_{c} superconducting mechanism.

Using self-consistent mean-field and functional renormalization-group approaches, we show that s-wave pairing symmetry is robust in the heavily electron-doped iron chalcogenides AFe_{2-x}Se_{2}, where A=K,​Cs. Recent neutron scattering experiments suggest that the effective nearest-neighbor spin exchange may be ferromagnetic in chalcogenides. This is different from the iron pnictides, where the nearest-neighbor magnetic exchange coupling is believed to be antiferromagnetic and leads to strong competition between s-wave and d-wave pairing in the electron-overdoped region. Our finding of a robust s-wave pairing in (K,​Cs)Fe_{2-x}Se_{2} differs from the d-wave pairing result obtained by other theories where nonlocal bare interaction terms and the next-to-nearest-neighbor J_{2} term are underestimated. Detecting the pairing symmetry in (K,​Cs)Fe_{2-x}Se_{2} may hence provide important insights regarding the mechanism of superconducting pairing in iron-based superconductors.