Anomalous State Research Articles

Methods of anomaly state detection for power systems based on bilateral cyber‐physical information

Cyberattacks have emerged as novel threats to modern power systems. By exploiting the vulnerabilities of insecure devices, an attacker can inject viruses to lurk and collect system conditions through sniffing and then launch well-designed attacks. Collaboratively applying bilateral cyber-physical information can help to detect anomalous system states caused by sniffing, which can isolate virus impacts on the cyber side and ensure the stable operation of power systems. Here, a dynamic weight ensemble isolation forest algorithm is proposed to mine anomaly system states utilizing bilateral information based on the hypothesis that the fused cyber-physical system state under assault has the shortest average path length in a constructed random forest. In addition, the proposed algorithm is able to realize improved performance in power system anomaly status mining and adapt to constantly changing power systems. The method is verified by simulations on a co-simulation platform. The results show that the method outperforms other anomaly detection methods.

A Statistical Feature-Based Anomaly Detection Method for PFC Using Canonical Correlation Analysis

Power factor correction (PFC) converters are widely used in power systems. The anomalous state of a PFC converter can develop into the complete or partial loss of the electric system. In some industrial applications, such as wind power generation and photovoltaic power generation, there is a fluctuation in the input voltage of the PFC converter, which brings great obstacles in anomaly detection. In order to effectively recognize an anomalous state, especially when the input voltage is unstable, a statistical feature-based anomaly detection method using canonical correlation analysis (CCA) is proposed. Firstly, statistical features are used to enhance the difference between the normal state and anomalous state. Then, the proposed anomaly detection method focuses on the correlation between the input voltage and the output voltage, so even if there is a fluctuation in the input voltage, the anomaly states can be detected precisely. The experimental results show the effectiveness of the method.

Quantum oscillation phenomena in low-dimensional superconductors

<sec>Low-dimensional superconductor serves as an excellent platform for investigating emergent superconducting quantum oscillation phenomena. The low-dimensional natures of these materials, originating from the finite size which is comparable with the superconducting coherence length, indicate that the corresponding physical properties will be constrained by quantum confinement effects. Importantly, some of the frontiers and hot issues in low-dimensional superconductors, including the anomalous metal state during the superconductor-insulator transition, spin-triplet pairing mechanism in superconductors, thermal-excited and electrical current-excited vortex dynamics in superconductors, and the “charge-vortex duality” in quantum dot materials and superconducting nanowires, are strongly correlated with the superconducting quantum oscillation effects. In recent years, all the above-mentioned topics have achieved breakthroughs based on the studies of superconducting quantum oscillation effects in low-dimensional superconductors. Generally, the periodicity and amplitude of the oscillation can clearly demonstrate the relation between the geometric structure of superconductors and various superconducting mechanisms. In particular, superconducting quantum oscillation phenomena are always correlated with the quantization of magnetic fluxoids and their dynamics, the pairing mechanism of superconducting electrons, and the excitation and fluctuation of superconducting systems.</sec><sec>In this review article, three types of typical superconducting quantum oscillation effects observed in low-dimensional superconductors will be discussed from the aspects of research methods, theoretical expectations, and experimental results. a) The Little-Parks effect is the superconducting version of the Aharonov-Bohm effect, whose phase, amplitude and period are all helpful in studying superconductivity: the phase reflects the pairing mechanism in superconductors, the amplitude can be used for investigating the anomalous metal state, and the period provides the information about the sample geometry. b) The vortex motion effect is excited by thermal fluctuation or electrical current, and the corresponding oscillation phenomena show distinct temperature-dependent amplitudes compared with the Little-Parks effect. c) The Weber blockade effect originates from the magnetic flux moving across the superconducting nanowire, and such an effect provides a unique nonmonotonic critical current <inline-formula><tex-math id="M1">\begin{document}$ {I}_{\mathrm{C}} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="12-20212289_M1.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="12-20212289_M1.png"/></alternatives></inline-formula> under a magnetic field in <inline-formula><tex-math id="M2">\begin{document}$I\text{-}V$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="12-20212289_M2.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="12-20212289_M2.png"/></alternatives></inline-formula> characteristics. The prospects of the above-mentioned quantum oscillation effects of low-dimensional superconductors for applications are also discussed at the end of this review, including quantum computing, device physics and low-temperature physics.</sec>

ALGAN: Anomaly Detection by Generating Pseudo Anomalous Data via Latent Variables

In many anomaly detection tasks, where anomalous data rarely appear and are difficult to collect, training using only normal data is important. Although it is possible to manually create anomalous data using prior knowledge, they may be subject to user bias. In this paper, we propose an Anomalous Latent variable Generative Adversarial Network (ALGAN) in which the GAN generator produces pseudo-anomalous data as well as fake-normal data, whereas the discriminator is trained to distinguish between normal and pseudo-anomalous data. This differs from the standard GAN discriminator, which specializes in classifying two similar classes. The training dataset contains only normal data; the latent variables are introduced in anomalous states and are input into the generator to produce diverse pseudo-anomalous data. We compared the performance of ALGAN with other existing methods on the MVTec-AD, Magnetic Tile Defects, and COIL-100 datasets. The experimental results showed that ALGAN exhibited an AUROC comparable to those of state-of-the-art methods while achieving a much faster prediction time.

ПРОГНОЗИРОВАНИЕ ПРОФИЛЯ ФУНКЦИОНИРОВАНИЯ КОМПЬЮТЕРНОЙ СИСТЕМЫ НА ОСНОВЕ МНОГОЗНАЧНЫХ ЗАКОНОМЕРНОСТЕЙ

Purpose of work is to create a new algorithm for predicting anomalous states of computer systems (CS) using the mathematical apparatus of multivalued dependencies (Multivalued Dependencies Prognosus Algorithm, MDPA), which are categorical concepts. The research method is the analysis of historical data using the mathematical apparatus of multivalued dependencies. Objects of study are theoretical and practical issues of solving and visualizing information security problems. Results of the study. A methodology and algorithm for predicting the state of CS have been developed. The boundaries of the input parameters of the algorithm are derived and justified. The boundaries of the input parameters need to be pre-configured for the correct generation of the prognosis. A software implementation of the proposed prediction algorithm has been developed. The efficiency of the algorithm has been tested on real experimental data. A spatial analysis of the prediction results was carried out. The main disadvantage of the proposed algorithm is the need to fine-tune the input parameters for each set of “historical data”. Scientific significance. The scope of application of multivalued dependencies has been expanded; a new algorithm for predicting anomalous states of CS, which are categorical concepts, has been proposed. The developed prediction algorithm can be generalized to any subject area containing historical data of any type

Probing long-range current-carrying edge modes by two quantum point contacts

The origin of anomalous current-carrying edge states in quasi-two-dimensional quantum samples with an insulating interior is currently mysterious. We propose to address this issue using a hybrid setup, an interferometric phase-sensitive configuration of two independent scanning probe tips, normal and superconducting, able to realize the quantum interference effect of quasiparticle currents moving in different directions along the metallic-like one-dimensional near-boundary channels. To simulate the dissipationless edge currents, we consider a quantum material with a simple Corbino disk geometry and analyze how the differential conductance spectrum depends on the distance between the two tips, the applied voltage bias, and the presence of a magnetic field. An essential difference between classical and quantum expectations should clarify the enigmatic origin of the long-range conducting modes observed in different materials at low temperatures. Strong dependence on the applied magnetic field can be useful for practical implementation of the quantum effects associated with the phase difference of electron wave functions in the ring geometry.

Topology of a parity–time symmetric non-Hermitian rhombic lattice

We investigate the topological properties of a trimerized parity–time () symmetric non-Hermitian rhombic lattice. Although the system is -symmetric, the topology is not inherited from the Hermitian lattice; in contrast, the topology can be altered by the non-Hermiticity and depends on the couplings between the sublattices. The bulk–boundary correspondence is valid and the Bloch bulk captures the band topology. Topological edge states present in the two band gaps and are predicted from the global Zak phase obtained through the Wilson loop approach. In addition, the anomalous edge states compactly localize within two diamond plaquettes at the boundaries when all bands are flat at the exceptional point of the lattice. Our findings reveal the topological properties of the -symmetric non-Hermitian rhombic lattice and shed light on the investigation of multi-band non-Hermitian topological phases.

Forecasting of Computer Network Anomalous States Based on Sequential Pattern Analysis of “Historical Data”

Forecasting of Computer Network Anomalous States Based on Sequential Pattern Analysis of “Historical Data”

Field-induced anomalous magnetic state beyond the magnetically ordered state in the slightly distorted triangular S=12 rare-earth antiferromagnet CeZn3P3

Magnetic properties of ${\mathrm{CeZn}}_{3}{\mathrm{P}}_{3}$, which has been believed to have the same hexagonal ${\mathrm{ScAl}}_{3}{\mathrm{C}}_{3}$-type crystal structure as that of a spin dimer system of ${\mathrm{YbAl}}_{3}{\mathrm{C}}_{3}$ at room temperature, have been investigated by magnetization, magnetostriction, specific heat ($C$), and magnetocaloric effect measurements. In this research, we have found that ${\mathrm{CeZn}}_{3}{\mathrm{P}}_{3}$ certainly has a slightly deformed crystal structure from the hexagonal one even at room temperature, which is in contrast to the structural phase transition of ${\mathrm{YbAl}}_{3}{\mathrm{C}}_{3}$ occuring at around 80 K, although the very slight deformation along the $c$ plane, i.e., slightly deformed triangular lattice, and the formation of the multidomain structure are common to both compounds. ${\mathrm{CeZn}}_{3}{\mathrm{P}}_{3}$ is thought to maintain its deformed structure from a high-temperature region above room temperature to an extremely low-temperature region and shows a magnetic order below ${T}_{\mathrm{N}}=0.8$ K. The analysis of the temperature dependence of the magnetic susceptibility ($\ensuremath{\chi}$) and $C$ has revealed that a Kramers doublet ground state with an easy-plane type anisotropy on the $c$ plane is well isolated from the excited states by the crystal field splitting energy of more than 300 K. Above ${T}_{\mathrm{N}}, \ensuremath{\chi}$ makes a broad peak at around 2 K, which certainly originates from the dimer formation due to the slight deformation of the triangular lattice. On the other hand, below ${T}_{\mathrm{N}}$, a magnetic phase diagram reminiscent of a magnetic flower blooming on the $c$ plane was observed, which may have a close relation to a quantum effect of a quasi $S=\frac{1}{2}$ spin system and a contribution of the orbital component. With increasing magnetic field, we have found an anomalous magnetic state beyond the usual magnetically ordered state, where $C/T$ is anomalously enhanced. This anomalous magnetic state is similar to that observed in ${\mathrm{YbAl}}_{3}{\mathrm{C}}_{3}$ induced by the field, although the magnetic ground state in ${\mathrm{YbAl}}_{3}{\mathrm{C}}_{3}$ is a nonmagnetic dimer state different from the normal magnetically ordered state in ${\mathrm{CeZn}}_{3}{\mathrm{P}}_{3}$.

Minimal model for Hilbert space fragmentation with local constraints

Motivated by previous works on a Floquet version of the PXP model [Mukherjee {\it et al.} Phys. Rev. B 102, 075123 (2020), Mukherjee {\it et al.} Phys. Rev. B 101, 245107 (2020)], we study a one-dimensional spin-$1/2$ lattice model with three-spin interactions in the same constrained Hilbert space (where all configurations with two adjacent $S^z=\uparrow$ spins are excluded). We show that this model possesses an extensive fragmentation of the Hilbert space which leads to a breakdown of thermalization upon unitary evolution starting from a large class of simple initial states. Despite the non-integrable nature of the Hamiltonian, many of its high-energy eigenstates admit a quasiparticle description. A class of these, which we dub as "bubble eigenstates", have integer eigenvalues (including mid-spectrum zero modes) and strictly localized quasiparticles while another class contains mobile quasiparticles leading to a dispersion in momentum space. Other anomalous eigenstates that arise due to a {\it secondary} fragmentation mechanism, including those that lead to flat bands in momentum space due to destructive quantum interference, are also discussed. The consequences of adding a (non-commuting) staggered magnetic field and a PXP term respectively to this model, where the former preserves the Hilbert space fragmentation while the latter destroys it, are discussed. A Floquet version with time-dependent staggered field also evades thermalization with additional features like freezing of exponentially many states at special drive frequencies. Finally, we map the model to a $U(1)$ lattice gauge theory coupled to dynamical fermions and discuss the interpretation of some of these anomalous states in this language. A class of gauge-invariant states show reduced mobility of the elementary charged excitations with only certain charge-neutral objects being mobile suggesting a connection to fractons.

Super-random states in vehicular traffic — Detection & explanation

This article deals with specific states of traffic flow on a two-lane freeway, in which statistical fluctuations of microscopic quantities (inter-vehicle gaps) are significantly higher than in systems with absolutely random events (Poisson systems). These anomalous states (super-random) are detected in empirical traffic data, specifically in the fast lane at traffic densities up to 25 vehicles per kilometer. The origin of these states is then explained mathematically (using the theory of balance particle systems and tools of random matrix theory), physically (by means of an one-dimensional particle gas subjected to local perturbations caused by overtaking cars) and empirically (using an analogy with phenomena observed in photon counting experiments). In the article we show that overtaking maneuvers, when vehicles from a slow lane are injected into a fast-lane stream of faster moving vehicles, disrupt a local balance in microstructure of fast-lane stream and cause atypical arrangement of vehicular positions, that is very rare, generally. With help of original numerical model we demonstrate that the anomalous states detected are identical to equilibrium states formed in a stochastic particle gas with a potential containing, in addition to a repulsive component, also an attractive component.

Tunable Berry curvature and transport crossover in topological Dirac semimetal KZnBi

Topological Dirac semimetals have emerged as a platform to engineer Berry curvature with time-reversal symmetry breaking, which allows to access diverse quantum states in a single material system. It is of interest to realize such diversity in Dirac semimetals that provides insight on correlation between Berry curvature and quantum transport phenomena. Here, we report the transition between anomalous Hall and chiral fermion states in three-dimensional topological Dirac semimetal KZnBi, which is demonstrated by tuning the direction and flux of Berry curvature. Angle-dependent magneto-transport measurements show that both anomalous Hall resistance and positive magnetoresistance are maximized at 0° between net Berry curvature and rotational axis. We find that the unexpected crossover of anomalous Hall resistance and negative magnetoresistance suddenly occurs when the angle reaches to ~70°, indicating that Berry curvature strongly correlates with quantum transports of Dirac and chiral fermions. It would be interesting to tune Berry curvature within other quantum phases such as topological superconductivity.

Early detection of lean blowout in a combustor using symbolic analysis of colour images

Recently, lean combustion has been accepted as one of the preferable modes to run both small and large scale energy sectors as it reduces the level of NOx (oxides of nitrogen) emissions. However, ultra-lean combustion is more susceptible to lean blowout (LBO) which significantly reduces engine life and operating reliability. Therefore, early detection of LBO is important so that operator can get sufficient lead time to initiate precautionary actions. The current investigation proposes a novel technique based on the conversion of flame colour matrix into symbolic strings. The generation of symbolic strings is done based on the partitioning of the hue space obtained from transformation of RGB (Red-Green-Blue) to HSV (Hue-Saturation-Value) using uniform partitioning method. The partitions are determined at the reference state and kept fixed for other equivalence ratios (anomalous or non-reference states). Thus, the hue value at each pixel of the image is assigned a symbol depending on its belonging to a particular partition. Thereafter, an array of symbolic state probability vector at reference combustion state is determined based on the probability of pixel hue value being in a particular symbolic state or symbol (number of symbolic states is considered as 8). Also, for other anomalous or non-reference combustion states, symbolic state probability vectors are estimated using the partition formed at the reference state. The difference in symbolic state probability vectors between reference and anomalous combustion states gives the anomaly measure, which is used here to detect the flame blowout. The early increasing trend of anomaly towards the blowout for both premixed and partially premixed flames indicate that the measure can be helpful to detect the approach towards LBO. The estimation of anomaly is shown for using the flame images of different quantities. The random selection of five images from a flame video shows to be very effective in capturing the trend of anomaly which also ensures low computational effort. Thus, the tool based on symbolic colour image analysis (SCIA) may also be helpful in the mitigation of LBO.

Extrinsic and Intrinsic Anomalous Metallic States in Transition Metal Dichalcogenide Ising Superconductors.

The metallic ground state in two-dimensional (2D) superconductors has attracted much attention but is still under intense scrutiny. Especially, the measurements in the ultralow temperature region are challenging for 2D superconductors due to the sensitivity to external perturbations. In this work, the resistance saturation induced by external noise, named as the "extrinsic anomalous metallic state", is observed in 2D transition metal dichalcogenide (TMD) superconductor 4Ha-TaSe2 nanodevices. However, with further decreasing temperature, credible evidence of the intrinsic anomalous metallic state is obtained by adequately filtering external radiation. Our work indicates that, at ultralow temperatures, the anomalous metallic state can be experimentally revealed as the quantum ground state in 2D crystalline TMD superconductors. Besides, Ising superconductivity revealed by ultrahigh in-plane critical field (Bc2∥) going beyond the Pauli paramagnetic limit (Bp) is detected in 4Ha-TaSe2, from the one-unit-cell device to the bulk situation, which might be due to the weak coupling between the TaSe2 submonolayers.

Detection and analysis of real-time anomalies in large-scale complex system

For data-driven anomaly detection, it is difficult to model a prediction model with high accuracy and sensitivity to anomalous states. In order to solve the above problems, this paper proposes an improved multivariate Transfer Entropy method to judge the physical causality between high-dimensional time series. According to the causality, combined with the LSTM (Long Short-Term Memory) model, the CF-LSTM (causality features-LSTM) model is proposed. The CF-LSTM model uses the causality features of the parameter to make predictions. Compared with other models, the CF-LSTM model improves the prediction accuracy and it is sensitive to anomalies. Based on this, an anomaly detection algorithm is proposed. Case analysis based on the actual data shows that the detection precision, recall, and F1-score (a measure of classification problem) of this method are improved compared with other anomaly detection models, which illustrates the effectiveness of this method.

Anomalous nematic state to stripe phase transition driven by in-plane magnetic fields

Anomalous nematic states, recently discovered in ultraclean two-dimensional electron gas, emerge from quantum Hall stripe phases upon further cooling. These states are hallmarked by a local minimum (maximum) in the hard (easy) longitudinal resistance and by an incipient plateau in the Hall resistance in nearly half-filled Landau levels. Here, we demonstrate that a modest in-plane magnetic field, applied either along $\ensuremath{\langle}110\ensuremath{\rangle}$ or $\ensuremath{\langle}1\overline{1}0\ensuremath{\rangle}$ crystal axis of GaAs, destroys anomalous nematic states and restores quantum Hall stripe phases aligned along their native $\ensuremath{\langle}110\ensuremath{\rangle}$ direction. These findings confirm that anomalous nematic states are distinct from other ground states and will assist future theories to identify their origin.

Symmetry analysis of anomalous Floquet topological phases

The topological characterization of nonequilibrium topological matter is highly nontrivial because familiar approaches designed for equilibrium topological phases may not apply. In the presence of crystal symmetry, Floquet topological insulator states cannot be easily distinguished from normal insulators by a set of symmetry eigenvalues at high symmetry points in the Brillouin zone. This work advocates a physically motivated, easy-to-implement approach to enhance the symmetry analysis to distinguish between a variety of Floquet topological phases. Using a two-dimensional inversion-symmetric periodically-driven system as an example, we show that the symmetry eigenvalues for anomalous Floquet topological states, of both first-order and second-order, are the same as for normal atomic insulators. However, the topological states can be distinguished from one another and from normal insulators by inspecting the occurrence of stable symmetry inversion points in their microscopic dynamics. The analysis points to a simple picture for understanding how topological boundary states can coexist with localized bulk states in anomalous Floquet topological phases.

On the anomalous low-resistance state and exceptional Hall component in hard-magnetic Weyl nanoflakes

Magnetic topological materials, which combine magnetism and topology, are expected to host emerging topological states and exotic quantum phenomena. In this study, with the aid of greatly enhanced coercive fields in high-quality nanoflakes of the magnetic Weyl semimetal Co3Sn2S2, we investigate anomalous electronic transport properties that are difficult to reveal in bulk Co3Sn2S2 or other magnetic materials. When the magnetization is antiparallel to the applied magnetic field, the low longitudinal resistance state occurs, which is in sharp contrast to the high resistance state for the parallel case. Meanwhile, an exceptional Hall component that can be up to three times larger than conventional anomalous Hall resistivity is also observed for transverse transport. These anomalous transport behaviors can be further understood by considering nonlinear magnetic textures and the chiral magnetic field associated with Weyl fermions, extending the longitudinal and transverse transport physics and providing novel degrees of freedom in the spintronic applications of emerging topological magnets.

Ранговый классификатор состояний природной среды

An approach to the multivariate classification of the states of natural-technical objects and systems is considered, based on the development of methods for dynamic detection of anomalies in information data flows. The approach is based on an estimate of the statistical discrepancy between the probability distributions of random variables over variably changeable time intervals, as well as an estimate of the probabilities of errors of the first and second kind. The structure of a multichannel software and measurement complex for detecting anomalous states of PTO and PTS is proposed, and the results of model calculations are presented. The use of the multivariate approach allows optimizing the processes of processing, analysis and integration of heterogeneous data, as well as increasing the sensitivity, reliability and efficiency of decisions.

Giant magnetoresistance effect due to the tunneling between quantum anomalous Hall edge states

A recent work predicted the tunneling effect between topological edge states where the tunneling probability is tuned by a transverse electric field [Xu et al., Phys. Rev. Lett. 123, 206801 (2019)]. Here we study this tunneling effect between quantum anomalous Hall edge states under a perpendicular magnetic field. It is shown that the tunneling probability depends exponentially on the magnetic field. We propose a magnetic transistor based on a quantum anomalous Hall ribbon to observe this effect experimentally. Numerical simulations show that the conductance of the device is very sensitive to the strength and direction of the magnetic field. The positive/negative magnetic field results in the on/off state of the transistor. A giant magnetoresistance is found, and the on/off ratio reaches up to greater than 1010 for a long ribbon. These findings should be useful for potential applications in magnetic read heads and magnetic field sensors.