High-performance chiral all-optical OR logic gate based on topological edge states of valley photonic crystal

For all-optical communication and information processing,it is necessary to develop all-optical logic gates based on photonic structures that can directly perform logic operations.All-optical logic gates have been demonstrated based on conventional waveguides and interferometry,as well as photonic crystal structures.Nonetheless,any defects in those structures will introduce high scattering loss,which compromises the fidelity and contrast ratio of the information process.Based on the spin-valley locking effect that can achieve defect-immune unidirectional transmission of topological edge states in valley photonic crystals(VPCs),we propose a high-performance all-optical logic OR gate based on a VPC structure.By tuning the working bandwidth of the two input channels,we prevent interference between the two channels to achieve a stable and high-fidelity output.The transmittance of both channels is higher than 0.8,and a high contrast ratio of 28.8 dB is achieved.Moreover,the chirality of the logic gate originated from the spin-valley locking effect allows using different circularly polarized light as inputs,representing“1”or“0”,which is highly desired in quantum computing.The device’s footprint is 18μm×12μm,allowing high-density on-chip integration.In addition,this design can be experimentally fabricated using current nanofabrication techniques and will have potential applications in optical communication,information processing,and quantum computing.

All-optical controlled-NOT logic gate achieving directional asymmetric transmission based on metasurface doublet

Optical logic gates play important roles in all-optical logic circuits,which lie at the heart of the next-generation optical computing technology.However,the intrinsic contradiction between compactness and robustness hinders the development in this field.Here,we propose a simple design principle that can possess multiple-input-output states according to the incident circular polarization and direction based on the metasurface doublet,which enables controlled-NOT logic gates in infrared region.Therefore,the directional asymmetric electromagnetic transmission can be achieved.As a proof of concept,a spin-dependent Janus metasurface is designed and experimentally verified that four distinct images corresponding to four input states can be captured in the far-field.In addition,since the design method is derived from geometric optics,it can be easily applied to other spectra.We believe that the proposed metasurface doublet may empower many potential applications in chiral imaging,chiroptical spectroscopy and optical computing.

High-efficiency ultra-fast all-optical photonic crystal diode based on the lateral-coupled nonlinear elliptical defect

An all-optical Fano-like diode featuring a nonlinear lateral elliptical micro-cavity and a reflecting column in the photonic crystal waveguide is proposed.The asymmetric micro-cavity is constructed by removing one rod and changing the shape of the lateral rod from a circle to an ellipse.A reflecting pillar is also introduced into the waveguide to construct an F-P cavity with the elliptical defect and enhance the asymmetric transmission for the incident light wave transmitting rightwards and leftwards,respectively.By designing the size of the ellipse and optimizing a reflecting rod at a suitable position,a maximum forward light transmittance of-1.14 dB and a minimum backward transmittance of-57.66 dB are achieved at the working wavelength of 1550.47 nm.The corresponding response time is about 10 ps when the intensity of the pump light beam resonant at 637 nm is 3.97 W/μm2.

Logical stochastic resonance in a cross-bifurcation non-smooth system

This paper investigates logical stochastic resonance(LSR)in a cross-bifurcation non-smooth system driven by Gaussian colored noise.In this system,a bifurcation parameter triggers a transition between monostability,bistability and tristability.By using Novikov's theorem and the unified colored noise approximation method,the approximate Fokker-Planck equation is obtained.Then we derive the generalized potential function and the transition rates to analyze the LSR phenomenon using numerical simulations.We simulate the logic operation of the system in the bistable and tristable regions respectively.We assess the impact of Gaussian colored noise on the LSR and discover that the reliability of the logic response depends on the noise strength and the bifurcation parameter.Furthermore,it is found that the bistable region has a more extensive parameter range to produce reliable logic operation compared with the tristable region,since the tristable region is more sensitive to noise than the bistable one.

Controllable all-optical stochastic logic gates and their delay storages based on the cascaded VCSELs with optical-injection

Using the dynamical properties of the polarization bistability that depends on the detuning of the injected light,we propose a novel approach to implement reliable all-optical stochastic logic gates in the cascaded vertical cavity surface emitting lasers（VCSELs） with optical-injection.Here,two logic inputs are encoded in the detuning of the injected light from a tunable CW laser.The logic outputs are decoded from the two orthogonal polarization lights emitted from the optically injected VCSELs.For the same logic inputs,under electro-optic modulation,we perform various digital signal processing（NOT,AND,NAND,XOR,XNOR,OR,NOR） in the all-optical domain by controlling the logic operation of the applied electric field.Also we explore their delay storages by using the mechanism of the generalized chaotic synchronization.To quantify the reliabilities of these logic gates,we further demonstrate their success probabilities.

Reconfigurable dynamic all-optical chaotic logic operations in an optically injected VCSEL

In a chaotic system of vertical cavity surface emitting laser （VCSEL） with external optical-injection, we propose a novel implementation scheme for reconfigurable dynamic all-optical chaotic logic operations （AOCLOs）. Under different key parameters, such as the bias current, the injection strength and the frequency detuning of the injected light field and the VCSEL, we also explore the evolutions of the polarization-bistability with the amplitude of the injected light field when the output of VCSEL is chaotic wave. According to the dynamic evolutions, we find out the optimal value of the frequency detuning that is considered as a control logic signal, and further implement different AOCLOs, such as AND, NAND, OR, NOR, XOR, and XNOR, by controlling the logic operation of the control logic signal between two logic inputs. Moreover, the ability to reconstruct these logic operations is demonstrated under relatively low noise strength of the spontaneous emission.

Realizing reliable XOR logic operation via logical chaotic resonance in a triple-well potential system

There exists an optimal range of intensity of a chaotic force in which the behavior of a chaos-driven bistable system with two weak inputs can be consistently mapped to a specific logic output. This phenomenon is called logical chaotic resonance(LCR). However, realization of a reliable exclusive disjunction(XOR) through LCR has not been reported.Here, we explore the possibility of using chaos to enhance the reliability of XOR logic operation in a triple-well potential system via LCR. The success probability P of obtaining XOR logic operation can take the maximum value of 1 in an optimal window of intensity D of a chaotic force. Namely, success probability P displays characteristic bell-shaped behavior by altering the intensity of the chaotic driving force, indicating the occurrence of LCR. Further, the effects of periodic force on LCR have been investigated. For a subthreshold chaotic force, a periodic force with appropriate amplitude and frequency can help enhance the reliability of XOR logic operation. Thus, LCR can be effectively regulated by changing the amplitude and frequency of the periodic force.

Modified 2 Satisfiability Reverse Analysis Method via Logical Permutation Operator

The effectiveness of the logic mining approach is strongly correlated to the quality of the induced logical representation that represent the behaviour of the data.Specifically,the optimum induced logical representation indicates the capability of the logic mining approach in generalizing the real datasets of different variants and dimensions.The main issues with the logic extracted by the standard logic mining techniques are lack of interpretability and the weakness in terms of the structural and arrangement of the 2 Satisfiability logic causing lower accuracy.To address the issues,the logical permutation serves as an alternative mechanism that can enhance the probability of the 2 Satisfiability logical rule becoming true by utilizing the definitive finite arrangement of attributes.This work aims to examine and analyze the significant effect of logical permutation on the performance of data extraction ability of the logic mining approach incorporated with the recurrent discrete Hopfield Neural Network.Based on the theory,the effect of permutation and associate memories in recurrent Hopfield Neural Network will potentially improve the accuracy of the existing logic mining approach.To validate the impact of the logical permutation on the retrieval phase of the logic mining model,the proposed work is experimentally tested on a different class of the benchmark real datasets ranging from the multivariate and timeseries datasets.The experimental results show the significant improvement in the proposed logical permutation-based logic mining according to the domains such as compatibility,accuracy,and competitiveness as opposed to the plethora of standard 2 Satisfiability Reverse Analysis methods.

All-optical logic devices based on black arsenic-phosphorus with strong nonlinear optical response and high stability

The Kerr nonlinearity in two-dimensional(2D)nanomaterials is emerging as an appealing and intriguing research area due to their prominent light processing,modulation,and manipulation abilities.In this contribution,2D black arsenic-phosphorus(B-AsP)nanosheets(NSs)were applied in nonlinear photonic devices based on spatial self-phase modula-tion(SSPM)method.By applying the Kerr nonlinearity in 2D B-AsP,an all-optical phase-modulated system is proposed to realize the functions of“on”and“off”in all-optical switching.By using the same all-optical phase-modulated system,another optical logic gate is proposed,and the logical“or”function is obtained based on the 2D B-AsP NSs dispersions.Moreover,by using the SSPM method,a 2D B-AsP/SnS_(2) hybrid structure is fabricated,and the result illustrates that the hybrid structure possesses the ability of the unidirectional nonlinear excitation,which helps in obtaining the function of spatial asymmetric light propagation.This function is considered an important prerequisite for the realization of diode functionalization,which is believed to be a factor in important basis for the design of isolators as well.The initial investig-ations indicate that 2D B-AsP is applicable for designing optical logical devices,which can be considered as an import-ant development in all-optical information processing.

A 16-bit 18-MSPS flash-assisted SAR ADC with hybrid synchronous and asynchronous control logic

This paper presents a 16-bit,18-MSPS(million samples per second)flash-assisted successive-approximation-register(SAR)analog-to-digital converter(ADC)utilizing hybrid synchronous and asynchronous(HYSAS)timing control logic based on an on-chip delay-locked loop(DLL).The HYSAS scheme can provide a longer settling time for the capacitive digital-to-analog converter(CDAC)than the synchronous and asynchronous SAR ADC.Therefore,the issue of incomplete settling or ringing in the DAC voltage for cases of either on-chip or off-chip reference voltage can be solved to a large extent.In addition,the fore-ground calibration of the CDAC’s mismatch is performed with a finite-impulse-response bandpass filter(FIR-BPF)based least-mean-square(LMS)algorithm in an off-chip FPGA(field programmable gate array).Fabricated in 40-nm CMOS process,the proto-type ADC achieves 94.02-dB spurious-free dynamic range(SFDR),and 75.98-dB signal-to-noise-and-distortion ratio(SNDR)for a 2.88-MHz input under 18-MSPS sampling rate.

Temperature-induced logical resonance in the Hodgkin–Huxley neuron

Logical resonance has been demonstrated to be present in the Fitz Hugh-Nagumo(FHN)neuron,namely,the FHN neuron can operate as a reliable logic gate within an optimal parameter window.Here we attempt to extend the results to the more biologically realistic Hodgkin-Huxley(HH)model of neurons.In general,biological organisms have an optimal temperature at which the biological functions are most effective.In view of this,we examine if there is an optimal range of temperature where the HH neuron can work like a specific logic gate,and how temperature influences the logical resonance.Here we use the success probability P to measure the reliability of the specific logic gate.For AND logic gate,P increases with temperature T,reaches the maximum in an optimal window of T,and eventually decreases,which indicates the occurrence of the temperature-induced logical resonance phenomenon in the HH neuron.Moreover,single and double logical resonances can be induced by altering the frequency of the modulating periodic signal under the proper temperatures,suggesting the appearance of temperature-controlled transition of logical resonance.These results provide important clues for constructing neuron-based energy-efficient new-fashioned logical devices.

All-optical logic gate computing for high-speed parallel information processing

Optical computing and optical neural network have gained increasing attention in recent years because of their potential advantages of parallel processing at the speed of light and low power consumption by comparison with electronic computing.The optical implementation of the fundamental building blocks of a digital computer,i.e.logic gates,has been investigated extensively in the past few decades.Optical logic gate computing is an alternative approach to various analogue optical computing architectures.In this paper,the latest development of optical logic gate computing with different kinds of implementations is reviewed.Firstly,the basic concepts of analogue and digital computing with logic gates in the electronic and optical domains are introduced.And then a comprehensive summary of various optical logic gate schemes including spatial encoding of light field,semiconductor optical amplifiers(SOA),highly nonlinear fiber(HNLF),microscale and nanoscale waveguides,and photonic crystal structures is presented.To conclude,the formidable challenges in developing practical all-optical logic gates are analyzed and the prospects of the future are discussed.

A Survey on Type-3 Fuzzy Logic Systems and Their Control Applications

In this paper,we offer a review of type-3 fuzzy logic systems and their applications in control.The main objective of this work is to observe and analyze in detail the applications in the control area using type-3 fuzzy logic systems.In this case,we review their most important applications in control and other related topics with type-3 fuzzy systems.Intelligent algorithms have been receiving increasing attention in control and for this reason a review in this area is important.This paper reviews the main applications that make use of Intelligent Computing methods.Specifically,type-3 fuzzy logic systems.The aim of this research is to be able to appreciate,in detail,the applications in control systems and to point out the scientific trends in the use of Intelligent Computing techniques.This is done with the construction and visualization of bibliometric networks,developed with VosViewer Software,which it is a free Java-based program,mainly intended to be used for analyzing and visualizing bibliometric networks.With this tool,we can create maps of publications,authors,or journals based on a co-citation network or construct maps of keywords,countries based on a co-occurrence networks,research groups,etc.

A Formal Model for Analyzing Fair Exchange Protocols Based on Event Logic

Fair exchange protocols play a critical role in enabling two distrustful entities to conduct electronic data exchanges in a fair and secure manner.These protocols are widely used in electronic payment systems and electronic contract signing,ensuring the reliability and security of network transactions.In order to address the limitations of current research methods and enhance the analytical capabilities for fair exchange protocols,this paper proposes a formal model for analyzing such protocols.The proposed model begins with a thorough analysis of fair exchange protocols,followed by the formal definition of fairness.This definition accurately captures the inherent requirements of fair exchange protocols.Building upon event logic,the model incorporates the time factor into predicates and introduces knowledge set axioms.This enhancement empowers the improved logic to effectively describe the state and knowledge of protocol participants at different time points,facilitating reasoning about their acquired knowledge.To maximize the intruder’s capabilities,channel errors are translated into the behaviors of the intruder.The participants are further categorized into honest participants and malicious participants,enabling a comprehensive evaluation of the intruder’s potential impact.By employing a typical fair exchange protocol as an illustrative example,this paper demonstrates the detailed steps of utilizing the proposed model for protocol analysis.The entire process of protocol execution under attack scenarios is presented,shedding light on the underlying reasons for the attacks and proposing corresponding countermeasures.The developedmodel enhances the ability to reason about and evaluate the security properties of fair exchange protocols,thereby contributing to the advancement of secure network transactions.

RESTlogic: Detecting Logic Vulnerabilities in Cloud REST APIs

logical testing model and resource lifecycle information,generate test cases and complete parameters,and alleviate inconsistency issues through parameter inference.Once again,we propose a method of analyzing test results using joint state codes and call stack information,which compensates for the shortcomings of traditional analysis methods.We will apply our method to testing REST services,including OpenStack,an open source cloud operating platform for experimental evaluation.We have found a series of inconsistencies,known vulnerabilities,and new unknown logical defects.

Multi-modal knowledge graph inference via media convergence and logic rule

Media convergence works by processing information from different modalities and applying them to different domains.It is difficult for the conventional knowledge graph to utilise multi-media features because the introduction of a large amount of information from other modalities reduces the effectiveness of representation learning and makes knowledge graph inference less effective.To address the issue,an inference method based on Media Convergence and Rule-guided Joint Inference model(MCRJI)has been pro-posed.The authors not only converge multi-media features of entities but also introduce logic rules to improve the accuracy and interpretability of link prediction.First,a multi-headed self-attention approach is used to obtain the attention of different media features of entities during semantic synthesis.Second,logic rules of different lengths are mined from knowledge graph to learn new entity representations.Finally,knowledge graph inference is performed based on representing entities that converge multi-media features.Numerous experimental results show that MCRJI outperforms other advanced baselines in using multi-media features and knowledge graph inference,demonstrating that MCRJI provides an excellent approach for knowledge graph inference with converged multi-media features.

Implementation of Fuzzy Logic Control into an Equivalent Minimization Strategy for Adaptive Energy Management of A Parallel Hybrid Electric Vehicle

As government agencies continue to tighten emissions regulations due to the continued increase in greenhouse gas production, automotive industries are seeking to produce increasingly efficient vehicle technology. Hybrid electric vehicles (HEVs) have been introduced to mitigate problems while improving fuel economy. HEVs have led to the demand of creating more advanced controls software to consider multiple components for propulsive power in a vehicle. A large section in the software development process is the implementation of an optimal energy management strategy meant to improve the overall fuel efficiency of the vehicle. Optimal strategies can be implemented when driving conditions are known a prior. The Equivalent Consumption Minimization Strategy (ECMS) is an optimal control strategy that uses an equivalence factor to equate electrical to mechanical power when performing torque split determination between the internal combustion engine and electric motor for propulsive and regenerative torque. This equivalence factor is determined from offline vehicle simulations using a sensitivity analysis to provide optimal fuel economy results while maintaining predetermined high voltage battery state of charge (SOC) constraints. When the control hierarchy is modified or different driving styles are applied, the analysis must be redone to update the equivalence factor. The goal of this work is to implement a fuzzy logic controller that dynamically updates the equivalence factor to improve fuel economy, maintain a strict charge sustaining window of operation for the high voltage battery, and reduce computational time required during algorithm development. The adaptive algorithm is validated against global optimum fuel economy and charge sustaining results from a sensitivity analysis performed for multiple drive cycles. Results show a maximum fuel economy improvement of 9.82% when using a mild driving style and a 95% success rate when maintaining an ending SOC within 5% of the desired SOC regardless of starting SOC.

Spin logic devices based on negative differential resistance -enhanced anomalous Hall effect

Owing to rapid developments in spintronics,spin-based logic devices have emerged as promising tools for next-generation computing technologies.This paper provides a comprehensive review of recent advancements in spin logic devices,particularly focusing on fundamental device concepts rooted in nanomagnets,magnetoresistive random access memory,spin–orbit torques,electric-field modu-lation,and magnetic domain walls.The operation principles of these devices are comprehensively analyzed,and recent progress in spin logic devices based on negative differential resistance-enhanced anomalous Hall effect is summarized.These devices exhibit reconfigur-able logic capabilities and integrate nonvolatile data storage and computing functionalities.For current-driven spin logic devices,negative differential resistance elements are employed to nonlinearly enhance anomalous Hall effect signals from magnetic bits,enabling reconfig-urable Boolean logic operations.Besides,voltage-driven spin logic devices employ another type of negative differential resistance ele-ment to achieve logic functionalities with excellent cascading ability.By cascading several elementary logic gates,the logic circuit of a full adder can be obtained,and the potential of voltage-driven spin logic devices for implementing complex logic functions can be veri-fied.This review contributes to the understanding of the evolving landscape of spin logic devices and underscores the promising pro-spects they offer for the future of emerging computing schemes.

Hierarchical Controller Synthesis Under Linear Temporal Logic Specifications Using Dynamic Quantization

Linear temporal logic(LTL)is an intuitive and expressive language to specify complex control tasks,and how to design an efficient control strategy for LTL specification is still a challenge.In this paper,we implement the dynamic quantization technique to propose a novel hierarchical control strategy for nonlinear control systems under LTL specifications.Based on the regions of interest involved in the LTL formula,an accepting path is derived first to provide a high-level solution for the controller synthesis problem.Second,we develop a dynamic quantization based approach to verify the realization of the accepting path.The realization verification results in the necessity of the controller design and a sequence of quantization regions for the controller design.Third,the techniques of dynamic quantization and abstraction-based control are combined together to establish the local-to-global control strategy.Both abstraction construction and controller design are local and dynamic,thereby resulting in the potential reduction of the computational complexity.Since each quantization region can be considered locally and individually,the proposed hierarchical mechanism is more efficient and can solve much larger problems than many existing methods.Finally,the proposed control strategy is illustrated via two examples from the path planning and tracking problems of mobile robots.

A Neuro T-Norm Fuzzy Logic Based System

In this study, we are first examining well-known approach to improve fuzzy reasoning model (FRM) by use of the genetic-based learning mechanism [1]. Later we propose our alternative way to build FRM, which has significant precision advantages and does not require any adjustment/learning. We put together neuro-fuzzy system (NFS) to connect the set of exemplar input feature vectors (FV) with associated output label (target), both represented by their membership functions (MF). Next unknown FV would be classified by getting upper value of current output MF. After that the fuzzy truths for all MF upper values are maximized and the label of the winner is considered as the class of the input FV. We use the knowledge in the exemplar-label pairs directly with no training. It sets up automatically and then classifies all input FV from the same population as the exemplar FVs. We show that our approach statistically is almost twice as accurate, as well-known genetic-based learning mechanism FRM.