Physical Realization Research Articles

A class of n-D Hamiltonian conservative chaotic systems with three-terminal memristor: Modeling, dynamical analysis, and FPGA implementation.

Memristors are commonly used to introduce various chaotic systems and can be used to enhance their chaotic characteristics. However, due to the strict construction conditions of Hamiltonian systems, there has been limited research on the development of memristive Hamiltonian conservative chaotic systems (MHCCSs). In this work, a method for constructing three-terminal memristors is proposed, and the three-terminal memristors are incorporated into the Hamiltonian system, resulting in the development of a class of n-D MHCCS. Based on this method, we model a 4D MHCCS as a standard model for detailed dynamic analysis. The dynamic analysis reveals that the MHCCS exhibits complex dynamic behaviors, including conservativeness, symmetry, chaos depending on parameters, extreme multistability, and chaos under a wide parameter range. The dynamic analysis shows that MHCCS not only retains the favorable characteristics of a conservative system but also has more complex nonlinear dynamics due to the incorporation of memristors, thereby further enhancing its chaotic characteristics. Furthermore, the pseudo-random number generator based on the MHCCS has excellent randomness in terms of the NIST test. Finally, the physical realizability of the system is verified through Field Programmable Gate Array experiments. This study demonstrates that the constructed class of MHCCSs is a good entropy source that can be applied to various chaotic embedded systems, including secure communication, cryptographic system, and pseudo-random number generator.

On the Functional Nature of Cognitive Systems

The functional nature of cognitive systems is outlined as a general conceptual model where typical notions of cognition are analyzed apart from the physical realization (biological or artificial) of such systems. The notion of function, one of the main logical bases of mathematics, logic, linguistics, physics, and computer science, is shown to be a unifying concept in analyzing cognition components: learning, meaning, comprehension, language, knowledge, and consciousness are related to increasing levels in the functional organization of cognition.

FlexSARCloak: A Flexible SAR Cloak Driven by Task-Oriented Learning.

Invisibility─the remarkable ability to render objects imperceptible─has long been a persistent dream of humankind. However, traditional cloaking materials are typically rigid and inflexible, limiting their adaptability to various shapes and requirements. Even when flexibility is achieved, uncontrollable scattering in complex electromagnetic environments continues to pose significant challenges in the design of flexible cloaks. In this paper, we present a task-oriented learning (TOL)-based metasurface design approach, successfully realizing a broadband, polarization-independent, flexible SAR cloak (FlexSARCloak). Experimental results reveal that the cloak achieves over 90% absorption efficiency across the 9-25 GHz frequency range for incidence angles ranging from 0 to 60°. Outdoor experiments further confirm that the FlexSARCloak achieves near-perfect invisibility under UAV-mounted SAR. Furthermore, a comprehensive series of environmental tests, including exposure to extreme temperatures, variable humidity, and sandstorm conditions, was conducted to simulate natural or extreme conditions, which successfully validated the stability of the electromagnetic performance. The proposed FlexSARCloak presents considerable potential for applications in electromagnetic protection and related domains. Moreover, the introduction of the TOL algorithm is expected to significantly accelerate the design and optimization of metasurfaces, paving the way for the physical realization of multifunctional metasurfaces.

Mapping indefinite causal order processes to composable quantum protocols in a spacetime

Abstract Formalisms for higher order quantum processes provide a theoretical formalisation of quantum processes where the order of agents' operations need not be definite and acyclic, but may be subject to quantum superpositions. This has led to the concept of indefinite causal structures (ICS) which have garnered much interest. However, the interface between these information-theoretic approaches and spatiotemporal notions of causality is less understood, and questions relating to the physical realisability of ICS in a spatiotemporal context persist despite progress in their information-theoretic characterisation. Further, previous work suggests that composition of processes is not so straightforward in ICS frameworks, which raises the question of how this connects with the observed composability of physical experiments in spacetime. To address these points, we compare the formalism of quantum circuits with quantum control of causal order (QC-QC), which models an interesting class of ICS processes, with that of causal boxes, which models composable quantum information protocols in spacetime. We incorporate the set-up assumptions of the QC-QC framework into the spatiotemporal perspective and show that every QC-QC can be mapped to a causal box that satisfies these set up assumptions and acts on a Fock space while reproducing the QC-QC's behaviour in a relevant subspace defined by the assumptions. Using a recently introduced concept of fine-graining, we show that the causal box corresponds to a fine-graining of the QC-QC, which unravels the original ICS of the QC-QC into a set of quantum operations with a well-defined and acyclic causal order, compatible with the spacetime structure. Our results also clarify how the composability of physical experiments is recovered, while highlighting the essential role of relativistic causality and the Fock space structure.

Revisiting Thomson's model with multiply charged superfluid helium nanodroplets.

We study superfluid helium droplets multiply charged with Na+ or Ca+ ions. When stable, the charges are found to reside in equilibrium close to the droplet surface, thus representing a physical realization of Thomson's model. We find the minimum radius of the helium droplet that can host a given number of ions using a model whose physical ingredients are the solvation energy of the cations, calculated within the helium density functional theory approach, and their mutual Coulomb repulsion energy. Our model goes beyond the often used liquid drop model, where charges are smeared out either within the droplet or on its surface, and which neglects the solid-like helium shell around the ions. We find that below a threshold droplet radius R0, the total energy of the system becomes higher than that of the separated system of the pristine helium droplet and the charges embedded in their solvation microcluster ("snowball"). However, the ions are still kept within the droplet by the presence of energy barriers, which hinder Coulomb explosion. A further reduction of the droplet radius below a value Rexpl eventually results in the disappearance of such barrier, leading to Coulomb explosion. Surprisingly, our results are rather insensitive to the ion atomic species. This makes room to discuss them in the context of intrinsic multicharged helium droplets, where the charges are triatomic He3+ ions. Our calculated values for Rexpl display the correct scaling with the number of cations compared to the available experimental results, at variance with other estimates for the critical radii.

Event‐based supervisor control for a cyber‐physical waterway lock system

AbstractAn event‐based supervisory control scheme, in the Ramdage–Wonham framework, will be proposed for the cyber‐physical Waterway Lock system, known as Lock III, in Tilburg, the Netherlands. The proposed control scheme imposes desired behavior, by appropriately disabling controllable events, so as to avoid activation of actuator commands that may lead to undesired and potentially hazardous operating states. The discrete event model of the total Waterway Lock system, comprising 54 actuator and sensor automata, will be presented in analytic 6‐tuple forms of its subsystems. The system's desired behavior, which is expressed using six rules, will be formulated as 84 regular and prefix closed languages that will be realized as appropriate supervisor automata. All supervisors are developed by a general two‐state supervisor form, which facilitates their implementation. A distributed control architecture will be proposed, which organizes all supervisors in distinct groups, each of which controls one and only one distinct command event. The complexity of the proposed control scheme will be computed to be equal to (168,324,564), being reasonable, as compared to the large number of subsystems and the restrictive design requirements. The physical realizability of the 84 supervisors, with respect to the 54 subsystems of the waterway lock system, will be proved analytically. Also, it will be proved analytically that the proposed supervisor architecture guarantees the nonblocking property of the controlled automaton, including all subsystems. The establishment of these analytic proofs supports the extendibility of the results to other applications. To demonstrate the resulting large‐scale controlled automaton's good performance, its marked behavior and simulation results will be presented.

Generation of Terahertz radiation from a soliton cavity in a laser-plasma system

Abstract Using particle-in-cell simulations, we demonstrate a novel mechanism for the generation of terahertz radiation in a laser-plasma system. The radiation originates from current oscillations trapped in a stable soliton cavity created by the laser in the under-dense plasma region. These oscillations behave like a current dipole antenna. The characteristics of the antenna can be controlled by tuning the laser-plasma parameters to achieve the desired output frequency. We discuss the optimum conditions for the physical realization of this mechanism and its potential practical applications.

Memristor & its application in biological field

Abstract Demand for highly integrated, low-power nonvolatile memories to get beyond the drawbacks of traditional memory systems has led to, Memristive/resistive switching devices which are excellent choices for non-volatile memory technology. Memristor is the 4th fundamental unit proposed by Professor Chua to give a relation between charge and magnetic flux. If a memristor’s constitutive relation is a straight line with a slope of M that passes through the origin in the ɸ –q plane, it is considered linear. The memristor’s physical realizations and potential uses remain a fascinating area for investigation.Semiconductor nanoparticles specially ZnO, ZnS QD exhibit Memristive characteristics. Employing this Memristive behaviour of biofunctionalized nanoscale particles and “voltage gap” as a novel sensing metric, several investigators attempted to assess the precise amount of microbiological contamination. Here in this work, Memristive property of some semiconductor nanoparticles like ZnO, ZnS as well as metal nanoparticle like PbS, Ag particles are studied and tried to focus on application of Memristive devices in near future in biological fields. The switching properties of bio-voltage memristors can now be used to achieve bio-voltage matching.

Delayed-feedback oscillators replicate the dynamics of multiplex networks: Wavefront propagation and stochastic resonance

The widespread development and use of neural networks have significantly enriched a wide range of computer algorithms and promise higher speed at lower cost. However, the imitation of neural networks by means of modern computing substrates is highly inefficient, whereas physical realization of large scale networks remains challenging. Fortunately, delayed-feedback oscillators, being much easier to realize experimentally, represent promising candidates for the empirical implementation of neural networks and next generation computing architectures. In the current research, we demonstrate that coupled bistable delayed-feedback oscillators emulate a multilayer network, where one single-layer network is connected to another single-layer network through coupling between replica nodes, i.e. the multiplex network. We show that all the aspects of the multiplexing impact on wavefront propagation and stochastic resonance identified in multilayer networks of bistable oscillators are entirely reproduced in the dynamics of time-delay oscillators. In particular, varying the coupling strength allows suppressing and enhancing the effect of stochastic resonance, as well as controlling the speed and direction of both deterministic and stochastic wavefront propagation. All the considered effects are studied in numerical simulations and confirmed in physical experiments, showing an excellent correspondence and disclosing thereby the robustness of the observed phenomena.

A novel 4D chaotic system coupling with dual-memristors and application in image encryption

A novel 4D dual-memristor chaotic system (4D-DMCS) is constructed by concurrently introducing two types of memristors: an ideal quadratic smooth memristor and a memristor with an absolute term, into a newly designed jerk chaotic system. The excellent nonlinear properties of the system are investigated by analyzing the Lyapunov exponent spectrum, and bifurcation diagram. The 4D-DMCS retains some characteristics of the original jerk chaotic system, such as the offset boosting in the x-axis direction. Simultaneously, the integration of the two memristors significantly enriches the dynamic behavior of the system, notably augmenting its transitional behaviors, fostering greater multistability, and elevating both spectral entropy and C0 complexity. This augmentation underscores the profound impact of the memristors on the system’s overall performance and complexity. The system is implemented through the STM32 microcontroller, further proving the physical realizability of the system. Ultimately, the 4D-DMCS exhibits remarkable performance when applied to image encryption, demonstrating its significant potential and effectiveness in this domain.

A novel eight-way power combiner on suspended substrate stripline for Ku-band applications

This work proposes a novel 8-way power combiner implemented using suspended substrate stripline technology for Ku-band applications. The equivalent circuit of the design is analyzed to obtain parameters for the physical realization of the structure. The combiner is well matched at both input and output ports with VSWR better than 1.6:1, achieves low insertion loss of less than 1dB and isolation of more than 16.8 dB over the range from 12 GHz to 18 GHz. The structure is also able to handle high thermal dissipated power due to its housing, hence, suitable to find application in high power-amplifier subsystems.

Autonomous and ubiquitous in-node learning algorithms of active directed graphs and its storage behavior

The brain’s memory system is extraordinarily complex, evidenced by the multitude of neurons involved and the intricate electrochemical activities within them, as well as the complex interactions among neurons. Memory research spans various levels, from cellular and molecular to cognitive behavioral studies, each with its own focus, making it challenging to fully describe the memory mechanism. Many details of how biological neuronal networks encode, store, and retrieve information remain unknown. In this study, we model biological neuronal networks as active directed graphs, where each node is self-adaptive and relies on local information for decision-making. To explore how these networks implement memory mechanisms, we propose a parallel distributed information access algorithm based on the node scale of the active directed graph. Here, subgraphs are seen as the physical realization of the information stored in the active directed graph. Unlike traditional algorithms with global perspectives, our algorithm emphasizes global node collaboration in resource utilization through local perspectives. While it may not achieve the global optimum like a global-view algorithm, it offers superior robustness, concurrency, decentralization, and biological feasibility. We also tested network capacity, fault tolerance, and robustness, finding that the algorithm performs better in sparser network structures.

Universality class of interacting directed single- and double-strand homopolymers.

This work examines a field theory for directed homopolymers in a good solvent. The field theory is based on a lattice model for single- and double-strand polymers with length variables, direction-dependent pairing energy and interactions. As for the less explicit O(n)-symmetric model, there is a close relation to the conventional one-component branched polymer and the associated Lee-Yang problem. We derive results in the limiting cases of nearly complete denaturation and nearly complete renaturation. The single-strand critical exponent is calculated in two-loop order. A plausible physical realization is RNA molecules with a periodic base sequence like AUAU.

Elliptic Stable Envelopes for Certain Non-Symplectic Varieties and Dynamical $R$-Matrices for Superspin Chains from the Bethe/Gauge Correspondence

We generalize Aganagic-Okounkov's theory of elliptic stable envelopes, and its physical realization in Dedushenko-Nekrasov's and Bullimore-Zhang's works, to certain varieties without holomorphic symplectic structure or polarization. These classes of varieties include, in particular, classical Higgs branches of 3d $\mathcal N=2$ quiver gauge theories. The Bethe/gauge correspondence relates such a gauge theory to an anisotropic/elliptic superspin chain, and the stable envelopes compute the $R$-matrix that solves the dynamical Yang-Baxter equation (dYBE) for this spin chain. As an illustrative example, we solve the dYBE for the elliptic $\mathfrak{sl}(1|1)$ spin chain with fundamental representations using the corresponding 3d $\mathcal N=2$ SQCD whose classical Higgs branch is the Lascoux resolution of a determinantal variety. Certain Janus partition functions of this theory on $I \times \mathbb E$ for an interval $I$ and an elliptic curve $\mathbb E$ compute the elliptic stable envelopes, and in turn the geometric elliptic $R$-matrix, of the anisotropic $\mathfrak{sl}(1|1)$ spin chain. Furthermore, we consider the 2d and 1d reductions of elliptic stable envelopes and the $R$-matrix. The reduction to 2d gives the K-theoretic stable envelopes and the trigonometric $R$-matrix, and a further reduction to 1d produces the cohomological stable envelopes and the rational $R$-matrix. The latter recovers Rimányi-Rozansky's results that appeared recently in the mathematical literature.

Parametrical synthesis of various radio devices with the set quantity of identical cascades of type «the nonlinear part – the mixed two-port network»

Background. Presence of possibility of analytical definition of a part of parametres of various radio devices, optimum by criterion of maintenance of preset values of modules and phases of transfer functions on necessary quantity of frequencies, considerably reduces time of numerical optimisation of other part of parametres by criterion of formation demanded frequency response and phase response in a strip of frequencies. Till now such problems dared concerning radio devices only with one cascade of type «a nonlinear part - the coordination the device» or «the coordination the device – a nonlinear part». In quality «the coordination devices were used the jet, resistive, complex or mixed two-port networks. The problem of multicascade radio devices with jet two-port networks is solved also. Change of basis for the coordination two-port networks and a place of inclusion of a nonlinear part leads to change of area of a physical realizability. Aim. Working out of algorithms of parametrical synthesis of radio devices with any quantity of identical and unequal cascades of type «a nonlinear part ‑the coordination the mixed two-port network» by criterion of maintenance of the set frequency characteristics. Nonlinear parts are presented in the form of a nonlinear element and parallel either consecutive on a current or pressure of a feedback. Methods. The theory of two-port networks, matrix algebra, a decomposition method, a method of synthesis of actuation microwave devices, numerical methods of optimisation. Results. In interests of achievement of the specified purpose systems of the algebraic equations are generated and solved. Models of optimum two-port networks in the form of mathematical expressions for definition of interrelations between elements of their classical matrix of transfer and for search of dependences of mixed of two-poles from frequency are received. It is shown, that at certain parities between quantity of cascades and values of resistance of a source of a signal and loading of the one-cascade radio device frequency characteristics of one-cascade and multicascade radio devices appear identical or similar. Such schemes are named by equivalent. Conclusion. The comparative analysis of theoretical results (frequency response and phase response radio devices, value of parametres), received by mathematical modelling in system MathCad, and the experimental results received by схемотехнического of modelling in systems OrCad and MicroCap, shows their satisfactory coincidence.

Understanding the Inherently Self-Adjusting Mechanism and Load Adaptability of the Mem-Damper

The tapered dashpot (damper) has been the earliest memristor found in the mechanical engineering domain, named mem-dashpot (mem-damper), since the missing memristor was postulated by Leon Chua. In this paper, a displacement-dependent viscous damper device with internal channels is investigated and recognized as a physical realization of the mem-damper by analyzing the mathematical and dynamic relationships of the device’s complementary port variables theoretically and experimentally. A vehicle suspension equipped with a mem-damper is taken as a carrier for presenting load adaptability of the mem-damper. An investigation reveals the inherently self-adjusting mechanism behind load adaptability from the viewpoint of energy storage, that is, a mem-damper with different initial displacement values can be equivalent to a semi-active damper performing an initial-position-dependent damping control strategy. Finally, the load adaptability of the mem-damper is demonstrated through both simulation and experiment of the suspension system with the mem-damper prototype. Due to such load adaptability, the suspension equipped with the mem-damper can offer more constant and smoother ride comfort than the one with the linear damper.

Photonic Ising machines for combinatorial optimization problems

The demand for efficient solvers of complicated combinatorial optimization problems, especially those classified as NP-complete or NP-hard, has recently led to increased exploration of novel computing architectures. One prominent collective state computing paradigm embodied in the so-called Ising machines has recently attracted considerable research attention due to its ability to optimize complex problems with large numbers of interacting variables. Ising model-inspired solvers, thus named due to mathematical similarities to the well-known model from solid-state physics, represent a promising alternative to traditional von Neumann computer architectures due to their high degree of inherent parallelism. While there are many possible physical realizations of Ising solvers, just as there are many possible implementations of any binary computer, photonic Ising machines (PIMs) use primarily optical components for computation, taking advantage of features like lower power consumption, fast calculation speeds, the leveraging of physical optics to perform the calculations themselves, possessing decent scalability and noise tolerance. Photonic computing in the form of PIMs may offer certain computational advantages that are not easily achieved with non-photonic approaches and is nonetheless an altogether fascinating application of photonics to computing. In this review, we provide an overview of Ising machines generally, introducing why they are useful, what types of problems they can tackle, and how different Ising solvers can be compared and benchmarked. We delineate their various operational mechanisms, advantages, and limitations vis-à-vis non-photonic Ising machines. We describe their scalability, interconnectivity, performance, and physical dimensions. As research in PIMs continues to progress, there is a potential that photonic computing could well emerge as a way to handle large and challenging optimization problems across diverse domains. This review serves as a comprehensive resource for researchers and practitioners interested in understanding capabilities and potential of PIMs in addressing such complex optimization problems.

Feasibility and design of nonlinear negative‐stiffness isolating approach for solid‐rocket‐motor‐type structures

AbstractSolid rocket motor (SRM)‐type structures are popular due to their reliability, considering that service safety during transportation can be improved by applying advanced vibration control technologies. In this study, a negative‐stiffness‐enhanced isolation system (NSeIS) with appropriately designed linear and nonlinear properties was developed to vertically isolate SRMs subjected to transportation‐ and deployment‐induced vibrations. The NSeIS design, based on the combination of a negative‐stiffness device and vertical isolator, involved a clear mechanical model, physical realization, and mechanical properties. Parametric analyses were performed on a typical SRM controlled with a linear and nonlinear NSeIS and a conventional isolation system. Subsequently, a feasible parameter domain and design recommendations were deduced. Finally, design cases for the SRM for time‐domain verification were considered. The results revealed that the NSeIS offers a flexible and enhanced isolating effect through the parallel arrangement of the negative‐stiffness device and conventional isolators. For the motor‐type structure, NSeIS ensures marked enhancements in performance and multiple levels of mitigation effects. Thus, compared with a conventional isolator with the same damping, NSeIS achieves a more substantial negative‐stiffness effect for a large displacement response range owing to its nonlinear property. NSeIS can isolate more vibration‐induced energy, thereby suppressing the interface Mises stress, which is essential for SRM‐type structures.

Towards an optimal design of acoustic Luneburg lenses.

Although the concept of acoustic Luneburg lenses was first proposed more than 50 years ago, its physical realization became feasible only in the last decade, owing to advancements in metamaterials research. Since then, numerous studies have explored the potential of these devices from the acoustic perspective. However, a comprehensive understanding of the mechanisms associated with the optimal performance of these lenses remains underexplored in the literature. This study conducts numerical investigations to identify parameters enhancing acoustic gain in Luneburg lenses. The analyses are conducted with the results obtained from a flattened Luneburg lens model based on the lattice Boltzmann method. Results, scaled with the Helmholtz number, He, indicate that the maximum acoustic gain occurs at He = 1.3, with performance sustained over a wide range of Helmholtz values. Analysis of surface impedance reveals underperformance for Helmholtz values below 0.5 due to viscous dissipation and above 2.0 due to Bragg reflections. These results provide a basis for evaluating the Helmholtz parameters that optimize the acoustic gain of Luneburg lenses.

Investigations on ironing parameters in screw extrusion additive manufacturing (SEAM)

Additive Manufacturing (AM) is a novel manufacturing process that enables the physical realization of a given 3D model via layered deposition. Material extrusion (MEX) is one of the most widely used forms of the various AM techniques, in which the screw extrusion-based AM (SEAM) processing offers the most versatile characteristics, in terms of material handling and flow rate capacities. It involves continuous extrusion of the semi-solid material via an extruder screw. Ironing is a common practice in MEX techniques, to maintain z-height and improve the surface morphologies while deposition. Most commercially used nozzles for MEX are thin-walled, such that the ratio of the nozzle width to the diameter (w/d) is close to 1. In this research, investigations on the ironing effect during screw extrusion-based material deposition are explored using a set of wider nozzles (w/d as high as 40). Special emphasis is laid on the deposited surface finish, interlayer strength, and geometrical conformance of the extrusion. The nozzle diameter and the stand-off distance (SOD) are also independently varied. It is found that the best dimensional stability is achieved when the SOD is set between 75 % and 100 % of the nozzle diameter. Ironing improved the surface finish and the interlayer strength in all instances, with an average improvement of 50 % and 200 %, respectively.