Physical Circuit Research Articles

A Variation-Aware Quantum Circuit Mapping Approach Based on Multi-Agent Cooperation

Quantum circuit mapping is an essential process required by executing quantum circuits using a noisy intermediate-scale quantum (NISQ) device. Since qubits and quantum gates of a NISQ device are error-prone and variable in quality, it is crucial to choose qubits or quantum gates in a variation-aware manner to maximize the success rate of executing circuits. To this end, this paper proposes a variation-aware method for quantum circuit mapping through the cooperation of multiple agents. Each agent in the proposed method can gradually construct a physical circuit that respects the device's connectivity constraints by inserting a SWAP gate at each step. Moreover, at each step, the circuit information of each agent is shared within the agent population through a communication mechanism that combines global and local information exchange, so that agents with poor fitness can get an opportunity to improve their physical circuits. The experimental results on extensive benchmark circuits confirm that the proposed method can effectively and consistently improve the overall circuit fidelity compared with the state-of-the-art methods.

Compact modeling of metal–oxide TFTs based on the Bayesian search-based artificial neural network and genetic algorithm

Thin-film transistors play an important role in ultra-high definition displays. The conventional physical model requires a significant amount of time and resources, while its generalizability is limited. This paper introduces a method for quickly incorporating the characteristics of emerging devices into circuit simulations using an artificial neural network (ANN) model. The multi-layer perceptron (MLP) model, with a simple structure and high modeling efficiency, is employed as a typical ANN model. The pivotal step in using the MLP model is to determine its topology. This hyperparameter problem can be easily solved using Bayesian search. To improve the accuracy of the model, a genetic algorithm is proposed to optimize the initial values of the weights and biases. Furthermore, by introducing the first derivative in the loss function, small signal parameters can be taken into consideration. This modeling approach significantly reduces the time required for compact device modeling. Our experimental results exhibit a strong correlation between the model’s output and the corresponding experimental data, thereby providing comprehensive validation for the effectiveness of our proposed model. Once the trained model parameters were extracted, we implemented the hybrid ANN model using Verilog-A. This circuit-level experiment demonstrates that this hybrid ANN model can accurately estimate various physical devices and circuits.

SkinLink

Applying customized epidermal electronics closely onto the human skin offers the potential for biometric sensing and unique, always-available on-skin interactions. However, iterating designs of an on-skin interface from schematics to physical circuit wiring can be time-consuming, even with tiny modifications; it is also challenging to preserve skin wearability after repeated alteration. We present SkinLink, a reconfigurable on-skin fabrication approach that allows users to intuitively explore and experiment with the circuitry adjustment on the body. We demonstrate SkinLink with a customized on-skin prototyping toolkit comprising tiny distributed circuit modules and a variety of streamlined trace modules that adapt to diverse body surfaces. To evaluate SkinLink's performance, we conducted a 14-participant usability study to compare and contrast the workflows with a benchmark on-skin construction toolkit. Four case studies targeting a film makeup artist, two beauty makeup artists, and a wearable computing designer further demonstrate different application scenarios and usages.

Modular Hardware Design with Timeline Types

Modular design is a key challenge for enabling large-scale reuse of hardware modules. Unlike software, however, hardware designs correspond to physical circuits and inherit constraints from them. Timing constraints—which cycle a signal arrives, when an input is read—and structural constraints—how often a multiplier accepts new inputs—are fundamental to hardware interfaces. Existing hardware design languages do not provide a way to encode these constraints; a user must read documentation, build scripts, or in the worst case, a module’s implementation to understand how to use it. We present Filament, a language for modular hardware design that supports the specification and enforcement of timing and structural constraints for statically scheduled pipelines. Filament usestimeline types, which describe the intervals of clock-cycle time when a given signal is available or required. Filament enablessafe compositionof hardware modules, ensures that the resulting designs are correctly pipelined, and predictably lowers them to efficient hardware.

Research on Automatic Design of Substation Secondary Circuit Based on Improved SPCD Model and Knowledge Graph

In view of the lack of automatic design research of the physical circuit of the substation secondary system, and the digital design and handover level that the substation urgently needs to improve, this paper proposes the following solutions. First of all, an improvement plan is proposed for the existing SPCD model, adding all design related information such as external function grouping and logical interface of the panel cabinet. Secondly, extract the function group elements and secondary cabinet elements of the improved SPCD model as knowledge graph nodes, and abstract the relationship between function group’s interfaces as knowledge graph relationships. Based on the Neo4j graph database, a typical bay knowledge graph for secondary design is conFstructed. Furthermore, the electric power secondary field data set is mined, the Word2vec model is trained by the secondary field data set, and the text similarity algorithm model in the secondary design field is established. Finally, based on the above research, a method for automatic design of substation secondary physical circuits and automatic generation of SPCD model file based on word2vec text similarity is proposed.

Averaged Behavior Model of Current-Mode Buck Converters for Transient Power Noise Analysis

Accurate evaluation and simulation of power noise is critical in the development of modern electronic devices. However, the widely used target impedance fails to predict the low-frequency noise generated in a device due to the existence of the dc–dc converter, whose output impedance can change under different loading conditions. A physical circuit model is then desired to replicate the behavior of a voltage regulator module, and the average technique is an efficient method to estimate the noise of a pulsewidth-modulated (PWM) converter. With the emergence of converters with adaptive on-time (AOT) controllers, more complex averaging methods are required, but none of them supports transient simulation. A general, efficient, and accurate modeling technique is presented in this article, whose framework supports both current-mode PWM and AOT controllers. In addition, a novel two-step parameter extraction method is proposed, which can be used to evaluate the equivalent values of internal feedback parameters of an encrypted simulation model or from measurement. The modeling method is validated by both simulation and measurement.

Theoretical analysis and experimental verification of fractional-order RC cobweb circuit network

Recent research has shown that ideal capacitors and inductors do not physically exist, and that the dynamics of real devices can be accurately described by fractional-order (FO) mathematical models. This paper investigates a class of 2×n order RC cobweb FO circuit network with central node. Based on the Kirchhoff’s laws, the impedance magnitude and phase between two points of the network are derived using difference equations and matrix transformations. Three impedance expressions are deduced, and their correctness is verified numerically and by simulations. The influence of various parameters of the electrical network, namely the resistance, capacitance, number of circuit units, frequency and fractional order, on the impedance is studied. Additionally, for the first time, physical experiments are presented to compare the effectiveness of FO and integer-order circuit networks for describing the impedance of actual physical circuits. These experiments confirm that FO circuit network models perform better than the integer-order ones for representing the characteristics of the impedance magnitude and phase.

A family of memristive multibutterfly chaotic systems with multidirectional initial-based offset boosting

Memristors are commonly used to construct memristive chaotic systems with complex dynamics because of their strong nonlinearity and unique memory effects. In this paper, a simplified multi-piecewise memristor is applied for designing a family of memristive multibutterfly chaotic systems (MMBCSs). By coupling different numbers of the simplified multi-piecewise memristors into a modified Sprott C system, three MMBCSs are constructed. Theoretical analysis and numerical simulations show that the three MMBCSs can not only generate connected 1D(direction)-, 2D(plane)-, and 3D(space)-multibutterfly chaotic attractors (MBCAs), respectively, but also can respectively produce unconnected 1D-, 2D-, and 3D-MBCAs. Also, the number and position of butterfly attractors can be easily controlled by switching the memristor’s integer parameters and initial states, respectively. More importantly, the constructed three MMBCSs exhibit different initial-based offset boosting including 1D-, 2D-, and 3D-boosting behaviors, respectively. Especially, the 3D-initial-offset behavior is found in chaotic systems at the first time. Furthermore, we further implement the physical circuit of the three MMBCSs, and various typical dynamical behaviors are demonstrated by hardware experiments and Multisim simulations. Finally, a medical image encryption solution for online medical treatment is designed based on the proposed MMBCSs.

Design of Secondary Circuit Visualization System for UHVDC Converter Stations

For the problems of complicated work content and error-prone workload of secondary circuits, a three-dimensional visualization method is proposed for the visualization and management of the physical circuits of the control and protection system of the converter station based on digital twin technology. The system can be used to improve the work efficiency of operation and maintenance personnel by constructing a secondary circuit information data model, generating corresponding data through artificial intelligence image recognition and manual review of secondary circuit drawings and schematics, and performing accurate corresponding circuit data analysis and 3D visualization management of the secondary physical circuits of control and security equipment, which can visualize the circuit information of control and security equipment in the station from outside to inside at multiple levels and multiple dimensions.

A 3D chaotic system with multi-transient behavior and its application in image encryption

Based on the special structure of the variable-boostable chaotic system VB19, that includes a smooth secondary flux-controlled memristor, a three-dimensional memristive chaotic system with only one equilibrium point is constructed. Numerical analysis reveals that the system has novel dynamical characteristics of controlling multiple types of attractors by a single parameter. At the same time, the existence of multiple transient behaviors and the coexistence of periodic and quasi-periodic attractors significantly increase the complexity of the system. Moreover, the system has a large range of high complexity phenomena, which is relatively rare in low-dimensional chaotic systems. A circuit is designed and implemented for this system in the physical circuit. Finally, this memristive system is applied to image encryption, whose excellent performance is demonstrated by key space, key sensitivity analysis, histogram analysis, and correlation coefficient analysis, which provides a reference for the further research of low dimensional memristive systems in the field of image encryption.

LEAP: Scaling Numerical Optimization Based Synthesis Using an Incremental Approach

While showing great promise, circuit synthesis techniques that combine numerical optimization with search over circuit structures face scalability challenges due to a large number of parameters, exponential search spaces, and complex objective functions. The LEAP algorithm improves scaling across these dimensions using iterative circuit synthesis, incremental reoptimization, dimensionality reduction, and improved numerical optimization. LEAP draws on the design of the optimal synthesis algorithm QSearch by extending it with an incremental approach to determine constant prefix solutions for a circuit. By narrowing the search space, LEAP improves scalability from four to six qubit circuits. LEAP was evaluated with known quantum circuits such as QFT and physical simulation circuits like the VQE, TFIM, and QITE. LEAP can compile four qubit unitaries up to 59× faster than QSearch and five and six qubit unitaries with up to 1.2× fewer CNOTs compared to the QFAST package. LEAP can reduce the CNOT count by up to 36×, or 7× on average, compared to the CQC Tket compiler. Despite its heuristics, LEAP has generated optimal circuits for many test cases with a priori known solutions. The techniques introduced by LEAP are applicable to other numerical optimization based synthesis approaches.

Active and Programmable Metasurfaces with Semiconductor Materials and Devices

Active metasurfaces provide promising tunabilities to artificial meta−atoms with unnatural optical properties and have found important applications in dynamic cloaking, reconfigurable intelligent surfaces, etc. As the development of semiconductor technologies, electrically controlled metasurfaces with semiconductor materials and devices have become the most promising candidate for the dynamic and programmable applications due to the large modulation range, compact footprint, pixel−control capability, and small switching time. Here, a technical review of active and programmable metasurfaces is given in terms of semiconductors, which consists of metasurfaces with diodes, transistors, and newly rising semiconductor materials. Physical models, equivalent circuits, recent advances, and development trends are discussed collectively and critically. This review represents a broad introduction for readers just entering this interesting field and provides perspective and depth for those well−established.

Biphasic action potential and chaos in a symmetrical Chua Corsage Memristor-based circuit.

Neuromorphic computing provides unique computing and memory capabilities that could break the limitation of conventional von Neumann computing. Toward realizing neuromorphic computing, fabrication and synthetization of hardware elements and circuits to emulate biological neurons are crucial. Despite the striking progress in exploring neuron circuits, the existing circuits can only reproduce monophasic action potentials, and no studies report on circuits that could emulate biphasic action potentials, limiting the development of neuromorphic devices. Here, we present a simple third-order memristive circuit built with a classical symmetrical Chua Corsage Memristor (SCCM) to accurately emulate biological neurons and show that the circuit can reproduce monophasic action potentials, biphasic action potentials, and chaos. Applying the edge of chaos criterion, we calculate that the SCCM and the proposed circuit have the symmetrical edge of chaos domains with respect to the origin, which plays an important role in generating biphasic action potentials. Also, we draw a parameter classification map of the proposed circuit, showing the edge of chaos domain (EOCD), the locally active domain, and the locally passive domain. Near the calculated EOCD, the third-order circuit generates monophasic action potentials, biphasic action potentials, chaos, and ten types of symmetrical bi-directional neuromorphic phenomena by only tuning the input voltage, showing a resemblance to biological neurons. Finally, a physical SCCM circuit and some experimentally measured neuromorphic waveforms are exhibited. The experimental results agree with the numerical simulations, verifying that the proposed circuit is suitable as artificial neurons.

E-Spin: A Stochastic Ising Spin Based on Electrically-Controlled MTJ for Constructing Large-Scale Ising Annealing Systems

With its unique computer paradigm, the Ising annealing machine has become an emerging research direction. The Ising annealing system is highly effective at addressing combinatorial optimization (CO) problems that are difficult for conventional computers to tackle. However, Ising spins, which comprise the Ising system, are difficult to implement in high-performance physical circuits. We propose a novel type of Ising spin based on an electrically-controlled magnetic tunnel junction (MTJ). Electrical operation imparts true randomness, great stability, precise control, compact size, and easy integration to the MTJ-based spin. In addition, simulations demonstrate that the frequency of electrically-controlled stochastic Ising spin (E-spin) is 50 times that of the thermal disturbance MTJ-based spin (p-bit). To develop a large-scale Ising annealing system, up to 64 E-spins are implemented. Our Ising annealing system demonstrates factorization of integers up to 264 with a temporal complexity of around O(n). The proposed E-spin shows superiority in constructing large-scale Ising annealing systems and solving CO problems.

A Novel Secure Scan Design Based on Delayed Physical Unclonable Function

The advanced integrated circuits have been widely used in various situations including the Internet of Things, wireless communication, etc. But its manufacturing process exists unreliability, so cryptographic chips must be rigorously tested. Due to scan testing provides high test coverage, it is applied to the testing of cryptographic integrated circuits. However, while providing good controllability and observability, it also provides attackers with a backdoor to steal keys. In the text, a novel protection scheme is put forward to resist scan-based attacks, in which we first use the responses generated by a strong physical unclonable function circuit to solidify fuse-antifuse structures in a non-linear shift register (NLSR), then determine the scan input code according to the configuration of the fuse-antifuse structures and the styles of connection between the NLSR cells and the scan cells. If the key is right, the chip can be tested normally; otherwise, the data in the scan chain cannot be propagated normally, it is also impossible for illegal users to derive the desired scan data. The proposed technique not only enhances the security of cryptographic chips, but also incurs acceptable overhead.

Applications of negative permeability metamaterials for electromagnetic resonance type wireless power transfer systems

With the development of electric drive systems such as unmanned aerial vehicles and electric vehicles, the charging problem of power supply devices has become increasingly prominent. However, the traditional charging method requires physical circuits, which makes it impossible to achieve freedom of the position in actual use. The wireless power transmission technology, which mainly relies on electromagnetic wave to complete energy transmission, is expected to get rid of the restriction of physical space location and solve the problem of charging location, which has great potential in medical treatment, rescue, detection and other fields. However, the low transmission efficiency and short transmission distance caused by electromagnetic field leakage are the two main problems faced by radio energy transmission systems. In general, with the increase of transmission distance, the transmission efficiency will drop sharply. Fortunately, inserting a negative permeability metamaterial with extraordinary electromagnetic characteristics into the transmitting and receiving coils will greatly alleviate this attenuation trend and can also shield electromagnetic radiation to a certain extent. In this paper, some experiments of negative permeability metamaterials used in electromagnetic resonance type wireless power transfer systems are summarized for reference.

Dynamics of chaotic circuit networks with local bridges

We investigate the influence of a local bridge on a social network of 25 coupled chaotic circuits. From synchronization phenomena of coupled chaotic circuits, we show that coupled chaotic circuits connected at both ends of a local bridge easily break down. Through computer simulations, the network is predicted to switch between global synchronization and partial synchronization. To analyze synchronization behavior, we define the asynchronous probability for a given time interval. Moreover, we demonstrate in experiments using real physical circuits the same synchronization behavior.

VACSEN: A Visualization Approach for Noise Awareness in Quantum Computing

Quantum computing has attracted considerable public attention due to its exponential speedup over classical computing. Despite its advantages, today's quantum computers intrinsically suffer from noise and are error-prone. To guarantee the high fidelity of the execution result of a quantum algorithm, it is crucial to inform users of the noises of the used quantum computer and the compiled physical circuits. However, an intuitive and systematic way to make users aware of the quantum computing noise is still missing. In this paper, we fill the gap by proposing a novel visualization approach to achieve noise-aware quantum computing. It provides a holistic picture of the noise of quantum computing through multiple interactively coordinated views: a Computer Evolution View with a circuit-like design overviews the temporal evolution of the noises of different quantum computers, a Circuit Filtering View facilitates quick filtering of multiple compiled physical circuits for the same quantum algorithm, and a Circuit Comparison View with a coupled bar chart enables detailed comparison of the filtered compiled circuits. We extensively evaluate the performance of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">VACSEN</i> through two case studies on quantum algorithms of different scales and in-depth interviews with 12 quantum computing users. The results demonstrate the effectiveness and usability of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">VACSEN</i> in achieving noise-aware quantum computing.

Revelation and experimental verification of quasi-periodic bursting, periodic bursting, periodic oscillation in third-order non-autonomous memristive FitzHugh-Nagumo neuron circuit

It has been declared that constructing physical hardware circuits with the reproduction of abundant electrical activities of neurons is significant in neuron-based engineering applications. To this end, a novel third-order non-autonomous memristive FitzHugh-Nagumo (FHN) neuron circuit is designed by employing a first-order generalized memristive-diode-bridge (MDB) emulator and an AC voltage source. The memristive FHN neuron circuit can generate abundant electrical activities since the involvement of the MDB emulator. In theoretical analysis and numerical simulation, the corresponding circuit state equations and normalized system are formulated to analyze the characteristics of the equilibrium point and investigate the dynamical behaviors related to the internal resistor of the MDB emulator. Then phase portrait, time-domain waveform, bifurcation diagram, and Lyapunov exponent spectra are numerically simulated, from which abundant non-chaotic firing activities of quasi-periodic bursting, periodic bursting, and periodic oscillation are revealed. Additionally, the 0–1 test is utilized to further distinguish the above three non-chaotic behaviors. In hardware experiment, a breadboard hardware circuit is constructed and experimental measurements are executed. It is demonstrated that the experimental results well support the numerical simulations. Studying these non-chaotic behaviors is very important to understand the intrinsic nature of neuronal firing activities. Most notably, the numerical revelation and experimental verification of quasi-periodic bursting behavior have been rarely reported in the previously published literature.

Physical constraint-aware CNOT quantum circuit synthesis and optimization

Physical constraint-aware CNOT quantum circuit synthesis and optimization