Logic Functions Research Articles

Reconfigurable optical logic in silicon platform

In this paper, we present a novel, scalable, and reconfigurable optical switch that performs multiple computational logic functions simultaneously. The free-carrier depletion effect is used to perform non-volatile switching operations due to its high speed and low power consumption. We adopt the concept of optical memory using a phase-change material to realize the non-volatile reconfigurability without a constant power supply, in addition to providing a large operating bandwidth required for reconfigurability. The proposed reconfigurable optical logic architecture is realized in a compact microdisk resonator configuration, utilizing both the carrier-depletion-based modulation and phase-change optical memory. This is the first time these two modulation schemes are implemented in the same optical microdisk for the purpose of reconfigurable optical logic.

Mathematical digital quantum computation by means of much more logical skills

We expand Deutsch’s algorithm for determining the mappings of a logical function using four orthogonal states. Using this, we propose a parallel computation for all of the combinations of values in variables of a logical function using sixteen orthogonal states. As an application of our algorithm, we demonstrate two typical arithmetic calculations in the binary system. We study an efficiency for operating a full adder/half adder by quantum-gated computing. The two typical arithmetic calculations are (1+1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(1+1)$$\\end{document} and (2+3)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(2+3)$$\\end{document}. The typical arithmetic calculation (2+3)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(2+3)$$\\end{document} is faster than that of its classical apparatus which would require 43=64\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$4^3=64$$\\end{document} steps when we introduce the full adder operation. Another typical arithmetic calculation (1+1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(1+1)$$\\end{document} is faster than that of its classical apparatus which would require 42=16\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$4^2=16$$\\end{document} steps when we introduce only the half adder operation.

Ionic-confining-assisted multiple-mode tunable light emitting of carbon nanodots

Multiple-mode light emitting in one material system is tremendous desirable for various applications. Herein, we have developed an ionic crystal confining strategy to prepare the carbon nanodots (CDs) with quadruple-mode light emitting and demonstrated their promising application in information anti-counterfeiting via optical logic gates. In detail, the quadruple-mode light emitting of CDs (QM-CDs) are prepared with the citric acid and urea with NaOH matrix via microwave-assisted polymerization. Mechanically, the high-density ionic bonds stemmed from the NaOH ionic-crystal can effectively inactivate nonradiative defect centers, stabilize triplet excitons, increase absorption cross-section and boost resonance energy transfer, evoking the outstanding solid-state fluorescence, upconversion photoluminescence (UCPL), phosphorescence, and chemiluminescence simultaneously. Meanwhile, the isolated NaOH matrix can promote the confining aggregation of CDs, leading to the redshifted emission wavelength and endowing the light emitting with tunable wavelength. With the excitability of logic functions between the light emitting and controlled excitation, the programmable multiple-inputs logic gates are established with the QM-CDs, enabling the application in high-throughput logical operations and information anti-counterfeiting. This research provides a new insight into the synthesize of multiple-mode luminescent CDs, and thus promote the applications of nanomaterials in intelligent encryption and anti-counterfeiting.

Design of Reconfigurable Logic Block Based Sequential Circuits Using Look Up Table Logics

Reconfigurable sequential circuits find applications in various digital systems, including communication networks, data processing units, embedded systems, and FPGA-based designs. Their ability to adapt and reconfigure their functionality onthe-fly allows them to accommodate dynamic requirements and optimize the use of hardware resources. Traditional implementations of sequential circuits involve static configurations, where the logic and functionality are fixed during synthesis. While these methods are straightforward to design and implement, they lack adaptability and cannot be modified without redesigning the entire circuit. The proposed method involves the utilization of a dedicated Reconfigurable Logic Block (RLB) within the sequential circuits, allowing for dynamic configuration changes without altering the overall circuit structure. The RLB can be programmed to provide different logic functions using look up tables, multiplexers, enabling the sequential circuit such as counters and shift registers to change its behaviour.

Metasurface computing components that support dual channel parallel processing and provide full type logic gate options

The logic gate components based on electromagnetic waves are crucial for building a digital computing platform with batch computing and low-cost energy consumption requirements. However, most of the reported logic gates have only one computational channel and have a single function. In order to improve the channel capacity and versatility of logic gates, we design a simple and compact graphene metasurface for dual channel parallel computing, with each channel's function being switchable across all types of logic functions. In the design, we combine the advantages of reconfigurable metasurfaces and polarization sensitive metasurfaces. Based on the polarization sensitive characteristics, we integrate two polarization logic gates into a single device. These two polarization logic gates can work simultaneously, and the crosstalk between them is 0. Based on the reconfigurable feature, the functions of both logic gates can be freely selected from NOT, AND, NAND, OR, NOR, XOR and XNOR. So, this component can achieve simultaneous operation of any two logical functions, and there are 49 combinations available. Our design philosophy provides inspiration for achieving ultra fast and high-density integrated signal processing.

Building a knowledge base for autonomous control of unmanned vehicles

This article presents an approach to building and using a knowledge base for autonomous control of unmanned vehicles (UV). Agriculture is presented as a subject area which features and limitations must be considered. The lack of a sufficient number and level of qualifications of machine operator leads to equipment downtime, a decrease in crop yields and the efficiency of using chemical fertilizers. The use of UV makes it possible to reduce the influence of these factors and the harmful effects on people working in agriculture. The article focuses on taking into account the features and limitations of the subject area when constructing the trajectory of unmanned vehicles and controlling processing facilities. An approach is proposed that consists of separate stages of designing a knowledge base schema, automating the process of filling the knowledge base and organizing the logical inference function. For each stage, developed models and algorithms are presented that help to form and use a knowledge base when solving the problem of autonomous control of unmanned vehicles. The article contains examples and illustrations designed to increase the clarity of the proposed approach.

A Simple and Rapid Quinoline Schiff Base as a Fluorescent Probe for Zn2+ and Its Application in Test Strips

AbstractA simple fluorescent probe, (E)‐N‐(3‐methoxy‐4‐methylphenyl)‐1‐(quinolin‐2‐yl)methanimine (L), was synthesized via Schiff base condensation reaction between quinoline‐2‐carboxaldehyde and 3‐methoxy‐4‐methylaniline. L can be used as a ′turn‐on′ fluorescent probe for the selective and sensitive detection of Zn2+ ions in a CH3OH/HEPES medium. The detection limit was 1.04×10−7 M. Job plot analysis shows that the binding stoichiometry of L and Zn2+ is 1 : 1, further verified by the single crystal structure. The fluorescence‐enhanced response of L towards Zn2+ ions may be related to the chelation‐enhanced fluorescence (CHEF) supported by theoretical calculations. By adding EDTA, the reversibility of the probe binding to Zn2+ ions is demonstrated, enabling the construction of a functional molecular logic circuit. In addition, probe L was successfully incorporated into test strips for the quantitative detection of Zn2+.

Long distance all-optical logic operations through a single multimode fiber empowered by wavefront shaping

Multimode fibers (MMFs) are a promising solution for high-throughput signal transmission in the time domain. However, crosstalk among different optical modes within the MMF scrambles input information and creates seemingly random speckle patterns at the output. To characterize this process, a transmission matrix (TM) can be used to relate input and output fields. Recent innovations use TMs to manipulate the output field by shaping the input wavefront for exciting advances in deep-brain imaging, neuron stimulation, quantum networks, and analog operators. However, these approaches consider input/output segments as independent, limiting their use for separate signal processing, such as logic operations. Our proposed method, which makes input/output segments as interdependent, adjusts the phase of corresponding output fields using phase bias maps superimposed on input segments. Coherent superposition enables signal logic operations through a 15-m-long MMF. In experiments, a single optical logic gate containing three basic logic functions and cascading multiple logic gates to handle binary operands is demonstrated. Bitwise operations are performed for multi-bit logic operations, and multiple optical logic gates are reconstructed simultaneously in a single logic gate with polarization multiplexing. The proposed method may open new avenues for long-range logic signal processing and transmission via MMFs.

MTS-PRO2SAT: Hybrid Mutation Tabu Search Algorithm in Optimizing Probabilistic 2 Satisfiability in Discrete Hopfield Neural Network

The primary objective of introducing metaheuristic algorithms into traditional systematic logic is to minimize the cost function. However, there is a lack of research on the impact of introducing metaheuristic algorithms on the cost function under different proportions of positive literals. In order to fill in this gap and improve the efficiency of the metaheuristic algorithm in systematic logic, we proposed a metaheuristic algorithm based on mutation tabu search and embedded it in probabilistic satisfiability logic in discrete Hopfield neural networks. Based on the traditional tabu search algorithm, the mutation operators of the genetic algorithm were combined to improve its global search ability during the learning phase and ensure that the cost function of the systematic logic converged to zero at different proportions of positive literals. Additionally, further optimization was carried out in the retrieval phase to enhance the diversity of solutions. Compared with nine other metaheuristic algorithms and exhaustive search algorithms, the proposed algorithm was superior to other algorithms in terms of time complexity and global convergence, and showed higher efficiency in the search solutions at the binary search space, consolidated the efficiency of systematic logic in the learning phase, and significantly improved the diversity of the global solution in the retrieval phase of systematic logic.

Coordination nanosheets based molecular computing for detection and differentiation of high-energy explosives TATB and FOX-7

Detection and differentiation of explosives is an issue of immediacy for security and environmental monitoring. At present, the most operated explosive system combines primary and secondary explosives. Although various advances are presently equipped for identifying primary explosives, the insensitive nature of secondary explosives makes their detection and differentiation challenging. Here, we report three coordination nanosheets (CNs) AM-8-Eu, AM-8-Tb, and AM-8-Zn containing three-way terpyridine ligands (AM-8) and Eu(III), Tb(III), and Zn(II) ions. These CNs act as a highly selective platform for detecting unexplored high-energy explosive 1,1-Diamino-2,2-dinitro ethylene (FOX-7) in solid and solution phases. For AM-8-Zn, calculated molecular electrostatic surface potential revealed two modes of interactions for triaminotrinitrobenzene (TATB) and FOX-7, producing two distinct spectral responses. Digital analysis of these responses revealed a complimentary implication (IMP)/not implication (NIMP) logic function. Finally, the unique feature of IMP gate is used to define all possible sixteen distinct binary Boolean operations on two logic values for “functional completeness”. The detection and differentiation of such insensitive high-energy explosives TATB and FOX-7, where Boolean logic can process information through distinct binary responses in solid and solution phases, have not been witnessed hitherto in a single chemical platform.

All-in-one, all-optical logic gates using liquid metal plasmon nonlinearity

Electronic processors are reaching the physical speed ceiling that heralds the era of optical processors. Multifunctional all-optical logic gates (AOLGs) of massively parallel processing are of great importance for large-scale integrated optical processors with speed far in excess of electronics, while are rather challenging due to limited operation bandwidth and multifunctional integration complexity. Here we for the first time experimentally demonstrate a reconfigurable all-in-one broadband AOLG that achieves nine fundamental Boolean logics in a single configuration, enabled by ultrabroadband (400–4000 nm) plasmon-enhanced thermo-optical nonlinearity (TONL) of liquid-metal Galinstan nanodroplet assemblies (GNAs). Due to the unique heterogeneity (broad-range geometry sizes, morphology, assembly profiles), the prepared GNAs exhibit broadband plasmonic opto-thermal effects (hybridization, local heating, energy transfer, etc.), resulting in a huge nonlinear refractive index under the order of 10−4−10−5 within visual-infrared range. Furthermore, a generalized control-signal light route is proposed for the dynamic TONL modulation of reversible spatial-phase shift, based on which nine logic functions are reconfigurable in one single AOLG configuration. Our work will provide a powerful strategy on large-bandwidth all-optical circuits for high-density data processing in the future.

YOLOFM: an improved fire and smoke object detection algorithm based on YOLOv5n

To address the current difficulties in fire detection algorithms, including inadequate feature extraction, excessive computational complexity, limited deployment on devices with limited resources, missed detections, inaccurate detections, and low accuracy, we developed a highly accurate algorithm named YOLOFM. We utilized LabelImg software to manually label a dataset containing 18644 images, named FM-VOC Dataset18644. In addition, we constructed a FocalNext network, which utilized the FocalNextBlock module from the CFnet network. This improves the integration of multi-scale information and reduces model parameters. We also proposed QAHARep-FPN, an FPN network that integrates the structure of quantization awareness and hardware awareness. This design effectively reduces redundant calculations of the model. A brand-new compression decoupled head, named NADH, was also created to enhance the correlation between the decoupling head structure and the calculation logic of the loss function. Instead of using the CIoU loss for bounding box regression, we proposed a Focal-SIoU loss. This promotes the swift convergence of the network and enhances the precision of the regression. The experimental results showed that YOLOFM improved the baseline network’s accuracy, recall, F1, mAP50, and mAP50-95 by 3.1%, 3.9%, 3.0%, 2.2%, and 7.9%, respectively. It achieves an equilibrium that combines performance and speed, resulting in a more dependable and accurate solution for detection jobs.

Design and analysis of 4-bit absolute-value comparator in 65nm technology using hybrid TG/CMOS

Comparators are an important part of the calculator architecture, and rapid advances in semiconductor and electronics technology have placed higher demands on their performance. Optimization of digital systems involves several levels in order to make improvements in their power consumption, delay, and other parameters. This paper designs a low-power, high speed, and area efficient 4-bit absolute-value comparator, which utilizes a static Complementary Metal-Oxide-Semiconductor (CMOS) and Transmission Gate (TG) hybrid structure. The design optimizes the system at the level of separate circuit blocks, logic gates and transistors. The logic functions are realized by means of transcoding and magnitude Comparison, and the input signals are all driven by two-stage inverters. MUX and XOR with excellent performance of TG structure are implemented using simulation and analysis. In this paper, the transistor sizes and supply voltages of each logic gate are calculated and optimized using MATLAB by applying logic effort theory. The design uses a 65nm technology, and transient simulation of the overall system in Cadence successfully realizes its logic functions with 0.83ns delay and 49.6uw power consumption, proving the effectiveness of the design. This study based on theoretical calculations and simulations is a good reference for the design and theoretical study of very large-scale integrated circuits (VLSI).

Ultraflexible, High-Performance Transistors and Logic Circuits on Biocompatible Polylactic Acid (PLA) Substrate.

Wearable and implantable devices have gained significant popularity, playing a crucial role in smart healthcare and human-machine interfaces, which necessitates the development of more complex electronic devices and circuits on biocompatible flexible materials. Polylactic acid (PLA) stands out due to its biodegradability, cost-effectiveness, and low immunogenicity. In this study, we utilize a solution-based spin-coating method to produce high-quality PLA thin films, serving as substrates for the fabrication of thin-film transistors (TFTs) in which the dielectric layer material is silicon dioxide, the channel layer material is IGZO, and the gate, drain, and source material is ITO at low temperatures (<40 °C) through a shadow masking technique. The resulting PLA-TFT devices exhibited remarkable flexibility, biocompatibility, and impressive electrical characteristics, including a charge carrier mobility of 27.81 cm2/(V s), a subthreshold swing of 162.8 mV/decade, and an ON/OFF current ratio of up to 1 × 106, and maintained performance under various deformations. We successfully constructed fundamental logic gate circuits using PLA-TFTs, including AND, OR, and NOT gates, which effectively performed logical functions and demonstrated stability under diverse bending conditions. These research findings provide valuable support for future endeavors in fabricating intricate logic circuits and realizing advanced functionalities on biocompatible flexible materials.

Diffusive kinks turn kirigami into machines

Kinks define boundaries between distinct configurations of a material. In the context of mechanical metamaterials, kinks have recently been shown to underpin logic, shape-changing and locomotion functionalities. So far such kinks propagate by virtue of inertia or of an external load. Here, we discover the emergence of propagating kinks in purely dissipative kirigami. To this end, we create kirigami that shape-change into different textures depending on how fast they are stretched. We find that if we stretch fast and wait, the viscoelastic kirigami can eventually snap from one texture to another. Crucially, such a snapping instability occurs in a sequence and a propagating diffusive kink emerges. As such, it mimics the slow sequential folding observed in biological systems, e.g., Mimosa Pudica. We finally demonstrate that diffusive kinks can be harnessed for basic machine-like functionalities, such as sensing, dynamic shape morphing, transport and manipulation of objects.

An Agent-Based Model to Reproduce the Boolean Logic Behaviour of Neuronal Self-Organised Communities through Pulse Delay Modulation and Generation of Logic Gates.

The human brain is arguably the most complex "machine" to ever exist. Its detailed functioning is yet to be fully understood, let alone modelled. Neurological processes have logical signal-processing and biophysical aspects, and both affect the brain's structure, functioning and adaptation. Mathematical approaches based on both information and graph theory have been extensively used in an attempt to approximate its biological functioning, along with Artificial Intelligence frameworks inspired by its logical functioning. In this article, an approach to model some aspects of the brain learning and signal processing is presented, mimicking the metastability and backpropagation found in the real brain while also accounting for neuroplasticity. Several simulations are carried out with this model to demonstrate how dynamic neuroplasticity, neural inhibition and neuron migration can reshape the brain's logical connectivity to synchronise signal processing and obtain certain target latencies. This work showcases the importance of dynamic logical and biophysical remodelling in brain plasticity. Combining mathematical (agents, graph theory, topology and backpropagation) and biomedical ingredients (metastability, neuroplasticity and migration), these preliminary results prove complex brain phenomena can be reproduced-under pertinent simplifications-via affordable computations, which can be construed as a starting point for more ambitiously accurate simulations.

Logical activation functions for training arbitrary probabilistic Boolean operations

In this work, we introduce a family of novel activation functions for deep neural networks that approximate n-ary, or n-argument, probabilistic logic. Logic has long been used to encode complex relationships between claims that are either true or false. Thus, these activation functions provide a step towards models that can efficiently encode information. Unfortunately, typical feedforward networks with elementwise activation functions cannot capture certain relationships succinctly, such as the exclusive disjunction (p xor q) and conditioned disjunction (if c then p else q). Our n-ary activation functions address this challenge by approximating belief functions (probabilistic Boolean logic) with logit representations of probability and experiments demonstrate the ability to learn arbitrary logical ground truths in a single layer. Further, by representing belief tables using a basis that associates the number of nonzero parameters with the effective arity of each belief function, we forge a concrete relationship between logical complexity and sparsity, thus opening new optimization approaches to suppress logical complexity during training. We provide a computationally efficient PyTorch implementation and test our activation functions against other logic-approximating activation functions on both traditional machine learning tasks as well as reproducing known logical relationships.

The ecological function of thyroid hormones.

Thyroid hormones (TH) are central hormonal regulators, orchestrating gene expression and complex biological processes vital for growth and reproduction in variable environments by triggering specific developmental processes in response to external cues. TH serve distinct roles in different species: inducing metamorphosis in amphibians or teleost fishes, governing metabolic processes in mammals, and acting as effectors of seasonality. These multifaceted roles raise questions about the underlying mechanisms of TH action. Recent evidence suggests a shared ecological role of TH across vertebrates, potentially extending to a significant portion of bilaterian species. According to this model, TH ensure that ontogenetic transitions align with environmental conditions, particularly in terms of energy expenditure, helping animals to match their ontogenetic transition with available resources. This alignment spans post-embryonic developmental transitions common to all vertebrates and more subtle adjustments during seasonal changes. The underlying logic of TH function is to synchronize transitions with the environment. This review briefly outlines the fundamental mechanisms of thyroid signalling and shows various ways in which animals use this hormonal system in natural environments. Lastly, we propose a model linking TH signalling, environmental conditions, ontogenetic trajectory and metabolism. This article is part of the theme issue 'Endocrine responses to environmental variation: conceptual approaches and recent developments'.

Randomized Testing of RISC-V CPUs Using Direct Instruction Injection

TestRIG (Testing with Random Instruction Generation) is a testing framework for RISC-V implementations. The RISC-V community has standardized a formal model of the architecture in the Sail language <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> , giving a human-readable specification that can also be used for simulation and verification. The Sail language is designed for this purpose by allowing instruction semantics to be described conveniently (for example, by supporting variable bit-widths). Ideally, a RISC-V implementor could formally prove equivalence between their implementation and the Sail model, but proof tools are not yet sufficiently automated to be routinely used on the whole-processor level. They instead focus on equivalence between combinational logic functions, with verification of a full out-of-order microarchitecture remaining an open problem. As a pragmatic compromise, we use TestRIG to check equivalence between the model and an implementation by generating random instruction sequences, executing the same sequences on the model and the implementation under test, and comparing execution traces (tandem execution). This approach does not prove equivalence but can demonstrate divergence, and is usable in all stages of development.

Molecular circuit for exponentiation based on the domain coding strategy.

DNA strand displacement (DSD) is an efficient technology for constructing molecular circuits. However, system computing speed and the scale of logical gate circuits remain a huge challenge. In this paper, a new method of coding DNA domains is proposed to carry out logic computation. The structure of DNA strands is designed regularly, and the rules of domain coding are described. Based on this, multiple-input and one-output logic computing modules are built, which are the basic components forming digital circuits. If the module has n inputs, it can implement 2n logic functions, which reduces the difficulty of designing and simplifies the structure of molecular logic circuits. In order to verify the superiority of this method for developing large-scale complex circuits, the square root and exponentiation molecular circuits are built. Under the same experimental conditions, compared with the dual-track circuits, the simulation results show that the molecular circuits designed based on the domain coding strategy have faster response time, simpler circuit structure, and better parallelism and scalability. The method of forming digital circuits based on domain coding provides a more effective way to realize intricate molecular control systems and promotes the development of DNA computing.