Computational Logic Research Articles

Anti-Interference All-Optical Logic Computing Based on a 2D Polarization-Sensitive Photodiode.

Optical logic operation is promising for ultrafast information processing and optical computing due to the high computation speed and low power consumption. However, conventional optical logic devices require either a complex structure and circuit design or a constant voltage supply, which impedes the development of high-density integrated circuits. Here, all-optical logic devices are designed using a self-powered polarization-sensitive photodiode of the GeSe homojunction, which is attributed to an anisotropic band structure and built-in electric field. The single photodiode can realize linear logic functions (AND, OR, NAND) and a nonlinear logic gate (XOR) by programming wavelength, power density, and polarization angle. Moreover, complex logic functions (XNOR, Y = IN1, Y = IN2, Y = IN1, and Y = IN2) can be achieved through integrating two photodiodes in parallel. In addition, the neural network algorithm is utilized to validate the feasibility of all-optical logic computing and anti-interference. This work proposes an avenue to design an all-optical reconfigurable logic operation in polarization-sensitive devices.

A Propositional Cirquent Calculus for Computability Logic

Cirquent calculus is a proof system with inherent ability to account for sharing subcomponents in logical expressions. Within its framework, this article constructs an axiomatization CL18 of the basic propositional fragment of computability logic—the game-semantically conceived logic of computational resources and tasks. The nonlogical atoms of this fragment represent arbitrary so called static games, and the connectives of its logical vocabulary are negation and the parallel and choice versions of conjunction and disjunction. The main technical result of the article is a proof of the soundness and completeness of CL18 with respect to the semantics of computability logic.

2025 Roadmap on 3D Nano-magnetism.

The transition from planar (2D) to three-dimensional (3D) magnetic nanostructures represents a significant advancement in both fundamental research and practical applications, offering vast potential for next-generation technologies like ultrahigh-density storage, memory, logic, and neuromorphic computing. Despite being a relatively new field, the emergence of 3D nanomagnetism presents numerous opportunities for innovation, prompting the creation of a comprehensive roadmap by leading international researchers. This roadmap aims to facilitate collaboration and interdisciplinary dialogue to address challenges in materials science, physics, engineering, and computing.
The roadmap comprises eighteen sections, roughly divided into three parts. The first section explores the fundamentals of 3D nanomagnetism, focusing on recent trends in fabrication techniques and imaging methods crucial for understanding complex spin textures, curved surfaces, and small-scale interactions. Techniques such as two-photon lithography and focused electron beam-induced deposition enable the creation of intricate 3D architectures, while advanced imaging methods like electron holography and Lorentz electron Ptychography provide sub-nanometer resolution for studying magnetization dynamics in three dimensions. Various 3D magnetic systems, including coupled multilayer systems, artificial spin ice, magneto-plasmonic systems, topological spin textures, and molecular magnets, are discussed.
The second section introduces analytical and numerical methods for investigating 3D nanomagnetic structures and curvilinear systems, highlighting geometrically curved architectures, interconnected nanowire systems, and other complex geometries. Finite element methods are emphasized for capturing complex geometries, along with direct frequency domain solutions for addressing magnonic problems.
The final section focuses on 3D magnonic crystals and networks, exploring their fundamental properties and potential applications in magnonic circuits, memory, and spintronics. Computational approaches using 3D nanomagnetic systems and complex topological textures in 3D spintronics are highlighted for their potential to enable faster and more energy-efficient computing.&#xD.

Toward magnonic logic and neuromorphic computing: controlling spin waves by spin-polarized current

Toward magnonic logic and neuromorphic computing: controlling spin waves by spin-polarized current

Platform Pragmatics

This article proposes platform pragmatics as a framework for understanding collective behaviour and forms of labour within platform ecosystems. It contributes to the field of platform criticism by problematising a certain view of users as passive victims of surveillance and algorithmic governmentality. The main argument is developed by thinking through the production of content and forms by users, and their circulation through computational logic and aective contagion. Through some illustrative cases and analyses of cultural habits, the article addresses the political and aesthetic configuration of these forms of production — not only of content/forms, but also of culture and subjectivity. This is explored by thinking through three themes: the subsumption of creativity and opportunism in platform economies; the mobilisation of speculative temporalities not only in computation but also across user practices; and the generalisation of self-reflexivity as a feminised cultural behaviour and aesthetic mode. Finally, I propose to understand platform pragmatics as a mode of subaltern power, that might be alien to traditional political reason, but precisely because of this needs to be grappled with through inventive cultural and social criticism.

Synthetic translational coupling element for multiplexed signal processing and cellular control.

Repurposing natural systems to develop customized functions in biological systems is one of the main thrusts of synthetic biology. Translational coupling is a common phenomenon in diverse polycistronic operons for efficient allocation of limited genetic space and cellular resources. These beneficial features of translation coupling can provide exciting opportunities for creating novel synthetic biological devices. Here, we introduce a modular synthetic translational coupling element (synTCE) and integrate this design with de novo designed riboregulators,toehold switches. A systematic exploration of sequence domain variants for synTCEs led to the identification of critical design considerations for improving the system performance. Next, this design approach was seamlessly integrated into logic computations and applied to construct multi-output transcripts with well-defined stoichiometric control. This module was further applied to signaling cascades for combined signal transduction and multi-input/multi-output synthetic devices. Further, the synTCEs can precisely manipulate the N-terminal ends of output proteins, facilitating effective protein localization and cellular population control. Therefore, the synTCEs could enhance computational capability and applicability of riboregulators for reprogramming biological systems, leading to future applications in synthetic biology, metabolic engineering and biotechnology.

TEACHING COMPUTATIONAL THINKING IN SAUDI ARABIAN SCHOOLS USING SMARTPHONE APPS

This study investigates the efficacy of smartphone applications in teaching computational thinking to students in Saudi Arabian primary and secondary schools. Computational thinking, encompassing problem-solving, computational logic, and algorithmic thinking, is an essential skill in the modern world. The research assesses various educational apps that support the development of computational thinking and examines their integration into the Saudi curriculum. This study incorporates qualitative and quantitative research techniques to provide an inclusive perspective. Participants included primary and secondary school students from various schools in Saudi Arabia. The research employed pre- and post-tests for quantitative analysis and interviews and questionnaires for qualitative data. Quantitative results include pre- and post-tests of the students in computational thinking with the aid of co-varying with Computational thinking, while interviews and questionnaires with teachers and students offer qualitative data. Best-selling educational applications for ScratchJr, Lightbot, Cargo-Bot, and Kodable are compared concerning how efficiently they introduce programming ideas and encourage rational thinking. Results have suggested that smartphone applications have a positive influence on students’ computational skills. An enhanced standard is also noticed regarding the students’ aspects that involve problem analysis, identification of pattern, and formation of algorithm. The use of applications such as ScratchJr and Lightbot is justified regarding an application’s capacity to improve students’ motivation and willingness to learn computational concepts. Teachers indicate that their students have shown more concern and engagement mainly when the teacher integrates these apps. Hence, based on the findings of the study, it is evident that incorporating Smartphone applications into the curriculum will lead to a reforming change in the teaching approaches towards efficiency as well as feasibility of the learners. These findings are valuable for the Saudi context for policy and teaching enhancement, signaling the need to provide more resources in digital tools and invest in the professional development of teachers to capture the virtues of advanced technology in improving learners’ performance.

Lightweight skin cancer detection IP hardware implementation using cycle expansion and optimal computation arrays methods

Skin cancer is recognized as one of the most perilous diseases globally. In the field of medical image classification, precise identification of early-stage skin lesions is imperative for accurate diagnosis. However, deploying these algorithms on low-cost devices and attaining high-efficiency operation with minimal energy consumption poses a formidable challenge due to their intricate computational demands. This study proposes a lightweight hardware design based on a convolutional neural network (CNN) for real-time processing of skin disease classifiers on portable devices. Our skin cancer recognition processor utilizes an optimally parallel designed processing engine (PE) for global computation, which greatly reduces hardware resource utilization by multiplexing of computational unit circuits. In addition, a design approach that provides loop unrolling effectively reduces the number of data accesses, thereby reducing computational complexity and logic resource requirements. The hardware circuits in this design perform data inference in convolutional, pooling, and fully connected layers based on 16-bit floating-point numbers. Evaluation of the HAM10000 database dataset shows that the architecture achieves an average classification accuracy of 97.8 %. We are the first to implement an all-hardware FPGA-based skin cancer detection platform that offers a 3.5x speedup in recognition compared to existing skin cancer accelerators at 50 MHz while consuming only 0.48 W of power. The implementation of this hardware architecture meets the major constraints of portable devices, featuring low resource utilization, low power consumption, and cost-effectiveness, while still providing efficient classification and high accuracy results.

Verifying chip designs at RTL level

As chip designs become increasingly complex, the potential for errors and defects in circuits inevitably rises, posing significant challenges to chip security and reliability. This study investigates the use of the SAT-based bounded model checking (BMC) for Propositional Projection Temporal Logic (PPTL) to verify Verilog chip designs at the register transfer level (RTL). To this end, we propose an algorithm to implement automated extraction of state transfer relations from AIGER netlist and construction of Kripke structure. Additionally, we employ PPTL with the full regular expressiveness to describe the circuit properties to be verified, especially the periodic repetitive properties. This is not possible with Linear Temporal Logic (LTL) and Computational Tree Logic (CTL). By combining the PPTL properties with finite system paths and transforming them into conjunctive normal forms (CNFs), we utilize an SAT solver for verification. Experimental results demonstrate that our verification tool, SAT-BMC4PPTL, achieves higher verification efficiency and comprehensiveness.

From Molecular Electronics to Molecular Intelligence.

Molecular electronics is a field that explores the ultimate limits of electronic device dimensions by using individual molecules as operable electronic devices. Over the past five decades since the proposal of a molecular rectifier by Aviram and Ratner in 1974 ( Chem. Phys. Lett.1974,29, 277-283), researchers have developed various fabrication and characterization techniques to explore the electrical properties of molecules. With the push of electrical characterizations and data analysis methodologies, the reproducibility issues of the single-molecule conductance measurement have been chiefly resolved, and the origins of conductance variation among different devices have been investigated. Numerous prototypical molecular electronic devices with external physical and chemical stimuli have been demonstrated based on the advances of instrumental and methodological developments. These devices enable functions such as switching, logic computing, and synaptic-like computing. However, as the goal of molecular electronics, how can molecular-based intelligence be achieved through single-molecule electronic devices? At the fiftieth anniversary of molecular electronics, we try to answer this question by summarizing recent progress and providing an outlook on single-molecule electronics. First, we review the fabrication methodologies for molecular junctions, which provide the foundation of molecular electronics. Second, the preliminary efforts of molecular logic devices toward integration circuits are discussed for future potential intelligent applications. Third, some molecular devices with sensing applications through physical and chemical stimuli are introduced, demonstrating phenomena at a single-molecule scale beyond conventional macroscopic devices. From this perspective, we summarize the current challenges and outlook prospects by describing the concepts of "AI for single-molecule electronics" and "single-molecule electronics for AI".

Study of Topological Spaces that Don’t Rely on Points as their Basis

Traditionally, the concept of points and neighborhood structures has been quite dominant in defining and further analyzing various properties in the study of topological spaces. In pointless topology-or point-free topology, also referred to as locale theory-the key emphasis is shifted from points to lattices of open sets. In addition to gaining further insight into spatial properties, this approach has important implications in fields like theoretical computer science, logic, and categorical theory. It is the purpose of the present work to be mainly interested in issues of the foundation of point-free topology: locales, frames, mutual relationships between them; the ways of interpreting classical topological concepts in the new language and the strong and weak points of such a point-free view. In the process, we focus on some of the significant applications of point-free topology, both within mathematics and beyond. The present paper is an attempt to give a broad overview of pointfree topology, discussing both its theoretical basis and its practical significance.

Revealing Bipolar Photoresponse in Multiheterostructured WTe2-GaTe/ReSe2-WTe2 P-N Diode by Hybrid 2D Contact Engineering.

The van der Waals (vdW) heterostructures based on two-dimensional (2D) semiconducting materials have been thoroughly investigated with regard to practical applications. Recent studies on 2D materials have reignited attraction in the p-n junction, with promising potential for applications in both electronics and optoelectronics. 2D materials provide exceptional band structural diversity in p-n junction devices, which is rare in regular bulk semiconductors. In this article, we demonstrate a p-n diode based on multiheterostructure configuration, WTe2-GaTe-ReSe2-WTe2, where WTe2 acts as heterocontact with GaTe/ReSe2 junction. Our devices with heterocontacts of WTe2 showed excellent performance in electronic and optoelectronic characteristics as compared to contacts with basic metal electrodes. However, the highest rectification ratio was achieved up to ∼2.09 × 106 with the lowest ideality factor of ∼1.23. Moreover, the maximum change in photocurrent (Iph) is measured around 312 nA at Vds = 0.5 V. The device showed a high responsivity (R) of 4.7 × 104 m·AW-1, maximum external quantum efficiency (EQE) of 2.49 × 104 (%), and detectivity (D*) of 2.1 × 1011 Jones at wavelength λ = 220 nm. Further, we revealed the bipolar photoresponse mechanisms in WTe2-GaTe-ReSe2-WTe2 devices due to band alignment at the interface, which can be modified by applying different gate voltages. Hence, our promising results render heterocontact engineering of the GaTe-ReSe2 heterostructured diode as an excellent candidate for next-generation optoelectronic logic and neuromorphic computing.

Sequence-Unconstrained DNA Computing: DSN cycling and PER circuitry for dynamic miRNAs analysis and multifunctional logic operations

DNA strand displacement and enzyme-driven catalysis are pivotal in regulating molecular interactions and constructing molecular logic circuits. However, their application in intricate hierarchical cascading networks has been hindered by sequence crosstalk restrictions on the multiple inputs and outputs. In this study, we present a sequence-unconstrained strategy to implement versatile molecular logic circuits, relying on duplex-specific nuclease (DSN)-assisted cycling and primer exchange reaction (PER) amplification circuitry (DSN-PER). Employing linear capture probe (CP) conjugated with magnetic beads (MBs) significantly minimizes crosstalk reactions compared to the previous molecular beacon probe (MBP) for DNA barcoding. Importantly, the sequence design of “barcodes” is fully independent of target binding sites on MBs, allowing for the sensitive detection of a broad range of microRNAs (miRNAs) using the DSN-PER method. Specifically, this platform supports the programming of common logic computations (YES, NOT, OR, INHIBIT, AND, and NOR) and hierarchical circuit operation (OR-AND) in response to a specific pattern of varying miRNAs. These versatile logic circuits offer unique features with flexible sequence design, potentially broadening the applications of dynamic nucleic acid nanotechnologies in multiplexed bio-computation, intelligent diagnostics, and sophisticated DNA nanodevices.

Clinical Utility of Synthesized 18-Lead Electrocardiography.

Eighteen-lead electrocardiography (18-ECG) includes, in addition to those in standard 12-lead ECG (12-ECG), six additional chest leads: V7-V9 and V3RV5R. Leads V7-V9 require the patient to be in a lateral decubitus position for the electrodes to be attached to the back. Synthesized 18-ECG (syn18-ECG) is a method that only records 12-ECG and uses computational logic to record the posterior wall (V7-V9) and right-sided (V3R-V5R) leads. We review the clinical utility of syn18-ECG in conditions including acute coronary syndromes, arrhythmias, acute pulmonary embolism, and Duchenne muscular dystrophy. The syn18-ECG waveform correlates well with the actual 18-ECG waveform, indicating that syn18-ECG is an excellent substitute for 18-ECG, excluding negative T waves. ST elevation in leads V7-V9 has the effect of reducing missed acute coronary syndromes in the posterior wall. In cases of arrhythmia, syn18-ECG can accurately estimate the target site of radiofrequency catheter ablation using a simple algorithm. The use of additional leads in Duchenne muscular dystrophy is expected to provide new insights. To facilitate gaining more knowledge regarding diseases that have not yet been investigated, it is imperative that the cost of syn18-ECG is reduced in the future.

К вопросу об эпистемологии, сознании и интеллекте

This paper is devoted to issues of epistemology, which has recently acquired par­ticular relevance in the national philosophy. The role of cultural-historical episte­mology in the modern theory of knowledge is revealed, where the authors hold the idea that knowing the origin and development of knowledge itself, and its cultural conditioning in specific historical experiences contributes to a better un­derstanding of its significance and the scope of use. The authors present their vi­sion of the problem of transition from gnosiology to epistemology as from a strict prescribed methodology to the choice of one’s ways and methods of con­ducting science, where a significant role is given to such disciplines as computer science and logic. In this context, the relationship between consciousness and in­telligence with the theory of knowledge, in particular with cultural-historical epistemology, is also analyzed, since both the philosophy of consciousness and epistemology seek to understand the nature of knowledge and beliefs based on our conscious experience. This approach, considering the influence of social norms, values and cultural traditions on our cognition and thinking, stimulates the development of the theoretical basis of epistemology and its practical appli­cation. The authors conclude that modern research in the field of consciousness and artificial intelligence and their application in the methodology of epistemo­logy contribute not only to rethinking views on the nature of subjectivity but also to establishing the objectivity of our judgments. Ultimately, this leads to the inte­gration of collective and individual consciousness as an important factor in un­derstanding the world and forming scientific knowledge

Mi Superpoder es la Programación: A tool for teaching programming to children and youth

Mi Superpoder es la Programación is a web tool designed to teach programming to children and young people. It focuses on developing logical thinking through interactive exercises that cover computer parts recognition, sequences, patterns, and flowcharts. The tool was developed to address the educational needs identified in the social project of the same name, where modern technologies and a serverless-based architecture were used to create an accessible and effective solution for teaching programming. Initial results indicate that students found the tool useful and demonstrated improvements in their understanding of computational logic. This analysis is framed within the global challenge of teaching programming to children and youth, demonstrating the potential of gamified tools across diverse educational contexts. Future plans include expanding the tool to incorporate more modules, allowing customization by teachers, and conducting broader evaluations in different educational environments.

Logic Computing Field-Effect Transistors Based on a Monolayer WSe2 Homojunction for the Semi-adder and Decoder.

Two-dimensional reconfigurable field-effect transistors (FETs) are promising candidates for next-generation computing hardware. However, exploring the cascade design of FETs for logic computing remains challenging. Here, by using density functional theory combined with the nonequilibrium Green's function method, we design a 5 nm split-gate FET based on a monolayer WSe2 homojunction, which can implement dynamic polarity control in different gate configurations. The series array of two FETs shows a functional family of logic gates (NOR, AND, XOR, A̅B, and AB̅), and the semi-adder designed by the logic functions AND and XOR reduces the number of transistors by 66.7%. The parallel array of two FETs demonstrates reconfigurable logic gates with NAND/OR/A̅+B/A+B̅ quadruple functions, which can realize the decoding function of 00-11 in the decoder. The cascade design of the electrically tunable FETs helps to tackle the logic device downscaling and integration dilemmas.

Realistic Cost to Execute Practical Quantum Circuits using Direct Clifford+T Lattice Surgery Compilation

We report a resource estimation pipeline that explicitly compiles quantum circuits expressed using the Clifford+T gate set into a surface code lattice surgery instruction set. The cadence of magic state requests from the compiled circuit enables the optimization of magic state distillation and storage requirements in a post-hoc analysis. To compile logical circuits into lattice surgery operations, we build upon the open-source Lattice Surgery Compiler. The revised compiler operates in two stages: the first translates logical gates into an abstract, layout-independent instruction set; the second compiles these into local lattice surgery instructions that are allocated to hardware tiles according to a specified resource layout. The second stage retains logical parallelism while avoiding resource contention in the fault-tolerant layer, aiding realism. Additionally, users can specify dedicated tiles at which magic states are replenished, enabling resource costs from the logical computation to be considered independently from magic state distillation and storage. We demonstrate the applicability of our pipeline to large, practical quantum circuits by providing resource estimates for the ground state estimation of molecules. We find that variable magic state consumption rates in real circuits can cause the resource costs of magic state storage to dominate unless production is varied to suit.

Dynamic Electric Discharge Paths in Liquid Metal Marble Arrays.

Electric discharge occurs ubiquitously in both natural and engineered systems, where the discharge paths provide critical information. However, control and visualization of discharge patterns is a challenging task. Here arrays of liquid metal marbles, droplets of a gallium-indium eutectic alloy with a copper-doped ZnS luminescent coating, are designed for pixelated visualization of electric discharge paths at optical imaging length-scales. The ZnS particles embed themselves into the surface of liquid metal droplets and are anchored by a self-limiting gallium oxide layer. The operation is achieved by generating spark discharges at inter-marble air gaps and reduced voltage drop across highly conducting liquid metal droplets. By taking advantage of the malleability of soft liquid metal marbles, the dynamic visualization platforms allow the manipulation of discharge path selections in configurable marble arrays and the embedding of artificial defect features. The systems are further integrated for characterizing dynamic changes in granular and soft systems, and for enabling logic computing and information encoded display. This demonstration holds promises for creating new-generation electric discharge-based optoelectronics.

Sequential-dependent synthesis of gold-chromium nanocomposites for multimode colorimetric sensing, advanced logic computing, and tri-layer information protection

Binary materials combine the properties and advantages of their components, but their fabrication paradigm needs updating to fully exploit their characteristics and broaden their application. Here, multifunctional bimetallic gold-chromium nanocomposites (Au–Cr NCs) were synthesized facilely in a sequential-dependent manner, and applied from multi-channel sensing to molecular informatization (including advanced logic computing and tri-layer information protection). By sequentially mixing Cr6+, Au3+, and NaBH4 (reducing agent), Au–Cr NCs with Au nanoparticles attached to Cr nanobelts can be prepared easily and quickly. The resulting Au–Cr NCs exhibited multi-signal sensing capability for hypochlorite, with significantly improved selectivity (about 5 times) and sensitivity (about 1650 times) when analyzing multiple signals. The synthesis process can be used to implement parallel molecular logic gates and customizable keypad lock operations. Moreover, by digitizing logical relationships and multimodal selective responses based on Au–Cr NCs, specific information (wise sayings and literary works sentence) can be encoded, encrypted and hidden to realize nano-cryptography and steganography. When combined with molecular keypad lock, a tri-layer information protection system can be constructed to enhance anti-cracking ability. This study promotes controllable preparation and multi-purpose applications of advanced multifunctional nanocomposites, but also opens up a new direction for nano-based sensing and digitization in multi-dimension.