Logic Operations Research Articles

Competition of decoherence and quantum speed limits for quantum-gate fidelity in the Jaynes-Cummings model

Quantum computers are operated by external driving fields, such as lasers, microwaves, or transmission lines, that execute logical operations on multiqubit registers, leaving the system in a pure state. However, the drive and the logical system might become correlated in such a way that, after tracing out the degrees of freedom of the driving field, the output state will not be pure. Previous works have pointed out that the resulting error scales inversely with the energy of the drive, thus imposing a limit on the energy efficiency of quantum computing. In this study, focusing on the Jaynes-Cummings model, we show how the same scaling can be seen as a consequence of two competing phenomena: the entanglement-induced error, which grows with time, and a minimal time for computation imposed by quantum speed limits. This evidence is made possible by quantifying, at any time, the computation error via the spectral radius associated with the density operator of the logical qubit. Moreover, we also prove that, in order to attain a given target state at a chosen fidelity, it is energetically more efficient to perform a single driven evolution of the logical qubits rather than to split the computation in subroutines, each operated by a dedicated pulse. Published by the American Physical Society 2024

Image authentication with exclusive-OR operated optical vortices

Optical vortices carrying orbital angular momentum have drawn much attention because they provide high-dimensional encoding. Employing an array of optical vortices, we demonstrate an authentication verification system. For security authentication, an exclusive-OR logic operation has been implemented employing a light beam consisting of an array of vortices. A liquid crystal spatial light modulator has been used to generate orthogonal states of optical vortices. The proposed technique can provide a secure method of authentication with straightforward implementation. We have presented simulation and experimental results to verify the proposed scheme.

Utilizing topological invariants for encoding and manipulating chiral phonon devices

As a fundamental degree of freedom, phonon chirality is expected to promote the development of quantum information technology just like electron spin. Currently, central to this area is the realization of efficient transmission and control of chiral information. In this paper, we propose an approach by integrating topological theory, leveraging topologically invariant Chern numbers, to encode hexagonal lattice systems. Our investigation reveals the presence of topologically protected chiral interface states within the shared band gaps of both trivial and non-trivial system units. By precisely modulating the magnetic field distribution within the encoding system, we can effectively manipulate the topological pathways. Building upon this framework, we design and implement a chiral phonon three-port device. Through dynamic calculations, we demonstrate the transmission process of chiral information, showcasing the chiral phonon switching effect and logical OR operation. Our findings not only establish a fundamental mechanism for the manipulation and control of phonon chiral information but also provide a promising direction for research in harnessing chirality degrees of freedom in practical applications.

Terpyridyl-Imidazole Based Ligand Coordinated to Ln(Hexafluoroacetyl acetonate)3 Core: Synthesis, Structural Characterization, Luminescence Properties, and Thermosensing Behaviors in Solution and PMMA Film.

A new array of ternary lanthanide complexes of the form [Ln(hfa)3(tpy-HImzphen)] have been synthesized and thoroughly characterized wherein Ln = LaIII (1), EuIII (2), SmIII (3), and TbIII (4); hfa = hexafluoroacetylacetonate; and tpy-HImzphen = 2-(4-[2,2':6',2″]terpyridin-4'-yl-phenyl)-1H-phenanthro[9,10-d]imidazole. Incorporation of tpy-HImzphen onto the Ln-hfa moiety induced a bathochromic shift of the absorption window of the complexes into the visible region. Extensive investigations of the luminescence characteristics have been conducted both at RT and at 77 K to understand the deactivation pathways of the complexes. Both steady-state and time-resolved emission spectral behaviors indicate four distinctive behaviors upon incorporation of tpy-HImzphen onto the lanthanide core, viz., a huge red-shift of the ligand-centered peak for LaIII; almost complete energy transfer for EuIII; very little energy transfer for SmIII, while reverse energy transfer in the case of TbIII. In addition, the EuIII-complex exhibits its excellence in luminescence thermometry in the solution state as well as in poly(methyl methacrylate) (PMMA) thin films. The thermosensitive luminescence response in solution was further utilized to mimic set-reset flip-flop logic operation. A plausible energy transfer scheme has been devised to explain dissimilar luminescence behaviors in the complexes. The role of LMCT was also considered for the observed thermosensing property of the Eu(III) complex.

Broadband Negative Photoconductive Response in Carbon Nanodots.

Due to the broadband response and low selectivity of external light, negative photoconductivity (NPC) effect holds great potential applications in photoelectric devices. Herein, different photoresponsive carbon nanodots (CDs) are prepared from diverse precursors and the broadband response from the NPC CDs are utilized to achieve the optoelectronic logic gates and optical imaging for the first time. In detail, the mcu-CDs which are prepared by the microwave-assisted polymerization of citric acid and urea possess the large specific surface area and abundant hydrophilic groups as sites for the adsorption of H2O molecules and thereby present a high conductivity in dark. Meanwhile, the low affinity of mcu-CDs to H2O molecules permits the light-induced desorption of H2O molecules by heat effect and thus endow the mcu-CDs with a low conductivity under illumination. The easy absorption and desorption of H2O molecules contribute to the extraordinary NPC of mcu-CDs. With the broadband NPC response in CDs, the optoelectronic logic gates and flexible optical imaging system are established, achieving the applications of "NOR" or "NAND" logic operations and high-quality optical images. These findings unveil the unique optoelectronic properties of CDs, and have the potential to advance the applications of CDs in optoelectronic devices.

Mechanical Computing with Transmissive Snapping of Kirigami Shells

AbstractContinuum shape‐morphing structures with the capability to encode memory and execute logic operations have garnered significant interest for the development of mechanical systems with embodied intelligence and soft robots. Achieving the integration of memory and computing within a mechanical system necessitates building blocks that possess a range of tunable, metastable states. Prior efforts have been dedicated to constructing mechanical memory and logic through the exploitation of snap‐through instabilities in multistable structures. Typically, the creation of each logic gate demands a distinct structural design. Here, presents an unconventional design strategy that leverages a single kirigami architecture to perform and switch between multiple fundamental logic operations. By utilizing the kirigami architecture as the fundamental element, mechanical signal transmission is demonstrated and half‐adder computations are performed. It is envisioned that this design strategy can be applied to a wide range of materials and structures, and reduce the complexity of developing materials systems with embodied intelligence.

An Exo III-powered closed-loop DNA circuit architecture for biosensing/imaging.

With their regulated Boolean logic operations in vitro and in vivo, DNA logic circuits have shown great promise for target recognition and disease diagnosis. However, significant obstacles must be overcome to improve their operational efficiency and broaden their range of applications. In this study, we propose an Exo III-powered closed-loop DNA circuit (ECDC) architecture that integrates four highly efficient AND logic gates. The ECDC utilizes Exo III as the sole enzyme-activated actuator, simplifying the circuit design and ensuring optimal performance. Moreover, the use of Exo III enables a self-feedback (autocatalytic) mechanism in the dynamic switching between AND logic gates within this circulating logic circuit. After validating the signal flow and examining the impact of each AND logic gate on the regulation of the circuit, we demonstrate the intelligent determination of miR-21 using the carefully designed ECDC architecturein vitro. The proposed ECDC exhibits a linear detection range for miR-21 from 0 to 300 nM, with a limit of detection (LOD) of approximately 0.01 nM, surpassing most reported methods. It also shows excellent selectivity for miR-21 detection and holds potential for identifying and imaging live cancer cells. This study presents a practical and efficient strategy for monitoring various nucleic acid-based biomarkersin vitro and in vivo through specific sequence modifications, offering significant potential for early cancer diagnosis, bioanalysis, and prognostic clinical applications.

Status of Research on Dental Caries during Pregnancy: A Biometric Exploration.

To describe the bibliometric characteristics of the state of scientific production on dental caries during pregnancy. A bibliometric study with a sample of 408 publications indexed in the Scopus database, which were selected based on a search strategy that included logical operators and the term MESH. The Scival tool was used to analyze the metadata. Jamieson Lisa Marie is positioned as the author with the most publications, and Schroth Robert as the one with the best-weighted impact (FWCI: 37.7). High-impact journals such as BMC Oral Health, Journal of Dental Research, and BMC Public Health stand out for their productivity and an average number of citations. The United States has a large number of publications and evidence of networks of scientific activity with Australia, Canada, and Brazil. The University of Adelaide leads the production and the work of two Latin American institutions (Universidade de São Paulo and Universidade Federal do Maranhão) stands out. International collaboration has improved during the study period. Scientific production on dental caries during pregnancy is increasingly published in high-impact journals, with growing international collaboration. The United States leads in publications, while Australian institutions are the most productive in this field. Caries during pregnancy is a problem that has an important impact on maternal and perinatal health; thus, its timely management and prevention are important areas of research in the field of oral health. How to cite this article: Muñoz-Hidalgo M, Verastegui-Cabanillas Y, Barja-Ore J. Status of Research on Dental Caries during Pregnancy: A Biometric Exploration. J Contemp Dent Pract 2024;25(4):386-391.

Mango Leaves (Mangifera indica)-Derived Highly Florescent Green Graphene Quantum Dot Nanoprobes for Enhanced On-Off Dual Detection of Cholesterol and Fe2+ Ions Based on Molecular Logic Operation.

In the present study, we have engineered a molecular logic gate system employing both Fe2+ ions and cholesterol as bioanalytes for innovative detection strategies. We utilized a green-synthesis method employing the mango leaves extract to create fluorescent graphene quantum dots termed "mGQDs". Through techniques like HR-TEM, i.e., high-resolution transmission electron microscopy, Raman spectroscopy, and XPS, i.e., X-ray photoelectron spectroscopy, the successful formation of mGQDs was confirmed. The photoluminescence (PL) characteristics of mGQDs were investigated for potential applications in metal ion detection, specifically Fe2+ traces in water, by using fluorescence techniques. Under 425 nm excitation, mGQDs exhibited emission bands at 495 and 677 nm in their PL spectrum. Fe2+-induced notable quenching of mGQDs' PL intensity decreased by 97% with 2.5 μM Fe2+ ions; however, adding 20 mM cholesterol resulted in a 92% recovery. Detection limits were established through a linear Stern-Volmer (S-V) plot at room temperature, yielding values of 4.07 μM for Fe2+ ions and 1.8 mM for cholesterol. Moreover, mGQDs demonstrated biocompatibility, aqueous solubility, and nontoxicity, facilitating the creation of a rapid nonenzymatic cholesterol detection method. Selectivity and detection studies underscored mGQDs' reliability in cholesterol level monitoring. Additionally, a molecular logic gate system employing Fe2+ metal ions and cholesterol as a bioanalyte was established for detection purposes. Overall, this research introduces an ecofriendly approach to craft mGQDs and highlights their effectiveness in detecting metal ions and cholesterol, suggesting their potential as versatile nanomaterials for diverse analytical and biomedical applications.

Optimal solutions to granular fuzzy relation equations with fuzzy logic operations

Fuzzy relation equations are commonly utilized to describe the fuzzy relationship between the antecedent and the consequent parts of complex data environment, and play a vital role in fuzzy system modeling. An interesting topic is to determine fuzzy relation equations based on existing fuzzy logic operations, including the t-norms and t-conorms (s-norms). However, fuzzy rule-based models developed in form of numeric values still face significant challenges in accuracy and interpretability. This study aims to introduce the idea of granular computing to formulate granular fuzzy relation equations based on the fuzzy logic operations and evaluate the performance of granular fuzzy relation equations using the general principle of justifiable granularity. A two-phase development of granular fuzzy relation equations is designed: In the first phase, fuzzy relation equations are constructed based on t-norms and t-conorms; in the second phase, granular augmentation of fuzzy relation equations is realized by allocating a certain level of information granularity as the granular parameters of fuzzy relations. The capability of granular outputs is evaluated with the aid of two conflicting criteria—coverage (cov) and specificity (sp). The optimal solutions to granular fuzzy relation equations are explored using combinations of optimization algorithms. The originality of this study lies on the development of granular fuzzy relation equations with fuzzy logic operations, which provides a human-centric platform of fuzzy system modeling to enhance accuracy and interpretability. Experimental studies are carried out based on the UCI and KEEL machine learning datasets to report on the feasibility and performance of the proposed model.

Fold-Transversal Clifford Gates for Quantum Codes

We generalize the concept of folding from surface codes to CSS codes by considering certain dualities within them. In particular, this gives a general method to implement logical operations in suitable LDPC quantum codes using transversal gates and qubit permutations only.To demonstrate our approach, we specifically consider a [[30, 8, 3]] hyperbolic quantum code called Bring's code. Further, we show that by restricting the logical subspace of Bring's code to four qubits, we can obtain the full Clifford group on that subspace.

Performing optical logic operations on linear polarization modes using diffractive deep neural networks

Performing optical logic operations on linear polarization modes using diffractive deep neural networks

Efficient Data Transfer and Multi-Bit Multiplier Design in Processing in Memory

Processing in Memory based on memristors is considered the most effective solution to overcome the Von Neumann bottleneck issue and has become a hot research topic. The execution efficiency of logical computation and in-memory data transmission is crucial for Processing in Memory. This paper presents a design scheme for data transmission and multi-bit multipliers within MAT (a data storage set in MPU) based on the memristive alternating crossbar array structure. Firstly, to improve the data transfer efficiency, we reserve the edge row and column of the array as assistant cells for OR AND (OA) and AND data transmission logic operations to reduce the data transfer steps. Furthermore, we convert the multipliers into multi-bit addition operations via Multiple Input Multiple Output (MIMO) logical operations, which effectively improves the execution efficiency of multipliers. PSpice simulation shows that the proposed data transmission and multi-bit multiplier solution has lower latency and power consumption and higher efficiency and flexibility.

Secured THz communication in photonic microcell networks based on spatial wave mixing of steered beams

Future 6G communication systems are envisioned to expand their carrier frequency to the THz region, where a broad unexplored region of spectrum is available. With this expansion, THz wireless communication has the potential to achieve ultra-high data transmission rates of up to 100Gbit/s. However, as large amounts of data are transmitted in an open wireless environment, there are significant concerns regarding communication security due to the susceptibility to eavesdropping, interception, and jamming. In this work, we proposed a secure approach for THz wireless communication based on spatial wave mixing and flexible beam steering. To achieve this, two frequency-modulated THz waves, which are generated by photonic THz sources and carry encrypted information with true randomness, are mixed at a THz envelope detector with an exclusive-OR logic operation. We analyzed the possible spatial location for the THz detector to ensure a secure microcell network deployment. Our results demonstrate that the size of the decryptable region is directly dependent on the directivity and width of the emitted THz beam. To address this, we have developed an array antenna with integrated uni-traveling-carrier photodiodes (UTC-PDs), which is capable of generating THz waves while also improving the flexibility of beam pointing, allowing for greater control over the location and size of the decodable region. By controlling fiber-optic delay lines, we successfully demonstrated that the directional gain of a 200GHz wave is increased by 8dB through a 1 × 3 UTC-PD-integrated planar bowtie antenna (PBA) array, together with continuous beam steering from -20° to 10°. Additionally, using a 1 × 4 UTC-PD-integrated PBA array to emulate two encryption transmitters and a Femi-level managed barrier diode to detect spatially mixed THz waves, we successfully achieved a feasibility experiment for real-time 200Mbit/s location-based decryption in the 200GHz band. These results indicate that the proposed scheme is feasible for secured THz communication, and would be a powerful candidate to mitigate security risks in 6G microcell networks.

Architecture of Molecular Logic Gates: From Design to Application as Optical Detection Devices

Three decades after A. P. de Silva’s seminal paper introduced the concept of logic gates at the molecular level, the field of molecular logic gates (MLGs) has witnessed significant advancements. MLGs are devices designed to perform logical operations, utilizing one or more physical or chemical stimulus signals (inputs) to generate an output response. Notably, MLGs have found diverse applications, with optical detection of analytes emerging as a notable evolution of traditional chemosensors. Organic synthesis methods are pivotal in crafting molecular architectures tailored as optical devices capable of analyte detection through logical functions. This review delves into the fundamental aspects and physical–chemical properties of MLGs, with a particular emphasis on synthetic strategies driving their design.

Programmable Computational RNA Droplets Assembled via Kissing-Loop Interaction.

DNA droplets, artificial liquid-like condensates of well-engineered DNA sequences, allow the critical aspects of phase-separated biological condensates to be harnessed programmably, such as molecular sensing and phase-state regulation. In contrast, their RNA-based counterparts remain less explored despite more diverse molecular structures and functions ranging from DNA-like to protein-like features. Here, we design and demonstrate computational RNA droplets capable of two-input AND logic operations. We use a multibranched RNA nanostructure as a building block comprising multiple single-stranded RNAs. Its branches engaged in RNA-specific kissing-loop (KL) interaction enables the self-assembly into a network-like microstructure. Upon two inputs of target miRNAs, the nanostructure is programmed to break up into lower-valency structures that are interconnected in a chain-like manner. We optimize KL sequences adapted from viral sequences by numerically and experimentally studying the base-wise adjustability of the interaction strength. Only upon receiving cognate microRNAs, RNA droplets selectively show a drastic phase-state change from liquid to dispersed states due to dismantling of the network-like microstructure. This demonstration strongly suggests that the multistranded motif design offers a flexible means to bottom-up programming of condensate phase behavior. Unlike submicroscopic RNA-based logic operators, the macroscopic phase change provides a naked-eye-distinguishable readout of molecular sensing. Our computational RNA droplets can be applied to in situ programmable assembly of computational biomolecular devices and artificial cells from transcriptionally derived RNA within biological/artificial cells.

New-Style Logic Operation and Neuromorphic Computing Enabled by Optoelectronic Artificial Synapses in an MXene/Y:HfO2 Ferroelectric Memristor.

Today's computing systems, to meet the enormous demands of information processing, have driven the development of brain-inspired neuromorphic systems. However, there are relatively few optoelectronic devices in most brain-inspired neuromorphic systems that can simultaneously regulate the conductivity through both optical and electrical signals. In this work, the Au/MXene/Y:HfO2/FTO ferroelectric memristor as an optoelectronic artificial synaptic device exhibited both digital and analog resistance switching (RS) behaviors under different voltages with a good switching ratio (>103). Under optoelectronic conditions, optimal weight update parameters and an enhanced algorithm achieved 97.1% recognition accuracy in convolutional neural networks. A new logic gate circuit specifically designed for optoelectronic inputs was established. Furthermore, the device integrates the impact of relative humidity to develop an innovative three-person voting mechanism with a veto power. These results provide a feasible approach for integrating optoelectronic artificial synapses with logic-based computing devices.

Realization of logic operations via spin–orbit torque driven perpendicular magnetization switching in a heavy metal/ferrimagnet bilayer

Programmable and non-volatile spin-based logic devices have attracted significant interest for use in logic circuits. Realization of logic operations via spin–orbit torque (SOT) driven magnetization switching could be a crucial step in the direction of building logic-in-memory architectures. In this work, we demonstrate experimentally, the realization of four logic operations in a heavy metal/ferrimagnet bilayer structure via SOT switching. We also propose a general scheme for choosing input parameters to achieve programmable logic operations. The bulk and tunable perpendicular magnetic anisotropy and relatively lower saturation magnetization in ferrimagnets are found to make them more energy efficient in performing logic operations, as compared to conventional ferromagnets. Thus, ferrimagnets are promising candidates for use in logic-in-memory architectures, leading to the realization of user-friendly spin logic devices in the future.

Modular CRISPR/Cas12a synergistic activation platform for detection and logic operations.

The revolutionary technology of CRISPR/Cas has reshaped the landscape of molecular biology and molecular engineering. This tool is of interest to researchers in multiple fields, including molecular diagnostics, molecular biochemistry circuits, and information storage. As CRISPR/Cas spreads to more niche areas, new application scenarios and requirements emerge. Developing programmability and compatibility of CRISPR/Cas becomes a critical issue in the new phase. Here, we report a redundancy-based modular CRISPR/Cas12a synergistic activation platform (MCSAP). The position, length, and concentration of the redundancy in the split DNA activators can finely regulate the activity of Cas12a. With the redundant structure as an interface, MCSAP serves as a modular plug-in to seamlessly integrate with the upstream molecular network. MCSAP successfully performs three different tasks: nucleic acid detection, enzyme detection, and logic operation. MCSAP can work as an effector for different molecular networks because of its compatibility and programmability. Our platform provides powerful yet easy-to-use tools and strategies for the fields of DNA nanotechnology, molecular engineering, and molecular biology.

Explainable hypoglycemia prediction models through dynamic structured grammatical evolution

Effective blood glucose management is crucial for people with diabetes to avoid acute complications. Predicting extreme values accurately and in a timely manner is of vital importance to them. People with diabetes are particularly concerned about suffering a hypoglycemia (low value) event and, moreover, that the event will be prolonged in time. It is crucial to predict hyperglycemia (high value) and hypoglycemia events that may cause health damages in the short term and potential permanent damages in the long term. This paper describes our research on predicting hypoglycemia events at 30, 60, 90, and 120 minutes using machine learning methods. We propose using structured Grammatical Evolution and dynamic structured Grammatical Evolution to produce interpretable mathematical expressions that predict a hypoglycemia event. Our proposal generates white-box models induced by a grammar based on if-then-else conditions using blood glucose, heart rate, number of steps, and burned calories as the inputs for the machine learning technique. We apply these techniques to create three types of models: individualized, cluster, and population-based. They all are then compared with the predictions of eleven machine learning techniques. We apply these techniques to a dataset of 24 real patients of the Hospital Universitario Principe de Asturias, Madrid, Spain. The resulting models, presented as if-then-else statements that incorporate numeric, relational, and logical operations between variables and constants, are inherently interpretable. The True Positive Rate and True Negative Rate metrics are above 0.90 for 30-minute predictions, 0.80 for 60 min, and 0.70 for 90 min and 120 min for the three types of models. Individualized models exhibit the best metrics, while cluster and population-based models perform similarly. Structured and dynamic structured grammatical evolution techniques perform similarly for all forecasting horizons. Regarding the comparison of different machine learning techniques, on the shorter forecasting horizons, our proposals have a high probability of winning, a probability that diminishes on the longer time horizons. Structured grammatical evolution provides advanced forecasting models that facilitate model explanation, modification, and retesting, offering flexibility for refining solutions post-creation and a deeper understanding of blood glucose behavior. These models have been integrated into the glUCModel application, designed to serve people with diabetes.