Information Processing Technology Research Articles

Unlocking the potential of photoexcited molecular electron spins for room temperature quantum information processing

Abstract Future information processing technologies like quantum memory devices have the potential to store and transfer quantum states to enable quantum computing and networking. A central consideration in practical applications for such devices is the nature of the light-matter interface which determines the storage state density and efficiency. Here, we employ an organic radical, α,γ-bisdiphenylene-β-phenylallyl doped into an o-terphenyl host to explore the potential for using tuneable and high-performance molecular media in microwave-based quantum applications. We demonstrate that this radical system exhibits millisecond-long spin-lattice relaxation and microsecond-long phase memory times at room temperature, while also having the capability to generate an oscillating spin-polarized state using a co-dissolved photo-activated tetraphenylporphyrin moiety, all enabled by using a viscous liquid host. This latest system builds upon collective wisdom from previous molecules-for-quantum literature by combining careful host matrix selection, with dynamical decoupling, and photoexcited triplet-radical spin polarisation to realise a versatile and robust quantum spin medium.

Research on laser measurement point cloud preprocessing and 3D reconstruction technology for free-form surfaces.

Surface morphology measurement and reconstruction technology based on point cloud data is one of the key technologies for 3D information processing in the digital manufacturing industry and has been widely applied in fields such as reverse engineering, computer vision, and unmanned driving system navigation. A method for 3D modeling of aircraft-engine blade profiles based on laser measurement point cloud data is proposed to address the difficulties in measuring the 3D morphology of aircraft-engine blades and the low modeling accuracy. This method first preprocesses the measured point cloud and then uses Poisson's algorithm to reconstruct the blade surface in three dimensions based on the calculation of the point cloud normal. Through error statistical analysis, the overall reconstruction effect is good. The experimental results further validated the generality and effectiveness of this method.

Scalable Synaptic Transistor Memory from Solution-Processed Carbon Nanotubes for High-Speed Neuromorphic Data Processing.

Neural networks as a core information processing technology in machine learning and artificial intelligence demand substantial computational resources to deal with the extensive multiply-accumulate operations. Neuromorphic computing is an emergent solution to address this problem, allowing the computation performed in memory arrays in parallel with high efficiencies conforming to the neural networks. Here, scalable synaptic transistor memories are developed from solution-sorted carbon nanotubes. The transistors exhibit a large switching ratio of over 105, a significant memory window of ≈12V arising from charge trapping, and low response delays down to tens of nanoseconds. These device characteristics endow highly stabilized reconfigurable conductance states, successful emulation of synaptic functions, and a high data processing speed. Importantly, the devices exhibit uniform characteristic metrics, e.g., with a 1.8% variation in the memory window, suggesting an industrial-scale manufacturing capability of the fabrication. Using the memories, a hardware convolution kernel is designed and parallel image processing is demonstrated at a speed of 1M bit per second per input channel. Given the efficacy of the convolution kernel, a promising prospect of the memories in implementing neuromorphic computing is envisaged. To explore the potential, large-scale convolution kernels are simulated and high-speed video processing is realized for autonomous driving.

Modal phase-matching in thin-film lithium niobate waveguides for efficient generation of entangled photon pairs

Thin-film lithium niobate (TFLN) waveguides have emerged as a pivotal platform for on-chip spontaneous parametric down-conversion (SPDC), serving as a crucible for the generation of entangled photon pairs. The periodic poling of TFLN, while capable of generating high-efficiency SPDC, demands intricate fabrication processes that can be onerous in terms of scalability and manufacturability. In this work, we introduce a novel approach to the generation of entangled photon pairs via SPDC within TFLN waveguides, harnessing the principles of modal phase-matching (MPM). To address the challenge of efficiently exciting pump light typically in a higher-order mode, we have engineered a mode converter that couples two asymmetrically dimensioned waveguides. This converter adeptly transforms the fundamental mode into a higher-order mode, demonstrating a conversion loss of 1.55 dB at 785 nm with a 3 dB bandwidth exceeding 30 nm. Subsequently, we have showcased the device’s capabilities by characterizing the pair generation rate (PGR), coincidences-to-accidentals ratio (CAR), and spectral profile of the entangled photon source. Our findings present a simplified and versatile method for the on-chip generation of entangled photon sources, which may pave the way for the application in the realms of quantum information processing and communication technologies.

Preparation of hybrid W entangled states between superconducting qubits and microwave resonators in circuit QED

Hybrid W entangled states are essential in quantum information processing, quantum communication, and quantum technology. In this Letter, we propose a simple method to prepare hybrid W entangled states between n superconducting (SC) qubits and n microwave resonators (MRs) in circuit QED. Only two basic operations are needed for the preparation of hybrid W states. The operational time decreases as the number of qubits increases. Since no ancillary cavity is required, the hardware resources for the state preparation are minimized. Because the state preparation does not involve any measurements, the hybrid W entangled states are generated in a deterministic way. Moreover, during the entire preparation, the high-energy levels of the SC qutrits remain unexcited, which greatly reduces decoherence of the SC qutrits. As an example, our numerical simulation demonstrates that high-fidelity preparation of the hybrid W entangled state of three SC qubits and three MRs is feasible within the current circuit QED technique. This method is universal and can be applied to generate hybrid W states of n matter qubits (e.g., atomic qubits, NV center qubits, quantum dot qubits, and magnon qubits) and n photonic qubits in various physical systems.

Phase analysis of biphoton joint spectra by interference between different SPDC sources

In spontaneous parametric down-conversion, the spectral correlations between the signal and the idler are expressed by the joint spectral amplitude (JSA) function. However, in the standard coincidence measurements, the phase information of the JSA is lost, and only the square of the absolute value of the JSA is recorded, thus preventing full characterization of the biphoton state. Here, we present an experimental technique to investigate the interference of biphoton joint spectral amplitudes, unlocking new avenues in quantum photonics research. Our method explores phase-dependent phenomena within entangled biphoton spectra. This is achieved by simultaneously pumping two structured nonlinear photonic crystals and observing their interference, which reveals previously inaccessible effects with direct intensity measurements. We demonstrate the versatility of our technique by analyzing two types of joint spectra: one exhibiting a two-lobe shape and the other a three-lobe shape. Additionally, we reconstruct the joint spectral amplitudes for both scenarios and observe good agreement with theoretical predictions. These results pave the way for developing advanced quantum communication and information processing technologies using biphoton spectra.

The Role of Information Processing and Digital Supply Chain Technology in Supply Chain Resilience through Supply Chain Risk (Management in Manufacturing Companies in DKI Jakarta)

The 2019 COVID-19 pandemic highlighted the importance of supply chain resilience in the face of global disruptions. Supply chain disruptions caused by isolation measures during the pandemic triggered market turmoil, logistical uncertainty, and reduced production capacity, which sometimes led to shutdowns. In this context, research on supply chain resilience is crucial to prepare companies for future disruptions. This research aims to examine the impact of supply chain resilience on supply chain continuity in manufacturing companies in DKI Jakarta, focusing on the role of digital supply chains, information processing capabilities, and supply chain risk management. This research method uses a quantitative approach. Data were collected from 300 respondents in the basic and chemical industry, miscellaneous industries, and consumer goods sectors through purposive sampling techniques. The analysis was conducted using Structural Equation Modeling (SEM) to identify the relationship between variables. The results showed that supply chain resilience has a significant positive influence on supply chain continuity. In addition, digital supply chains, information processing capabilities, and effective supply chain risk management were shown to support supply chain resilience in the studied sectors. The implication of this research is that it is important for companies to invest in digital technology, develop better information processing capabilities, and implement effective risk management to strengthen their supply chain resilience and continuity in the face of future global uncertainty.

SUBSTANTIATION OF METHODOLOGICAL RECOMMENDATIONS FOR THE USE OF INFORMATION AND MEASURING SYSTEM BUILT ON THE LATEST HARDWARE DEVELOPMENTS DURING THE TESTING OF AME

The constant process of development of both hardware and software perfection inevitably leads to the improvement (creation) of existing (new) advanced information and measurement systems. At the same time, there is a need to develop methodological recommendations for the use of advanced information gathering and processing systems built on the basis of the latest hardware systems and complexes and software products for conducting heterogeneous tests. At the same time, there is a need to develop methodological recommendations for the use of a promising IMS for collecting and processing information built on the basis of the latest hardware systems and complexes and software products for conducting heterogeneous tests. Modern systems used for testing AME are measuring complexes that include modules for connecting sensors, modules for converting analogue sensor signals into digital form, modules for storing the received information in digital form and modules for communication with external computerised devices. Depending on the tasks of the test or experiment, the IMS can be supplemented (simplified) by the need to use certain measuring complexes and systems to measure parameters and obtain reliable information. The ideas, principles and algorithms that currently constitute the methodology of information processing have already made it possible to make a significant breakthrough in information processing technology. Processing methods and principles of their implementation for each field have their own specific features, which are primarily determined by the specific type of information carrier, encoding methods and ways of presenting the results of information processing. As a result, information processing arrangements for different areas often appear to be outwardly dissimilar. However, this external dissimilarity hides the same methodology and principles of building processing systems, which is crucial. The authors of the article study the capabilities of the latest hardware systems and complexes which should be included in advanced IMS and substantiate new methodological approaches, in accordance with regulatory and legal documents, to the use of such IMS during testing of AME.

High-fidelity spin readout via the double latching mechanism

Projective measurement of single-electron spins, or spin readout, is among the most fundamental technologies for spin-based quantum information processing. Implementing spin readout with both high-fidelity and scalability is indispensable for developing fault-tolerant quantum computers in large-scale spin-qubit arrays. To achieve high fidelity, a latching mechanism is useful. However, the fidelity can be decreased by spin relaxation and charge state leakage, and the scalability is currently challenging. Here, we propose and demonstrate a double-latching high-fidelity spin readout scheme, which suppresses errors via an additional latching process. We experimentally show that the double-latching mechanism provides significantly higher fidelity than the conventional latching mechanism and estimate a potential spin readout fidelity of 99.94% using highly spin-dependent tunnel rates. Due to isolation from error-inducing processes, the double-latching mechanism combined with scalable charge readout is expected to be useful for large-scale spin-qubit arrays while maintaining high fidelity.

Fault Line Selection of Small Current Grounding System Research Based on Zero Sequence Circuit Current Phase

Abstract This paper investigates fault line selection in small current grounding systems, focusing on the zero sequence current phase characteristics. Small current grounding systems, prevalent in medium voltage distribution networks, face challenges in fault detection due to minimal fault currents during single status phase grounding faults. Traditional methods relying on manual line switching and zero sequence voltage monitoring are inefficient and can induce overvoltage. This study categorizes fault line selection techniques into three approaches: steady-state fault information, transient information, and modern signal processing technology. The analysis of zero sequence currents in non-grounded systems reveals that fault line zero sequence currents equal the sum of system capacitive currents, flowing opposite to those in non-fault lines. Additionally, transient signal analysis shows that these signals provide more robust information for fault detection. MATLAB simulations validate the theoretical models, demonstrating that zero sequence current direction and amplitude effectively identify fault lines. The results confirm the efficacy of combining steady-state and transient signal analyses for accurate fault line selection, contributing to enhanced safety and reliability in power distribution networks. This research offers practical insights and tools for engineers, improving fault management and reducing potential economic losses in small current grounding systems.

PT Symmetry Breaking Induced Anomalous Valley Hall Effect in 2D Antiferromagnetic Semiconductor.

Realizing the anomalous valley Hall (AVH) effect in two-dimensional (2D) materials is of crucial importance for information processing and recording technology. While the research in this field mainly focuses on ferromagnetic systems, little is known about antiferromagnetic systems. Here, using k·p model analysis, we report a novel mechanism of realizing the AVH effect in 2D antiferromagnetic materials. This physics is related to the PT symmetry breaking induced by intrinsic staggered sublattice potential, which is introduced by asymmetric magnetic ions located at different sublattices. With reversal of the magnetic orientation on different sublattices, the AVH effect can be reversed. Based on first-principles calculations, we further demonstrate this mechanism in an antiferromagnetic monolayer of NiRuCl6. Intriguingly, due to the d orbital mismatch near the Fermi level, monolayer NiRuCl6 simultaneously owns zero net magnetization and large spin splitting and valley polarizations, which facilitates the observation of the AVH effect. Our findings greatly enrich the research on valley physics in antiferromagnetic systems.

Research on the Design of Performance Evaluation System for Physical Education Major Based on Multimedia Information Processing Technology

The Massive Open Online Course (MOOC) platform, despite its reach and potential, faces significant challenges related to learner diversity, including variations in student backgrounds, work experiences, and learning environments. By integrating the principles of ant colony clustering algorithms with MOOC platform dynamics, our study devises a strategy for grouping students based on shared characteristics, thereby fostering a tailored learning environment. A streamlined MOOC platform design framework is outlined, accompanied by a detailed blueprint for a peer-evaluation information system, aimed at accurately gauging students' academic progress within their disciplines. This platform enables students to effortlessly access and engage with courses aligned with their interests, while the reciprocal assessment mechanism heightens understanding of course materials and alleviates pressure on educators. Our research contributes a pragmatic solution to the challenge of student assignment clustering within MOOCs, enhancing both individual learning outcomes and the broader instructional quality.

Isostructural Oxamate Complexes with Visible Luminescence (Eu3+) and Field-Induced Single-Molecule Magnet (Nd3+).

The search for new metal-organic compounds as candidates for quantum information processing technologies is in the spotlight. Several metal ions and organic linkers have been used to obtain such compounds. Herein, we describe the synthesis, crystal structures, and cryomagnetic properties of two air-stable isostructural neodymium(III) and europium(III) one-dimensional (1D) coordination polymers of formula [Nd(Hmpa)3(DMSO)2]n (1) and [Eu(Hmpa)3(DMSO)2]n (2) [Hmpa = N-(4-methylphenyl)oxamate, and DMSO = dimethylsulfoxide]. These complexes were prepared by reacting n-Bu4N(Hmpa) proligand [n-Bu4N+ = tetra-n-butylammonium] and the correspondent LnCl3·6H2O salt (Ln = Nd or Eu) in the open air and mild conditions. The crystal structures of 1 and 2 reveal the Ln3+ ion surrounded by two DMSO molecules and three oxamate ligands, one of them connecting to adjacent mononuclear entities through carboxylate bridges featuring a 1D coordination polymer, while the other two establishing double N-H···O hydrogen bonds among adjacent polymers to give a resultant supramolecular 2D network. Cryomagnetic measurements in the static (dc) and dynamic current (ac) regimes reveal that 1 behaves as a field-induced single-molecule magnet below 8.8 K. A photoluminescence study shows that Hmpa ligands efficiently sensitize the luminescence of Eu3+ complex in the visible region in the solid state at room temperature.

An example of the application of artificial intelligence models in human resources processes

Creating job postings and selecting suitable candidates among these job postings is a challenging process. This process increases the workload of human resources and causes the process to proceed slowly. It is of great importance for human resources departments to utilize information processing technologies to create job postings effectively and to evaluate the CVs of applicants to these postings. This study introduces and analyzes two different technologies that can help human resources. In the process of preparing job advertisements in the field of IT, in the first stage, the word cloud method is used to decide which keywords should be emphasized in the advertisement texts. In the second stage, the resumes of the applicants are analyzed using three different deep learning models such as CNN (Convolutional Neural Network), GRU (Gated Recurrent Unit), and LSTM (Long Short-Term Memory) for classification purposes. While the performance of these models is evaluated using metrics such as accuracy, MCC, F_1 score, and MSE, the decision-making processes of the models with explainable artificial intelligence are also analyzed. In this context, the GRU model, which achieved an accuracy of 99%, provided the most superior result in this study and the literature. This research shows that deep learning models provide high accuracy rates and efficiency in human resources resume classification and candidate matching processes. It also explains that using the word cloud method, the most appropriate keywords can be identified, and advertisements can be created.

PENGUKURAN TINGKAT KEMATANGAN TATA KELOLA TEKNOLOGI INFORMASI STUDI KASUS: PT. TRIPLE “A”

In today's digital age, information technology (IT) plays a vital role in supporting and improving a company's business performance. This article measures the degree of IT governance maturity in PT. Triple “A” Securities using the Weill and Ross IT Governance model as well as the COBIT 4.1 framework. The scope of the research includes the analysis of the plan and organize process in COBIT 4.1 and the measurement of the maturity rate using the COBIT 4.1 Maturity Model. The results of the study show that some IT processes in PT are at the initial (initial) and repeatable (repeatable) maturity levels, with an average maturity rating of 1.85, indicating that the company is between level 1 (ad hoc) and level 2 (repetable). Further analysis is done on IT decisions, business strategy, IT strategy, and process control. The conclusions of this study provide insight into the IT governance patterns that exist in the PT. Triple “A” Securities and suggest areas of improvement to improve the maturity of IT governance in the future. This research is also expected to be a benchmark for companies in managing IT more effectively and efficiently, as well as identifying obstacles and encouraging the implementation of good IT governance.

Effective regulation of the interaction process among three optical solitons

Abstract The interaction between three optical solitons is a complex and valuable research direction, which is of practical application for promoting the development of optical communication and all-optical information processing technology. In this paper, we start from the study of the variable-coefficient coupled higher-order nonlinear Schrödinger equation (VCHNLSE), and obtain an analytical three-soliton solution of this equation. Based on the obtained solution, the interaction of the three optical solitons is explored when they are incident from different initial velocities and phases. When the higher-order dispersion and nonlinear functions are sinusoidal, hyperbolic secant, and hyperbolic tangent functions, the transmission properties of three optical solitons before and after interactions are discussed. Besides, this paper achieves effective regulation of amplitude and velocity of optical solitons as well as of the local state of interaction process, and interaction-free transmission of the three optical solitons is obtained with a small spacing. The relevant conclusions of the paper are of great significance in promoting the development of high-speed and large-capacity optical communication, optical signal processing, and optical computing.

A practical implementation of virtualized protection system with IEC61850 under Docker

Substation Automation Systems (SAS) are currently designed and operated based on IEC 61850 standard. This standard along with the evolution of the information processing technology brings the possibility of developing new centralized SAS architectures based on virtualized protection and control. However, communication latency must be evaluated as it can limit the scalability of virtualized SAS. This paper explores via a practical simulation case the effects of the number of virtual IEDs in the data traffic of a virtualized IEC61850 SAS based on Docker. Simulation results have shown that the increase in the network traffic due to a higher number of virtual IEDs produces a longer delay in tripping operation under a fault condition.

Exploring the Impact of IT Governance Mechanisms on IT Agility

ABSTRACT As Information Technology (IT) becomes more integral, the importance of governance and the need to adapt IT to respond to environmental changes and opportunities increases. This study analyzes the impact of IT governance relational mechanisms, processes, and structures on IT agility. A practitioner focus group and survey shows that only relational governance mechanisms have a significant positive impact on IT agility. We discuss the implications for practitioners and researchers interested in IT governance and agility.

Design and Application of Virtual Cloud OMS Computing in Smart Airport

Airport management takes airport information management as its key link, and it is also the key to ensure the safe operation of airports. As a modern information management and processing technology, cloud computing plays an indispensable role in the fields of efficient information processing, strengthening management and improving work efficiency. Under the development background of the information age, the management mode of airport operation and maintenance has also changed to some extent. In the growth of the new era, airport operation and maintenance managers need to introduce new technologies and then combine more advanced technologies with the airport operation and maintenance system (OMS) so as to promote the normal operation of the airport OMS based on advanced data acquisition, analysis, and integration technologies. This article studies the application of cloud computing technology and designs a virtual cloud OMS based on deep learning (DL) from the perspective of the security requirements of the management information system (MIS) to realize the fault diagnosis and identification of the airport MIS. The fault diagnosis technology of the airport MIS based on virtual cloud OMS and DL proposed in this study has broad prospects in practical application. It can be applied to airport operation and maintenance management, security, and other links, providing intelligent support for airport operation.

Technology roadmapping for the e-commerce sector: A text-mining approach

Due to rapid technological advancements and shifting consumer dynamics, the e-commerce industry has undergone rapid transformation. Further, emerging technologies, including artificial intelligence, blockchain, and augmented reality, have the ability to revolutionize the e-commerce landscape. However, limited studies have mapped the technological evolution in the e-commerce sector. Therefore, this study offers a multi-faceted forecast of e-commerce technologies by combining patent analysis, semantic network analysis, and topic modelling approaches. The study analyzes 4113 patents and categorizes them into two time periods: 2001–2012 and 2013–2023. This study constructs co-word maps, defines the relationships between the words, and examines how the co-word relationships have changed over the time period. In the period between 2001 and 2012, the patents are categorized into four clusters: information processing and communication technologies, product purchase and sale management, e-commerce systems, and digital transaction and security management. For the period spanning between 2013 and 2023, the patents are classified into seven clusters: user experience, integrating devices, product information management, e-commerce infrastructure, advanced e-commerce authentication, pricing and payment solution, platform development, and e-commerce optimization. It aims to bridge theory and practice by developing a roadmap of near-, mid-, and far-future e-commerce technologies. The study highlights implications for practice and theory.