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83 articles for “quantum techniques”
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Quantum Data Harmonization: Resolving Disparate Information Realms with AI-driven Data Science
Abstract: The proliferation of heterogeneous data structures across fragmented information systems hampers insights derivation necessitating harmonization methodologies reconciling multidimensional datasets for collective analytics. This article reviews quantum techniques leveraging qubit superposition for probabilistic data transformations as a novel data harmonization paradigm tailored for varied schemas commonly confronting interdisciplinary analyses spanning healthcare, finance and environmental domains. Hybrid quantum-classical algorithms and AI-based automation workflows hold promise coordinating dispersed data pools through learned mappings …
Published in Journal of Advances in Shell Programming · Vol. 10, Issue 2, 2023 · pp. 34–38 Read article
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Entangled Shields: Securing Digital Systems in the Quantum Cryptographic Revolution
Abstract: Quantum computing utilizing principles of superposition and entanglement is poised to revolutionize the computational landscape, presenting unprecedented challenges and opportunities across various disciplines. Among these, cryptography stands at the forefront due to its reliance on computational hardness assumptions, which Quantum algorithms, such as Grover’s and Shor’s, can efficiently exploit. This study explores theoretical foundations and practical applications of quantum-safe cryptographic primitives, such as lattice-based cryptography, hash-based signature schemes, code-based systems, …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 33–43 Read article
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Quantum Leaps: How Quantum Computing Shapes the Evolution of Artificial Intelligence
Abstract: Quantum computing leverages quantum mechanical phenomena to enable powerful new forms of computation. With the ability to dramatically exceed the capabilities of classical supercomputers on select complex problems, many researchers anticipate revolutionary impacts of quantum computing on a variety of fields, including artificial intelligence. This research proposal outlines an investigation analyzing the intersection of quantum computation and artificial intelligence. The key research questions explore how quantum algorithms and hardware may …
Published in Recent Trends in Parallel Computing · Vol. 10, Issue 3, 2023 · pp. 7–17 Read article
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Quantum Cryptography
Abstract: Introduction to cryptography, certain cryptographic techniques, and quantum cryptography, as well as the differences between traditional and quantum cryptography, are all covered in this paper. Quantum cryptography is the science of performing cryptographic operations using quantum mechanics principles. Quantum key distribution is the most well-known example of quantum cryptography, which provides an information-theoretically secure solution to the key exchange problem. Quantum cryptography is an attempt to create a shared and …
Published in Journal of Operating Systems Development & Trends · Vol. 8, Issue 3, 2021 · pp. 20–27 Read article
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Thin-Film Quantum Photonic Technologies for Quantum Teleportation
Abstract: One of the most important protocols in distributed quantum computing and quantum communication is quantum teleportation, which allows quantum information to be sent between distant nodes without actually sending the quantum particle. The teleportation process is fundamentally based on quantum entanglement, Bell state measurements, and classical communication channels, which collectively allow the accurate reconstruction of an unknown quantum state at a remote location. In recent years, rapid progress in integrated …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 13, Issue 2, 2026 · pp. 01–19 Read article
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Enhancing Security in Unified Software Architecture for Smart Computing IoT Devices via Mobile App Authentication Using Quantum-Based Encryption
Abstract: Security remains a critical concern in the landscape of smart computing for IoT devices, necessitating robust measures to safeguard sensitive data and user privacy. In this context, the utilization of quantum-based encryption presents a promising avenue to enhance security in unified software architecture. This study proposes a model aimed at fortifying the security of IoT devices by integrating mobile app authentication with quantum-based encryption techniques. The model leverages Quantum Key …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 41–48 Read article
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Role of Artificial Intelligence in Quantum Materials Research
Abstract: Quantum materials have emerged as a transformative class of advanced materials due to their extraordinary electronic, magnetic, optical, and topological properties governed by quantum mechanical phenomena. These materials are expected to revolutionize next-generation technologies such as quantum computing, spintronics, superconducting electronics, nanoelectronics, intelligent sensing systems, and energy-efficient devices. However, conventional methods for discovering and optimizing quantum materials are often expensive, time-consuming, and computationally intensive because of the enormous complexity of …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 2, 2026 · pp. 13–27 Read article
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Optimal Allocation of FACTS Devices Using Quantum Inspired Evolutionary Programming
Abstract: Quantum Inspired Evolutionary Programming (QIEP) is an optimization technique that combines the benefits of quantum computing and evolutionary algorithms together. In this paper this technique is used to find optimal allocation of Flexible AC Transmission System (FACTS) devices. The results are compared with the results found from genetic algorithms (GAs). Based on the results it can be concluded that QIEP technique is better than GAs. Keywords: QIEP, quantum computing, evolutionary …
Published in Trends in Electrical Engineering · Vol. 5, Issue 1, 2015 · pp. 23–27 Read article
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Quantum-Inspired Neural Networks: Accelerating AI for Large-Scale Data Processing
Abstract: Recently, the world of artificial intelligence has been buzzing with exciting ideas inspired by quantum computing, especially when it comes to processing large amounts of data. Introducing the Quantum-Inspired Neural Network (QINN), a novel approach to conventional neural networks that blends concepts from quantum mechanics with machine learning techniques. Unlike typical networks that rely on neurons, QINNs utilize qubit-based representations, enabling them to perform computations in a more flexible and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 12–17 Read article
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Encryption Mechanism under Prevalent Invasion
Abstract: The digital and computerized era is fast approaching which has increased the amount of data exchanged over the internet. The information transmitted can be accessed by an unauthorized user who can manipulate the data. This fact reveals the need for security mechanisms resulting in various cryptographic algorithms having enhanced protection mechanisms which fulfill the increased demand for security in cyber-attacks and data exploitation. The main goal of these strategies is …
Published in Journal Of Network security · Vol. 9, Issue 2, 2021 · pp. 28–34 Read article
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An Investigative Study of Quantum-safe Secure Multi-party Computation
Abstract: This article represents the comprehensive investigation in the emerging field of quantum-safe secure multi-party computation (QSSMPC) and presents novel perspectives to address the impending threat posed by quantum computers to classical cryptographic systems. As the era of quantum computing approaches, traditional encryption methods become vulnerable to quantum algorithms, necessitating the development of quantum-resistant cryptographic protocols. In this context, the paper introduces innovative approaches to secure multi-party computation in a quantum-safe …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 39–44 Read article
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From Quantum Chemistry to Bioprocess Intensification: Advanced Computational Modeling and Enzyme-Based Catalytic Platforms for Green Chemical Transformations
Abstract: Green chemistry requires the development of sustainable catalytic systems that minimize waste generation, reduce energy consumption, and improve process efficiency. Computational chemistry and biocatalysis have emerged as complementary approaches for environmentally responsible chemical manufacturing. Computational techniques such as quantum chemistry, density functional theory (DFT), molecular dynamics, and machine learning provide mechanistic insights into catalytic reactions and support the rational design of efficient catalysts. These approaches enable the prediction of reaction …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 45–52 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 · pp. 10–22 Read article
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Role of Quantum Chemistry in Catalysis: A Comprehensive Review
Abstract: Catalysis plays a crucial role in modern chemical manufacturing, energy conversion, and environmental protection by enabling chemical reactions to occur more rapidly, selectively, and with reduced energy consumption. A fundamental understanding of catalytic processes at the atomic and electronic levels is essential for the rational design and optimization of catalysts. Quantum chemistry has emerged as a powerful theoretical and computational framework that enables detailed investigation of electronic structure, reaction energetics, …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 1, 2026 · pp. 01–16 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 Read article
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Exploring the Potential of Laser Ablation for Multi-functional Nanoparticle Production
Abstract: The extraordinary class of materials known as nanomaterials has come into being. A large variety of elements with minimum one dimension between 1 and 100 nm are included. Reasonably designed nanomaterials can have exceptionally large surface areas. Nanomaterials can be made to have exceptional mechanical, optical, electrical, magnetic, and catalytic properties that are very different from those of their bulk counterparts. To achieve the necessary features tuning, nanomaterials' size, shape, …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 36–41 Read article
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Next-Generation Photochemical Research Using Cathodoluminescence: Mapping Optical Properties and Resonances at the Nanoscale
Abstract: This study explores the principles and diverse applications of CL, particularly in the analysis of inorganic compounds and nanophotonic structures. It examines various facets of CL, including aperture effects, transmission modes, resolution, momentum, scanning techniques, and modulation within CL imaging. The study underscores significant advancements in CL technology, highlighting its utility in characterizing nanostructures, plasmonic materials, and optoelectronic devices. The discussion emphasizes CL's role in mapping the Local Density of …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 2, Issue 2, 2024 · pp. 01–05 Read article
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Quantum dots: Properties, Synthesis and Applications
Abstract: AbstractSemiconductor nanocrystal or quantum dots are Nano particles composed of ten to few hundreds of atoms but confined in a very small region. These are zero dimensional materials and are gaining attention to the researchers because of their interesting optical, electronic and opto-electronic properties compared to bulk. Quantum mechanical confinement plays a key role in determining the peculiar behaviour compared to bulk. Various preparation methods such as chemical, colloidal synthesis, …
Published in Research & Reviews : Journal of Physics · Vol. 9, Issue 1, 2020 Read article
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Advanced Computational Models for Predicting Molecular Interactions
Abstract: Understanding molecular interactions is essential for a number of disciplines, including biochemistry, materials science, and medication development. Traditional experimental methods, while accurate, are often time-consuming and expensive. Advanced computational models have emerged as powerful tools to predict molecular interactions efficiently. In order to predict the behavior and interactions of molecules at the atomic and subatomic levels, this paper reviews the most recent developments in computational techniques, such as machine learning …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 8–13 Read article
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Using Machine Learning to Guess Photochemical Reaction Pathways
Abstract: Photochemical reactions are crucial to many activities in the fields of energy conversion, environmental cleanup, and synthetic chemistry. However, predicting their causes and results effectively is still very hard since they entail excited electronic states, nonadiabatic transitions, and complicated potential energy surfaces. Machine learning (ML) has been a powerful technique to go along with classic quantum chemistry methods in the last few years. It offers better prediction capability and lower …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 01–12 Read article