Search
120 articles for “quantum computers”
-
Nuclear Hulthén potentials for F and G partial waves
Abstract: In the past few decades, several investigation have been made and at the same time a number of theoretical models have also been projected for the nucleon-nucleon scattering in the low and intermediate energy range. These phenomenological models involve large number of free parameters to be fitted to reproduce the physical observables. In contrast to these potentials a two-term four parameter nuclear Hulthén type interaction is proposed to describe the …
Published in Research & Reviews : Journal of Physics · Vol. 10, Issue 2, 2021 · pp. 31–37 Read article
-
A Comprehensive Study of Quantum Cryptography
Abstract: Quantum cryptography has emerged as one of the most promising fields in modern information security, offering innovative solutions that have the potential to transform the future of global cyber-defense. Unlike classical cryptographic systems, which depend primarily on the computational difficulty of solving complex mathematical problems, quantum cryptography is grounded in the fundamental and unbreakable laws of quantum mechanics. Core principles such as superposition, entanglement, and the uncertainty principle form the …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 12–26 Read article
-
Performance Enhancement of Laser based Modern Railway Mobile Platform Crossing System
Abstract: AbstractIn this work, the modern railway mobile platform crossing system is improved through the proper computation of GaInP based 635 nm multiple quantum well red laser maintaining the perfect peak intensity of the power which is achieved at 635 nm. By analyzing the performance of the designed Ga0.5In0.5P/ (Al0.5Ga0.5)0.5In0.5P edge emitting laser the peak material gain is obtained. Sustaining threshold current of 6.7 mA, a maximum resonance frequency of 10 …
Published in Trends in Opto-electro & Optical Communication · Vol. 4, Issue 1, 2014 · pp. 23–28 Read article
-
Finest Round Robin Scheduling Algorithm using Effective Time Quantum
Abstract: Scheduling is a most important task of operating-system function. Almost all computer resources are scheduled before use. CPU scheduling is the main task of multi -programmed operating systems. By switching the CPU among processes, the operating system can make the computer more effectively [1]. The CPU is one of the primary computer resources so its scheduling is central to operating-system design. In a simple computer system, the CPU then just …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 1, Issue 1, 2014 · pp. 4–8 Read article
-
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
-
Harnessing Artificial Intelligence for Precision Physics: A Machine Learning Framework for Data Reconstruction in Support of India's Deep-Tech Missions
Abstract: India's emergence as a global leader in deep-tech innovation is driven by ambitious scientific megaprojects, including the Laser Interferometer Gravitational-Wave Observatory (LIGO)-India, the X-ray Polarimeter Satellite (XPoSat), the Aditya-L1 solar observatory, and the National Quantum Mission (NQM). However, the unprecedented scale and complexity of the observational data generated by these missions present severe computational bottlenecks. Traditional analytical frameworks struggle with non-stationary noise transients, diffusion blurring, and the exponential scaling limits …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 2, 2026 · pp. 48–55 Read article
-
Complex Space-Time and the Structure of Relativistic Quantum Theory
Abstract: Relativistic quantum mechanics was developed to reconcile the principles of quantum mechanics with Einstein’s theory of relativity. Despite its success in describing high-energy particles, the theory continues to face unresolved conceptual and mathematical difficulties, particularly in relation to the nature of time, causality, and relativistic consistency. In recent years, the idea of extending space-time into the complex domain has emerged as a useful and potentially meaningful approach to these problems. …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 22–27 Read article
-
Integrated Computational and Bio-catalytic Transformations: DFT-Guided Mechanistic Insights, Machine Learning, and Nano-biocatalyst Engineering for Sustainable Catalysis
Abstract: Computational catalysis has emerged as a transformative scientific discipline that integrates quantum chemistry, molecular modeling, machine learning, and density functional theory (DFT) to understand catalytic mechanisms and design highly efficient catalytic systems for sustainable industrial applications. The increasing global demand for environmentally responsible chemical manufacturing has accelerated research on advanced catalytic materials including transition metal catalysts, metal–organic frameworks (MOFs), homogeneous catalysts, heterogeneous systems, and bimetallic catalysts involving nickel and iron. …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 36–44 Read article
-
Shape Features based classification of Herbal Plants from its Powder using Microscopic Image
Abstract: An identification and classification of herbal plants from its powder using the microscopic image is a challenging task. In this paper, a new approach for identification and classification of Indian herbal plants liquorice, rhubarb and dhatura using the microscopic image is proposed. This paper evaluates the effectiveness of the shape based features with a different classifier for classification of herbal plants. The analysis of microscopic images performed in three stages: …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 2, 2018 · pp. 48–58 Read article
-
Emerging Paradigms in Parallel Computing: Trends and Innovations
Abstract: Parallel computing is at an inflection point with revolutionary new paradigms and technologies. The goal of this paper is to survey the recent trend in parallel computing from architecture, programming model and applications. Mahajan cites a litany of architectural developments such as heterogeneous computing systems with integrated graphics processing unit/central processing unit ; the emerging promise from quantum and neuromorphic architectures (please see later); advances in packing transistors using novel …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 39–43 Read article
-
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
-
CPU Scheduling Algorithm Round Robin with Dynamic Time Quantum
Abstract: CPU programming in the operating system is one of the basic factors for determining the performance of the multitasking operating system which makes a computer system more productive by changing the CPU between processes. An operating system manages all operations that continuously and consistently manage the available resources provided by the system in an optimal approach. Process planning is the important operating system functionality for process management. The most popular …
Published in Journal of Electronic Design Technology · Vol. 12, Issue 2, 2021 · pp. 31–37 Read article
-
Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 15–24 Read article
-
Design and Performance Analysis of a 635 nm Ga0.5In0.5P/(Al0.7Ga0.3)0.5In0.5P Multiple Quantum Well Separate Confinement Heterostructure Red Laser Considering Thermal Limitations
Abstract: AbstractIn this work, the performance characteristics of a GaInP - based 635 nm multiple quantum well (MQW) separate confinement heterostructure (SCH) Red laser has been obtained through computations. The material gain of Ga0.5In0.5P/(Al0.5Ga0.5)0.5In0.5P MQW edge emitting laser (EEL) has been theoretically obtained. The peak material gain obtained from the analysis has been used for analyzing the performance of the designed double-heterostructure laser. A maximum output power of 71.18 mW and …
Published in Trends in Opto-electro & Optical Communication · Vol. 3, Issue 1, 2013 · pp. 11–17 Read article
-
McEliece Cryptosystem based User Authentication Scheme in Fog Computing Environment
Abstract: AbstractIn the recent past, the notion of Internet of Things has gained tremendous pace worldwide. IoT provides several services for the ease of human life in several significant areas such as health care, logistics, power grid etc. To keep these devices connected in an efficient network, the concept of Fog network has taken precedence over all other network architectures. Fog network has taken the services provided by a centralized cloud …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 6, Issue 1, 2019 · pp. 17–23 Read article
-
Modelling and Electrical Characterization of Single Electron Transistor
Abstract: A nano-electronic device with low power consumption, high performance, and quantum effects is the single electron transistor (SET). It's used in charge sensor applications, infrared radiation detectors, and spectroscopy. However, it faces limitations in lithography, co-tunneling effect, low gain, high output impedance, and background charges. Therefore, prior simulation is needed to optimize SET's work function and understanding physics concepts. A master equation approach is used to propose a new model …
Published in Journal of Semiconductor Devices and Circuits · Vol. 10, Issue 3, 2024 · pp. 19–25 Read article
-
Report on the Effects of Mole Fraction, Doping Concentration, Gate Length and Nano-Layer Thickness to Control the Device Engineering in the Nanoelectronic AlGaN/GaN HEMTs at 300 K to Enhance the Reputation of the NIT Arunachal Pradesh
Abstract: In this work, we report total 20748 individual simulation-outputs according to the performed simulation-studies on the Nanoelectronic AlGaN/GaN high electron mobility transistors (HEMTs). This series of simulation work has been performed using the SILVACO-ATLAS software tool. In this work, the drain characteristics is investigated with respect to the Aluminium mole fraction, doping concentration, drain voltage, gate voltage, gate length and thickness of the AlGaN nano-layer. The investigation on the effect …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 19, Issue 1, 2017 · pp. 15–47 Read article
-
Hierarchical Computational Modeling of Physical Structure Across Quark, Nuclear, and Atomic Scales
Abstract: We present a modular, multi-scale computational framework that integrates physical modeling and visualization across quark, nuclear, and atomic scales within a unified pipeline. Developed to address the traditional fragmentation between sub-nucleonic, nuclear, and electronic representations, the system provides a continuous data flow and visualization bridge spanning from femtometers to ångströms. The framework consists of three primary modules: a particle-level module illustrating nucleons as confined quark-triplets with effective flux-tube geometries; a …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 1, 2026 · pp. 38–53 Read article
-
Improved Performance Characteristics of a Designed 1050 nm Bottom Emitting MQW VCSEL using Al0.25Ga0.22In0.53As/InP Materials
Abstract: AbstractIn this work, the design and performance characteristics of a bottom emitting Al0.25Ga0.22In0.53As/InP Multi-Quantum Well (MQW) Vertical-Cavity Surface-Emitting Lasers (VCSEL) have been presented for operation at a wavelength of 1050 nm. The transparency carrier density and bandgap energy of the QW and barrier materials are computed. An improved performance of the designed VCSEL has been obtained by selecting a material with high gain and lower transparency carrier density in the …
Published in Trends in Opto-electro & Optical Communication · Vol. 3, Issue 3, 2013 · pp. 22–30 Read article
-
Study of an Improved Quantum Particle Swarm Optimization-Based Framework for Neural Network Optimization in Modelling of Polymer Data
Abstract: The accurate forecasting of polymer viscosity at various physicochemical conditions has been quite critical due to the nonlinear interactions and interrelations between the variables. This paper suggests a better hybrid modelling framework, which involves the use of Artificial Neural Networks (ANN) and more advanced versions of Quantum Particle Swarm Optimization (QPSO) to better predict polymer viscosity. The input parameters taken are, namely, log (shear rate), polymer concentration, NaCl concentration, Ca …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 282–297 Read article