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Journal of Tecnologia Quantica
Published by Yayasan Adra Karima Hubbi
ISSN : 30626757     EISSN : 30481740     DOI : 10.70177/quantica
Core Subject : Science,
Physics
Journal of Tecnologia Quantica is dedicated to bringing together the latest and most important results and perspectives from across the emerging field of quantum science and technology. Journal of Tecnologia Quantica is a highly selective journal; submissions must be both essential reading for a particular sub-field and of interest to the broader quantum science and technology community with the expectation for lasting scientific and technological impact. We therefore anticipate that only a small proportion of submissions to Journal of Tecnologia Quantica will be selected for publication. We feel that the rapidly growing QST community is looking for a journal with this profile, and one that together we can achieve. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.
Arjuna Subject : Fisika dan Astronomi - Fisika Nuklir dan Molekuler, dan Ooptik
Articles 60 Documents
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Quantum Computing and Complexity Theory Sucipto, Purwo Agus; Judijanto, Loso; Qudah, Nasser
Journal of Tecnologia Quantica Vol. 2 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i1.1967

Abstract

The background of this research is driven by the rapid development of quantum computing which has the potential to change the paradigm in complexity theory and computational algorithms. The purpose of this study is to explore the advantages and limitations of quantum algorithms in solving problems with high complexity, as well as to understand their role in complexity theory. The research method used involves quantum computer simulations to analyze the performance of Shor and Grover's algorithms in solving cryptographic problems and large database searches, as well as comparing them with classical algorithms. The results show that quantum algorithms have significant advantages in solving certain problems, although there are technical obstacles in quantum hardware that affect overall performance. Quantum computing has great potential in the fields of cryptography and big data processing, but challenges such as quantum errors and decoherence still have to be overcome. The conclusion of this study confirms the importance of further research in improving quantum hardware and developing more efficient algorithms, as well as opening up new opportunities for the application of quantum computing in various industries.
Quantum Biology: The Interaction of Quantum Mechanics in Biological Systems Phuntsho, Dorji; Lhamo, Pema; Ahmad, Omar
Journal of Tecnologia Quantica Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i3.1968

Abstract

Research Background: Quantum Biology is a branch of science that studies the interaction between quantum mechanics and biological systems. Some early studies have shown that quantum phenomena affect the efficiency of biological processes, but understanding of their applications is still limited. Research Objectives: This study aims to investigate how quantum mechanics plays a role in biological processes, especially in photosynthesis and magnetic navigation in migratory birds. Research Methods: This research uses laboratory experiments with an interdisciplinary approach, combining quantum physics and molecular biology techniques. The samples used included plant culture cells and migratory birds, as well as data analysis using mathematical modeling to describe quantum phenomena in biological systems. Research Results: The results show that quantum phenomena, such as coherence and entanglement, play a role in improving the efficiency of photosynthesis and the ability of birds to navigate based on the Earth's magnetic field. The study also identified a quantum mechanism that accelerates metabolic processes in cells. Research Conclusions: This study provides strong evidence that quantum mechanics can directly affect biological systems. These findings open up opportunities for the development of quantum-based biotechnology, as well as provide new insights into understanding more efficient and coordinated biological processes.
Quantum Computing to Forecast Extreme Weather Rith, Vicheka; Vann, Dara; Santos, Luis
Journal of Tecnologia Quantica Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i3.1970

Abstract

The background of this research focuses on the challenges in forecasting extreme weather that is increasingly frequent due to climate change. Conventional weather models still face limitations in terms of accuracy and computational time, especially in predicting extreme weather phenomena. The purpose of this study is to explore the potential of quantum computing in predicting extreme weather by improving prediction accuracy and accelerating computational processes. The research method used involves the development and testing of weather prediction models based on quantum algorithms on extreme weather phenomena such as tropical storms, heavy rains, and heat waves. The results show that the quantum model is able to improve prediction accuracy by up to 92% for tropical storms and accelerate the computational time from 48 hours to 5 hours. The conclusion of the study is that quantum computing offers a more efficient and accurate solution in forecasting extreme weather, with great potential for practical applications in early warning and mitigation of weather disasters.
The Effectiveness of Interactive Learning Media Based on Augmented Reality in Enhancing Elementary School Students’ Learning Motivation Faisal, Faisal; Rachmat, Rachmat; Asia, Siti Nur; Suherwin, Suherwin; Ibrahim, Abdul
Journal of Tecnologia Quantica Vol. 2 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i3.2443

Abstract

This study aims to analyze the effectiveness of using augmented reality (AR) based learning media in enhancing the learning motivation of elementary school students. By employing a multiple linear regression approach on simulated data, this research evaluates the influence of several key factors, namely AR visualization quality, teacher support, ease of use, and supporting infrastructure. The analysis results show that AR visualization quality, teacher support, and ease of use significantly affect the improvement of learning motivation. The developed model has a coefficient of determination (R² ? 0.77), indicating that 77% of the variation in learning motivation can be explained by the independent variables, with a relatively small prediction error (RMSE ? 0.53). The F-test also confirmed that the model is overall significant. These findings indicate that the integration of AR in learning not only increases visual appeal but also strengthens the role of teachers and enhances students’ ease of interaction with the material. Nevertheless, this study is still based on simulated data, so further research with broader and more realistic empirical data is required to validate the results.
Implementation of Blockchain Technology to Improve Transparency and Accountability in the Mineral Supply Chain Kasmira, Kasmira
Journal of Tecnologia Quantica Vol. 2 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i5.2537

Abstract

This study analyzes the potential and challenges of implementing blockchain technology to enhance transparency, accountability, and traceability in mineral supply chains. Using a qualitative approach with case-study methods and thematic analysis of interviews, company reports, regulatory documents, and scientific literature, the study compares initiatives by several industry actors. The findings show that blockchain strengthens end?to?end provenance tracking, authenticity verification, compliance with environmental and ethical standards, and minimizes data manipulation and illicit trade practices. In addition, blockchain integration drives operational efficiency and inter?stakeholder trust through immutable, auditable transaction logs. However, adoption faces structural barriers in the form of regulatory uncertainty, limited digital infrastructure in developing countries, and organizational resistance to system change. This study recommends establishing clear regulatory frameworks, public–private collaboration, cross?platform data standardization, and capacity building including integration with IoT and digital identity to maximize blockchain’s impact on more sustainable and responsible governance of mineral supply chains.
Error Correction Codes for Fault-Tolerant Quantum Computation in Superconducting Qubit Architectures Judijanto, Loso; Rith, Vicheka; Sok, Vanna
Journal of Tecnologia Quantica Vol. 2 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i4.2790

Abstract

Fault-tolerant quantum computation remains a central challenge in superconducting qubit architectures, where decoherence, crosstalk, and gate infidelities significantly degrade computational reliability. Although quantum error correction (QEC) codes are widely assumed to provide scalable protection, their practical performance depends critically on hardware-specific noise characteristics that are often underexamined. This study aims to evaluate the effectiveness of leading QEC codes specifically the surface code, Bacon-Shor code, and low-density parity-check (LDPC) quantum codes when implemented on contemporary superconducting qubit platforms. A simulation-based methodological approach is employed, integrating stochastic noise modeling, syndrome extraction analysis, and threshold estimation using density-matrix simulations calibrated with experimentally reported parameters. The results indicate that while the surface code maintains the highest threshold under realistic two-qubit gate fidelities, LDPC-based schemes exhibit superior logical qubit compression but suffer from decoding overhead that limits near-term applicability. The study also identifies parameter regimes where Bacon-Shor codes offer competitive performance due to their reduced measurement complexity. The findings suggest that no single QEC code uniformly outperforms others; instead, code selection must be matched to hardware-specific noise anisotropy and architectural constraints. The research concludes that optimizing QEC for superconducting qubits requires hybrid design strategies that integrate code efficiency with architecture-aware gate scheduling.
A Novel Quantum Algorithm for Solving Non-Linear Differential Equations with Potential Exponential Speedup Judijanto, Loso; Rocha, Thiago; Lima, Rafaela
Journal of Tecnologia Quantica Vol. 2 No. 6 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i4.2792

Abstract

Non-linear differential equations constitute the mathematical foundation of complex physical, biological, and engineering systems, yet classical numerical solvers often suffer from prohibitive computational costs as system dimensionality increases. Quantum computation offers a promising pathway for accelerating such calculations, although existing quantum algorithms primarily address linear differential models and fail to generalize efficiently to non-linear regimes. This study aims to develop and evaluate a novel quantum algorithm designed specifically to approximate solutions to non-linear differential equations with a potential exponential speedup over classical methods. The proposed approach integrates a variational quantum ansatz with non-linear Hamiltonian embedding and amplitude encoding to capture non-linearity within a tractable quantum framework. Simulations were conducted on noisy intermediate-scale quantum (NISQ) models and idealized quantum circuits to benchmark accuracy, convergence behavior, and computational scaling. The results indicate that the algorithm achieves stable convergence across representative non-linear systems while demonstrating a significant reduction in computational complexity relative to classical solvers, particularly for high-dimensional models. The study concludes that the proposed algorithm represents a viable direction for quantum-enhanced numerical analysis and may serve as a foundation for future quantum solvers targeting complex dynamical systems.
Topological Quantum Computation Using Majorana Fermions in Nanowire Networks: A Theoretical Feasibility Study Judijanto, Loso; Zaman, Khalil; Ali, Zara
Journal of Tecnologia Quantica Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i4.2793

Abstract

Topological quantum computation offers a promising pathway toward fault-tolerant quantum information processing, with Majorana fermions emerging as key quasiparticles capable of encoding quantum states protected from local decoherence. Nanowire networks engineered to host Majorana zero modes have been widely proposed, yet their practical feasibility requires rigorous theoretical assessment under realistic physical constraints. This study aims to evaluate the theoretical viability of implementing topological quantum computation using Majorana fermions in semiconductor–superconductor nanowire networks. A modeling framework incorporating Bogoliubov–de Gennes equations, topological phase diagrams, non-Abelian braiding protocols, and disorder-induced perturbations is employed to assess stability and control requirements. Simulations investigate parameter regimes involving magnetic field strength, spin–orbit coupling, proximity-induced superconductivity, and wire-junction geometries. The results show that stable Majorana modes can be achieved within narrow but experimentally accessible parameter windows, and that non-Abelian braiding operations remain topologically robust against moderate disorder and quasiparticle poisoning. The study concludes that while significant engineering challenges persist—particularly regarding temperature constraints, material uniformity, and junction coherence—Majorana-based topological quantum computation remains theoretically feasible with current technological progress.
The Post-Quantum Cryptography Challenge: A Security Analysis of Lattice-Based vs. Code-Based Algorithms Judijanto, Loso; Hui, Zhou; Wei, Sun
Journal of Tecnologia Quantica Vol. 3 No. 2 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i5.2794

Abstract

The emergence of large-scale quantum computers poses a critical threat to classical public-key cryptographic systems, prompting the rapid development of post-quantum cryptography as a foundational component of future digital security. Lattice-based and code-based algorithms have become leading candidates due to their strong conjectured resistance to quantum attacks; however, their comparative security characteristics remain insufficiently examined under unified analytical frameworks. This study aims to provide a comprehensive security analysis of lattice-based and code-based post-quantum cryptographic algorithms by evaluating their resilience against known classical and quantum attack vectors. A structured methodological approach is employed, combining complexity-theoretic assessment, parameter-sensitivity evaluation, and simulated attack modeling across representative schemes such as CRYSTALS-Kyber, NTRU, Classic McEliece, and BIKE. The results indicate that lattice-based schemes offer strong security margins under current attack models but exhibit notable sensitivity to parameter misconfiguration and structured lattice weaknesses. Code-based schemes demonstrate exceptional robustness due to the hardness of decoding random linear codes, yet face practical limitations in key size and implementation overhead. The study concludes that both families remain viable for post-quantum standardization, although their security assurances depend heavily on careful parameter selection and continued cryptanalytic scrutiny as quantum hardware evolves.
Diamond-Based Quantum Sensors for High-Resolution Magnetic Field Imaging of Neural Activity A, Muhammad Firdaus; Tan, Ethan; Lee, Ava
Journal of Tecnologia Quantica Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i5.2795

Abstract

Advances in quantum sensing technologies have opened new opportunities for noninvasive, high-resolution detection of neural activity, particularly through diamond-based quantum sensors utilizing nitrogen–vacancy (NV) centers. Conventional neuroimaging techniques often face limitations in spatial resolution, temporal precision, and sensitivity to weak magnetic fields generated by neuronal currents. These constraints motivate the development of quantum-enhanced sensing approaches capable of capturing neural dynamics with unprecedented fidelity. This study aims to evaluate the performance of diamond-based quantum sensors for high-resolution magnetic field imaging and to assess their potential for real-time neural activity monitoring. A combined experimental and simulation-based methodology was employed, involving controlled magnetic field measurements using NV-center ensembles, calibration against established magnetometry systems, and computational modeling of neuronal magnetic signatures. The results show that NV-based sensors achieve sub-micron spatial resolution and detect magnetic fields in the nanotesla range, significantly outperforming traditional optical and electromagnetic techniques. The findings further demonstrate strong temporal responsiveness, enabling the reconstruction of fast neuronal firing patterns. The study concludes that diamond-based quantum sensors represent a promising frontier for next-generation neuroimaging, offering a scalable, minimally invasive platform for studying neural circuits with high spatial–temporal precision.

Page 5 of 6 | Total Record : 60

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