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Journal articles on the topic 'Quantum-Classical Bridge'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Anusha Kondam. "Quantum API Gateways: Exploring the Future of Secure and Scalable Communication in Quantum Computing Environments." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 3 (2025): 957–64. https://doi.org/10.32628/cseit25113373.

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As quantum computing advances, the need for secure and scalable communication in quantum environments becomes increasingly important. Quantum API Gateways have emerged as a promising solution to address this challenge. These gateways bridge classical and quantum communication, enabling the secure transfer of information between classical and quantum systems. Through advanced cryptographic techniques and quantum key distribution protocols, Quantum API Gateways provide high security for data transmission in quantum computing environments. They also offer a scalable approach, allowing for the sea

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2

J, Navyasri. "A Learning-Oriented Quantum Circuit Simulator with Classical Problem Extensions." International Journal for Research in Applied Science and Engineering Technology 13, no. 7 (2025): 842–46. https://doi.org/10.22214/ijraset.2025.72898.

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Quantum computing introduces new paradigms for solving complex computational problems. In this paper, we present the development of a full-stack quantum computing simulator that enables users to design, simulate, and visualize quantum circuits, while also integrating classical NP problem solvers. Built using Python, Qiskit, React, and Flask/FastAPI, the simulator supports up to 20 qubits and includes features like quantum gate editing, Bloch sphere visualization, and classical algorithms for 3-SAT and Knapsack. The project aims to bridge accessibility and functionality in quantum computing edu

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Curtis, Lorenzo J., and David G. Ellis. "Probabilities as a bridge between classical and quantum-mechanical treatments." European Journal of Physics 27, no. 3 (2006): 485–96. http://dx.doi.org/10.1088/0143-0807/27/3/002.

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Li, Suyu, Canneng Liang, and Mingxing Jin. "Precision Limit for Observation: The Bridge for Quantum Classical Transitions." Journal of Quantum Information Science 15, no. 01 (2025): 59–74. https://doi.org/10.4236/jqis.2025.151004.

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5

SINGH, PARAMPREET. "QUANTUM GEOMETRY AND THE BIG BANG." International Journal of Modern Physics D 15, no. 10 (2006): 1707–23. http://dx.doi.org/10.1142/s0218271806009054.

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Loop quantum cosmology provides a new paradigm on the genesis of our universe in which the classical expanding branch is joined via a quantum geometric bridge to a classical contracting branch. The evolution between two phases of our universe is non-singular and deterministic, which is a direct manifestation of incorporating non-perturbative quantum geometric features of loop quantum gravity. Using analytical and numerical techniques, details of the quantum nature of big bang can be quantified and reliable physical predictions can be made. The quantum description can also be well approximated

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Tunçel, Kaya. "Exploration and Development of Quantum Computing Algorithms for Optimization, Cryptography, and Machine Learning Applications." Human Computer Interaction 8, no. 1 (2024): 1. http://dx.doi.org/10.62802/1dwq2w96.

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Quantum computing, with its potential to revolutionize computation, relies fundamentally on the development of efficient algorithms to leverage its unparalleled processing capabilities. This research delves into the creation, exploration, and refinement of quantum computing algorithms, focusing on their applications in optimization, cryptography, and machine learning. Quantum algorithms such as Shor's and Grover's have demonstrated remarkable advantages in factorization and search problems, while more recent innovations are tackling complex challenges in global optimization and data analysis.

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Pennini, Flavia, and Angelo Plastino. "Quantumness’ Degree of Thermal Optics’ Approximations." Symmetry 14, no. 10 (2022): 2052. http://dx.doi.org/10.3390/sym14102052.

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We assess the degree of quantumness of the P, Q, and W quantum optics’ approximations in a thermal context governed by the canonical ensemble treatment. First, we remint the reader of the bridge connecting quantum optics with statistical mechanics using the abovementioned approximations at the temperature T. With the ensuing materials, we explore with some detail some features of the above bridge, related to the entropy and to thermal uncertainties. Some new relations concerning the degree of quantumness of the P, Q, and W are obtained by comparison between them and the exact and classical tre

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Azanaw, Girmay Mengesha. "Quantum–Classical Synergies in Topology Optimization for 3D-Printed UHPC Bridge Structures: A Critical Review of Computational Paradigms, Sustainability Metrics, and Scalability Barriers." International Journal of Emerging Science and Engineering 13, no. 7 (2025): 15–23. https://doi.org/10.35940/ijese.g2606.13070625.

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Recent advances in quantum computing, combined with classical algorithms, are reshaping how engineers approach topology optimization (TO), particularly in the context of 3Dprinted ultra-high-performance concrete (UHPC) bridge structures. This review critically examines how hybrid quantum– classical methods are influencing structural design workflows, with a focus on theoretical frameworks, computational strategies, sustainability metrics, and practical scalability. Drawing on a wide range of current academic literature and case-based studies, the paper assesses how quantum approaches, such as

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Güler, Ata Ulaş. "Quantum Algorithms for Image Processing: Enhancing Computational Efficiency and Accuracy in High-Dimensional Visual Data Analysis." Human Computer Interaction 8, no. 1 (2024): 57. http://dx.doi.org/10.62802/hxc0ag94.

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Quantum algorithms have emerged as a transformative approach to address the computational challenges of high-dimensional image processing tasks. This research investigates the integration of quantum computing principles, such as Quantum Fourier Transform (QFT) and Quantum Principal Component Analysis (QPCA), to optimize processes like edge detection, noise reduction, and image segmentation. These quantum-enhanced techniques promise significant improvements in computational efficiency and accuracy compared to classical methods, especially when handling complex visual data in real-time applicati

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Choppakatla, Arathi. "Quantum Machine Learning: Bridging the Gap Between Quantum Computing and Artificial Intelligence: An Overview." International Journal for Research in Applied Science and Engineering Technology 11, no. 8 (2023): 1149–53. http://dx.doi.org/10.22214/ijraset.2023.55318.

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Abstract: Quantum Machine Learning (QML) at the intersection of quantum computing and artificial intelligence (AI) is explored, emphasizing its role in connecting these domains. The transformative potential of QML in enhancing classical machine learning and the introduction of the Variational Quantum Classifier (VQC) algorithm (Ref. 4) are highlighted. Fundamental quantum principles, quantum feature maps, and the VQC's use of parameterized quantum circuits are discussed (Refs. 1, 3). The paper addresses practical implementation, optimization techniques, and the VQC's performance through empiri

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REGISTER, LEONARD F. "SCHRÖDINGER EQUATION MONTE CARLO: BRIDGING THE GAP FROM QUANTUM TO CLASSICAL TRANSPORT." International Journal of High Speed Electronics and Systems 09, no. 01 (1998): 251–79. http://dx.doi.org/10.1142/s0129156498000129.

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Schrödinger Equation and (based) Monte Carlo (SEMC), a simulation method designed to bridge the gap from quantum to classical transport, is described. This method provides a non-perturbative, current conserving quantum mechanical treatment of carriers, phonons, and their coupling, yet the SEMC algorithm is analogous to and compatible with that of semiclassical Monte Carlo (SMC). Indeed, SEMC allows carriers to be followed through a sequence of stochastically sampled scattering events. Phase breaking and energy dissipation for charge carriers within the Schrödinger-equation-based method are mod

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12

Gu, Yan, and Jiao Wang. "The Group-Algebraic Formalism of Quantum Probability and Its Applications in Quantum Statistical Mechanics." Entropy 27, no. 1 (2025): 59. https://doi.org/10.3390/e27010059.

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We show that the theory of quantum statistical mechanics is a special model in the framework of the quantum probability theory developed by mathematicians, by extending the characteristic function in the classical probability theory to the quantum probability theory. As dynamical variables of a quantum system must respect certain commutation relations, we take the group generated by a Lie algebra constructed with these commutation relations as the bridge, so that the classical characteristic function defined in a Euclidean space is transformed to a normalized, non-negative definite function de

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13

Souissi, Abdessatar, Tarek Hamdi, Farrukh Mukhamedov, and Amenallah Andolsi. "On the Structure of Quantum Markov Chains on Cayley Trees Associated with Open Quantum Random Walks." Axioms 12, no. 9 (2023): 864. http://dx.doi.org/10.3390/axioms12090864.

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Quantum Markov chains (QMCs) and open quantum random walks (OQRWs) represent different quantum extensions of the classical Markov chain framework. QMCs stand as a more profound layer within the realm of Markovian dynamics. The exploration of both QMCs and OQRWs has been a predominant focus over the past decade. Recently, a significant connection between QMCs and OQRWs has been forged, yielding valuable applications. This bridge is particularly impactful when studying QMCs on tree structures, where it intersects with the realm of phase transitions in models naturally arising from quantum statis

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14

Hansen, F. "Characterizations of symmetric monotone metrics on the state space of quantum systems." Quantum Information and Computation 6, no. 7 (2006): 597–605. http://dx.doi.org/10.26421/qic6.7-3.

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The quantum Fisher information is a Riemannian metric, defined on the state space of a quantum system, which is symmetric and decreasing under stochastic mappings. Contrary to the classical case such a metric is not unique. We complete the characterization, initiated by Morozova, Chentsov and Petz, of these metrics by providing a closed and tractable formula for the set of Morozova-Chentsov functions. In addition, we provide a continuously increasing bridge between the smallest and largest symmetric monotone metrics.

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Hsiang, Jen-Tsung, and Bei-Lok Hu. "Intrinsic Entropy of Squeezed Quantum Fields and Nonequilibrium Quantum Dynamics of Cosmological Perturbations." Entropy 23, no. 11 (2021): 1544. http://dx.doi.org/10.3390/e23111544.

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Density contrasts in the universe are governed by scalar cosmological perturbations which, when expressed in terms of gauge-invariant variables, contain a classical component from scalar metric perturbations and a quantum component from inflaton field fluctuations. It has long been known that the effect of cosmological expansion on a quantum field amounts to squeezing. Thus, the entropy of cosmological perturbations can be studied by treating them in the framework of squeezed quantum systems. Entropy of a free quantum field is a seemingly simple yet subtle issue. In this paper, different from

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16

Nakaji, Kouhei, Suguru Endo, Yuichiro Matsuzaki, and Hideaki Hakoshima. "Measurement optimization of variational quantum simulation by classical shadow and derandomization." Quantum 7 (May 4, 2023): 995. http://dx.doi.org/10.22331/q-2023-05-04-995.

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Simulating large quantum systems is the ultimate goal of quantum computing. Variational quantum simulation (VQS) gives us a tool to achieve the goal in near-term devices by distributing the computation load to both classical and quantum computers. However, as the size of the quantum system becomes large, the execution of VQS becomes more and more challenging. One of the most severe challenges is the drastic increase in the number of measurements; for example, the number of measurements tends to increase by the fourth power of the number of qubits in a quantum simulation with a chemical Hamilto

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17

Ge Xian-Hui. "Zeno's paradox and black hole information loss problem." Acta Physica Sinica 74, no. 8 (2025): 0. https://doi.org/10.7498/aps.74.20241751.

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The black hole information paradox—a fundamental conflict between quantum unitarity and semi-classical gravity—remains unresolved within the framework of quantum gravity. This work establishes a conceptual bridge between this modern dilemma and Zeno’s ancient paradox of motion, emphasizing their shared dependence on limit processes to reconcile infinite divisibility with finite physical outcomes. While prior works established information conservation in black hole evaporation via replica wormholes, this study transcends mere unitarity verification to address a deeper question: <i>How do

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18

J, Kamalakumari, Ajmeera Kiran, Gadige Radha, Yedla Chandini, Mohit Tiwari, and Hemamalini V. "Quantum Cryptography Protocols Ensuring Secure Communication in the Era of Quantum Computing." ITM Web of Conferences 76 (2025): 05009. https://doi.org/10.1051/itmconf/20257605009.

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Quantum cryptography has emerged as a revolutionary technology for ensuring secure communication in the era of quantum computing. While existing research primarily focuses on theoretical frameworks and small-scale experimental setups, significant challenges remain in practical implementation, scalability, and security vulnerabilities. This study aims to bridge the gap between theory and real-world deployment by developing robust quantum cryptographic protocols that address key challenges such as noise management, side-channel attacks, and Trojan horse attacks. Additionally, we propose an optim

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Lokesh BS. "Secure Quantum Machine Learning via Quantum Cryptography: Theoretical Framework and Implementation Insights." Journal of Information Systems Engineering and Management 10, no. 49s (2025): 1255–65. https://doi.org/10.52783/jisem.v10i49s.10122.

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As quantum machine learning (QML) continues to evolve, it promises unparalleled computational advantages in processing complex data. However, the rise of QML also introduces critical concerns regarding data security and privacy, particularly in sensitive domains such as healthcare, finance, and defense. Classical cryptographic methods fall short in addressing threats that arise in quantum communication and computation environments. To bridge this gap, this paper presents a hybrid framework that integrates quantum cryptography—specifically Quantum Key Distribution (QKD)—with QML pipelines, ensu

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20

Davoudi, Zohreh, Chung-Chun Hsieh, and Saurabh V. Kadam. "Scattering wave packets of hadrons in gauge theories: Preparation on a quantum computer." Quantum 8 (November 11, 2024): 1520. http://dx.doi.org/10.22331/q-2024-11-11-1520.

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Quantum simulation holds promise of enabling a complete description of high-energy scattering processes rooted in gauge theories of the Standard Model. A first step in such simulations is preparation of interacting hadronic wave packets. To create the wave packets, one typically resorts to adiabatic evolution to bridge between wave packets in the free theory and those in the interacting theory, rendering the simulation resource intensive. In this work, we construct a wave-packet creation operator directly in the interacting theory to circumvent adiabatic evolution, taking advantage of resource

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21

Cao, Zhaozhong. "Uncertainty principle and complementary variables." Highlights in Science, Engineering and Technology 61 (July 30, 2023): 18–23. http://dx.doi.org/10.54097/hset.v61i.10260.

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The two most important areas in modern physics are quantum mechanics and the theory of relativity. Unlike classical physics, where Newton's mechanics dominates, these two areas change human beings' fundamental view of the universe. One of the theories that build up the base of quantum mechanics is Heisenberg's Uncertainty Principle. Starting from a thought experiment, Heisenberg's microscope in the setting of classical physics, Werner Heisenberg built a bridge between classical and quantum physics by presenting a counterintuitive outcome in the thought experiment. Since then, the observer of a

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22

Lin, Wayne, Georgios Piliouras, Ryann Sim, and Antonios Varvitsiotis. "Learning in Quantum Common-Interest Games and the Separability Problem." Quantum 9 (April 3, 2025): 1689. https://doi.org/10.22331/q-2025-04-03-1689.

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Learning in games has emerged as a powerful tool for machine learning with numerous applications. Quantum games model interactions between strategic players who have access to quantum resources, and several recent works have studied learning in the competitive regime of quantum zero-sum games. Going beyond this setting, we introduce quantum common-interest games (CIGs) where players have density matrices as strategies and their interests are perfectly aligned. We bridge the gap between optimization and game theory by establishing the equivalence between KKT (first-order stationary) points of a

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23

Moffat, John W. "Complex Riemannian Spacetime and Singularity-Free Black Holes and Cosmology." Axioms 14, no. 6 (2025): 459. https://doi.org/10.3390/axioms14060459.

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An approach is presented to address singularities in general relativity using a complex Riemannian spacetime extension. We demonstrate how this method can be applied to both black hole and cosmological singularities, specifically focusing on the Schwarzschild and Kerr black holes and the Friedmann–Lemaître–Robertson–Walker (FLRW) Big Bang cosmology. By extending the relevant coordinates into the complex plane and carefully choosing integration contours, we show that it is possible to regularize these singularities, resulting in physically meaningful, singularity-free solutions when projected b

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LaRacuente, Nicholas, Kaitlin N. Smith, Poolad Imany, Kevin L. Silverman, and Frederic T. Chong. "Modeling Short-Range Microwave Networks to Scale Superconducting Quantum Computation." Quantum 9 (January 8, 2025): 1581. https://doi.org/10.22331/q-2025-01-08-1581.

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A core challenge for superconducting quantum computers is to scale up the number of qubits in each processor without increasing noise or cross-talk. Distributed quantum computing across small qubit arrays, known as chiplets, can address these challenges in a scalable manner. We propose a chiplet architecture over microwave links with potential to exceed monolithic performance on near-term hardware. Our methods of modeling and evaluating the chiplet architecture bridge the physical and network layers in these processors. We find evidence that distributing computation across chiplets may reduce

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25

Caprasecca, Stefano, and Benedetta Mennucci. "Excitation Energy Transfer in Donor-Bridge-Acceptor Systems: A Combined Quantum-Mechanical/Classical Analysis of the Role of the Bridge and the Solvent." Journal of Physical Chemistry A 118, no. 33 (2014): 6484–91. http://dx.doi.org/10.1021/jp502815r.

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26

Krupka, Katarzyna M., Michał Pocheć, Jarosław J. Panek, and Aneta Jezierska. "Comprehensive Empirical Model of Substitution—Influence on Hydrogen Bonding in Aromatic Schiff Bases." International Journal of Molecular Sciences 23, no. 20 (2022): 12439. http://dx.doi.org/10.3390/ijms232012439.

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In this work, over 500 structures of tri-ring aromatic Schiff bases with different substitution patterns were investigated to develop a unified description of the substituent effect on the intramolecular hydrogen bridge. Both proximal and distal effects were examined using Density Functional Theory (DFT) in the gas phase and with solvent reaction field (Polarizable Continuum Model (PCM) and water as the solvent). In order to investigate and characterize the non-covalent interactions, a topological analysis was performed using the Quantum Theory of Atoms In Molecules (QTAIM) theory and Non-Cova

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KAZYURA, N. V., and R. N. BELOKOPYTOV. "RESEARCH OF THE BRIDGE CRANE LABORATORY MECHATRONIC COMPLEX." Vestnik LSTU, no. 1 (2025): 15–19. https://doi.org/10.53015/30343275_2025_1_15.

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The article presents the Bridge Crane laboratory mechatronic complex designed to research the functional aspects and methods of operating real cranes. The main attention is paid to the complex design including the mechanisms for moving along the X, Y axes and lifting cargo along the Z axis, as well as to the control system based on the programmable logic controller (PLC) of the Schneider Electric Quantum series. Particular importance is given to the analysis of modern control methods: classical and adaptive algorithms that dynamically adjust parameters depending on the weight of the load, on t

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de Graaf, S. E., S. Un, A. G. Shard, and T. Lindström. "Chemical and structural identification of material defects in superconducting quantum circuits." Materials for Quantum Technology 2, no. 3 (2022): 032001. http://dx.doi.org/10.1088/2633-4356/ac78ba.

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Abstract Quantum circuits show unprecedented sensitivity to external fluctuations compared to their classical counterparts, and it can take as little as a single atomic defect somewhere in a mm-sized area to completely spoil device performance. For improved device coherence it is thus essential to find ways to reduce the number of defects, thereby lowering the hardware threshold for achieving fault-tolerant large-scale error-corrected quantum computing. Given the evasive nature of these defects, the materials science required to understand them is at present in uncharted territories, and new t

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Almatarneh, Rami, Mohammad Aljaidi, Ayoub A. Lsarhan, and Amjad A. Alsuwaylimi. "QR-DEF: A quantum-resistant hybrid encryption framework with dynamic entropy fusion and biomimetic obfuscation." International Journal of Innovative Research and Scientific Studies 8, no. 4 (2025): 156–66. https://doi.org/10.53894/ijirss.v8i3.7747.

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The growing threat of quantum computing has increased the need for cryptographic frameworks that go beyond classical cryptographic paradigms. Quantum-Resistant Dynamic Entropy Fusion (QR-DEF) is a new hybrid encryption paradigm that integrates lattice-based cryptography, dynamic environmental entropy, and bio-inspired obfuscation to mitigate vulnerabilities in post-quantum and classical paradigms. QR-DEF employs the NTRU lattice-based cryptosystem to create a static Shor's algorithm-resistant "Master Seed" and pulls dynamic entropy from fixed public parameters (e.g., blockchain nonces, weather

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Astbury, Frederick George. "Unveiling the Fifth Dimension: A Novel Approach to Quantum Mechanics." Quantum Reports 7, no. 1 (2025): 8. https://doi.org/10.3390/quantum7010008.

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Quantum mechanics (QM) has long challenged our understanding of time, space, and reality, with phenomena such as superposition, wave–particle duality, and quantum entanglement defying classical notions of causality and locality. Despite the predictive success of QM, its interpretations—such as the Copenhagen and many-worlds interpretations—remain contentious and incomplete. This paper introduces Strip Theory, a novel framework that reconceptualises time as a two-dimensional manifold comprising foretime, the sequential dimension, and sidetime, an orthogonal possibility dimension representing pa

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31

Wojtkowiak, Kamil, Aneta Jezierska, and Jarosław J. Panek. "Revealing Intra- and Intermolecular Interactions Determining Physico-Chemical Features of Selected Quinolone Carboxylic Acid Derivatives." Molecules 27, no. 7 (2022): 2299. http://dx.doi.org/10.3390/molecules27072299.

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The intra- and intermolecular interactions of selected quinolone carboxylic acid derivatives were studied in monomers, dimers and crystals. The investigated compounds are well-recognized as medicines or as bases for further studies in drug design. We employed density functional theory (DFT) in its classical formulation to develop gas-phase and solvent reaction field (PCM) models describing geometric, energetic and electronic structure parameters for monomers and dimers. The electronic structure was investigated based on the atoms in molecules (AIM) and natural bond orbital (NBO) theories. Spec

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Choi, Seonghyun, and Woojoo Lee. "Developing a Grover's quantum algorithm emulator on standalone FPGAs: optimization and implementation." AIMS Mathematics 9, no. 11 (2024): 30939–71. http://dx.doi.org/10.3934/math.20241493.

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<p>Quantum computing (QC) leverages superposition, entanglement, and parallelism to solve complex problems that are challenging for classical computing methods. The immense potential of QC has spurred explosive interest and research in both academia and industry. However, the practicality of QC based on large-scale quantum computers remains limited by issues of scalability and error correction. To bridge this gap, QC emulators utilizing classical computing resources have emerged, with modern implementations employing FPGAs for efficiency. Nevertheless, FPGA-based QC emulators face signif

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Pomorski, Krzysztof. "Electrostatically Interacting Wannier Qubits in Curved Space." Materials 17, no. 19 (2024): 4846. http://dx.doi.org/10.3390/ma17194846.

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A derivation of a tight-binding model from Schrödinger formalism for various topologies of position-based semiconductor qubits is presented in the case of static and time-dependent electric fields. The simplistic tight-binding model enables the description of single-electron devices at a large integration scale. The case of two electrostatically Wannier qubits (also known as position-based qubits) in a Schrödinger model is presented with omission of spin degrees of freedom. The concept of programmable quantum matter can be implemented in the chain of coupled semiconductor quantum dots. Highly

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Temitope Oluwatosin Fatunmbi. "Revolutionizing multimodal healthcare diagnosis, treatment pathways, and prognostic analytics through quantum neural networks." World Journal of Advanced Research and Reviews 17, no. 1 (2023): 1319–38. https://doi.org/10.30574/wjarr.2023.17.1.0017.

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The advent of quantum computing has introduced significant potential to revolutionize healthcare through quantum neural networks (QNNs), offering unprecedented capabilities in processing and analyzing multimodal medical data. Traditional computational methods, including classical machine learning models, face challenges when handling the complex, high-dimensional, and often heterogeneous nature of medical data. Quantum neural networks, leveraging quantum mechanics’ fundamental principles, provide a robust framework capable of handling such data with enhanced accuracy and efficiency. This paper

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Temitope Oluwatosin Fatunmbi. "Integrating quantum neural networks with machine learning algorithms for optimizing healthcare diagnostics and treatment outcomes." World Journal of Advanced Research and Reviews 17, no. 3 (2023): 1059–77. https://doi.org/10.30574/wjarr.2023.17.3.0306.

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The rapid advancements in artificial intelligence (AI) and quantum computing have catalyzed an unprecedented shift in the methodologies utilized for healthcare diagnostics and treatment optimization. This research paper explores the integration of quantum neural networks (QNNs) with classical machine learning (ML) algorithms to enhance diagnostic accuracy, facilitate personalized treatment plans, and predict patient outcomes with a higher degree of precision. Quantum neural networks, leveraging the principles of quantum mechanics such as superposition, entanglement, and quantum parallelism, ha

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Rossi, Zane M., and Isaac L. Chuang. "Multivariable quantum signal processing (M-QSP): prophecies of the two-headed oracle." Quantum 6 (September 20, 2022): 811. http://dx.doi.org/10.22331/q-2022-09-20-811.

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Recent work shows that quantum signal processing (QSP) and its multi-qubit lifted version, quantum singular value transformation (QSVT), unify and improve the presentation of most quantum algorithms. QSP/QSVT characterize the ability, by alternating ansätze, to obliviously transform the singular values of subsystems of unitary matrices by polynomial functions; these algorithms are numerically stable and analytically well-understood. That said, QSP/QSVT require consistent access to a single oracle, saying nothing about computing joint properties of two or more oracles; these can be far cheaper

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Weinhold, Frank. "Thermodynamics of Intrinsic Reaction Coordinate (IRC) Chemical Reaction Pathways." Entropy 27, no. 4 (2025): 390. https://doi.org/10.3390/e27040390.

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We address the scientific “time” concept in the context of more general relaxation processes toward the Wärmetod of thermodynamic equilibrium. More specifically, we sketch a construction of a conceptual ladder of chemical reaction steps that can rigorously bridge a description from the microscopic domain of molecular quantum chemistry to the macroscopic materials domain of Gibbsian thermodynamics. This conceptual reformulation follows the pioneering work of Kenichi Fukui (Nobel 1981) in rigorously formulating the intrinsic reaction coordinate (IRC) pathway for controlled description of non-equ

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Martyn, John M., Yuan Liu, Zachary E. Chin, and Isaac L. Chuang. "Efficient fully-coherent quantum signal processing algorithms for real-time dynamics simulation." Journal of Chemical Physics 158, no. 2 (2023): 024106. http://dx.doi.org/10.1063/5.0124385.

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Simulating the unitary dynamics of a quantum system is a fundamental problem of quantum mechanics, in which quantum computers are believed to have significant advantage over their classical counterparts. One prominent such instance is the simulation of electronic dynamics, which plays an essential role in chemical reactions, non-equilibrium dynamics, and material design. These systems are time- dependent, which requires that the corresponding simulation algorithm can be successfully concatenated with itself over different time intervals to reproduce the overall coherent quantum dynamics of the

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Yarman, T., B. Akkus, M. Arik, et al. "The Energy probability distribution of quantum levels of a particle imprisoned in a three dimensional box." Journal of Physics: Conference Series 2197, no. 1 (2022): 012028. http://dx.doi.org/10.1088/1742-6596/2197/1/012028.

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Abstract This work was trigerred by the earlier achivements of Yarman et al, aiming to bridge themordynamics and quantum mechanics, whence, Planck constant came to replace Boltzmann constant, and “average quantum level number” came to replace “temperature”. This evoked that the classical Maxwell energy probability distribution p(E) with respect to energy E of gas molecules might be taken care of, by the “energy probability distribution of the quantum levels” of a particle imprisoned in a given volume, assuming that in the case we have many particles, following Pauli exclusion principle, no pai

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Mani, Tomoyasu. "Molecular qubits based on photogenerated spin-correlated radical pairs for quantum sensing." Chemical Physics Reviews 3, no. 2 (2022): 021301. http://dx.doi.org/10.1063/5.0084072.

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Photogenerated spin-correlated radical pairs (SCRPs) in electron donor–bridge–acceptor (D–B–A) molecules can act as molecular qubits and inherently spin qubit pairs. SCRPs can take singlet and triplet spin states, comprising the quantum superposition state. Their synthetic accessibility and well-defined structures, together with their ability to be prepared in an initially pure, entangled spin state and optical addressability, make them one of the promising avenues for advancing quantum information science. Coherence between two spin states and spin selective electron transfer reactions form t

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Pan, Chengxin. "Enfolding wholes in parts: quantum holography and International Relations." European Journal of International Relations 26, no. 1_suppl (2020): 14–38. http://dx.doi.org/10.1177/1354066120938844.

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This article stands at the intersection between the relational turn in International Relations (IR) and the quantum turn in the social sciences (and more recently in IR as well). The relational turn draws much-needed attention to the centrality of relations in global politics, yet its imprecise conceptualization of whole-part relations casts shadow over its relational ontological foundation. The quantum turn, meanwhile, challenges the observed–observer dichotomy as well as the classical views about causality, determinacy, and measurement. Yet, despite their common stance against the Newtonian

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Andrew Perry, Julian. "Pulse-Induced Electrochemical Phenomena: Proposed Mechanisms using Extended Electrodynamic Theories." Journal of Electrical Electronics Engineering 04, no. 02 (2025): 01–20. https://doi.org/10.33140/jeee.04.02.07.

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Prior studies have shown that energy gains can result from the application of inductively generated high voltage pulses to the cathode of both Lead-Acid (Pb-A) and Lithium Iron Phosphate (LFP) batteries using specific operational parameters, including pulse repetition rate and peak pulse voltage. It has also been shown that internal enthalpy cannot be the cause of the energy gains due to a lack of correlation between measured charge capacities and those predicted from a thermodynamic analysis of the electrochemical changes occurring when measured energy releases occur, together with battery be

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PV, Muhammad Ismayil. "Quantum-Inspired C# for Hybrid Quantum-Classical Applications." December 5, 2024. https://doi.org/10.5281/zenodo.14280103.

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This research paper introduces Quantum-Inspired C#, a groundbreaking extension to the C# programming language designed to enable seamless hybrid quantum-classical application development. By integrating quantum-inspired constructs within the familiar .NET ecosystem, this framework empowers developers to experiment with quantum algorithms while leveraging classical computational capabilities. The paper discusses the technical background, methodology, and potential applications of this framework, providing insights into its practical implementation and performance. It also includes mathematical

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Spriggs, Thomas, Arash Ahmadi, Bokai Chen, and Eliska Greplova. "Quantum resources of quantum and classical variational methods." Machine Learning: Science and Technology, January 21, 2025. https://doi.org/10.1088/2632-2153/adaca2.

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Abstract Variational techniques have long been at the heart of atomic, solid-state, and many-body physics. They have recently extended to quantum and classical machine learning, providing a basis for representing quantum states via neural networks. These methods generally aim to minimize the energy of a given ansätz, though open questions remain about the expressivity of quantum and classical variational ansätze. The connection between variational techniques and quantum computing, through variational quantum algorithms, offers opportunities to explore the quantum complexity of classical method

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Zhang, Lin, Yutao Hu, Zhao Yao, et al. "Controllable quantum scars induced by spin–orbit couplings in quantum dots." Discover Nano 19, no. 1 (2024). http://dx.doi.org/10.1186/s11671-024-04015-7.

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AbstractSpin–orbit couplings (SOCs), originating from the relativistic corrections in the Dirac equation, offer nonlinearity in the classical limit and are capable of driving chaotic dynamics. In a nanoscale quantum dot confined by a two-dimensional parabolic potential with SOCs, various quantum scar states emerge quasi-periodically in the eigenstates of the system, when the ratio of confinement energies in the two directions is nearly commensurable. The scars, displaying both quantum interference and classical trajectory features on the electron density, due to relativistic effects, serve as

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Ebrahimi, Mohammad. "The Quantum Homunculus in Biology: How DNA and Biomolecules Bridge the Classical and Quantum Realms." International Journal of Innovative Science and Research Technology, May 13, 2025, 3365–69. https://doi.org/10.38124/ijisrt/25apr2073.

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Biological systems exhibit a remarkable duality, operating across quantum and classical regimes. This article introduces the concept of the Quantum Homunculus ("Quantuculus")—a proposed network of wave-like signals emitted by cells, with distinct frequency-amplitude signatures in health and disease. We discuss how biomolecules, particularly DNA, mediate this duality: at nanometer scales (e.g., 2 nm DNA width), quantum effects like coherent charge transfer and proton tunneling dominate, while chromosomal DNA (∼10 cm) behaves classically due to rapid decoherence. The boundary between these regim

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Cai, Ning, Yuan Gao, Wei Li, and Yang Qi. "Auxiliary-Field Monte Carlo Method for frustrated spin systems." Chinese Physics B, January 8, 2025. https://doi.org/10.1088/1674-1056/ada758.

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Abstract We extend a semiclassical numerical method, bosonic auxiliary-field Monte Carlo, to quantum spin systems. This method breaks the lattice into clusters, solves each clusters precisely and couples them with classical auxiliary fields through classical Monte Carlo simulation. We test the method with antiferromagnetic spin models in one-dimensional chains, square lattices and triangular lattices, and obtain reasonable results in finite temperatures. This algorithm builds a bridge between classical Monte Carlo method and quantum methods. The algorithm can be improved with either progress i

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Ye, Chong-Qiang, Jian Li, Xiu-Bo Chen, Yanyan Hou, and Zhuo Wang. "Security and application of semi-quantum key distribution protocol for users with different quantum capabilities." EPJ Quantum Technology 10, no. 1 (2023). http://dx.doi.org/10.1140/epjqt/s40507-023-00180-3.

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AbstractSemi-quantum protocols serve as a bridge between quantum users and “classical” users with limited quantum capabilities, providing support for application scenarios that cannot afford the excessively high cost of quantum resources. In this paper, we present a semi-quantum key distribution (SQKD) protocol based on Bell states and single particles, which is designed for key distribution between different types of users. The protocol enables simultaneous key distribution between quantum and classical users, as well as key establishment between two classical users. The security analysis dem

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Kardashin, Andrey, Alexey Uvarov, and Jacob Biamonte. "Quantum Machine Learning Tensor Network States." Frontiers in Physics 8 (March 1, 2021). http://dx.doi.org/10.3389/fphy.2020.586374.

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Tensor network algorithms seek to minimize correlations to compress the classical data representing quantum states. Tensor network algorithms and similar tools—called tensor network methods—form the backbone of modern numerical methods used to simulate many-body physics and have a further range of applications in machine learning. Finding and contracting tensor network states is a computational task, which may be accelerated by quantum computing. We present a quantum algorithm that returns a classical description of a rank-r tensor network state satisfying an area law and approximating an eige

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Videla, Pablo E., and Victor S. Batista. "Matsubara dynamics approximation for generalized multi-time correlation functions." Journal of Chemical Physics 158, no. 18 (2023). http://dx.doi.org/10.1063/5.0146654.

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We introduce a semi-classical approximation for calculating generalized multi-time correlation functions based on Matsubara dynamics, a classical dynamics approach that conserves the quantum Boltzmann distribution. This method is exact for the zero time and harmonic limits and reduces to classical dynamics when only one Matsubara mode is considered (i.e., the centroid). Generalized multi-time correlation functions can be expressed as canonical phase-space integrals, involving classically evolved observables coupled through Poisson brackets in a smooth Matsubara space. Numerical tests on a simp

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