Principles Of Quantum Mechanics Research Articles

How Well Can Quantum Embedding Method Predict the Reaction Profiles for Hydrogenation of Small Li Clusters?

Quantum computing leverages the principles of quantum mechanics in novel ways to tackle complex chemistry problems that cannot be accurately addressed using traditional quantum chemistry methods. However, the high computational cost and available number of physical qubits with high fidelity limit its application to small chemical systems. This work employed a quantum-classical framework which features a quantum active space-embedding approach to perform simulations of chemical reactions that require up to 14 qubits. This framework was applied to prototypical example metal hydrogenation reactions: the coupling between hydrogen and Li2, Li3, and Li4 clusters. Particular attention was paid to the computation of barriers and reaction energies. The predicted reaction profiles compare well with advanced classical quantum chemistry methods, demonstrating the potential of the quantum embedding algorithm to map out reaction profiles of realistic gas-phase chemical reactions to ascertain qualitative energetic trends. Additionally, the predicted potential energy curves provide a benchmark to compare against both current and future quantum embedding approaches.

An Overview of Postprocessing in Quantum Key Distribution

Quantum key distribution (QKD) technology is a frontier in the field of secure communication, leveraging the principles of quantum mechanics to offer information-theoretically secure keys. Postprocessing is an important part of a whole QKD system because it directly impacts the secure key rate and the security of the system. In particular, with the fast increase in the photon transmission frequency in a QKD system, the processing speed of postprocessing becomes an essential issue. Our study embarks on a comprehensive review of the development of postprocessing of QKD, including five subprotocols, namely, parameter estimation, sifting, information reconciliation, privacy amplification, and channel authentication. Furthermore, we emphasize the issues raised in the implementation of these subprotocols under practical scenarios, such as limited computation or storage resources and fluctuations in channel environments. Based on the composable security theory, we demonstrate how enhancements in each subprotocol influence the secure key rate and security parameters, which can provide meaningful insights for future advancements in QKD.

Quantum Battery in the Heisenberg Spin Chain Models with Dzyaloshinskii‐Moriya Interaction

AbstractQuantum battery (QB) is an energy storage and extraction device conforming to the principles of quantum mechanics. In this study, the characteristics of QBs are considered for the Heisenberg spin chain models in the absence and presence of Dzyaloshinskii‐Moriya (DM) interaction. The results show that the DM interaction can enhance the ergotropy and power of QBs, which shows the collective charging can outperform parallel charging regarding QB's performance. Besides, it turns out that first‐order coherence is a crucial quantum resource during charging, while quantum steering between the cells is not conducive to the energy storage of QBs. The investigations offer insight into the properties of QBs with Heisenberg spin chain models with DM interaction and facilitate us to acquire the performance in the framework of realistic quantum batteries.

Quantum Chimp Optimization Algorithm: A Novel Integration of Quantum Mechanics Into the Chimp Optimization Framework for Enhanced Performance

Abstract This research introduces the Quantum Chimp Optimization Algorithm (QChOA), a pioneering methodology that integrates quantum mechanics principles into the Chimp Optimization Algorithm (ChOA). By incorporating non-linearity and uncertainty, the QChOA significantly improves the ChOA’s exploration and exploitation capabilities. A distinctive feature of the QChOA is its ability to displace a ’chimp,’ representing a potential solution, leading to heightened fitness levels compared to the current top search agent. Our comprehensive evaluation includes twenty- nine standard optimization test functions, thirty CEC-BC functions, the CEC06 test suite, ten real-world engineering challenges, and the IEEE CEC 2022 competition’s dynamic optimization problems. Comparative analyses involve four ChOA variants, three leading quantum-behaved algorithms, three state-ofthe-art algorithms, and eighteen benchmarks. Employing three non-parametric statistical tests (Wilcoxon rank-sum, Holm-Bonferroni, and Friedman average rank tests), results show that the QChOA outperforms counterparts in 51 out of 70 scenarios, exhibiting performance on par with SHADE and CMA-ES, and statistical equivalence to jDE100 and DISHchain1e+12. The study underscores the QChOA’s reliability and adaptability, positioning it as a valuable technique for diverse and intricate optimization challenges in the field.

Quantum mechanics principle and other physics principles involved in light and laser therapy

Quantum mechanics principle and other physics principles involved in light and laser therapy

Quantum Machine Learning: The Superhero That Classical Machine Learning Never Knew It Needed

Quantum Machine Learning (QML) is an emerging interdisciplinary field that combines the principles of quantum mechanics and machine learning to develop algorithms that can potentially outperform classical algorithms in certain tasks. QML leverages the unique properties of quantum systems, such as superposition and entanglement, to process information in ways that are not possible with classical computers. This paper provides a comprehensive overview of QML, including its principles, algorithms, and applications. We focus particularly on supervised learning methods, which involve training a quantum model on labeled data to make predictions on new, unseen data. We discuss the potential of QML to revolutionize various domains, such as finance, chemistry, and materials science, and highlight the challenges associated with the development and implementation of QML algorithms, including the need for more advanced quantum hardware and software. This paper aims to provide a clear understanding of the current state of QML research and its potential impact on future computational capabilities.

Testing Multi-Subroutine Quantum Programs: From Unit Testing to Integration Testing

Quantum computing has emerged as a promising field with the potential to revolutionize various domains by harnessing the principles of quantum mechanics. As quantum hardware and algorithms continue to advance, developing high-quality quantum software has become crucial. However, testing quantum programs poses unique challenges due to the distinctive characteristics of quantum systems and the complexity of multi-subroutine programs. This article addresses the specific testing requirements of multi-subroutine quantum programs. We begin by investigating critical properties by surveying existing quantum libraries and providing insights into the challenges of testing these programs. Building upon this understanding, we focus on testing criteria and techniques based on the whole testing process perspective, spanning from unit testing to integration testing. We delve into various aspects, including IO analysis, quantum relation checking, structural testing, behavior testing, integration of subroutine pairs, and test case generation. We also introduce novel testing principles and criteria to guide the testing process. We conduct comprehensive testing on typical quantum subroutines, including diverse mutants and randomized inputs, to evaluate our proposed approach. The analysis of failures provides valuable insights into the effectiveness of our testing methodology. Additionally, we present case studies on representative multi-subroutine quantum programs, demonstrating the practical application and effectiveness of our proposed testing principles and criteria.

Exploiting OFDM method for quantum communication

Orthogonal frequency-division multiplexing (OFDM) is a crucial modulation method used in contemporary digital communication systems for its significant spectral efficiency, low latency, and robustness in challenging environments. This work examines the novel use of OFDM in quantum communication, an area that offers exceptional security and efficiency in information transfer using quantum mechanics principles. In the rapidly evolving field of quantum computing, understanding, and mitigating quantum bit errors is paramount. This paper presents a rigorous analysis of bit error rates (BER) in quantum circuits, focusing on the impact of the quantum Fourier transform and its inverse, contrasted against quantum circuits employing dynamic gate sequences. Our research methodology encompasses simulations over a diverse set of parameters, including varying qubit counts ranging from 2 to 8 and theta angles (15, 30, 45, and 60°), as well as random theta values, utilizing the advanced capabilities of the Qiskit framework. Our findings indicate that quantum OFDM substantially improves quantum communication, lowering errors and boosting security. The quantum model outperforms the reference model in BER, with further enhancements as qubits increase.

BAOS-CNN: A novel deep neuroevolution algorithm for multispecies seagrass detection.

Deep learning, a subset of machine learning that utilizes neural networks, has seen significant advancements in recent years. These advancements have led to breakthroughs in a wide range of fields, from natural language processing to computer vision, and have the potential to revolutionize many industries or organizations. They have also demonstrated exceptional performance in the identification and mapping of seagrass images. However, these deep learning models, particularly the popular Convolutional Neural Networks (CNNs) require architectural engineering and hyperparameter tuning. This paper proposes a Deep Neuroevolutionary (DNE) model that can automate the architectural engineering and hyperparameter tuning of CNNs models by developing and using a novel metaheuristic algorithm, named 'Boosted Atomic Orbital Search (BAOS)'. The proposed BAOS is an improved version of the recently proposed Atomic Orbital Search (AOS) algorithm which is based on the principle of atomic model and quantum mechanics. The proposed algorithm leverages the power of the Lévy flight technique to boost the performance of the AOS algorithm. The proposed DNE algorithm (BAOS-CNN) is trained, evaluated and compared with six popular optimisation algorithms on a patch-based multi-species seagrass dataset. This proposed BAOS-CNN model achieves the highest overall accuracy (97.48%) among the seven evolutionary-based CNN models. The proposed model also achieves the state-of-the-art overall accuracy of 92.30% and 93.5% on the publicly available four classes and five classes version of the 'DeepSeagrass' dataset, respectively. This multi-species seagrass dataset is available at: https://ro.ecu.edu.au/datasets/141/.

Quantum Key Distribution In Quantum Communication

Quantum Key Distribution (QKD) stands as a revolutionary paradigm in secure communication, leveraging the principles of quantum mechanics to establish cryptographic keys with unprecedented levels of security. This paper explores the foundational concepts and key protocols of QKD, emphasizing its role in addressing the vulnerabilities associated with classical key exchange methods. The discussion covers quantum entanglement, quantum superposition, and the no-cloning theorem as the cornerstones of QKD. Furthermore, the abstract delves into the practical implementations and challenges, highlighting the potential of QKD to redefine the landscape of secure communication in an increasingly interconnected world. Key words: Quantum Key Distribution, Quantum communication, quantum entanglement, cryptographic security, no-cloning theorem, secure communication, unbreakable security, quantum technology.

A reference architecture for quantum computing as a service

Quantum computers (QCs) aim to disrupt the status-quo of computing – replacing traditional systems and platforms that are driven by digital circuits and modular software – with hardware and software that operate on the principle of quantum mechanics. QCs that rely on quantum mechanics can exploit quantum circuits (i.e., quantum bits for manipulating quantum gates) to achieve ‘quantum computational supremacy’ over traditional, i.e., digital computing systems. Currently, the issues that impede mass-scale adoption of quantum systems are rooted in the fact that building, maintaining, and/or programming QCs is a complex and radically distinct engineering paradigm when compared to the challenges of classical computing and software engineering. Quantum service orientation is seen as a solution that synergises the research on service computing and quantum software engineering (QSE) to allow developers and users to build and utilise quantum software services based on pay-per-shot utility computing model. The pay-per-shot model represents a single execution of instruction on quantum processing unit and it allows vendors (e.g., Amazon Braket) to offer their QC platforms, simulators, and software services to end-users. This research contributes by (i) developing a reference architecture for enabling Quantum Computing as a Service (QCaaS), (ii) implementing microservices with the quantum-classic split pattern as an architectural use-case, and (iii) evaluating the architecture based on practitioners’ feedback. The proposed reference architecture follows a layered software pattern to support the three phases of service lifecycle namely development, deployment, and split of quantum software services. In the QSE context, the research focuses on unifying architectural methods and service-orientation patterns to promote reuse knowledge and best practices to tackle emerging and futuristic challenges of architecting QCaaS.

Cyber Protection Applications of Quantum Computing: A Review

Quantum computing is a cutting-edge field of information technology that harnesses the principles of quantum mechanics to perform computations. It has major implications for the cyber security industry. Existing cyber protection applications are working well, but there are still challenges and vulnerabilities in computer networks. Sometimes data and privacy are also compromised. These complications lead to research questions asking what kind of cyber protection applications of quantum computing are there and what potential methods or techniques can be used for cyber protection? These questions will reveal how much power quantum computing has and to what extent it can outperform the conventional computing systems. This scoping review was conducted by considering 815 papers. It showed the possibilities that can be achieved if quantum technologies are implemented in cyber environments. This scoping review discusses various domains such as algorithms and applications, bioinformatics, cloud and edge computing, the organization of complex systems, application areas focused on security and threats, and the broader quantum computing ecosystem. In each of these areas, there is significant scope for quantum computing to be implemented and to revolutionize the working environment. Numerous quantum computing applications for cyber protection and a number of techniques to protect our data and privacy were identified. The results are not limited to network security but also include data security. This paper also discusses societal aspects, e.g., the applications of quantum computing in the social sciences. This scoping review discusses how to enhance the efficiency and security of quantum computing in various cyber security domains. Additionally, it encourages the reader to think about what kind of techniques and methods can be deployed to secure the cyber world.

Quantum private comparison for the socialist millionaire problem

The socialist millionaire problem aims to compare the equality of two inputs from two users while keeping their inputs undisclosed to anyone. Quantum private comparison (QPC), whose security relies on the principles of quantum mechanics, can solve this problem and achieve the information-theoretic security of information processing. The current QPC protocols mainly utilize the bitwise XOR operation to implement the comparison, leading to insufficient security. In this paper, we propose a rotation operation-based QPC protocol to solve the socialist millionaire problem, which utilizes Bell states as quantum resources and rotation operations for classical calculations. The proposed protocol only utilizes easy-to-implement technologies such as Bell states, rotation operations, and Bell-basis measurements, making it more practical. The analysis demonstrates that our protocol can meet both the correctness and security requirements. Compared with the existing QPC protocols, our protocol has improved performance in terms of practicability and security.

Quantum Cryptography: Fundamentals and Advanced Techniques

Abstract: Quantum-cryptography represents a revolutionary advancement in the field of secure correspondence, leveraging the principles of quantum-mechanics to ensure unprecedented levels of security. This review paper provides a comprehensive exploration of both the foundational principles and advanced techniques underpinning quantum cryptographic systems. We begin by examining the theoretical foundations, including quantum key distribution (QKD) protocols such as BB84 and E91, and the critical role of entanglement and superposition in these processes. The paper then delves into the latest advancements and techniques in the field, including device-independent QKD, quantum cryptographic networks, and post-quantum cryptographic methods designed to be resilient against quantum computer attacks. Additionally, we discuss practical implementation challenges and the current state of experimental quantum cryptography. By synthesizing recent research findings and technological developments, this review aims to provide a thorough comprehension of the current environment and future directions of quantum cryptography, highlighting its potential to revolutionize secure communications in the quantum era.

Improving the exploitability of Simulated Adiabatic Bifurcation through a flexible and open-source digital architecture

Combinatorial Optimization (CO) problems exhibit exponential complexity, constraining classical computers from providing fast and satisfactory outcomes. Quantum Computers (QCs) can effectively find optimal or near-optimal solutions by exploring the solutions space of a problem encoded in a qubits system, exploiting principles of quantum mechanics. However, non-idealities and high costs limit their availability. These can be overcome by emulating QCs on cheaper and more accessible classical computing platforms, like Field-Programmable Gate Arrays (FPGAs). This article presents a digital architecture, implementing the Ising-compatible Simulated Adiabatic Bifurcation algorithm. It mimics the quantum adiabatic evolution of a network of non-linear Kerr oscillators. The architecture, described in VHDL and targeting FPGAs, consists of processing elements for computing the Kerr oscillators’ evolution, a set of units considering their Ising-related interactions and an evolution variables update unit. The proposed approach includes a speedup-targeting approximation of the algorithm, a method for handling single-variable constraints, and a software model that allows architecture customization for specific problems. Tests were conducted using an Altera Cyclone V SoC with FPGA logic and the Nios II processor for interface purposes. The results demonstrate the functionality of the architecture and its scalability with the problem size, making it suitable for real-world applications.

Robust biometric identity authentication scheme using quantum voice encryption and quantum secure direct communications for cybersecurity

A significant problem facing cybersecurity is that most client/server identity authentication schemes depend on computational complexity which is recently challenged by the super exponential computational abilities of quantum computers. Quantum cryptography with its quantum mechanics principles solves this problem and provides mathematically un-hackable secure communication for the quantum computers epoch. Biometric authentication has a big challenge related to its protection as it has to be submitted and stored in encrypted form. Unfortunately, most existing biometric cryptosystems rely on classical cryptography, so they are insecure in quantum era. This problem is solved in this paper by introducing a novel three-factor biometric quantum identity authentication scheme combining something you know (password), something you produce (client’s voice), and something you are (client’s face image) is proposed. The scheme consists of two phases: client enrollment and client login/authentication. The methodology is to use in the enrollment phase, two layers of quantum encryption for the client’s voice signal. Each layer consists of two simple quantum circuits of SWAP and C-NOT quantum gates respectively using a different pseudorandom key obtained from a cellular automata (CA) pseudorandom generator. The proposed scheme has many merits. Firstly, it introduces a new design of muti-factors quantum biometric authentication scheme as the biometric voice data is processed, transmitted, and stored at the server database in an encrypted unconditionally secure quantum form which provides parallel processing, real-time communications, inherent level of security against attacks, tamper-proof security and exponential powerful storage capability due to the quantum properties. Secondly, the proposed scheme achieves double-layers security by combing quantum voice encryption and quantum secure direct communication in one process such that the quantum channel eavesdropper cannot obtain any valuable information in case of information leakage. Thirdly, the distribution and management of encryption key problem is solved as there is no need for key exchange prior to communication. Fourthly, it achieves high communication efficiency as although it is a three-factor biometric identity authentication, only one biometric data is sent in quantum encrypted form to the server. Fifthly, the numerical simulations showed that the proposed scheme has large key space, high key sensitivity and more robust performance against different types of attacks compared to other existing classical and quantum voice encryption schemes. Finally, as an identity authentication method, the proposed scheme achieves identification accuracy of 100% with zero False Rejection Rate (FRR) and zero False acceptance rate (FAR) which is perfect.

Clashing perspectives: Kantian epistemology and quantum chemistry theory

In this contribution, the role of epistemology in understanding quantum chemistry is discussed. Quantum chemistry is the study of the behavior of atoms and molecules using the principles of quantum mechanics. Epistemology helps us evaluate claims to knowledge, distinguish between justified and unjustified beliefs, and assess the reliability of scientific methods. In quantum chemistry, the epistemology of knowledge is heavily influenced by the mathematical nature of quantum mechanics, and models can be tested, proven, and validated through experimentation. This paper also discusses key concepts used in quantum chemistry, such as the wave-particle duality of matter and the uncertainty principle. This work utilizes Kant’s philosophy of science to frame debates and discussions in quantum chemistry, particularly with regard to the interplay between empirical observation and theory. Additionally, the text explores how Kant’s ideas about the role of the mind in constructing our understanding of the world can help us comprehend the counterintuitive phenomena of quantum mechanics and its applications in quantum chemistry theory.

A Quantum Chemical Study on the Bonding Mechanism, Electronic Structure, and Optical Properties of Cellulose and Polyaniline Nanohybrid

A Quantum Chemical Study on the Bonding Mechanism, Electronic Structure, and Optical Properties of Cellulose and Polyaniline Nanohybrid

Information entropies with Varshni-Hellmann potential in higher dimensions

This work investigates the behavior of Shannon entropy and Fisher information for the Varshni-Hellmann potential (VHP) in one and three dimensions using the Nikiforov-Uvarov method. We employ the Greene-Aldrich approximation scheme to obtain the energy eigenvalues and normalized wavefunctions, which are then used to calculate these information-theoretic quantities. Our analysis revealed remarkably similar high-order features in both position and momentum spaces. Notably, our calculations showed enhanced accuracy in predicting particle localization within position space. Furthermore, the combined position and momentum entropies obeyed the lower and upper bounds established by the Berkner-Bialynicki-Birula-Mycieslki inequality. Additionally, for three-dimensional systems, the Stam-Cramer-Rao inequalities were fulfilled for different eigenstates with respect to the calculated Fisher information. It is observed that as the position Fisher entropy decreases, indicating a more precise measurement of position, the momentum Fisher entropy must increase. This implies that the Fisher information regarding momentum decreases, resulting in a decrease in the precision of momentum measurement. This demonstrates how position and momentum uncertainties complement each other in quantum mechanics. Exploring the balance between position and momentum Fisher entropy reveals a fundamental aspect of the uncertainty principle in quantum mechanics, highlighting the restrictions on measuring certain pairs of conjugate variables simultaneously with high precision.

Chip-Based Electronic System for Quantum Key Distribution.

Quantum Key Distribution (QKD) has garnered significant attention due to its unconditional security based on the fundamental principles of quantum mechanics. While QKD has been demonstrated by various groups and commercial QKD products are available, the development of a fully chip-based QKD system, aimed at reducing costs, size, and power consumption, remains a significant technological challenge. Most researchers focus on the optical aspects, leaving the integration of the electronic components largely unexplored. In this paper, we present the design of a fully integrated electrical control chip for QKD applications. The chip, fabricated using 28 nm CMOS technology, comprises five main modules: an ARM processor for digital signal processing, delay cells for timing synchronization, ADC for sampling analog signals from monitors, OPAMP for signal amplification, and DAC for generating the required voltage for phase or intensity modulators. According to the simulations, the minimum delay is 11ps, the open-loop gain of the operational amplifier is 86.2 dB, the sampling rate of the ADC reaches 50 MHz, and the DAC achieves a high rate of 100 MHz. To the best of our knowledge, this marks the first design and evaluation of a fully integrated driver chip for QKD, holding the potential to significantly enhance QKD system performance. Thus, we believe our work could inspire future investigations toward the development of more efficient and reliable QKD systems.