Formulating and Solving Routing Problems on Quantum Computers by Stuart Harwood, Claudio Gambella, Dimitar Trenev, Andrea Simonetto, David Bernal Neira, Donny Greenberg

“…The NP-hard complexity of vehicle routing problems has fostered the adoption of tailored exact approaches, matheuristics, and metaheuristics on classical computing devices. The ongoing evolution of quantum computing hardware and the recent advances of quantum algorithms (i.e., VQE, QAOA, and ADMM) for mathematical programming make decision-making for routing problems an avenue of research worthwhile to be explored on quantum devices. …”
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Quantum Variational Autoencoder Based on Weak Measurements With Fuzzy Filtering of Input Data by Vyacheslav Korolyov, Maksim Ogurtsov, Oleksandr Khodsinskyi

“…Introduction. The development of quantum computing and artificial intelligence necessitates the development of hybrid quantum-classical algorithms for solving complex computational problems. …”
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Modeling Energy Communities: A Case Study of Quantum Approximate Optimization on a Superconducting Processor by Mateo Alonso, Guillermo Rubinos Rodriguez, Pablo Diez-Valle, Ana Garbayo, Xela Garcia-Santiago, Gonzalo Blazquez Gil

“…Given the increasing complexity as the problem size grows and the limitations of classical computing methods in addressing it, we study an approach that models the problem using QUBO and solves it applying quantum optimization algorithms. …”
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Quantum Machine Learning: Recent Advances, Challenges, and Perspectives by Pradeep Lamichhane, Danda B. Rawat

“…QML combines quantum computing and machine learning to solve complex problems in different domains, leveraging quantum algorithms to enhance classical machine learning techniques. …”
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Variational Quantum Monte Carlo Solution of the Many-Electron Schrödinger Equation Based on Deep Neural Networks by Huiping Su, Hongbo Gao, Xinmiao Wang, Xi He, Da Shen

“…The solution of Schrödinger equation generates the quantisation properties of the system, which can completely describe the quantum behaviour of microscopic particles in a physical system. …”
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The cost of solving linear differential equations on a quantum computer: fast-forwarding to explicit resource counts by David Jennings, Matteo Lostaglio, Robert B. Lowrie, Sam Pallister, Andrew T. Sornborger

“…First, we give the first non-asymptotic computation of the cost of encoding the solution to general linear ordinary differential equations into quantum states – either the solution at a final time, or an encoding of the whole history within a time interval. …”
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A Blockchain-Assisted Fair Exchange Signature Protocol Using Quantum Key Distribution for Metaverse Environment by Sunil Prajapat, Pankaj Kumar, Goutham Reddy Alavalapati

“…This paper presents a novel blockchain-assisted fair exchange signature protocol leveraging quantum key distribution (QKD) to ensure security against both classical and quantum adversaries. …”
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Deep learning enhanced quantum holography with undetected photons by Weiru Fan, Gewei Qian, Yutong Wang, Chen-Ran Xu, Ziyang Chen, Xun Liu, Wei Li, Xu Liu, Feng Liu, Xingqi Xu, Da-Wei Wang, Vladislav V. Yakovlev

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Quantum Machine Learning: Exploring the Role of Data Encoding Techniques, Challenges, and Future Directions by Deepak Ranga, Aryan Rana, Sunil Prajapat, Pankaj Kumar, Kranti Kumar, Athanasios V. Vasilakos

“…Quantum computing and machine learning (ML) have received significant developments which have set the stage for the next frontier of creative work and usefulness. …”
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Ranking of post-quantum cryptography digital signature schemes using evaluation based on distance from average solutions by Anitha Kumari Kumarasamy, Jaishriram Pichaikutty Muthu, Darshan Kirthic Muthusamy Sadhasivam, Pranavv Aaditya Mohanraj

“… With the development of quantum computing technology, the current cryptographic systems face significant threats. …”
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Spectrum allocation based on quantum cuckoo search algorithm in cognitive radio network by Xianping WANG, Hui CAO

“…There are discrete optimization problems for spectrum allocation in cognitive wireless network.A novel combinatorial optimization algorithm called quantum cuckoo search algorithm （QCSA）was proposed,which was based on quantum computing and cuckoo search algorithm.The quantum nest was used to represent multiple dimensionality solution for the optimization problem,and the global optimal position was found according to Lévy flights and quantum mutation strategy.In additional,some classical benchmark functions were employed to prove the effectiveness of QCSA,and a spectrum allocation method based on QCSA was proposed for cognitive network.Compared with classical spectrum allocation methods by using different network utility functions,the global optimal solution can be searched so fast.Simulation results show that the proposed spectrum allocation method based on QCSA is better than other traditional methods under different network utility functions.…”
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Spectrum allocation based on quantum cuckoo search algorithm in cognitive radio network by Xianping WANG, Hui CAO

“…There are discrete optimization problems for spectrum allocation in cognitive wireless network.A novel combinatorial optimization algorithm called quantum cuckoo search algorithm （QCSA）was proposed,which was based on quantum computing and cuckoo search algorithm.The quantum nest was used to represent multiple dimensionality solution for the optimization problem,and the global optimal position was found according to Lévy flights and quantum mutation strategy.In additional,some classical benchmark functions were employed to prove the effectiveness of QCSA,and a spectrum allocation method based on QCSA was proposed for cognitive network.Compared with classical spectrum allocation methods by using different network utility functions,the global optimal solution can be searched so fast.Simulation results show that the proposed spectrum allocation method based on QCSA is better than other traditional methods under different network utility functions.…”
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Algebraic classification of Hietarinta’s solutions of Yang-Baxter equations: invertible 4 × 4 operators by Somnath Maity, Vivek Kumar Singh, Pramod Padmanabhan, Vladimir Korepin

“…Abstract In order to examine the simulation of integrable quantum systems using quantum computers, it is crucial to first classify Yang-Baxter operators. …”
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Utility of NISQ devices: optimizing experimental parameters for the fabrication of Au atomic junction using gate-based quantum computers by Takumi Kanezashi, Daisuke Tsukayama, Jun-ichi Shirakashi, Tetsuo Shibuya, Hiroshi Imai

“…This study investigated the feasibility of autonomously fabricating Au atomic junctions through gate-based quantum computing using a noisy intermediate-scale quantum (NISQ) device, which effectively approximates solutions to combinatorial optimization problems. …”
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Defining quantum-ready primitives for hybrid HPC-QC supercomputing: a case study in Hamiltonian simulation by Andrea Delgado, Prasanna Date

“…These results contribute to the ongoing development of optimized hybrid solutions, advancing the role of quantum-enhanced computing in scientific research.…”
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Quantum-Inspired Control Strategies for Reducing DC-Link Voltage Fluctuations in DFIG Wind Energy Converters by Sarika Shrivastava, Saifullah Khalid, Dinesh Kumar Nishad

“…The approach integrates quantum computing principles into classical control frameworks, creating a hybrid methodology that leverages quantum-inspired optimization while maintaining implementation feasibility on conventional hardware. …”
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Pyramid Quantum Neural Network Based Resource Allocation with IoT: A Deep Learning Method by Khushwant Singh, Mohit Yadav, Kirti, Sunil Kumar, Bobur Sobirov

“…PY-QNN builds on quantum computing to improve the accuracy, scalability, and computation performance of Deep Learning. …”
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Neural quantum kernels: Training quantum kernels with quantum neural networks by Pablo Rodriguez-Grasa, Yue Ban, Mikel Sanz

“…Furthermore, we demonstrate neural quantum kernels can alleviate exponential concentration and enhance generalization capabilities compared to problem-agnostic kernels, positioning them as a scalable and robust solution for quantum machine learning applications.…”
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Modeling of binary nanooxides with solid solutions and mixed phases by V. M. Gun’ko

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A review on machine learning applications in hydrogen energy systems by Zaid Allal, Hassan N. Noura, Ola Salman, Flavien Vernier, Khaled Chahine

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