We consider the dynamics of relativistic spin-half particles in quantum graphs with transparent branching points. The system is modeled by combining the quantum graph concept with the one of transparent boundary conditions applied to the Dirac equation on metric graphs. Within such an approach, we derive simple constraints, which turn the usual Kirchhoff-type boundary conditions at the vertex equivalent to the transparent ones. Our method is applied to quantum star graph. An extension to more complicated graph topologies is straightforward.
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http://dx.doi.org/10.1103/PhysRevE.101.062208 | DOI Listing |
J Chem Phys
January 2025
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China.
Structural indicators, also known as structural descriptors, including order parameters, have been proposed to quantify the structural properties of water to account for its anomalous behaviors. However, these indicators, mainly designed for bulk water, are not naturally transferrable to the vicinity of ions due to disruptions in the immediate neighboring space and a resulting loss of feature completeness. To address these non-bulk defects, we introduced a structural indicator that draws on the concept of clique number from graph theory and the criterion in agglomerative clustering, denoted as the average cluster number.
View Article and Find Full Text PDFEntropy (Basel)
November 2024
Beijing QBoson Quantum Technology Co., Ltd., Beijing 100015, China.
Fraud detection within transaction data is crucial for maintaining financial security, especially in the era of big data. This paper introduces a novel fraud detection method that utilizes quantum computing to implement community detection in transaction networks. We model transaction data as an undirected graph, where nodes represent accounts and edges indicate transactions between them.
View Article and Find Full Text PDFJ Mol Graph Model
January 2025
School of Materials Science and Engineering, Yancheng Institute of Technology, Yancheng, 224051, China. Electronic address:
MXenes quantum dots (QDs), including NbC, NbCO, and NbCF, are emerging materials with exceptional structural, electronic, and optical properties, making them highly suitable for biomedical applications. This study investigates the structural optimization, stability, electronic properties, and drug-loading potential of these QDs using fluorouracil (Flu) as a model drug. Structural analyses show that the functionalization of NbC with O and F atoms enhances stability, with binding energies (BEs) of 7.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1205, Bangladesh.
Prediction and discovery of new materials with desired properties are at the forefront of quantum science and technology research. A major bottleneck in this field is the computational resources and time complexity related to finding new materials from ab initio calculations. In this work, an effective and robust deep learning-based model is proposed by incorporating persistent homology with graph neural network which offers an accuracy of and an F1 score of in classifying topological versus non-topological materials, outperforming the other state-of-the-art classifier models.
View Article and Find Full Text PDFJ Mol Graph Model
March 2025
Chemical Engineering Department, Ondokuz Mayıs University, 55139, Samsun, Turkey. Electronic address:
The mechanism of the base-catalyzed thiol-epoxide stage of the thiol-ene/thiol-epoxide curing process was investigated using quantum chemical tools. This study searched for conventional tertiary amines with low to medium basicity as initiators to control reaction rates and tailor industrial applications. Challenges arise from the stronger basicity of initiators, leading to an uncontrollable and short curing application period.
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