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Interplay between the extended s-wave symmetry of the gap and the spin-orbit coupling in the low-electron concentration regime of quasi-two-dimensional superconductors

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arXiv 2022年

作者： Zegrodnik, Michal Wójcik, P. Academic Centre for Materials and Nanotechnology AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow30-059 Poland Al. Mickiewicza 30 Krakow30-059 Poland

We analyze the real-space paired state with the k-dependent superconducting gap in the presence of Rashba type spin-orbit coupling and external magnetic field. We show that the extended s-wave pairing symmetry is the most probable scenario to appear in the low-electron concentration regime. According to our study, the van Hove singularity induced by the spin-orbit coupling may lead to a significant enhancement of the superconducting gap, critical temperature and critical magnetic field. Moreover, the combined effect of the spin-orbit coupling and the external magnetic field results in a non-zero total momentum of the Cooper pairs, which is a characteristic feature of the so-called helical state. In such situation, due to the C4 symmetry breaking, a small d-wave and p-wave contributions to the pairing appear, which significantly change the character of the helical state. The obtained results are discussed in the context of the experimental data related with the unconventional superconducting features of the transition metal oxide interfaces as well as the recently reported supercurrent diode effect. Copyright © 2022, The Authors. All rights reserved.

关键词： Transition metals

Quantum Optics Applications of Hexagonal Boron Nitride Defects

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arXiv 2024年

作者： Çakan, Aslı Cholsuk, Chanaprom Gale, Angus Kianinia, Mehran Paçal, Serkan Ateş, Serkan Aharonovich, Igor Toth, Milos Vogl, Tobias Department of Computer Engineering TUM School of Computation Information and Technology Technical University of Munich Munich80333 Germany Munich80799 Germany Abbe Center of Photonics Institute of Applied Physics Friedrich Schiller University Jena Jena07745 Germany School of Mathematical and Physical Sciences Faculty of Science University of Technology Sydney UltimoNSW2007 Australia University of Technology Sydney UltimoNSW2007 Australia Department of Physics Izmir Institute of Technology Izmir35430 Turkey

Hexagonal boron nitride (hBN) has emerged as a compelling platform for both classical and quantum technologies. In particular, the past decade has witnessed a surge of novel ideas and developments, which may be overwhelming for newcomers to the field. This review provides an overview of the fundamental concepts and key applications of hBN, including quantum sensing, quantum key distribution, quantum computing, and quantum memory. Additionally, we highlight critical experimental and theoretical advances that have expanded the capabilities of hBN, in a cohesive and accessible manner. The objective is to equip readers with a comprehensive understanding of the diverse applications of hBN, and provide insights into ongoing research efforts. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum computers

Heatline visualization in hydromagnetic natural convection flow inside a prismatic heat exchanger using nanofluid

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International Journal of Thermofluids 2022年 16卷

作者： Islam, Saiful Bairagi, Tanmoy Islam, Tarikul Rana, B.M.J. Reza-E-Rabbi, S.K. Rahman, M.M. Department of Mathematics Bangladesh University of Engineering and Technology Dhaka Bangladesh Department of Computer Science and Engineering Stamford University Bangladesh Dhaka Bangladesh Department of Mathematics Bangabandhu Sheikh Mujibur Rahman Science and Technology University Gopalganj Bangladesh Department of Applied Mathematics Gono Bishwabidyalay Dhaka Bangladesh Mathematics Discipline Khulna University Khulna Bangladesh

This article deals with a numerical analysis of magneto hydrodynamic natural convection phenomena in a prismatic heat exchanger containing Cu-nanoparticles with water as a base fluid. The nature of this fluid flow is steady, and a heat exchanger is created by involving two uniform cylinders with the same shape in a prismatic cavity. To create the heat exchanger and the buoyancy force, a hot cylinder and another cool cylinder are taken a left and right sides respectively. All other walls of this prismatic cavity are kept as heat insulation. For solving governing equations, the finite element technique is applied by involving Galerkin weighted residual method. The impact of the magnetic field, the buoyancy force, and the size of nanoparticles are explained with the help of involving parameters Rayleigh number (Ra), Hartmann number (Ha), and the nanoparticles volume fraction (). These parameters are graphically and physically explained by using streamline, isotherm, and heatline contours. The Nusselt number is also calculated and explained in detail to show the validation of this investigation. The outcomes indicate that the natural convective heat and energy transfer are improved by increasing the Rayleigh number, and the nanoparticle volume fraction. Reverse behavior is noticed for the upsurge of Hartmann number. The findings of this heat exchanger model can be pragmatic to construct an operative cooling system for numerous shape mechanical chambers. © 2022 The Author(s)

关键词： Magnetohydrodynamics

Lecture Notes in Networks and Systems

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Foreword

Lecture Notes in Networks and Systems 2023年 710 LNNS卷 v-vi页

作者： Biele, Cezary Kacprzyk, Janusz Kopeć, Wieslaw Owsiński, Jan W. Romanowski, Andrzej Sikorski, Marcin National Information Processing Institute Warsaw Poland Polish-Japanese Academy of Information Technology Warsaw Poland Institute of Applied Computer Science Lódż University of Technology Lódź Poland Polish Academy of Sciences Systems Research Institute Warsaw Poland Department of Informatics in Management Faculty of Management and Economics Gdańsk University of Technology Gdańsk Poland

Learning with Partial Labels from Semi-supervised Perspective

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arXiv 2022年

作者： Li, Ximing Jiang, Yuanzhi Li, Changchun Wang, Yiyuan Ouyang, Jihong College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of MOE Jilin University China College of Information Science and Technology Northeast Normal University China Key Laboratory of Applied Statistics of MOE Northeast Normal University China

Partial Label (PL) learning refers to the task of learning from the partially labeled data, where each training instance is ambiguously equipped with a set of candidate labels but only one is valid. Advances in the recent deep PL learning literature have shown that the deep learning paradigms, e.g., self-training, contrastive learning, or class activate values, can achieve promising performance. Inspired by the impressive success of deep Semi-Supervised (SS) learning, we transform the PL learning problem into the SS learning problem, and propose a novel PL learning method, namely Partial Label learning with Semi-supervised Perspective (PLSP). Specifically, we first form the pseudo-labeled dataset by selecting a small number of reliable pseudo-labeled instances with high-confidence prediction scores and treating the remaining instances as pseudo-unlabeled ones. Then we design a SS learning objective, consisting of a supervised loss for pseudo-labeled instances and a semantic consistency regularization for pseudo-unlabeled instances. We further introduce a complementary regularization for those non-candidate labels to constrain the model predictions on them to be as small as possible. Empirical results demonstrate that PLSP significantly outperforms the existing PL baseline methods, especially on high ambiguity levels. Code available: https://***/changchunli/PLSP. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep learning

Correction: A Model for Estimating Resiliency of AI-Based Classifiers Defending Against Cyber Attacks

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International Journal of Computational Intelligence Systems 2025年第1期18卷 1-1页

作者： Barik, Kousik Misra, Sanjay Fernandez-Sanz, Luis Department of Computer Science Universidad de Alcalá Alcalá de Henares Madrid Spain Department of Computer Science and Communication Østfold University College Halden Norway Department of Applied Data Science Institute for Energy Technology Halden Norway

Thermal properties of structurally balanced systems on diluted and densified triangulations

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arXiv 2021年

作者： Woloszyn, Maciej Malarz, Krzysztof AGH University of Science and Technology Faculty of Physics and Applied Computer Science al. Mickiewicza 30 Kraków30-059 Poland

The dynamics of social relations and the possibility of reaching the state of structural balance (Heider balance) are discussed for various networks of interacting actors under the influence of the temperature modeling the social noise level. For that purpose, two main types of lattices are considered. The first is created by removing some links from a regular triangular lattice to produce a diluted triangular lattice, and the second by adding more links to create an enhanced triangular lattice. In both those cases, the full range of possible graph densities is discussed, limited by the extreme cases of networks which consist of a small number of separated triads and fully connected networks. It is shown that the existence of the balanced state is not possible if the average node degree is too close to the value characterizing the regular triangular lattice. Otherwise, both balanced (or partially balanced) and imbalanced states are possible, depending on the temperature. However, only for graphs which are dense enough a phase transition of the first kind is observed, while less enhanced networks (and all diluted) indicate a smooth cross-over between the two states. The crossover temperatures are size-independent only for the diluted triangular lattices and depend on the size of the system for the enhanced triangular lattices, as is the case also for the critical temperatures of the phase transition observed in denser enhanced lattices. © 2021, CC BY.

关键词： Hadrons

Innovative machine learning for drilling fluid density prediction: a novel central force search-adaptive XGBoost in HPHT environments

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Frontiers in Energy Research 2024年 12卷

作者： Shanmugasundar, G. Manjunatha, R. Cep, Robert Logesh, K. Kaushik, Vikas Raju, S. Srinadh Elangovan, Muniyandy Department of Mechanical Engineering Sri Sai Ram Institute of Technology Chennai India Karnataka Bangalore India Department of Machining Assembly and Engineering Metrology Faculty of Mechanical Engineering VSB-Technical University of Ostrava Ostrava Czech Republic Department of Mechanical Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi India Department of Mechanical Engineering Chandigarh Engineering College Chandigarh Group of Colleges-Jhanjeri Punjab Mohali India Department of Computer Science and Engineering Raghu Engineering College Visakhapatnam India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan

Oil and gas industries are facing a special dilemma when it comes to high-pressure, high-temperature (HPHT) drilling as the accurate forecasting of the drilling fluid density (DFD) is a vital factor for safe and efficient operations. Complicated relationships and inconsistencies in HPHT situations are rarely mapped by current forecasting models, while their buggy performance and safety risks during drilling can be underestimated. In this research, we propose a novel machine learning (ML) approach to enhance the accuracy of DFD anticipation under HPHT conditions: central force search-adaptive extreme gradient boosting (CFS-XGB). This paper uses a dataset that has drilling variables together with the DFD for HPHT situations to examine the accuracy of the CFS-XGB model. Excluding the abnormalities of data or mistakes, the reliability of the original data is maintained by applying min–max normalization. After that, finding the important features with the help of the boosted principal component analysis (BPCA) approach to the normalized data will ensure a major improvement in the CFS-XGB methodology’s prediction efficacy. This research is experimented in the Python platform, and the performance of the proposed CFS-XGB method is analyzed in terms of MSE, R2, and AAPRE metrics. The suggested approach performs better than the current methods in forecasting the drilling fluid concentration in HPHT settings, according to the experimental data. This development in predictive modeling helps increase the productivity and safety of drilling operations, which will eventually help the oil and gas sector manage the challenges posed by HPHT drilling settings. Copyright © 2024 Shanmugasundar, Manjunatha, Cep, Logesh, Kaushik, Raju and Elangovan.

关键词： Gas industry

A Portable 3D-Printed Dielectric Lens Antennas for Liquid-Mixture Characterization

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A Portable 3D-Printed Dielectric Lens Antennas for Liquid-Mi...

International Symposium on Antennas and Propagation (ISAP)

作者： Patchadaporn Sangpet Prayoot Akkaraekthalin Wanwisa Thaiwirot Nutapong Somjit Sukanya Chudpooti Nonchanutt Chudpooti Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand School of Electronic and Electrical Engineering University of Leeds Leeds United Kingdom Department of Industrial Physics and Medical Instrumentation Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand

The Fused Deposition Modeling (FDM) method is utilized in this research to present dielectric lens antennas that were 3D printed. The ultra-wideband (UWB) stub antenna’s antenna characteristic is intended to be improved by the 3D-printed dielectric lens antennas. The proportion of ethanol in the liquid mixture sample is categorized using the transmission-line measuring technique. The device-under-test (DUT) is placed between two 3D-printed dielectric lens antennas. The glass bottle is filled with a 100-ml liquid sample and covered with a plastic cap. The 3D EM Simulation CST Studio is used to optimize the 10 mm gap between the dielectric lens antennas and the DUT. Six concentrations of the ethanol/water mixture, such as empty, 60%, 65%, 70%, and 80%, are measured to examine the measurement system. The measurement outcomes indicate the various S21 (transmission coefficient) levels between 9 GHz and 11 GHz. According to the trend of the suggested system, the level of the transmission coefficient, S21, will change downward when the proportion of ethanol is increased. Several better advantages, such as a non-destructive method, non-contact measurement, and support with a real-time monitoring system, are provided by the transmission-line measuring methodology using 3D-printed dielectric lens antennas.

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