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Entanglement wedge method, out-of-time-ordered correlators, and pole skipping

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Physical Review D 2025年第10期111卷 106013-106013页

作者： Banashree Baishya Adrita Chakraborty Nibedita Padhi Department of Physics Indian Institute of Technology Guwahati Assam-781039 India Faculty of Physics and Applied Computer Science AGH University of Krakow al. Adama Mickiewicza 30 30-059 Krakow Poland Department of Physics Indian Institute of Technology Kharagpur Kharagpur 721302 India

We investigate two salient chaotic features, namely Lyapunov exponent and butterfly velocity, for an asymptotically Lifshitz black hole background with arbitrary dynamical critical exponent. These features are computed using three methods: entanglement wedge method, out-of-time-ordered correlator computation, and pole skipping. We present a comparative study where all of these methods yield exactly similar results for the butterfly velocity and Lyapunov exponent. This establishes an equivalence between all three methods for probing chaos in the chosen gravity background. Furthermore, we evaluate the chaos at the classical level by computing the eikonal phase and Lyapunov exponent from the bulk gravity. In the classical approach, we comment on potential limitations while choosing the turning point of the null geodesic in our gravity background. All chaotic properties emerge as nontrivial functions of the anisotropy index. By examining the classical eikonal phase, we uncover different scattering scenarios in the near-horizon and near-boundary regimes. Finally, we remark on a possible classical/quantum correspondence from the analysis of classical eikonal phase shift and Lyapunov exponent.

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computer assisted proof of drift orbits along normally hyperbolic manifolds II: Application to the restricted three body problem

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arXiv 2021年

作者： Capiński, Maciej J. Wodka, Natalia Faculty of Applied Mathematics AGH University of Science and Technology al. Mickiewicza 30 Kraków30-059 Poland

We present a computer assisted proof or diffusion in the Planar Elliptic Restricted Three Body Problem. We treat the elliptic problem as a perturbation of the circular problem, where the perturbation parameter is the eccentricity of the primaries. The unperturbed system preserves energy, and we show that for sufficiently small perturbations we have orbits with explicit energy changes, independent from the size of the perturbation. The result is based on shadowing of orbits along transversal intersections of stable/unstable manifolds of a normally hyperbolic cylinder. © 2021, CC BY.

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On-Chip Multidimensional Dynamic Control of Twisted Moiré Photonic Crystal for Smart Sensing and Imaging

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arXiv 2023年

作者： Tang, Haoning Lou, Beicheng Du, Fan Gao, Guangqi Zhang, Mingjie Ni, Xueqi Hu, Evelyn Yacoby, Amir Cao, Yuan Fan, Shanhui Mazur, Eric School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Department of Applied Physics Ginzton Laboratory Stanford University StanfordCA94305 United States Department of Physics Faculty of Art and Sciences Harvard University CambridgeMA02138 United States Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA94720 United States

Reconfigurable optics, optical systems that have a dynamically tunable configuration, are emerging as a new frontier in photonics research. Recently, twisted moiré photonic crystal has become a competitive candidate for implementing reconfigurable optics because of its high degree of tunability. However, despite its great potential as versatile optics components, simultaneous and dynamic modulation of multiple degrees of freedom in twisted moiré photonic crystal has remained out of reach, severely limiting its area of application. In this paper, we present a MEMS-integrated twisted moiré photonic crystal sensor that offers precise control over the interlayer gap and twist angle between two photonic crystal layers, and demonstrate an active twisted moiré photonic crystal-based optical sensor that can simultaneously resolve wavelength and polarization. Leveraging twist- and gap-tuned resonance modes, we achieve high-accuracy spectropolarimetric reconstruction of light using an adaptive sensing algorithm, over a broad operational bandwidth in the telecom range and full Poincaré sphere. Our research showcases the remarkable capabilities of multidimensional control over emergent degrees of freedom in reconfigurable nanophotonics platforms and establishes a scalable pathway towards creating comprehensive flat-optics devices suitable for versatile light manipulation and information processing tasks. Extracting phase, polarization, and wavelength information from an optical signal typically necessitates the use of separate optical components, such as interferometers, polarizers, and narrow-band filters or spectrometers, that cannot easily be integrated1 and are limited in resolution and speed. Recently, however, computational sensing has made it possible to reconstruct target parameters from the optical signal obtained with a single © 2023, CC BY.

关键词： Photonic crystals

Anchoring Groups for Ordered and Highly Stable Sams on Naturally Oxidized Aluminum – Phosphonate Versus Carboxylate

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SSRN

SSRN 2024年

作者： Cegielka, Daria M. Koziel, Krzysztof Zharnikov, Michael Cyganik, Piotr Jagiellonian University Doctoral School of Exact and Natural Sciences Lojasiewicza 11 Krakow30-348 Poland Jagiellonian University Faculty of Physics Astronomy and Applied Computer Science Smoluchowski Institute of Physics Lojasiewicza 11 Krakow30-348 Poland Jagiellonian University Faculty of Chemistry Gronostajowa 2 Krakow30-387 Poland Angewandte Physikalische Chemie Universität Heidelberg Im Neuenheimer Feld 253 HeidelbergD-69120 Germany

Modification of metal oxide surfaces by self-assembled monolayers (SAMs) is attracting growing attention. Carboxylic (CA) and phosphonic (PA) acids are most popular anchoring groups in this context, applied to create hydrophobic coatings, biosensors, and organic field-effect transistors. The efficiency of these devices is crucially affected by the structural quality and stability of the SAM. In this context, we studied the effect of the preparation procedure (solvent, incubation time, and temperature) on the quality of PA SAMs on naturally oxidized aluminum. We demonstrate formation of PA SAMs matching structural quality of archetypical alkanethiols on gold. Next, we compare their stability with analogue CA SAMs. Our data show that PA SAMs not only exhibit much higher hydrolytic stability but are also capable to protect aluminum substrate from oxidation and degradation. Importantly, even small improvement of the PA SAMs quality, translates into enormous increase of their hydrolytic stability crucial for majority of applications. Finally, we demonstrate that the thermal stability of PA on oxidized aluminum is by ~250 K higher than CA SAMs, and by ~200 K higher than for thiols on gold, which makes PA SAMs an excellent candidate for organic electronics, where overheating problems and high-temperature fabrication procedures are common issues. © 2024, The Authors. All rights reserved.

关键词： Aluminum

Artificial Intelligence Approaches for Predictive Maintenance in the Steel Industry: A Survey

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arXiv 2024年

作者： Jakubowski, Jakub Wojak-Strzelecka, Natalia Ribeiro, Rita P. Pashami, Sepideh Bobek, Szymon Gama, João Nalepa, Grzegorz J. Department of Applied Computer Science AGH University of Science and Technology al. Adama Mickiewicza 30 Kraków30-059 Poland ArcelorMittal Poland al. Józefa Pilsudskiego 92 Dabrowa Gornicza41-308 Poland Mark Kac Center for Complex Systems Research ul. prof. Stanislawa Lojasiewicza 11 Kraków30-348 Poland RISE Research Institutes of Sweden Sweden Center for Applied Intelligent Systems Research Halmstad University Halmstad Sweden INESC TEC. Porto4200-465 Portugal Faculty of Sciences University of Porto Porto4200-465 Portugal Faculty of Economics University of Porto Porto4200-465 Portugal

Predictive Maintenance (PdM) emerged as one of the pillars of Industry 4.0, and became crucial for enhancing operational efficiency, allowing to minimize downtime, extend lifespan of equipment, and prevent failures. A wide range of PdM tasks can be performed using Artificial Intelligence (AI) methods, which often use data generated from industrial sensors. The steel industry, which is an important branch of the global economy, is one of the potential beneficiaries of this trend, given its large environmental footprint, the globalized nature of the market, and the demanding working conditions. This survey synthesizes the current state of knowledge in the field of AI-based PdM within the steel industry and is addressed to researchers and practitioners. We identified 219 articles related to this topic and formulated five research questions, allowing us to gain a global perspective on current trends and the main research gaps. We examined equipment and facilities subjected to PdM, determined common PdM approaches, and identified trends in the AI methods used to develop these solutions. We explored the characteristics of the data used in the surveyed articles and assessed the practical implications of the research presented there. Most of the research focuses on the blast furnace or hot rolling, using data from industrial sensors. Current trends show increasing interest in the domain, especially in the use of deep learning. The main challenges include implementing the proposed methods in a production environment, incorporating them into maintenance plans, and enhancing the accessibility and reproducibility of the research. Copyright © 2024, The Authors. All rights reserved.

关键词： Hot rolling

Hybrid vision transformer and Xception model for reliable CT-based ovarian neoplasms diagnosis

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Intelligence-Based Medicine 2025年 11卷 100227-100227页

作者： Alshdaifat, Eman Hussein Gharaibeh, Hasan Sindiani, Amer Mahmoud Madain, Rola Al-Mnayyis, Asma'a Mohammad Abu Mhanna, Hamad Yahia Almahmoud, Rawan Eimad Akhdar, Hanan Fawaz Amin, Mohammad Nasayreh, Ahmad Hamad, Raneem Department of Obstetrics and Gynecology Faculty of Medicine Yarmouk University Irbid 211633 Jordan Artificial Intelligence and Data Innovation Office King Hussein Cancer Center Jordan Amman 11622 Jordan Department of Obstetrics and Gynecology Faculty of Medicine Jordan University of Science and Technology Irbid 22110 Jordan Department of Internal Medicine College of Medicine Yarmouk University Irbid 211633 Jordan School of Physics University Sains Malaysia (USM) Penang 11800 Malaysia Physics Department Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh 13318 Saudi Arabia Computer Science Department Faculty of Information Technology and Computer Sciences Yarmouk University Irbid 21163 Jordan Faculty of Medicine Yarmouk University-Irbid 21163 Jordan

Ovarian cancer is a major global health concern, characterized by high mortality rates and a lack of accurate diagnostic methods. Rapid and accurate detection of ovarian cancer is essential to improve patient outcomes and formulate appropriate treatment protocols. Medical imaging methods are essential for identifying ovarian cancer;however, achieving accurate diagnosis remains a challenge. This paper presents a robust methodology for ovarian cancer detection, including the identification and classification of benign and malignant tumors, using the Xception_ViT model. This hybrid approach was chosen because it combines the advantages of traditional CNN-based models (such as Xception) with the capabilities of modern Transformers-based models (such as ViT). This combination allows the model to take advantage of Xception, which extracts features from images. The Vision Transformer (ViT) model is then used to identify connections between diverse visual elements, enhancing the model's understanding of complex components. A Multi-Layer Perceptron (MLP) layer is finally integrated with the proposed model for image classification. The effectiveness of the model is evaluated using three computed tomography (CT) image datasets from King Abdullah university Hospital (KAUH) in Jordan. The first dataset consists of the ovarian cancer computed tomography dataset (KAUH-OCCTD), the second is the benign ovarian tumors dataset (KAUH-BOTD), and the third is the malignant ovarian tumors dataset (KAUH-MOTD). The three datasets collected from 500 women are characterized by their diversity in ovarian tumor classification and are the first of their kind collected in Jordan. The proposed model Xception_ViT achieved an accuracy of 98.09 % in identifying ovarian cancer on the KAUH-OCCTD dataset, and an accuracy of 96.05 % and 98.73 % on the KAUH-BOTD and KAUH-MOTD datasets, respectively, in distinguishing between benign and malignant ovarian tumors. The proposed model outperformed the pre-trai

关键词： CT Ovarian cancer Ovarian diagnosis Ovarian neoplasms Transformer Xception

Design of a Dual-Polarized High-Gain Yagi Antenna Array for 2G/3G/LTE Base Stations

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Design of a Dual-Polarized High-Gain Yagi Antenna Array for ...

IEEE International Conference on Electronic Information and Communication technology (ICEICT)

作者： Liwei Rao Botao Feng Xiao Ding Sanshan Sun Wenzhe Gu Qingsheng Zeng College of Electronics and Information Engineering Shenzhen University Shenzhen China Faculty of Humanities and Arts Macau University of Science and Technology Macau China College of Physics and Electronic Engineering Sichuan Normal University Sichuan China School of Computer Science and Engineering Huizhou University Huizhou China College of Astronautics Nanjing University of Aeronautics and Astronautics Nanjing China

The present paper introduces a novel Yagi antenna array consisting of dual-polarized dipoles. The antenna consists of a pair of dipoles and two orthogonally mounted Yagi antennas with dielectric plates. To ensure that the antenna performance is consistent in both polarization directions, a symmetrical structure is adopted. Simulated results show a wide working frequency band ranging from 1.7 to 2.8 GHz(48.9%) with a high gain of 15±3 dBi, and the 30°-horizontal and vertical beam widths.

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New Promising Zinc Alloys for Absorbable Implants Produced by Hydrostatic Extrusion

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SSRN

SSRN 2023年

作者： Jarzębska, Anna Gieleciak, Magdalena Bigos, Agnieszka Maj, Lukasz Trembecka-Wójciga, Klaudia Bugajska, Monika Bieda, Magdalena Rogal, Lukasz Kawalko, Jakub Przybysz, Sylwia Wojtas, Daniel Mzyk, Aldona Schirhagl, Romana Institute of Metallurgy and Materials Science Polish Academy of Sciences Krakow Poland Academic Centre for Materials and Nanotechnology AGH University of Science and Technology Krakow Poland Institute of High Pressure Physics Polish Academy of Sciences Warszawa Poland Faculty of Medicine Masaryk University Brno Czech Republic Department of Health Technology Danish Technical University Kongens Lyngby Denmark Department of Biomedical Engineering Groningen University University Medical Center Groningen Groningen Netherlands

Within the present study, complementary analysis of the effect of hydrostatic extrusion on zinc-based materials was provided for the first time. Microstructure of pure Zn, Zn-Mg and Zn-Mg-Cu alloys was examined by advanced microscopy techniques like electron backscattered diffraction and transmission electron microscopy. Uniaxial tensile tests were carried out to reveal mechanical properties of the materials. Corrosion properties were assessed based on electrochemical and static immersion tests. Finally, the cytotoxic effect of zinc extracts on endothelial cells were examined by standard MTT assays combined with confocal *** results showed that 3-pass hydrostatic extrusion results in significant refinement, not only of the grains, but also of the intermetallic phase Mg2Zn11 for the investigated alloys. Both phases create a band-like microstructure in the extrusion direction, which is reflected in beneficial mechanical properties. The alloys exhibited ultimate tensile strength exceeding 300 MPa and elongation higher than 20%. Corrosion tests indicated that hydrostatic extrusion did not deteriorate the degradation rate, since all the materials showed a similar level of degradation. Moreover, the uniform distribution of the intermetallic phase contributed to homogeneous corrosion of Zn alloys. Biological studies indicated that the least cytotoxic response in endothelial cells was obtained for the Zn-Mg ***, hydrostatic extrusion is a promising method for the fabrication of high-strength Zn-based materials with uniform degradation and sufficient biocompatibility as absorbable implants. © 2023, The Authors. All rights reserved.

关键词： Zinc alloys

Investigation of the effectiveness of applying ChatGPT in Dialogic Teaching Using Electroencephalography

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arXiv 2024年

作者： Zhang, Jiayue Liu, Yiheng Cai, Wenqi Wu, Lanlan Peng, Yali Yu, Jingjing Qi, Senqing Long, Taotao Ge, Bao School of Physics and Information Technology Shaanxi Normal University Xi’an China School of Psychology Shaanxi Normal University Xi’an China School of Computer Science Shaanxi Normal University Xi’an China Key Laboratory of Modern Teaching Technology Ministry of Education Shaanxi Normal University Xi’an China Faculty of Artificial Intelligence in Education Central China Normal University Wuhan China Key Laboratory of Modern Teaching Technology Ministry of Education School of Physics and Information Technology Shaanxi Normal University Xi’an China

In recent years, the rapid development of artificial intelligence technology, especially the emergence of large language models (LLMs) such as ChatGPT, has presented significant prospects for application in the field of education. LLMs possess the capability to interpret knowledge, answer questions, and consider context, thus providing support for dialogic teaching to students. Therefore, an examination of the capacity of LLMs to effectively fulfill instructional roles, thereby facilitating student learning akin to human educators within dialogic teaching scenarios, is an exceptionally valuable research topic. This research recruited 34 undergraduate students as participants, who were randomly divided into two groups. The experimental group engaged in dialogic teaching using ChatGPT, while the control group interacted with human teachers. Both groups learned the histogram equalization unit in the information-related course "Digital Image Processing". The research findings show comparable scores between the two groups on the retention test. However, students who engaged in dialogue with ChatGPT exhibited lower performance on the transfer test. Electroencephalography data revealed that students who interacted with ChatGPT exhibited higher levels of cognitive activity, suggesting that ChatGPT could help students establish a knowledge foundation and stimulate cognitive activity. However, its strengths on promoting students' knowledge application and creativity were insignificant. Based upon the research findings, it is evident that ChatGPT cannot fully excel in fulfilling teaching tasks in the dialogue teaching in information related courses. Combining ChatGPT with traditional human teachers might be a more ideal approach. The synergistic use of both can provide students with more comprehensive learning support, thus contributing to enhancing the quality of teaching. © 2024, CC BY.

关键词： Students