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arXiv 2023年

作者： Villegas, Arturo Passos, Marcello H.M. Pereira, Silvania F. Torres, Juan P. ICFO Institut de Ciencies Fotoniques The Barcelona Institute of Science and Technology Castelldefels Barcelona08860 Spain Av. Carl Friedrich Gauss 7 Barcelona08860 Spain Department of Imaging Physics Faculty of Applied Sciences Delft University of Technology Lorentzweg 1 Delft2628 CJ Netherlands Department of Signal Theory and Communications Universitat Politecnica de Catalunya Barcelona08034 Spain

We show a general method to estimate with optimum precision, i.e., the best precision determined by the light-matter interaction process, a set of parameters that characterize a phase object. The method derives from ideas presented by Pezze et al., [Phys. Rev. Lett. 119, 130504 (2017)]. Our goal is to illuminate the main characteristics of this method as well as its applications to the physics community, probably not familiar with the formal quantum language usually employed in works related to quantum estimation theory. First, we derive precision bounds for the estimation of the set of parameters characterizing the phase object. We compute the Crámer-Rao lower bound for two experimentally relevant types of illumination: a multimode coherent state with mean photon number N, and N copies of a multimode single-photon quantum state. We show under which conditions these two models are equivalent. Second, we show that the optimum precision can be achieved by projecting the light reflected/transmitted from the object onto a set of modes with engineered spatial shape. We describe how to construct these modes, and demonstrate explicitly that the precision of the estimation using these measurements is optimum. As example, we apply these results to the estimation of the height and sidewall angle of a cliff-like nanostructure, an object relevant in semiconductor industry for the evaluation of nanofabrication techniques. Copyright © 2023, The Authors. All rights reserved.

关键词： Parameter estimation

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A new multi-criteria model for ranking chess players

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Procedia computer science 2021年 192卷 4290-4299页

作者： Aleksandra Kaczyńska Joanna Kołodziejczyk Wojciech Sałabun Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Żołnierska 49 71-210 Szczecin Poland

Chess is a very demanding sport as it requires advanced planning and strategic thinking skills. The degree of difficulty of the game also depends on the time allotted for a game, which can range from a few minutes to several tens of minutes. For this reason, the games are divided into several categories: standard, blitz, and bullet. However, as many chess players specialize in only some of the categories, it is difficult to determine the best chess player. It is very important to keep a proper ranking of the players. One way to recognize their achievements is the FIDE (Fédération Internationale des Échecs) titles awarded to the best players. However, there is still the problem of how to determine the best among the Grandmasters. There are many very talented players competing in chess. Creating a single ranking for all types of chess, regardless of the time allotted for the game, is a difficult challenge, as many undeniably outstanding chess players do not specialize in all types. Creating a ranking for only one type would not accurately describe the level of players. Therefore, a ranking was created based on all of them using the COMET method, which belongs to the multi-criteria decision-making methods (MCDA). It is based on fuzzy logic and uses characteristic objects for the assessment of alternatives, which guarantees immunity to the paradox of reversal rankings. Expert opinion was used for correct evaluation. This article presents the ranking of chess players regardless of the type of game they specialize in, to prove that it should be possible to identify the single best chess player.

关键词： Chess MCDA COMET players evaluation decision making

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Transmission Spectra Investigation of Nanoporous Al2O3 Matrices Filled with KDP, ADP and TGS Crystals at Visible, NIR, and SubTerahertz Ranges 11

Transmission Spectra Investigation of Nanoporous Al2O3 Matri...

引用

11th IEEE International Conference "Nanomaterials: Applications and Properties", NAP 2021

作者： Andrushchak, Nazariy Adamiv, Volodymyr Haiduchok, Volodymyr Teslyuk, Ihor Yashchyshyn, Yevhen Andrushchak, Anatoliy Computer-Aided Design Systems Lviv Polytechnic National University Lviv Ukraine Department of Optical Materials Vlokh Institute of Physical Optics Lviv Ukraine Scientific research company "Electron-Carat" Lviv Ukraine Institute of Radioelectronics and Multimedia Technology Warsaw University of Technology Warsaw Poland Department of Applied Physics and Nanomaterials Science Lviv Polytechnic National University Lviv Ukraine

ISBN: (纸本)9781665439077

In this paper, the modified technology of nanoporous aluminum oxide (Al2O3) matrices filling with the KDP, ADP, and TGS crystals is proposed. The transmission spectra of the grown structures were studied at 300-3000 nm and 50-1200 GHz spectral ranges. Because of the performed investigation, due to the significant transmission of nanoporous matrices in the terahertz range, in-depth analysis needs to be performed for their use as substrates for the implementation of nanoplasmonic devices, given the regular (periodic) structure of nanopores in these matrices. ©2021 IEEE

关键词： Aluminum oxide

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TFPnP: tuning-free plug-and-play proximal algorithms with applications to inverse imaging problems

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2022年第1期23卷 699-746页

作者： Kaixuan Wei Angelica Aviles-Rivero Jingwei Liang Ying Fu Hua Huang Carola-Bibiane Schönlieb School of Computer Science and Technology Beijing Institute of Technology Beijing China Department of Pure Mathematics and Mathematical Statistics University of Cambridge Cambridge UK Institute of Natural Sciences and School of Mathematical Sciences Shanghai Jiao Tong University Shanghai China School of Artificial Intelligence Beijing Normal University Beijing China Department of Applied Mathematics and Theoretical Physics University of Cambridge Cambridge UK

Plug-and-Play (PnP) is a non-convex optimization framework that combines proximal algorithms, for example, the alternating direction method of multipliers (ADMM), with advanced denoising priors. Over the past few years, great empirical success has been obtained by PnP algorithms, especially for the ones that integrate deep learning-based denoisers. However, a key problem of PnP approaches is the need for manual parameter tweaking which is essential to obtain high-quality results across the high discrepancy in imaging conditions and varying scene content. In this work, we present a class of tuning-free PnP proximal algorithms that can determine parameters such as denoising strength, termination time, and other optimization-specific parameters automatically. A core part of our approach is a policy network for automated parameter search which can be effectively learned via a mixture of model-free and model-based deep reinforcement learning strategies. We demonstrate, through rigorous numerical and visual experiments, that the learned policy can customize parameters to different settings, and is often more efficient and effective than existing handcrafted criteria. Moreover, we discuss several practical considerations of PnP denoisers, which together with our learned policy yield state-of-the-art results. This advanced performance is prevalent on both linear and nonlinear exemplar inverse imaging problems, and in particular shows promising results on compressed sensing MRI, sparse-view CT, single-photon imaging, and phase retrieval.

关键词： plug-and-play proximal optimization reinforcement learning inverse imaging problems

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Expulsion from structurally balanced paradise

arXiv

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arXiv 2020年

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

We perform simulations of structural balance evolution on a triangular lattice using the heat-bath algorithm. In contrast to similar approaches — but applied to analysis of complete graphs — the triangular lattice topology successfully prevents the occurrence of even partial Heider’s balance. Starting with the state of Heider’s paradise, it is just a matter of time when the evolution of the system leads to an unbalanced and disordered state. The time of the system relaxation does not depend on the system size. The lack of any signs of balanced state was not observed in earlier investigated systems dealing with structural balance. Copyright © 2020, The Authors. All rights reserved.

关键词： Topology

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A systematic study of transfer learning for colorectal cancer detection

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Informatics in Medicine Unlocked 2023年 40卷

作者： Luo, Ruihao Bocklitz, Thomas Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP) Friedrich-Schiller-Universität Jena Member of the Leibniz Centre for Photonics in Infection Research (LPI) Jena Germany Leibniz Institute of Photonic Technology (IPHT) Member of Leibniz Health Technologies Member of the Leibniz Centre for Photonics in Infection Research (LPI) Jena Germany Institute of Computer Science Faculty of Mathematics Physics & Computer Science Universität Bayreuth Bayreuth Germany

Background and objective: With the rapid development of data science methods like deep learning, these methods have already been used into the field of healthcare and medicine. However, due to regulations and ethical issues, it is practically difficult to obtain large amount of medical data for training deep learning models. Transfer learning is a powerful tool to reuse the knowledge gained from different domains, which makes it possible to retrain deep learning models only with small datasets in medical image processing. In this contribution, a systematic study of model transfer techniques like fine tuning parts of the network or adding additional layers, for medical image data was conducted. Methods: The study accomplished a binary classification task based on a colorectal cancer dataset, including microsatellite unstable or hypermutated (MSIMUT) and microsatellite stable (MSS) images. By using K-fold cross-validation, the performances of five pretrained models (DenseNet121, DenseNet201, InceptionV3, MobileNetV2 and ResNet50) were assessed according to balanced accuracy. As baseline methods, combinations of transfer learning as feature extractor and principal component analysis with linear discriminant analysis (PCA-LDA) or support vector machine (PCA-SVM) were utilised, and compared with the transfer learning counterparts. Conclusions: The results have shown that adding convolutional layers perform obviously better than simply using the original network or fine-tuning some last layers of the network. Furthermore, a proposed bagging method performed well on a testing dataset. This study reduces the workload for future transfer learning tasks in the biomedical domain and allows to test promising transfer learning strategies first. © 2023

关键词： Colorectal cancer K-fold cross-validation Medical image analysis Transfer learning

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Fast evaluation of interaction integrals for confined systems with machine learning

arXiv

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arXiv 2020年

作者： Mreńca-Kolasińska, Alina Kolasiński, Krzysztof Szafran, Bartlomiej AGH University of Science and Technology Faculty of Physics and Applied Computer Science al. Mickiewicza 30 Kraków30-059 Poland

The calculation of interaction integrals is a bottleneck for the treatment of many-body quantum systems due to its high numerical cost. We conduct configuration interaction calculations of the few-electron states confined in III-V semiconductor two-dimensional structures using a shallow neural network to calculate the two-electron integrals, which can be used for general isotropic interaction potentials. This approach allows for a speed-up of the evaluation of the energy levels and controllable accuracy. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum optics

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Primordial black holes from null energy condition violation during inflation

arXiv

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arXiv 2023年

作者： Cai, Yong Zhu, Mian Piao, Yun-Song Institute for Astrophysics School of Physics Zhengzhou University Zhengzhou450001 China Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Krakow30-348 Poland School of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China International Centre for Theoretical Physics Asia-Pacific University of Chinese Academy of Sciences Beijing100190 China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study UCAS Hangzhou310024 China Institute of Theoretical Physics Chinese Academy of Sciences P.O. Box 2735 Beijing100190 China

Primordial black holes (PBHs) and the violation of the null energy condition (NEC) have significant implications for our understanding of the very early universe. We present a novel approach to generate PBHs via the NEC violation in a single-field inflationary scenario. In our scenario, the universe transitions from a first slow-roll inflation stage with a Hubble parameter H = Hinf1 to a second slow-roll inflation stage with H = Hinf2 Hinf1, passing through an intermediate stage of NEC violation. The NEC violation naturally enhances the primordial scalar power spectrum at a certain wavelength, leading to the production of PBHs with masses and abundances of observational interest. We also investigate the phenomenological signatures of scalar-induced gravitational waves (SIGWs) resulting from the enhanced density perturbations. Our work highlights the potential of utilizing a combination of PBHs, SIGWs, and primordial gravitational waves as a valuable probe for studying NEC violation during inflation, opening up new avenues for exploring the early universe. © 2023, CC BY.

关键词： Black holes

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How strongly do rank similarity coefficients differ used in decision making problems?

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Procedia computer science 2021年 192卷 4570-4577页

作者： Andrii Shekhovtsov Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Żołnierska 49 71-210 Szczecin Poland

It is common practice in the MCDA to use several multi-criteria decision methods and then compares obtained rankings with one or two different rank correlation coefficients. The problem is that different rank correlation coefficient gives different values for the same pair of rankings, and the number of studies which tries to investigate it is small. Studying the similarity of rankings is a very important challenge in multi-criteria decision support, and the coefficients themselves seem to be the most practical ways of evaluating rankings. This paper compares chosen rank correlation coefficients to show how much different they are. Spearman’s, Weighted Spearman’s, Kendall Tau and Rank similarity correlation coefficient are compared statistically. The paper confirms that the coefficients are closely related, and their dependence is graphically represented, which initiates research towards allows for their better selection in the future. In conclusions, directions of further development are indicated.

关键词： MCDA ranking rank correlation

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Unraveling the mysteries of wormhole formation in Rastall-Rainbow gravity: A comprehensive study using the embedding approach

arXiv

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arXiv 2024年

作者： Errehymy, Abdelghani Banerjee, Ayan Donmez, Orhan Daoud, Mohammed Nisar, Kottakkaran Sooppy Abdel-Aty, Abdel-Haleem Astrophysics Research Centre School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Private Bag X54001 Durban4000 South Africa Astrophysics and Cosmology Research Unit School of Mathematics Statistics and Computer Science University of KwaZulu–Natal Private Bag X54001 Durban4000 South Africa College of Engineering and Technology American University of the Middle East Egaila54200 Kuwait Department of Physics Faculty of Sciences Ibn Tofail University P.O. Box 133 Kenitra14000 Morocco Abdus Salam International Centre for Theoretical Physics Miramare Trieste34151 Italy Department of Mathematics College of Science and Humanities in Alkharj Prince Sattam bin Abdulaziz University Al Kharj Saudi Arabia Department of Physics College of Sciences University of Bisha P.O. Box 344 Bisha61922 Saudi Arabia

The present work looks for the possible existence of static and spherically symmetric wormhole geometries in Rastall-Rainbow gravity. Since, the Rastall-Rainbow gravity model has been constructed with the combination of Rastall theory and the gravity’s rainbow formalism. Taking advantage of the Karmarkar condition for embedding class one metrics, we solve the modified field equations analytically that describe wormholes for specific choice of redshift function. For specific parameter ranges, the solution represents a traversable wormhole that exhibits the violation of null energy condition and consequently the weak energy condition also. Furthermore, we focus on the wormhole stability via adiabatic sound velocity analysis. This model establishes a strong connection between two model parameters, namely, the Rastall parameters and the Rainbow functions, and how it affects the wormhole solution. Copyright © 2024, The Authors. All rights reserved.

关键词： Embeddings

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