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Initial development of the urbisphere urban hyperspectral library: Berlin, Germany

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Initial development of the urbisphere urban hyperspectral li...

Urban Remote Sensing Joint Event

作者： Giannis Lantzanakis Dimitris Tsirantonakis Nektarios Chrysoulakis Sue Grimmond Andreas Christen Joern Birkmann Institute of Applied and Computational Mathematics Remote Sensing Lab Foundation for Research and Technology Hellas Heraklion Greece Department of Meteorology University of Reading Reading UK Environmental Meteorology University of Freiburg Freiburg Germany Institute of Spatial and Regional Planning University of Stuttgart Stuttgart Germany

The future sustainability of cities is linked directly with their adaptive capacity in response to both ongoing urbanization, weather extremes and climate change. Many possible actions are related to urban materials and their thermal and radiative properties. To explore alternatives using modelling and to monitor applications the thermal and radiative properties of materials are critical. However, there is a lack of hyperspectral data for a wide range of common materials. A Spectral Evolution RS-3500 spectroradiometer is used to measure 2151 spectral (1 nm) bands between 350 to 2500 nm in four representative neighborhoods of Berlin (Charlottenburg, Neukolln, Lichtenberg and Mitte) during August 2022. The data are processed to contribute 284 hyperspectral measurements of surfaces into the urbisphere hyperspectral library.

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Orthogonal Fourier Analysis on domains

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Expositiones Mathematicae 2024年

作者： Kolountzakis, Mihail N. Department of Mathematics and Applied Mathematics University of Crete Voutes Campus Heraklion 70013 Greece Institute of Computer Science Foundation of Research and Technology Hellas N. Plastira 100 Vassilika Vouton Heraklion 700 13 Greece

In this paper we go over the history of the Fuglede or Spectral Set Conjecture as it has developed over the last 30 years or so. We do not aim to be exhaustive and we do not cover important areas of development such as the results on the problem in classes of finite groups or the version of the problem that focuses on spectral measures instead of sets. The selection of the material has been strongly influenced by personal taste, history and capabilities. We are trying to be more descriptive than detailed and we point out several open questions. © 2024 Elsevier GmbH

关键词： Fuglede conjecture Spectral sets Tilings

A Deep Learning Approach to Nonconvex Energy Minimization for Martensitic Phase Transitions

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arXiv 2022年

作者： Chen, Xiaoli Rosakis, Phoebus Wu, Zhizhang Zhang, Zhiwen Institute for Functional Intelligent Materials Department of Mathematics National University of Singapore 119077 Singapore Department of Mathematics and Applied Mathematics University of Crete Greece Institute of Applied and Computational Mathematics Foundation for Research and Technology-Hellas Heraklion Greece Department of Mathematics The University of Hong Kong Pokfulam Road Hong Kong

We propose a mesh-free method to solve nonconvex energy minimization problems for martensitic phase transitions and twinning in crystals, using the deep learning approach. These problems pose multiple challenges to both analysis and computation, as they involve multiwell gradient energies with large numbers of local minima, each involving a topologically complex microstructure of free boundaries with gradient jumps. We use the Deep Ritz method, whereby candidates for minimizers are represented by parameter-dependent deep neural networks, and the energy is minimized with respect to network parameters. The new essential ingredient is a novel activation function proposed here, which is a smoothened rectified linear unit we call SmReLU;this captures the structure of minimizers where usual activation functions fail. The method is mesh-free and thus can approximate free boundaries essential to this problem without any special treatment, and is extremely simple to implement. We show the results of many numerical computations demonstrating the success of our method. © 2022, CC BY.

关键词： Deep neural networks

Function-space regularized Rényi divergences

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arXiv 2022年

作者： Birrell, Jeremiah Pantazis, Yannis Dupuis, Paul Katsoulakis, Markos A. Rey-Bellet, Luc Department of Mathematics and Statistics University of Massachusetts AmherstMA01003 United States Institute of Applied and Computational Mathematics Foundation for Research and Technology Hellas HeraklionGR-70013 Greece Division of Applied Mathematics Brown University ProvidenceRI02912 United States

We propose a new family of regularized Rényi divergences parametrized not only by the order α but also by a variational function space. These new objects are defined by taking the infimal convolution of the standard Rényi divergence with the integral probability metric (IPM) associated with the chosen function space. We derive a novel dual variational representation that can be used to construct numerically tractable divergence estimators. This representation avoids risk-sensitive terms and therefore exhibits lower variance, making it well-behaved when α > 1;this addresses a notable weakness of prior approaches. We prove several properties of these new divergences, showing that they interpolate between the classical Rényi divergences and IPMs. We also study the α → ∞ limit, which leads to a regularized worst-case-regret and a new variational representation in the classical case. Moreover, we show that the proposed regularized Rényi divergences inherit features from IPMs such as the ability to compare distributions that are not absolutely continuous, e.g., empirical measures and distributions with low-dimensional support. We present numerical results on both synthetic and real datasets, showing the utility of these new divergences in both estimation and GAN training applications;in particular, we demonstrate significantly reduced variance and improved training performance. Copyright © 2022, The Authors. All rights reserved.

关键词： Integral equations

Machine Learning for the edge energies of high symmetry Au nanoparticles

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arXiv 2022年

作者： Pervolarakis, Emmanouil Tritsaris, Georgios A. Rosakis, Phoebus Remediakis, Ioannis N. Department of Materials Science and Technology University of Crete Heraklion70013 Greece John A. Paulson School of Engineering and Applied Sciences Harvard University MA Cambridge02138 United States Department of Mathematics and Applied Mathematics University of Crete Heraklion70013 Greece Institute of Applied & Computational Mathematics Foundation for Research and Technology Hellas Crete Heraklion71110 Greece Institute of Electronic Structure and Laser Foundation for Research and Technology Hellas Crete Heraklion71110 Greece

We present data-driven simulations for gold nanostructures, and develop a model that links total energy to geometrical features of the particle, with the ultimate goal of deriving reliable edge energies of gold. Assuming that the total energy can be decomposed into contributions from the bulk, surfaces, edges, and vertices, we use machine learning for reliable multi-variant fits of the associated coefficients. The proposed method of total energy calculations using machine learning produces almost ab-initio-like accuracy with minimal computational cost. Furthermore, a clear definition and metric for edge energy is introduced for edge-energy density calculations that avoid the troublesome definition of edge length in nanostructures. Our results for edge-energy density are 0.22 eV/Å for (100)/(100) edges and 0.20 eV/Å for (111)/(111) edges. Calculated vertex energies are about 1 eV/atom. The present method can be readily extended to other metals and edge orientations as well as arbitrary nanoparticle shapes. Copyright © 2022, The Authors. All rights reserved.

关键词： Machine learning

No treeline shift despite climate change over the last 70 years

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Forest Ecosystems 2022年第1期9卷 13-22页

作者： Mirela Beloiu Dimitris Poursanidis Antonis Tsakirakis Nektarios Chrysoulakis Samuel Hoffmann Petros Lymberakis Antonis Barnias David Kienle Carl Beierkuhnlein Department of Biogeography University of BayreuthUniversitatsstraaße 3095447BayreuthGermany Remote Sensing Lab Institute of Applied and Computational MathematicsFoundation for Research and Technology Hellas100 N.Plastira Str.Vassilika VoutonHeraklion70013Greece Samaria National Park Management BodyOld National Road Chanion-KissamouAgioi ApostoloiChaniaCreteGreece Natural History Museum of Crete University of CreteKnossou Av.71409IrakleioCreteGreece GIB Department of Geography University of Bayreuth95447BayreuthGermany BayCEER Bayreuth Center of Ecology and Environmental Research University of Bayreuth95448BayreuthGermany

Background:The recent rise in temperature and shifting precipitation regimes threaten ecosystems around the globe to different *** are expected to respond to climate warming by shifting to higher elevations,but it is unclear whether they can track temperature ***,we integrated high-resolution aerial imagery with local climatic and topographic characteristics to study the treeline dynamic from 1945 to 2015 on the semiarid Mediterranean island of Crete,***:During the study period,the mean annual temperature at the treeline increased by 0.81℃,while the average precipitation decreased by 170 *** treeline is characterized by a diffuse form,with trees growing on steep limestone slopes(>50°)and shallow ***,the treeline elevation decreases with increasing distance from the coast and with aspect(south>north).Yet,we found no shift in the treeline over the past 70 years,despite an increase in temperature in all four study ***,the treeline elevation correlated strongly with topographic exposure to wind(R^(2)=0.74,p<0.001).Therefore,the temporal lag in treeline response to warming could be explained by a combination of topographic and microclimatic factors,such as the absence of a shelter effect and a decrease in ***:Although there was no treeline shift over the last 70 years,climate change has already started shifting the treeline altitudinal ***,the lack of climate-mediated migration at the treeline should raise concerns about the threats posed by warming,such as drought damages,and wildfire,especially in the Mediterranean ***,conservation management should discuss options and needs to support adaptive management.

关键词： Aerial imagery Protected area Continental island Mediterranean region High mountains Temperature Precipitation Climate change Forest dynamics

(f,Γ)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics

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Journal of Machine Learning research 2022年 23卷

作者： Birrell, Jeremiah Dupuis, Paul Katsoulakis, Markos A. Pantazis, Yannis Rey-Bellet, Luc TRIPODS Institute for Theoretical Foundations of Data Science University of Massachusetts Amherst AmherstMA01003 United States Division of Applied Mathematics Brown University ProvidenceRI02912 United States Department of Mathematics and Statistics University of Massachusetts Amherst AmherstMA01003 United States Institute of Applied and Computational Mathematics Foundation for Research and Technology - Hellas HeraklionGR-70013 Greece

We develop a rigorous and general framework for constructing information-theoretic divergences that subsume both f-divergences and integral probability metrics (IPMs), such as the 1-Wasserstein distance. We prove under which assumptions these divergences, hereafter referred to as (f, Γ)-divergences, provide a notion of 'distance' between probability measures and show that they can be expressed as a two-stage mass-redistribution/mass-transport process. The (f, Γ)-divergences inherit features from IPMs, such as the ability to compare distributions which are not absolutely continuous, as well as from f-divergences, namely the strict concavity of their variational representations and the ability to control heavy-tailed distributions for particular choices of f. When combined, these features establish a divergence with improved properties for estimation, statistical learning, and uncertainty quantification applications. Using statistical learning as an example, we demonstrate their advantage in training generative adversarial networks (GANs) for heavy-tailed, not-absolutely continuous sample distributions. We also show improved performance and stability over gradient-penalized Wasserstein GAN in image generation. © 2022 Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Yannis Pantazis, and Luc Rey-Bellet.

关键词： Generative adversarial networks

The Effect of Intra- and Inter-ring Couplings in Leaky Integrate-and-Fire Multiplex Networks

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arXiv 2023年

作者： Anesiadis, K. Hizanidis, J. Institute of Nanoscience and Nanotechnology National Center for Scientific Research Demokritos AthensGR-15341 Greece School of Mathematical and Physical Sciences National Technical University of Athens AthensGR-15780 Greece Department of Physics University of Crete Herakleio GR-71003 Greece Institute of Applied and Computational Mathematics Foundation for Research and Technology – Hellas Herakleio GR-70013 Greece

We study the dynamics of identical Leaky Integrate-and-Fire (LIF) neurons on a multiplex composed of two ring networks with symmetric nonlocal coupling within each ring and one-to-one connections between rings. We investigate the impact of different intra-ring coupling strengths in the two rings for attractive and repulsive inter-ring coupling and show that they can lead to subthreshold oscillations. The corresponding parameter spaces where this phenomenon occurs are determined numerically. Moreover, we show that depending on whether the couplings between the two rings are attractive or repulsive, the interaction produces qualitatively different behavior in the synchronization patterns and the mean frequency profiles. Copyright © 2023, The Authors. All rights reserved.

关键词： Couplings

Symmetry-Governed Dynamics of Magnetic Skyrmions Under Field Pulses

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arXiv 2024年

作者： Kuchkin, Vladyslav M. Barton-Singer, Bruno Bessarab, Pavel F. Kiselev, Nikolai S. Department of Physics and Materials Science University of Luxembourg LuxembourgL-1511 Luxembourg Institute of Applied and Computational Mathematics Foundation for Research and Technology - Hellas Heraklion700 13 Greece Science Institute University of Iceland Reykjavík107 Iceland Department of Physics and Electrical Engineering Linnaeus University KalmarSE-39231 Sweden Peter Grünberg Institute Forschungszentrum Jülich and JARA Jülich52425 Germany

Topological magnetic solitons, such as skyrmions, exhibit intriguing particle-like properties that make them attractive for fundamental research and practical applications. While many magnetic systems can host skyrmions as statically stable configurations, chiral magnets stand out for their ability to accommodate a wide diversity of skyrmions with arbitrary topological charges and varied morphologies. Despite extensive investigation, a complete understanding of chiral magnetic skyrmions has remained elusive. We present a classification of all chiral skyrmions, demonstrating three classes based on their response to external magnetic field pulses: stationary, translating, and rotating. We highlight the role of magnetic texture symmetry in this classification. Skyrmions with varied dynamics offer avenues for exploring phenomena like skyrmion-skyrmion scattering that might be crucial for future applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Textures