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arXiv 2025年

作者： Farcy, Marion Rosdahl, Joakim Dubois, Yohan Blaizot, Jérémy Martin-Alvarez, Sergio Haehnelt, Martin Kimm, Taysun Teyssier, Romain Institute for Physics Laboratory for Galaxy Evolution and Spectral Modelling EPFL Observatoire de Sauverny Chemin Pegasi 51 Versoix1290 Switzerland Centre de Recherche Astrophysique de Lyon CNRS UMR 5574 Univ. Lyon Ens de Lyon 9 avenue Charles André Saint-Genis-LavalF-69230 France Institut d’Astrophysique de Paris CNRS UMR 7095 Sorbonne Université 98 bis bd Arago Paris75014 France Stanford University StanfordCA94305 United States Kavli Institute for Cosmology Institute of Astronomy Madingley Road CambridgeCB3 0HA United Kingdom Department of Astronomy Yonsei University 50 Yonsei-ro Seodaemun-gu Seoul03722 Korea Republic of Department of Astrophysical Sciences Princeton University Peyton Hall PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University Fine Hall Washington Road PrincetonNJ08544-1000 United States

Galaxies form and evolve via a multitude of complex physics. In this work, we investigate the role of cosmic ray (CR) feedback in galaxy evolution and reionisation, by examining its impact on the escape of ionising radiation from galaxies. For this purpose, we present two sphinx cosmological radiation-magneto-hydrodynamics simulations, allowing for the first time a study of the impact of CR feedback on thousands of resolved galaxies during the Epoch of Reionisation (EoR). The simulations differ in their feedback prescriptions: one adopts a calibrated strong supernova (SN) feedback, while the other simulation reduces the strength of SN feedback and includes CR feedback instead. We show that both comparably regulate star formation, reasonably match observations of high-redshift UV luminosity functions, and produce a similar amount of hydrogen ionising photons. In contrast to the model with strong SN feedback, the model with CRs lead to incomplete reionisation, which is in strong disagreement with observational estimates of the reionisation history. This is due to CR feedback shaping the ISM differently, filling with gas the low density cavities otherwise carved by SN explosions. As a result, this reduces the escape of ionising photons, at any halo mass, and primarily in the close vicinity of the stars. Our study indicates that CR feedback regulates galaxy growth during the EoR, but negatively affects reionisation, a tension which paves the way for further exploration and refinement of existing galaxy formation and feedback models. Such improvements are crucial in order to capture and understand the process of reionisation and the underlying evolution of galaxies through cosmic time. © 2025, CC BY.

关键词： Cosmic rays

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Mapping Structural Heterogeneity at the Nanoscale with Scanning Nano-structure Electron Microscopy (SNEM)

arXiv

引用

arXiv 2021年

作者： Rakita, Yevgeny Hart, James L. Das, Partha Pratim Foley, Daniel L. Nicolopoulos, Stavros Shahrezaei, Sina Mathaudhu, Suveen Nigel Taheri, Mitra L. Billinge, Simon J.L. Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States Department of Materials Science and Engineering Johns Hopkins University BaltimoreMD21218 United States NanoMEGAS SPRL Rue Émile Claus 49 Bte 9 BrusselsB1050 Belgium Materials Science and Engineering Program University of California Riverside RiversideCA29521 United States Department of Mechanical Engineering University of California Riverside RiversideCA92521 United States Condensed Matter Physics and Materials Science Department Brookhaven National Laboratory UptonNY11973 United States

Here we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr65Cu17.5Ni10Al7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modelled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods. © 2021, CC BY.

关键词： Electrons

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Steady Rayleigh-BénardRayleigh-Bénard convection between stress-free boundaries

arXiv

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arXiv 2020年

作者： Wen, Baole Goluskin, David LeDuc, Matthew Chini, Gregory P. Doering, Charles R. Department of Mathematics University of Michigan Ann ArborMI48109-1043 United States Department of Mathematics & Statistics University of Victoria VictoriaBCV8P 5C2 Canada Department of Physics University of Michigan Ann ArborMI48109-1040 United States Program in Integrated Applied Mathematics University of New Hampshire DurhamNH03824 United States Department of Mechanical Engineering University of New Hampshire DurhamNH03824 United States Center for the Study of Complex Systems University of Michigan Ann ArborMI48109-1042 United States

Steady two-dimensional Rayleigh-Bénard convection between stress-free isothermal boundaries is studied via numerical computations. We explore properties of steady convective rolls with aspect ratios π/5 ⩽ Γ ⩽ 4π, where Γ is the width-to-height ratio for a pair of counter-rotating rolls, over eight orders of magnitude in the Rayleigh number, 103 ⩽ Ra ⩽ 1011, and four orders of magnitude in the Prandtl number, 10−2 ⩽ Pr ⩽ 102. At large Ra where steady rolls are dynamically unstable, the computed rolls display Ra → ∞ asymptotic scaling. In this regime, the Nusselt number Nu that measures heat transport scales as Ra1/3 uniformly in Pr. The prefactor of this scaling depends on Γ and is largest at Γ ≈ 1.9. The Reynolds number Re for large-Ra rolls scales as Pr−1Ra2/3 with a prefactor that is largest at Γ ≈ 4.5. All of these large-Ra features agree quantitatively with the semi-analytical asymptotic solutions constructed by Chini & Cox (2009). Convergence of Nu and Re to their asymptotic scalings occurs more slowly when Pr is larger and when Γ is smaller. Copyright © 2020, The Authors. All rights reserved.

关键词： Prandtl number

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BEAST DB: Grand-Canonical Database of Electrocatalyst Properties

arXiv

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arXiv 2024年

作者： Tezak, Cooper Clary, Jacob Gerits, Sophie Quinton, Joshua Rich, Benjamin Singstock, Nicholas Alherz, Abdulaziz Aubry, Taylor Clark, Struan Hurst, Rachel Ben, Mauro Del Sutton, Christopher Sundararaman, Ravishankar Musgrave, Charles Vigil-Fowler, Derek Department of Chemical and Biological Engineering University of Colorado Boulder BoulderCO80309 United States Materials Chemical and Computational Science Directorate National Renewable Energy Laboratory GoldenCO80401 United States Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute TroyNY12180 United States Department of Chemistry University of Colorado Boulder BoulderCO80309 United States Department of Mechanical Engineering University of Colorado Boulder BoulderCO80309 United States Department of Chemical Engineering College of Engineering and Petroleum Kuwait University Safat13060 Kuwait Applied Mathematics & Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Chemistry and Biochemistry University of South Carolina ColumbiaSC29208 United States Department of Materials Science and Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Materials Science and Engineering Program University of Colorado Boulder BoulderCO80309 United States Renewable and Sustainable Energy Institute University of Colorado Boulder BoulderCO80309 United States Department of Chemical Engineering University of Utah Salt Lake CityUT84112 United States

We present BEAST DB, an open-source database comprised of ab initio electrochemical data computed using grand-canonical density functional theory in implicit solvent at consistent calculation parameters. The database contains over 20,000 surface calculations and covers a broad set of heterogenous catalyst materials and electrochemical reactions. Calculations were performed at self-consistent fixed potential as well as constant charge to facilitate comparisons to the computational hydrogen electrode. This article presents common use cases of the database to rationalize trends in catalyst activity, screen catalyst material spaces, understand elementary mechanistic steps, analyze electronic structure, and train machine learning models to predict higher fidelity properties. Users can interact graphically with the database by querying for individual calculations to gain granular understanding of reaction steps or by querying for an entire reaction pathway on a given material using an interactive reaction pathway tool. BEAST DB will be periodically updated, with planned future updates to include advanced electronic structure data, surface speciation studies, and greater reaction coverage. Copyright © 2024, The Authors. All rights reserved.

关键词： Database systems

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QUANTIFYING INTERSPECIFIC COMPETITION BETWEEN CANCER AND NORMAL CELLS USING USING NONLINEAR MIXED EFFECTS AND ORDINARY DIFFERENTIAL EQUATION MODELING

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Hematology, Transfusion and Cell Therapy 2025年 47卷 103779-103779页

作者： Letícia Fernanda Alves Mauro César Cafundó Morais João Frederico Costa Azevedo Meyer Diego Samuel Rodrigues PhD Program in Applied Mathematics Universidade Estadual de Campinas (UNICAMP) Campinas SP Brazil Department of Clinical Analysis Faculdade de Ciências Farmacêuticas Universidade de São Paulo (USP) São Paulo SP Brazil Instituto de Matemática Estatística e Computação Científica Universidade Estadual de Campinas (UNICAMP) Campinas SP Brazil Faculdade de Tecnologia Universidade Estadual de Campinas (UNICAMP) Limeira SP Brazil

Introduction/Justification Tumor growth has been widely studied through various methodologies. In mathematical oncology, researchers use ordinary differential equations (ODEs) to analyze tumor dynamics. These models present meaningful parameters to link mathematical theory with experimental data. For in vitro cocultures, parameters quantifying cellular competition clarify interactions between tumor and normal cells. Objectives This research investigates the interaction between cancer and normal cells during competition, focusing on the in vitro growth of SK-MEL-147 (metastatic melanoma) and HaCaT (immortalized epithelial cells) cell lines. Using an ODE model with cell numbers as dependent variables, we quantify interspecific competition through the parameters α_{12} (impact of SK-MEL-147 on HaCaT) and α_{21} (impact of HaCaT on SK-MEL-147). Materials and Methods The in vitro cell growth experiments from Morais \textit{et al}., (2017), https://***/10.1038/s41598-017-07553-6, allowed us to estimate parameters for Gatenby's 1996 ODE model. We used a nonlinear mixed effects model from NLMEModeling (https://***/10.48550/arXiv.2011.06879) to account for observation errors and biological variability. Results The curve fitting matched the experimental data for both cell types. Parameter estimates showed that SK-MEL-147 cells experienced stronger inhibition from HaCaT cells than the reverse, suggesting normal cells hinder cancer cell growth upon contact. Conclusion Nonlinear mixed effects modeling successfully fit Gatenby's mathematical model to the experimental data, providing competition parameters that clarified interspecific interactions in tumor dynamics. Such models can predict cell growth behavior, supporting experimental design and reducing the need for preliminary \textit{in vitro} tests.

关键词： HaCaT Cell Lineage SK-MEL-147 Cell Lineage Skin cancer

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Reed-Muller codes polarize

arXiv

引用

arXiv 2019年

作者： Abbe, Emmanuel Ye, Min Mathematics Institute School of Computer and Communication Sciences Epfl Switzerland Program in Applied and Computational Mathematics Department of Electrical Engineering Princeton University United States Department of Electrical Engineering Princeton University PrincetonNJ United States

Reed-Muller (RM) codes and polar codes are generated by the same matrix Gm= [1 0/1 1]⊗mbut using different subset of rows. RM codes select simply rows having largest weights. Polar codes select instead rows having the largest conditional mutual information proceeding top to down in Gm;while this is a more elaborate and channel-dependent rule, the top-to-down ordering has the advantage of making the conditional mutual information polarize, giving directly a capacity-achieving code on any binary memoryless symmetric channel (BMSC). RM codes are yet to be proved to have such property. In this paper, we reconnect RM codes to polarization theory. It is shown that proceeding in the RM code ordering, i.e., not top-to-down but from the lightest to the heaviest rows in Gm, the conditional mutual information again polarizes. We further demonstrate that it does so faster than for polar codes. This implies that Gmcontains another code, different than the polar code and called here the twin code, that is provably capacity-achieving on any BMSC. This proves a necessary condition for RM codes to achieve capacity on BMSCs. It further gives a sufficient condition if the rows with largest conditional mutual information correspond to the heaviest rows, i.e., if the twin code is the RM code. We show here that the two codes bare similarity with each other and give further evidence that they are likely the same. Copyright © 2019, The Authors. All rights reserved.

关键词： Forward error correction

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Forest fires and carbon emission release in semi-arid regions of Indonesia: the evidence from medium resolution of satellite imagery

引用

IOP Conference Series: Earth and Environmental Science 2021年第1期622卷

作者： AN Armanto Perdinan BD Dasanto R Hidayati Applied Climatology Study Program Faculty of Mathematics and Natural Science Graduate School of IPB University Bogor West Java Indonesia 16680 Department of Geophysics and Meteorology IPB University Bogor Indonesia 16680

Forest fires are one of the causes of forest degradation and deforestation in Indonesia. Tropical savanna forests are one of the forest ecosystems found in the Indonesian region with a semi-arid climate type prone to drought and fire. Forest fires contribute to the release of greenhouse gas emissions into the atmosphere. The calculation method to estimate the burnt area is still an obstacle in calculating greenhouse gas emissions due to forest fires. This research aims to assess the burnt area in tropical savanna forest cover type using medium resolution satellite imagery data by utilizing the Normalized Burn Ratio index in four villages in East Sumba Regency and estimating greenhouse gas emissions these activities. The results showed that the NBR method does not produce an estimate of the burned area with a fair degree of accuracy because the characteristic of channel 7 (SWIR) is sensitive to vegetation moisture content. The savanna forest cover type is the type of land cover identified as the most dominant burned area. It produces the highest greenhouse gas emissions compared to other land cover types.

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On Phase Reduction and Time Period of Noisy Oscillators

On Phase Reduction and Time Period of Noisy Oscillators

引用

IEEE Annual Conference on Decision and Control

作者： Zahra Aminzare Philip Holmes Vaibhav Srivastava Department of Mathematics University of Iowa IA USA Program in Applied and Computational Mathematics Princeton Neuroscience Institute Princeton University Princeton NJ USA Electrical and Computer Engineering Michigan State University East Lansing MI USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

We study phase reduction for noisy oscillator models by deriving a reduced order stochastic differential equation describing the phase evolution using the first and second order Phase Response Curves (PRCs). We discuss direct methods and ordinary differential equations for computing these PRCs, and derive approximate first and second moments of the time period of the oscillator models in terms of functions of the PRCs. We illustrate the theoretical results on a noisy Hopf bifurcation normal form, on a noisy Van der Pol oscillator, and on a noisy bursting neuron model.

关键词： Oscillators Limit-cycles Noise measurement Biological system modeling Perturbation methods Bifurcation Stochastic processes

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Predicting permeability via statistical learning on higher-order microstructural information

arXiv

引用

arXiv 2020年

作者： Röding, Magnus Ma, Zheng Torquato, Salvatore RISE Research Institutes of Sweden Göteborg41276 Sweden Department of Physics Princeton University PrincetonNJ08544 United States Department of Chemistry Department of Physics Princeton Institute for the Science and Technology of Materials Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

Quantitative structure-property relationships are crucial for the understanding and prediction of the physical properties of complex materials. For fluid flow in porous materials, characterizing the geometry of the pore microstructure facilitates prediction of permeability, a key property that has been extensively studied in material science, geophysics and chemical engineering. In this work, we study the predictability of different structural descriptors via both linear regressions and neural networks. A large data set of 30,000 virtual, porous microstructures of different types, including both granular and continuous solid phases, is created for this end. We compute permeabilities of these structures using the lattice Boltzmann method, and characterize the pore space geometry using one-point correlation functions (porosity, specific surface), two-point surface-surface, surface-void, and void-void correlation functions, as well as the geodesic tortuosity as an implicit descriptor. Then, we study the prediction of the permeability using different combinations of these descriptors. We obtain significant improvements of performance when compared to a Kozeny-Carman regression with only lowest-order descriptors (porosity and specific surface). We find that combining all three two-point correlation functions and tortuosity provides the best prediction of permeability, with the void-void correlation function being the most informative individual descriptor. Moreover, the combination of porosity, specific surface, and geodesic tortuosity provides very good predictive performance. This shows that higher-order correlation functions are extremely useful for forming a general model for predicting physical properties of complex materials. Additionally, our results suggest that artificial neural networks are superior to the more conventional regression methods for establishing quantitative structure-property relationships. We make the data and code used publicly available to fac

关键词： Forecasting

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A FAST SIMPLE ALGORITHM FOR COMPUTING THE POTENTIAL OF CHARGES ON A LINE

arXiv

引用

arXiv 2019年

作者： Gimbutas, Zydrunas Marshall, Nicholas F. Rokhlin, Vladimir National Institute of Standards and Technology Boulder CO80305 United States Department of Mathematics Princeton University Princeton NJ08540 United States Program in Applied Mathematics Yale University New HavenCT06511 United States

We present a fast method for evaluating expressions of the form (Equation presented). where αi are real numbers, and xi are points in a compact interval of . This expression can be viewed as representing the electrostatic potential generated by charges on a line in 3. While fast algorithms for computing the electrostatic potential of general distributions of charges in 3 exist, in a number of situations in computational physics it is useful to have a simple and extremely fast method for evaluating the potential of charges on a line;we present such a method in this paper, and report numerical results for several examples. Copyright © 2019, The Authors. All rights reserved.

关键词： Numerical methods

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