检索结果-内蒙古大学图书馆

The impact of cosmic ray feedback during the epoch of reionisation

学校读者我要写书评

暂无评论

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

Phase Diagram of a Deep Potential Water Model

学校读者我要写书评

暂无评论

Physical Review Letters 2021年第23期126卷 236001-236001页

作者： Linfeng Zhang Han Wang Roberto Car Weinan E Department of Mathematics and Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA and Beijing Institute of Big Data Research Beijing 100871 People’s Republic of China

Using the Deep Potential methodology, we construct a model that reproduces accurately the potential energy surface of the SCAN approximation of density functional theory for water, from low temperature and pressure to about 2400 K and 50 GPa, excluding the vapor stability region. The computational efficiency of the model makes it possible to predict its phase diagram using molecular dynamics. Satisfactory overall agreement with experimental results is obtained. The fluid phases, molecular and ionic, and all the stable ice polymorphs, ordered and disordered, are predicted correctly, with the exception of ice III and XV that are stable in experiments, but metastable in the model. The evolution of the atomic dynamics upon heating, as ice VII transforms first into ice VII′′ and then into an ionic fluid, reveals that molecular dissociation and breaking of the ice rules coexist with strong covalent fluctuations, explaining why only partial ionization was inferred in experiments.

关键词： Classical statistical mechanics First order phase transitions Interatomic & molecular potentials Phase diagrams Potential energy surfaces Water First-principles calculations Machine learning Molecular dynamics

Active learning of uniformly accurate interatomic potentials for materials simulation

学校读者我要写书评

暂无评论

Physical Review Materials 2019年第2期3卷 023804-023804页

作者： Linfeng Zhang De-Ye Lin Han Wang Roberto Car Weinan E Department of Mathematics and Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA and Beijing Institute of Big Data Research Beijing 100871 People's Republic of China

An active learning procedure called deep potential generator (DP-GEN) is proposed for the construction of accurate and transferable machine learning-based models of the potential energy surface (PES) for the molecular modeling of materials. This procedure consists of three main components: exploration, generation of accurate reference data, and training. Application to the sample systems of Al, Mg, and Al-Mg alloys demonstrates that DP-GEN can produce uniformly accurate PES models with a minimal number of reference data.

关键词： Atomic & molecular structure Potential energy surfaces Alloys Amorphous materials Liquids Density functional theory First-principles calculations Molecular dynamics

Robust camera location estimation by convex programming

学校读者我要写书评

暂无评论

Robust camera location estimation by convex programming

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Onur Özyeşil Amit Singer Program in Applied and Computational Mathematics Princeton University Princeton NJ USA Department of Mathematics Princeton University Princeton NJ USA

3D structure recovery from a collection of 2D images requires the estimation of the camera locations and orientations, i.e. the camera motion. For large, irregular collections of images, existing methods for the location estimation part, which can be formulated as the inverse problem of estimating n locations t 1 , t 2 , ..., tn in ℝ 3 from noisy measurements of a subset of the pairwise directions t i -t j /∥t i -t j ∥, are sensitive to outliers in direction measurements. In this paper, we firstly provide a complete characterization of well-posed instances of the location estimation problem, by presenting its relation to the existing theory of parallel rigidity. For robust estimation of camera locations, we introduce a two-step approach, comprised of a pairwise direction estimation method robust to outliers in point correspondences between image pairs, and a convex program to maintain robustness to outlier directions. In the presence of partially corrupted measurements, we empirically demonstrate that our convex formulation can even recover the locations exactly. Lastly, we demonstrate the utility of our formulations through experiments on Internet photo collections.

关键词： Estimation Cameras Robustness Noise measurement Three-dimensional displays Accuracy Minimization

Positive photoresist process simulation over nonplanar substrates

学校读者我要写书评

暂无评论

Journal of Vacuum Science & Technology B: Microelectronics P...

Journal of Vacuum Science & Technology B: Microelectronics Processing and Phenomena 1990年第6期8卷 1432-1436页

作者： Eytan Barouch Brian Bradie Uwe Hollerbach Steven A. Orszag Department of Mathematics and Computer Science Clarkson University Potsdam New York 13676 Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544

A three‐dimensional computational simulator of nonplanar substrates coated with positive photoresists is presented. The model includes four major steps: projection printing, exposure, post‐exposure baking (PEB), and dissolution. Projection printing is based on Hopkins’ classical work. The exposure model employs the full nonlinear wave equation coupled with the photoactive compound (PAC) bleaching rate equation. These equations are solved using a spectral element iterative scheme. The PEB is treated as a material diffusion equation employing ideas introduced by Mack and the dissolution algorithm is our LEAD (least action dissolution) algorithm modified for nonplanar substrates. Several realistic examples are presented displaying final profiles at various dissolution times.

关键词：

Preserving dissipation in approximate inertial forms for the Kuramoto-Sivashinsky equation

学校读者我要写书评

暂无评论

Journal of Dynamics and Differential Equations 1991年第2期3卷 179-197页

作者： Jolly, M.S. Kevrekidis, I.G. Titi, E.S. Program in Applied and Computational Mathematics Princeton University Princeton 08544 New Jersey United States Department of Mathematics Indiana University Bloomington 47405 Indiana United States Department of Chemical Engineering Princeton University Princeton 08544 New Jersey United States Mathematical Sciences Institute Cornell University Ithaca 14853 New York United States Department of Mathematics University of California Irvine 92717 California United States

It has been observed, in earlier computations of bifurcation diagrams for dissipative partial differential equations, that the use of certain explicit approximate inertial forms can give rise to numerical artifacts such as spurious turning points and inaccurate solution branches. These shortcomings were attributed to a lack of dissipation in the forms used. We show analytically and verify numerically that with an appropriate adjustment we can eliminate these numerical artifacts. The motivation for this adjustment is to enforce dissipation, while maintaining the same order of approximation. We demonstrate with computations that the most natural remedy, namely, preparation of the equation, can be highly sensitive to assumptions on the size of the absorbing ball. In addition, we show that certain implicit forms are dissipative without any adjustment. As an illustrative example we use here the Kuramoto-Sivashinsky equation. © 1991 Plenum Publishing Corporation.

关键词： dissipation Inertial manifold Kuramoto-Sivashinsky non-linear Galerkin method

Structural variability from noisy tomographic projections

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Andén, Joakim Singer, Amit Center for Computational Biology Flatiron Institute New YorkNY United States Department of Mathematics and Program in Applied and Computational Mathematics Princeton University NJ United States

In cryo-electron microscopy, the 3D electric potentials of an ensemble of molecules are projected along arbitrary viewing directions to yield noisy 2D images. The volume maps representing these potentials typically exhibit a great deal of structural variability, which is described by their 3D covariance matrix. Typically, this covariance matrix is approximately low-rank and can be used to cluster the volumes or estimate the intrinsic geometry of the conformation space. We formulate the estimation of this covariance matrix as a linear inverse problem, yielding a consistent least-squares estimator. For n images of size N-by-N pixels, we propose an algorithm for calculating this covariance estimator with computational complexity O(nN4 + √κN6 log N), where the condition number κ is empirically in the range 10-200. Its efficiency relies on the observation that the normal equations are equivalent to a deconvolution problem in 6D. This is then solved by the conjugate gradient method with an appropriate circulant preconditioner. The result is the first computationally efficient algorithm for consistent estimation of the 3D covariance from noisy projections. It also compares favorably in runtime with respect to previously proposed non-consistent estimators. Motivated by the recent success of eigenvalue shrinkage procedures for high-dimensional covariance matrix estimation, we incorporate a shrinkage procedure that improves accuracy at lower signal-to-noise ratios. We evaluate our methods on simulated datasets and achieve classification results comparable to state-of-the-art methods in shorter running time. We also present results on clustering volumes in an experimental dataset, illustrating the power of the proposed algorithm for practical determination of structural variability.92C55, 68U10, 44A12, 65R32, 62G05, 62H30, 62J10, 62J07 Copyright © 2017, The Authors. All rights reserved.

关键词： Conjugate gradient method

Deterministic guarantees for Burer–Monteiro factorizations of smooth semidefinite programs

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Boumal, Nicolas Voroninski, Vladislav Bandeira, Afonso S. Mathematics Department Program in Applied and Computational Mathematics Princeton University Department of Mathematics Center for Data Science Courant Institute of Mathematical Sciences New York University

We consider semidefinite programs (SDPs) with equality constraints. The variable to be optimized is a positive semidefinite matrix X of size n. Following the Burer–Monteiro approach, we optimize a factor Y of size n× p instead, such that X = YY. This ensures positive semidefiniteness at no cost and can reduce the dimension of the problem if p is small, but results in a non-convex optimization problem with a quadratic cost function and quadratic equality constraints in Y. In this paper, we show that if the set of constraints on Y regularly defines a smooth manifold, then, despite non-convexity, first- and second-order necessary optimality conditions are also sufficient, provided p is large enough. For smaller values of p, we show a similar result holds for almost all (linear) cost functions. Under those conditions, a global optimum Y maps to a global optimum X = YY of the SDP. We deduce old and new consequences for SDP relaxations of the generalized eigenvector problem, the trust-region subproblem and quadratic optimization over several spheres, as well as for the Max-Cut and Orthogonal-Cut SDPs which are common relaxations in stochastic block modeling and synchronization of rotations. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

DeePKS-kit: A package for developing machine learning-based chemically accurate energy and density functional models

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Chen, Yixiao Zhang, Linfeng Wang, Han Weinan, E. Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Huayuan Road 6 Beijing100088 China Department of Mathematics Princeton University PrincetonNJ United States

We introduce DeePKS-kit, an open-source software package for developing machine learning based energy and density functional models. DeePKS-kit is interfaced with PyTorch, an open-source machine learning library, and PySCF, an ab initio computational chemistry program that provides simple and customized tools for developing quantum chemistry codes. It supports the DeePHF and DeePKS methods. In addition to explaining the details in the methodology and the software, we also provide an example of developing a chemically accurate model for water clusters. Copyright © 2020, The Authors. All rights reserved.

关键词： Electronic structure