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Education 教育
IF 10.2 1区 数学 Q1 Mathematics Pub Date : 2023-08-08 DOI: 10.1137/23n975752
Hélène Frankowska
SIAM Review, Volume 65, Issue 3, Page 867-867, August 2023.
In this issue, the Education section presents two contributions. “The One-Dimensional Version of Peixoto's Structural Stability Theorem: A Calculus-Based Proof,” by Aminur Rahman and D. Blackmore, proposes, in the one-dimensional setting, a novel proof of Peixoto's structural stability and density theorem, which is fundamental in dynamical systems theory. In this framework the structural stability theorem says that a $C^1$ dynamical system $dot x =f(x)$ on $mathbb{S} ^1$ is structurally stable if and only if it has finitely many equilibrium points, all of which are hyperbolic. In the above $mathbb{S} ^1$ denotes the unit circle in $mathbb{R}^2$ and a point $x_star$ is called hyperbolic if $f'(x_star) neq 0$. The Peixto density result says that the set of all $C^1$ structurally stable systems on $mathbb{S}^1$ is open and dense in the space of all $C^1$ dynamical systems on $mathbb{S} ^1$ endowed with the $C^1$ norm. The original Peixoto's theorem is more complex and is valid for any smooth closed surface. Its proof, however, is long and not accessible using the tools available to advanced undergraduates, in contrast with the proposed one-dimensional proof, which an undergraduate could follow. This does not mean that the proof itself is elementary. Preliminaries recall all the basic definitions that are needed to successfully conduct the task. The style is rigorous and self-contained. The article also provides some historical comments, making the reading lively and encouraging further learning. The second paper, “Piecewise Smooth Models of Pumping a Child's Swing,” is presented by Brigid Murphy and Paul Glendinning. It concerns models of a child, in either a seated or standing position, swinging on a playground swing. In the article, which arose from the MSc dissertation by one of the authors, these models are analyzed using Lagrangian mechanics and may serve as an introduction to the different ways in which piecewise smooth systems do arise in modeling. The authors describe control strategies of swingers, and, in particular, whether it is possible for the swing to go through a full turn over its pivot. Piecewise smooth terms do naturally appear while discussing the strategies, and this future is analyzed in detail. Indeed the instantaneous reposition of the body of the swinger leads to a jump in the configuration of the swing. Numerical simulations are performed with a standard software package. These investigations would be suitable for undergraduate projects related to classical mechanics courses. At a higher degree level, projects could include further refinement of the existing methods and/or getting more accurate numerical solutions using available specialized software packages. The final section also discusses various related mathematical questions that would be interesting to investigate in this context and mentions other models involving jumps described using piecewise smoot
SIAM评论,第65卷第3期,第867-867页,2023年8月。在本期中,教育部分提供了两个贡献。Aminur Rahman和D.Blackmore的“Peikodo结构稳定性定理的一维版本:基于微积分的证明”,在一维环境中提出了Peikoto结构稳定性和密度定理的新证明,这是动力系统理论的基础。在这个框架中,结构稳定性定理表明,$mathbb{S}^1$上的$C^1$动力系统$dot x=f(x)$是结构稳定的,当且仅当它有有限多个平衡点,所有这些平衡点都是双曲的。在上面的$mathbb{S}^1$表示$mathbb{R}^2$中的单位圆,如果$f'(x_star)neq0$,则点$x_star$称为双曲点。Peixto密度结果表明,在$mathbb{S}^1$上所有结构稳定的$C^1$系统的集合在$math bb{S}^1$上所有具有$C^1$范数的$C^ 1$动力系统的空间中是开的和稠密的。原来的Peikodo定理更为复杂,适用于任何光滑的闭曲面。然而,与本科生可以遵循的一维证明相比,它的证明很长,使用高级本科生可用的工具是不容易获得的。这并不意味着证明本身就是基本的。前言回顾了成功执行任务所需的所有基本定义。风格严谨,自成一体。文章还提供了一些历史评论,使阅读变得生动,并鼓励进一步学习。第二篇论文“儿童挥杆的分段平滑模型”由Brigid Murphy和Paul Glendining提出。它涉及一个孩子的模型,无论是坐着还是站着,在操场上荡秋千。这篇文章源于其中一位作者的硕士论文,使用拉格朗日力学对这些模型进行了分析,并可以介绍在建模中出现分段光滑系统的不同方式。作者描述了挥杆者的控制策略,特别是挥杆是否有可能在其枢轴上完成一个完整的转弯。在讨论策略时,分段平滑术语确实会自然出现,并对未来进行了详细分析。事实上,挥杆者身体的瞬间重新定位导致挥杆配置的跳跃。使用标准软件包进行数值模拟。这些研究将适用于与经典力学课程相关的本科生项目。在更高的学位水平上,项目可以包括进一步完善现有方法和/或使用可用的专业软件包获得更准确的数值解。最后一节还讨论了在这种情况下值得研究的各种相关数学问题,并提到了使用分段平滑项描述的涉及跳跃的其他模型。
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引用次数: 0
Bayesian Inverse Problems Are Usually Well-Posed 贝叶斯反问题通常是好姿势的
IF 10.2 1区 数学 Q1 Mathematics Pub Date : 2023-08-08 DOI: 10.1137/23m1556435
Jonas Latz
SIAM Review, Volume 65, Issue 3, Page 831-865, August 2023.
Inverse problems describe the task of blending a mathematical model with observational data---a fundamental task in many scientific and engineering disciplines. The solvability of such a task is usually classified through its well-posedness. A problem is well-posed if it has a unique solution that depends continuously on input or data. Inverse problems are usually ill-posed, but can sometimes be approached through a methodology that formulates a possibly well-posed problem. Usual methodologies are the variational and the Bayesian approach to inverse problems. For the Bayesian approach, Stuart [Acta Numer., 19 (2010), pp. 451--559] has given assumptions under which the posterior measure---the Bayesian inverse problem's solution---exists, is unique, and is Lipschitz continuous with respect to the Hellinger distance and, thus, well-posed. In this work, we simplify and generalize this concept: Indeed, we show well-posedness by proving existence, uniqueness, and continuity in Hellinger distance, Wasserstein distance, and total variation distance, and with respect to weak convergence, respectively, under significantly weaker assumptions. An immense class of practically relevant Bayesian inverse problems satisfies those conditions. The conditions can often be verified without analyzing the underlying mathematical model---the model can be treated as a black box.
SIAM评论,第65卷第3期,第831-865页,2023年8月。反问题描述了将数学模型与观测数据相结合的任务——这是许多科学和工程学科的基本任务。这类任务的可解性通常通过其适定性来分类。如果一个问题有一个持续依赖于输入或数据的独特解决方案,那么它就是一个好问题。反问题通常是不适定的,但有时可以通过公式化可能是适定问题的方法来处理。常用的方法是反问题的变分法和贝叶斯方法。对于贝叶斯方法,Stuart[Acta Numer.,19(2010),pp.451-559]给出了后验测度(贝叶斯逆问题的解)存在、唯一、相对于Hellinger距离是Lipschitz连续的假设,因此,是适定的。在这项工作中,我们简化并推广了这一概念:事实上,我们通过在明显较弱的假设下分别证明Hellinger距离、Wasserstein距离和总变差距离的存在性、唯一性和连续性,以及关于弱收敛性,展示了适定性。一大类实际相关的贝叶斯反问题满足这些条件。这些条件通常可以在不分析底层数学模型的情况下进行验证——该模型可以被视为黑盒。
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引用次数: 0
A Comprehensive Proof of Bertrand's Theorem 伯特兰定理的一个全面证明
IF 10.2 1区 数学 Q1 Mathematics Pub Date : 2023-05-01 DOI: 10.1137/21m1436658
P. Leenheer, Jack W. Musgrove, Tyler Schimleck
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引用次数: 0
Nonlinear Perron-Frobenius Theorems for Nonnegative Tensors 非负张量的非线性Perron-Frobenius定理
IF 10.2 1区 数学 Q1 Mathematics Pub Date : 2023-05-01 DOI: 10.1137/23m1557489
A. Gautier, Francesco Tudisco, Matthias Hein
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引用次数: 1
Education 教育
1区 数学 Q1 Mathematics Pub Date : 2023-05-01 DOI: 10.1137/23n975703
Hélène Frankowska
The Education section in this issue presents two contributions. In `"Nesterov's Method for Convex Optimization," Noel J. Walkington proposes a teaching guide for a first course in optimization of this well-known algorithm for computing the minimum of a convex function. This algorithm, first proposed in 1983 by Yuri Nesterov, though well recognized in computational optimization in the presence of large data as a more efficient tool than the steepest descent method, is still absent in most modern textbooks on optimization. The author of the present article develops an elementary analysis of Nesterov's first order algorithm that parallels that of steepest descent but with an additional requirement proposed by Nesterov. Two cases are discussed. The first concerns an unconstrained minimization problem, while the second includes closed convex constraints represented using infinite penalization of the cost. More generally, the cost function becomes the sum of a smooth convex function and a lower semicontinuous convex function. Several student-level exercises are included in this paper. Results are nicely illustrated by an example of a signal recovery problem and a discussion of the Uzawa algorithm for optimization problems with constraints defined by inequalities involving convex functions. The second paper, "A Comprehensive Proof of Bertrand's Theorem," is presented by Patrick De Leenheer, John Musgrove, and Tyler Schimleck. It concerns the behavior of the solutions of the classical two-body problem and states that, among all possible gravitational laws, there are only two exhibiting the property that all bounded orbits are closed: Newtonian gravitation and Hookean gravitation. Historically, even if Newton was aware that there are to specific gravitational laws having the above property, it was only two centuries later, in 1873, that Bertrand realized that these are the only ones. Bertrand's theorem, due to its important consequences, has been integrated into the undergraduate curriculum in theoretical mechanics, but its proof, accessible to undergraduate mathematics or physics students, seems to be absent from modern textbooks. Although Bertrand's original paper did not contain a precise proof, V. Arnold proposed a sketch of it based on six subproblems. Among other contributions, this article provides a complete proof of the sixth subproblem under a specific assumption imposed on the magnitude of the force in the motion model. Under this assumption, a complete proof of Bertrand's theorem is then given, incorporating also earlier contributions by other authors. Still, comprehensive does not mean simple here, and this paper may be used to conceive several research projects for advanced-level undergraduate students in mathematics or physics.
本期的“教育”部分有两篇文章。在“Nesterov的凸优化方法”中,Noel J. Walkington提出了一个关于这个著名算法优化的第一门课程的教学指南,用于计算凸函数的最小值。该算法由Yuri Nesterov于1983年首次提出,虽然在大数据存在的计算优化中被公认为比最陡下降法更有效的工具,但在大多数现代优化教科书中仍然没有。本文的作者对Nesterov的一阶算法进行了初步分析,该算法与最陡下降算法相似,但带有Nesterov提出的附加要求。讨论了两个案例。第一个问题涉及无约束最小化问题,而第二个问题包括使用无限代价惩罚表示的闭合凸约束。更一般地说,代价函数变成光滑凸函数和下半连续凸函数的和。本文包含了几个学生水平的练习。通过一个信号恢复问题的例子和讨论Uzawa算法对包含凸函数的不等式定义约束的优化问题的结果很好地说明了这一点。第二篇论文,“伯特兰定理的全面证明”,由Patrick De Leenheer, John Musgrove和Tyler Schimleck提出。它关注经典二体问题解的行为,并指出,在所有可能的引力定律中,只有两个定律表现出所有有界轨道都闭合的性质:牛顿引力和胡克引力。从历史上看,即使牛顿意识到有特定的万有引力定律具有上述性质,直到两个世纪后的1873年,伯特兰才意识到这些定律是唯一的。由于其重要的结果,伯特兰定理已经被纳入了理论力学的本科课程,但是它的证明,对于数学或物理专业的本科生来说,似乎没有在现代教科书中出现。尽管Bertrand的原始论文没有包含精确的证明,V. Arnold还是提出了一个基于六个子问题的草图。在其他贡献中,本文提供了在运动模型中对力的大小施加的特定假设下的第六子问题的完整证明。在此假设下,结合其他作者的早期贡献,给出了伯特兰定理的完整证明。然而,全面并不意味着简单,本文可以用来设想几个研究项目的高等水平的本科生数学或物理。
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引用次数: 0
Nesterov's Method for Convex Optimization Nesterov的凸优化方法
IF 10.2 1区 数学 Q1 Mathematics Pub Date : 2023-05-01 DOI: 10.1137/21m1390037
N. Walkington
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引用次数: 1
Survey and Review 调查及检讨
1区 数学 Q1 Mathematics Pub Date : 2023-05-01 DOI: 10.1137/23n975673
Marlis Hochbruck
A point process is called self-exciting if the arrival of an event increases the probability of similar events for some period of time. Typical examples include earthquakes, which frequently cause aftershocks due to increased geological tension in their region; raised intrusion rates in the vicinity of a burglary; retweets in social media incited by some provocative posting; or trading frenzies following a huge stock order. A Hawkes process is a point process that models self-excitement among time events. In contrast to a Markov chain (in which the probability of each event depends only on the state attained in the previous event), chances of arrival of events are increased for some time period after the initial arrival in a Hawkes process. The first Survey and Review paper in this issue, “Hawkes Processes Modeling, Inference, and Control: An Overview,” by Rafael Lima, discusses recent advances in Hawkes process modeling and inference. The parametric, nonparametric, deep learning, and reinforcement learning approaches are covered. Current research challenges for the topic and the real-world limitations of each approach are also addressed. The paper should be of interest to experts in the field, but it also aims to be suitable for newcomers. The second Survey and Review paper, “Proximal Splitting Algorithms for Convex Optimization: A Tour of Recent Advances, with New Twists,” by Laurent Condat, Daichi Kitahara, Andrés Contreras, and Akira Hirabayashi, is dedicated to the solution of convex nonsmooth optimization problems in high-dimensional spaces. The objective function $f$ is assumed to be a sum of simple convex functions $f_j$ with the property that the minimization problem for each $f_j$ is simple, but for $f$ it is hard. For nonsmooth functions, gradient-based optimization algorithms are infeasible. In proximal algorithms, the gradient is replaced by the so-called proximity operator. While closed forms of proximity operators are known for many functions of practical interest, there is no general closed form for the proximity operator of a sum of functions. Therefore, splitting algorithms handle the proximity operators of the functions $f_j$ individually. The paper provides a constructive and self-contained introduction to the class of proximal splitting algorithms. New variants of the algorithms under consideration are developed. Existing convergence results are revisited, unified, and, in some cases, improved. Reading the paper will be rewarding for anyone interested in high-dimensional nonsmooth convex optimization.
如果一个事件的到来在一段时间内增加了类似事件发生的概率,则点过程称为自激过程。典型的例子包括地震,由于其所在地区的地质张力增加,地震经常引起余震;入室行窃附近的闯入率上升;在社交媒体上被一些挑衅性的帖子煽动转发;或者巨额股票订单后的交易狂热。霍克斯过程是一个模拟时间事件中自我兴奋的点过程。与马尔可夫链(其中每个事件的概率仅取决于前一个事件所达到的状态)相反,在霍克斯过程中,事件到达的机会在初始到达后的一段时间内增加。这期的第一篇调查和评论论文,“Hawkes过程建模、推理和控制:概述”,作者是Rafael Lima,讨论了Hawkes过程建模和推理的最新进展。涵盖了参数、非参数、深度学习和强化学习方法。当前的研究挑战的主题和现实世界的限制,每个方法也解决。这篇论文应该对该领域的专家感兴趣,但它也旨在适合新手。第二篇综述论文,“凸优化的近距离分裂算法:最新进展的回顾”,由Laurent Condat、Daichi Kitahara、andr Contreras和Akira Hirabayashi撰写,致力于解决高维空间中的凸非光滑优化问题。假设目标函数$f$是简单凸函数$f_j$的和,其性质是每个$f_j$的最小化问题很简单,但$f$很难。对于非光滑函数,基于梯度的优化算法是不可行的。在接近算法中,梯度被所谓的接近算子所取代。虽然对于许多实用的函数,接近算子的封闭形式是已知的,但对于函数和的接近算子,没有一般的封闭形式。因此,拆分算法分别处理函数$f_j$的接近运算符。本文对一类近端分裂算法提供了一个建设性的、完备的介绍。正在考虑的算法的新变体被开发出来。现有的收敛结果将被重新访问、统一,并在某些情况下进行改进。对于任何对高维非光滑凸优化感兴趣的人来说,阅读这篇论文都是有益的。
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引用次数: 0
Research Spotlights 研究聚光灯
1区 数学 Q1 Mathematics Pub Date : 2023-05-01 DOI: 10.1137/23n975685
Stefan M. Wild
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引用次数: 0
SIGEST SIGEST
1区 数学 Q1 Mathematics Pub Date : 2023-05-01 DOI: 10.1137/23n975697
None The Editors
The SIGEST article in this issue is “Nonlinear Perron--Frobenius Theorems for Nonnegative Tensors,” by Antoine Gautier, Francesco Tudisco, and Matthias Hein. Most computational and applied mathematicians will be aware of the results that Perron published in 1907 about the eigensystems of positive matrices, which were then extended by Frobenius in 1912 to the case of nonnegative matrices. This theory has impacted many areas of mathematics, including graph theory, Markov chains, and matrix computation, and it forms a fundamental component in the analysis of a range of models in areas such as demography, economics, wireless networking, and search engine optimization. Our SIGEST article, which first appeared in SIAM Journal on Matrix Analysis and Applications in 2019, extends Perron--Frobenius theory in two directions. First, the authors generalize from matrices to multidimensional arrays. This ties in with one of SIAM Review's most highly cited offerings: •Tensor decompositions and applications, T. G. Kolda and B. W. Bader, SIAM Review, 51 (3) (2009), pp. 455--500. It may also be viewed as extending the theory from graphs to hypergraphs---objects that are currently of much interest, as evidenced by several recent SIAM Review articles, including •Hypergraph cuts with general splitting functions, N. Veldt, A. R. Benson and J. Kleinberg, SIAM Review, 64 (3) (2022), pp. 650--685. By studying this higher-order setting, the authors open up new applications in network science, computer vision, and machine learning. The second major direction of the article is to develop and study nonlinear versions of the underlying spectral problems, and corresponding extensions of the traditional power method. This makes available new classes of iterations for which a comprehensive and satisfactory convergence theory is available. In preparing this SIGEST version, the authors have included new material. The introduction has been extended, and section 2 has been added to provide nontrivial examples of tensor eigenvalue problems in applications, including problems from computer vision and optimal transport. Moreover, subsection 4.1 includes a new nonlinear Perron--Frobenius theorem (Theorem 4.4) that builds on the previously known results in Theorems 4.2. and 4.3.
这期SIGEST的文章是“非线性Perron——非负张量的Frobenius定理”,作者是Antoine Gautier, Francesco Tudisco和Matthias Hein。大多数计算数学家和应用数学家都知道Perron在1907年发表的关于正矩阵的特征系统的结果,然后Frobenius在1912年将其推广到非负矩阵的情况。这一理论影响了数学的许多领域,包括图论、马尔可夫链和矩阵计算,它在人口统计学、经济学、无线网络和搜索引擎优化等领域的一系列模型分析中形成了一个基本组成部分。我们的SIGEST文章首次发表在2019年的SIAM矩阵分析与应用杂志上,从两个方向扩展了Perron- Frobenius理论。首先,作者将矩阵推广到多维数组。•张量分解和应用,T. G. Kolda和B. W. Bader, SIAM Review, 51(3)(2009),第455—500页。它也可以被视为将理论从图扩展到超图——这是目前非常感兴趣的对象,最近的几篇SIAM评论文章证明了这一点,包括带有一般分裂函数的超图切割,N. Veldt, A. R. Benson和J. Kleinberg, SIAM评论,64 (3)(2022),pp. 650—685。通过研究这种高阶设置,作者在网络科学、计算机视觉和机器学习方面开辟了新的应用。本文的第二个主要方向是发展和研究底层谱问题的非线性版本,以及传统幂方法的相应扩展。这使得新的迭代类成为可能,对于这些迭代类,可以得到一个全面的、令人满意的收敛理论。在准备这个SIGEST版本时,作者加入了新的材料。介绍部分已经扩展,并增加了第2节,以提供应用中张量特征值问题的非平凡示例,包括来自计算机视觉和最优传输的问题。此外,第4.1小节包括一个新的非线性Perron—Frobenius定理(定理4.4),它建立在先前已知的定理4.2的结果之上。和4.3。
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引用次数: 0
Research Spotlights 研究聚光灯
IF 10.2 1区 数学 Q1 Mathematics Pub Date : 2023-02-01 DOI: 10.1137/23n975624
Stefan M. Wild
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引用次数: 0
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